release: bump 0.7.7 -> 0.7.8 (#232)

Version bump 0.7.7 -> 0.7.8 for the R binding release.

.gitattributes

@@ -1,3 +1,26 @@
 # Shell scripts must keep LF line endings so they run on Linux/macOS CI and
 # local shells regardless of the committer's platform autocrlf setting.
 *.sh text eol=lf
+
+# The cbindgen-generated C header is committed; pin it to LF so its CI drift
+# check (regenerate + `git diff`) never trips on a CRLF normalization.
+bindings/c/include/wickra.h text eol=lf
+
+# C# sources (including the generated binding) are pinned to LF so the committed
+# files stay stable regardless of the committer's autocrlf setting.
+*.cs text eol=lf
+
+# Go sources (including the generated binding) are pinned to LF so gofmt's CI
+# check never trips on a CRLF checkout on Windows.
+*.go text eol=lf
+go.mod text eol=lf
+go.sum text eol=lf
+
+# R binding: `R CMD check` requires LF in sources, Makevars and shell scripts.
+*.R text eol=lf
+*.Rd text eol=lf
+bindings/r/configure.win text eol=lf
+bindings/r/src/Makevars text eol=lf
+bindings/r/src/Makevars.win text eol=lf
+bindings/r/src/wickra.c text eol=lf
+

.github/ISSUE_TEMPLATE/bug_report.md

@@ -30,9 +30,9 @@ assignees: ""
 ## Environment
 
 - Wickra version:
-- Language / binding: <!-- Rust crate / Python / Node / WASM -->
+- Language / binding: <!-- Rust crate / Python / Node / WASM / C ABI / C# (.NET) / Go / R -->
 - OS and architecture:
-- Rust / Python / Node version (If relevant):
+- Rust / Python / Node / .NET version (If relevant):
 
 ## Additional context
 

.github/ISSUE_TEMPLATE/bug_report_detailed.md

@@ -26,7 +26,7 @@ assignees: []
 | Binding version      | `e.g. python 0.4.2 / node 0.4.2`       |
 | OS / arch            | `e.g. Windows 11 x86_64, Linux glibc`  |
 | Rust toolchain       | `rustc --version` (If building from source) |
-| Python / Node version | `python --version` / `node --version` |
+| Python / Node / .NET version | `python --version` / `node --version` / `dotnet --version` |
 
 ## Minimal reproducer
 

.github/ISSUE_TEMPLATE/feature_request.md

@@ -25,6 +25,10 @@ assignees: ""
 - [ ] Should be exposed in the Python binding
 - [ ] Should be exposed in the Node binding
 - [ ] Should be exposed in the WASM binding
+- [ ] Should be exposed in the C ABI
+- [ ] Should be exposed in the C# / .NET binding
+- [ ] Should be exposed in the Go binding
+- [ ] Should be exposed in the R binding
 
 ## Additional context
 

.github/ISSUE_TEMPLATE/performance_regression.md

@@ -13,7 +13,7 @@ assignees: []
 ## Affected code path
 
 - Indicator / API: `e.g. EMA.update`
-- Binding: `Rust / Python / Node / Wasm`
+- Binding: `Rust / Python / Node / Wasm / C ABI / C# (.NET) / Go / R`
 - Hot loop or one-shot call?
 
 ## Versions compared

.github/ISSUE_TEMPLATE/question.md

@@ -33,4 +33,4 @@ import wickra as ta
 ## Environment (Only if relevant)
 
 - Wickra version: `e.g. 0.4.2`
-- Binding: `Rust / Python / Node / Wasm`
+- Binding: `Rust / Python / Node / Wasm / C ABI / C# (.NET) / Go / R`

.github/PULL_REQUEST_TEMPLATE.md

@@ -22,7 +22,7 @@
 - [ ] `cargo clippy --workspace --all-targets -- -D warnings` is clean.
 - [ ] `cargo test --workspace` passes.
 - [ ] New behaviour has tests; bug fixes have a regression test.
-- [ ] Public API changes are mirrored in the Python / Node / WASM bindings
+- [ ] Public API changes are mirrored in the Python / Node / WASM bindings, and the C ABI + C# + Go + R bindings are regenerated
       and their type stubs (If applicable).
 - [ ] The relevant page on the [documentation site](https://docs.wickra.org)
       and the `README.md` are updated (If applicable). Docs edits go to a

.github/PULL_REQUEST_TEMPLATE/detailed.md

@@ -23,6 +23,10 @@ Please fill in the sections below. Delete any that don't apply.
 - [ ] Python binding (`bindings/python`)
 - [ ] Node.js binding (`bindings/node`)
 - [ ] WebAssembly binding (`bindings/wasm`)
+- [ ] C ABI (`bindings/c`)
+- [ ] C# / .NET binding (`bindings/csharp`)
+- [ ] Go binding (`bindings/go`)
+- [ ] R binding (`bindings/r`)
 - [ ] Examples / docs
 
 ## Linked issues

.github/requirements/bench.in

@@ -5,5 +5,7 @@
 maturin
 numpy
 pandas
+TA-Lib
+tulipy
 talipp
 finta

.github/requirements/bench.txt

@@ -1,5 +1,13 @@
 # This file was autogenerated by uv via the following command:
 #    ./scripts/update-lockfiles.sh
+build==1.5.0 \
+    --hash=sha256:13f3eecb844759ab66efec90ca17639bbf14dc06cb2fdf37a9010322d9c50a6f \
+    --hash=sha256:302c22c3ba2a0fd5f3911918651341ebb3896176cbdec15bd421f80b1afc7647
+    # via ta-lib
+colorama==0.4.6 \
+    --hash=sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44 \
+    --hash=sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6
+    # via build
 finta==1.3 \
     --hash=sha256:b94b94df311c18bf5402eb2fe8fd2db5e1bdaff08baf58a7367d05c7abdd10d3 \
     --hash=sha256:f2fa0673748f4be8f57e57cf6d5c00a4d44bc6071ea69dbb9a1d329d045cbba2
@@ -97,6 +105,12 @@ numpy==2.4.6 \
     #   -r .github/requirements/bench.in
     #   finta
     #   pandas
+    #   ta-lib
+    #   tulipy
+packaging==26.2 \
+    --hash=sha256:5fc45236b9446107ff2415ce77c807cee2862cb6fac22b8a73826d0693b0980e \
+    --hash=sha256:ff452ff5a3e828ce110190feff1178bb1f2ea2281fa2075aadb987c2fb221661
+    # via build
 pandas==3.0.3 \
     --hash=sha256:0383c72c75cdcca61a9e116e611143902dbfd08bff356829c2f6d1cf40a9ca8c \
     --hash=sha256:05f1f1752b8533ea03f7f39a9c15b1a058d067bb48f4748948e7a8691e0510f2 \
@@ -149,6 +163,10 @@ pandas==3.0.3 \
     # via
     #   -r .github/requirements/bench.in
     #   finta
+pyproject-hooks==1.2.0 \
+    --hash=sha256:1e859bd5c40fae9448642dd871adf459e5e2084186e8d2c2a79a824c970da1f8 \
+    --hash=sha256:9e5c6bfa8dcc30091c74b0cf803c81fdd29d94f01992a7707bc97babb1141913
+    # via build
 python-dateutil==2.9.0.post0 \
     --hash=sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3 \
     --hash=sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427
@@ -157,10 +175,72 @@ six==1.17.0 \
     --hash=sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274 \
     --hash=sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81
     # via python-dateutil
+ta-lib==0.6.8 \
+    --hash=sha256:02388054c059945e5f02625f5075bac20a1803573cb43e7d096091027511961f \
+    --hash=sha256:094677b279a59c3f01c3aca8a889fda3523fd641a3805f69a2d642121b72e55e \
+    --hash=sha256:0a08a29690a922ba92a6cf42902a8a93c6fbda4cfed62c3c5b0471560ef60135 \
+    --hash=sha256:0ccd478ff5735831bf2a61d653466bfda8afadc26ad58ca6b1edb9e7521cc674 \
+    --hash=sha256:0e371d14b49e70caa973a234c8823341dd446f5c5d7acc826868bb42b272bdc0 \
+    --hash=sha256:11a373c9308eae3bac2d56d37017f9ab63968cc074a8b95be879aae3d13133aa \
+    --hash=sha256:128ec92e6a0e9ff7a38edef80e3b74f15bb2ed1c531d5d3252c8dca22677651b \
+    --hash=sha256:1fb4028437201e19014e4e374272b739867c8a3eb655da46675ef4c2ff14b616 \
+    --hash=sha256:282e49c766b5952dd8796f77d7ed3ae412cdd88e31f845b1fbbb86ac6cb7bebf \
+    --hash=sha256:2b369cabb48485fbf444beb3f5a878075367b99c2c86db2f796afeabebc749e0 \
+    --hash=sha256:2bf714333788bf5175f2512b86d2ed129e89ae6f6c2923e8a297a1e3395e13b5 \
+    --hash=sha256:30de46b55873b51be945a09edf486afcc190dc47eff9fb5d2b12c9f7e3d743da \
+    --hash=sha256:34e3b12407ddf99f6627435aa8a165f094339bb7dc33de92e1d7472e9f237304 \
+    --hash=sha256:36b2a516fce57309840f5ef3fa2fd0c4449293fc72536a0400d2e1e26b414da8 \
+    --hash=sha256:3a9195299df9d7d2a6e9d16bebd6b706b0ea99e4b871864c4b034c2577e21a77 \
+    --hash=sha256:3c32fc0f546ceecc47dd45f33d72ab4a1e341b80d9081c2d77b100add5d49104 \
+    --hash=sha256:3d7333e907bff3e3997e54f89733ffa8d619842a3e1cd962bca34bdc11944c28 \
+    --hash=sha256:4795e93d130c9b7fb661f0cead49752ae6a980437df74b99d5918026c212443e \
+    --hash=sha256:490e19a45cd3cdd6dfe6b46019f7ffe1103500750b41b51996a870e7c1c5f066 \
+    --hash=sha256:4aa0fe08383f3e5fc7d2f8cf9b42ac778f4d53fd75bcd2799a858225954eab89 \
+    --hash=sha256:559326d8f3d904cd4aa61f6a392d5626f35eec6a9f6cc83bcddb0abf88c40516 \
+    --hash=sha256:5929c83bd8cb7572d1c17ffdbf0eac235bf3c4d53cde1950cf89d944eaf97525 \
+    --hash=sha256:5bfd21b6acb32e20d4e279c34405a34e63da345be4b2b6eabd683e1a88857406 \
+    --hash=sha256:613cf06313331f49dd7b85a5a24fbddb1156c9723b6921a231906241726e5aee \
+    --hash=sha256:66a8e1c1e899d15a2f7510e43527fba22d895e7f6058d027db3e3837d88a69de \
+    --hash=sha256:691a62926ba09f2653ec0908554b3635497efb7751c5d46b916cd1ebbb1d3c25 \
+    --hash=sha256:6c1fd18e45c39d5a4be4b0d6a20c141e43fe46daeb1b2e2f304ebae7015ab6e6 \
+    --hash=sha256:6c6a1e8f98de92e817491b50aa4d01d69a1b41a4ed3173747e8f16f0d4cf81cc \
+    --hash=sha256:6cf029b886cfb28a2701503b7c602b811f2daa45276bd6459b0c71e051deb497 \
+    --hash=sha256:71506116eac0d3e3598d6325b4b818c3a0f6acb3222b24d30ad726e8c4bf7ea8 \
+    --hash=sha256:7993164e8e9f78ec31d38c47850ca6ba5451788b5b49a8a2dbb3322b36b5693b \
+    --hash=sha256:7a5cc6bf60791d8274edfdfe2dd7cec3f00f656dcc92e2b0a9af06c8b18ce6a6 \
+    --hash=sha256:87c1cc1057d903b78a8257a7c5f497db6fd5284f5080392bd57b66031d7389a3 \
+    --hash=sha256:98376c75bd6c103c74396953084a5e0798ffe476aecbfcc51ec6d100a685ac38 \
+    --hash=sha256:a395524b0fafa10446d11e11acb4742e919523de58aac03b791f26d7a783bcf0 \
+    --hash=sha256:a5100a4be91b7d4b7c8fe16a3600bd0951e10205eb1066b6873afd3996b51ee4 \
+    --hash=sha256:a63a52221f8c73f82f4e00493351d987f594931198589287aee96f8da673cfd5 \
+    --hash=sha256:a89734a7bcb2ea3b6fd600a74d6fbcdb8d3fa3f7917dbd978e039710b5509c9c \
+    --hash=sha256:b165f5e6de1ccc964e863bd2035807a4d3bad3e0481f9db2dc52034d6ad4f9de \
+    --hash=sha256:b3845e4c2fa32963fb7f384ebbaa2761b0e6b96145239bf80e956d4aff4b071c \
+    --hash=sha256:b3b017d9103e7a7372a146773be32b184ff7330bd708d40b1f56f06a686756ed \
+    --hash=sha256:b6c6e4858d8c3f88e19b7aa94b6a7619108f0bee51da9fa67b0785a8b59955f9 \
+    --hash=sha256:bfad1202fb1f9140e3810cc607058395f59032d9128cc0d716900c78bea5f337 \
+    --hash=sha256:c01809fb602e2fefc8cbfb3b603bb59d2a2eaee8708410896d48a835ba00e7c5 \
+    --hash=sha256:cce8de9d48289927ed18aaa420740efd52b2cd9289da32e3799afbb3a02822e8 \
+    --hash=sha256:ce2bc1ea01200b6d8130ab917296d05d77a1a571ec6c1ee25cfca6d55cd5db4a \
+    --hash=sha256:d4601e2a8b46ffbf540601a4926fd6cc5aae8a13b36fdd467f1040f01f9edaed \
+    --hash=sha256:d556d1c256b3700b60b6b061664a667b2e49d599c2772d46a9f2348f2dc4ab5c \
+    --hash=sha256:ddf7453acd03b966624ebefdb38169b5bbbeea1a1a58c90b095667247f9de327 \
+    --hash=sha256:e781eeb65b2007af553389c8a7fb7bc53cb856118b0fcffb2c26b0f49561c686 \
+    --hash=sha256:e920c272cd9e70a6b10eae9203cc96845da142e1dd4482de9343dda3738a9862 \
+    --hash=sha256:f5b6174bf4bf9152e368561dff410203c6921e4dd2afbcda3283a95957158112 \
+    --hash=sha256:f69bd42fd2515060af69b120668213121264bb7976b113954b6f9db327727c65 \
+    --hash=sha256:f823d0f6b04a6797fbe253bcf91666e71a6b63c290683819650c68b2468ebe64 \
+    --hash=sha256:fa7e9f2e80a9535f9692e113d02b4268b5f88675a730d1b0ef0abeb74c9a4e80
+    # via -r .github/requirements/bench.in
 talipp==2.7.0 \
     --hash=sha256:567f59ad74366cb59a14a00d350f35fd9d22e6924d6228bad581e6dcf1de2205 \
     --hash=sha256:f749f22b9ad615605e71faf26457bb7f5e3fe16f04d3287f4ca54fd16bc3d4eb
     # via -r .github/requirements/bench.in
+tulipy==0.4.0 \
+    --hash=sha256:540704956b5b940a5f6306aa393a37536a6d7c3cbc07efe47512f3496e5203ab \
+    --hash=sha256:95542e40537afdd345d875baf37485eac993c6a819d00c51432e9de8df21eba8 \
+    --hash=sha256:fbc31727ef7657c93ad910bfdce65fecc6aaa7a5e961fe00240718e7a3fc79d8
+    # via -r .github/requirements/bench.in
 tzdata==2026.2 \
     --hash=sha256:9173fde7d80d9018e02a662e168e5a2d04f87c41ea174b139fbef642eda62d10 \
     --hash=sha256:bbe9af844f658da81a5f95019480da3a89415801f6cc966806612cc7169bffe7

.github/workflows/bench.yml

@@ -117,3 +117,29 @@ jobs:
         with:
           name: cross-library-bench
           path: bindings/python/benchmark.txt
+
+  rust-cross-bench:
+    name: Rust cross-library benchmark report
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false
+
+      - uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable branch, 2026-03-27
+
+      - uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
+        continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
+        timeout-minutes: 6
+
+      # Wickra vs the other Rust TA crates (kand, ta-rs, yata) on an identical
+      # candle series — the like-for-like engine comparison with no binding
+      # overhead. Streaming + batch, in crates/wickra-bench/benches/cross_lib.rs.
+      - name: Run Rust cross-library benchmark
+        run: cargo bench -p wickra-bench --bench cross_lib | tee rust_cross_bench.txt
+
+      - name: Upload Rust report
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
+        with:
+          name: rust-cross-bench
+          path: rust_cross_bench.txt

.github/workflows/ci.yml

@@ -53,6 +53,22 @@ jobs:
         continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
         timeout-minutes: 6
 
+      - name: Warm cargo registry (retry transient DNS/registry flakes)
+        shell: bash
+        # CARGO_NET_RETRY rides out short blips, but a longer runner DNS outage
+        # outlasts cargo's rapid in-process retries: the crates.io index fetch
+        # the first cargo step does ("Could not resolve host: index.crates.io")
+        # then fails the whole job. Pre-fetch the dependency graph here with real
+        # backoff so clippy/build/test resolve from the warmed local cache.
+        run: |
+          for attempt in 1 2 3 4 5; do
+            if cargo fetch; then exit 0; fi
+            echo "::warning::cargo fetch failed (attempt $attempt/5) — likely a registry/DNS flake; retrying in $((attempt * 20))s..."
+            sleep $((attempt * 20))
+          done
+          echo "::error::cargo fetch still failing after 5 attempts"
+          exit 1
+
       - name: Format check
         run: cargo fmt --all -- --check
 
@@ -232,6 +248,19 @@ jobs:
         continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
         timeout-minutes: 6
 
+      - name: Warm cargo registry (retry transient DNS/registry flakes)
+        shell: bash
+        # See the rust job: pre-fetch with backoff so the clippy index update
+        # can't fail the job on a transient "Could not resolve host" DNS blip.
+        run: |
+          for attempt in 1 2 3 4 5; do
+            if cargo fetch; then exit 0; fi
+            echo "::warning::cargo fetch failed (attempt $attempt/5) — likely a registry/DNS flake; retrying in $((attempt * 20))s..."
+            sleep $((attempt * 20))
+          done
+          echo "::error::cargo fetch still failing after 5 attempts"
+          exit 1
+
       - name: Clippy (bindings, all targets)
         run: cargo clippy -p wickra-node -p wickra-python --all-targets -- -D warnings
 
@@ -272,6 +301,19 @@ jobs:
         continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
         timeout-minutes: 6
 
+      - name: Warm cargo registry (retry transient DNS/registry flakes)
+        shell: bash
+        # See the rust job: pre-fetch with backoff so the first cargo step can't
+        # fail the job on a transient "Could not resolve host" DNS blip.
+        run: |
+          for attempt in 1 2 3 4 5; do
+            if cargo fetch; then exit 0; fi
+            echo "::warning::cargo fetch failed (attempt $attempt/5) — likely a registry/DNS flake; retrying in $((attempt * 20))s..."
+            sleep $((attempt * 20))
+          done
+          echo "::error::cargo fetch still failing after 5 attempts"
+          exit 1
+
       - name: Build on MSRV
         run: cargo build ${{ matrix.packages }} --verbose
 
@@ -580,6 +622,280 @@ jobs:
         working-directory: bindings/node
         run: node --test __tests__/
 
+  c-abi:
+    name: C ABI on ${{ matrix.os }}
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os: [ubuntu-latest, macos-latest, windows-latest]
+    steps:
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false
+
+      - name: Install Rust toolchain
+        uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable branch, 2026-03-27
+
+      - name: Cache cargo
+        uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
+        continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
+        timeout-minutes: 6
+
+      - name: Install cbindgen
+        uses: taiki-e/install-action@0fd46367812ee04360509b4169d9f659d6892bb2 # v2.79.15
+        timeout-minutes: 10 # fail fast on a stuck download instead of hanging the job
+        with:
+          tool: cbindgen
+
+      - name: Build the C ABI library (cdylib + staticlib)
+        run: cargo build -p wickra-c --release
+
+      - name: Rust unit tests
+        run: cargo test -p wickra-c
+
+      # The generated header is platform-independent, so checking drift on one OS
+      # is enough — and avoids a spurious CRLF/LF diff on the Windows runner.
+      - name: Check the committed header is in sync with cbindgen
+        if: runner.os == 'Linux'
+        shell: bash
+        run: |
+          cbindgen --config bindings/c/cbindgen.toml --crate wickra-c --output bindings/c/include/wickra.h
+          if ! git diff --quiet -- bindings/c/include/wickra.h; then
+            echo "::error::bindings/c/include/wickra.h is out of sync — run cbindgen and commit the result"
+            git --no-pager diff -- bindings/c/include/wickra.h
+            exit 1
+          fi
+
+      # The real cross-language test: a foreign C consumer links the generated
+      # header + the compiled library and runs. If this passes on all three OSes,
+      # every C-capable language can link the same way.
+      - name: Build and run the C smoke example (CMake + ctest)
+        shell: bash
+        run: |
+          cmake -S examples/c -B examples/c/build
+          cmake --build examples/c/build --config Release
+          ctest --test-dir examples/c/build -C Release --output-on-failure
+
+  csharp:
+    name: C# on ${{ matrix.os }}
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os: [ubuntu-latest, macos-latest, windows-latest]
+    steps:
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false
+
+      - name: Install Rust toolchain
+        uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable branch, 2026-03-27
+
+      - name: Cache cargo
+        uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
+        continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
+        timeout-minutes: 6
+
+      # The binding links against the C ABI hub at runtime; build it first so the
+      # DllImportResolver finds target/release/wickra.{dll,so,dylib}. .NET 8 SDK is
+      # preinstalled on the GitHub runners, so no setup-dotnet step is needed.
+      - name: Build the C ABI library
+        run: cargo build -p wickra-c --release
+
+      - name: .NET info
+        run: dotnet --info
+
+      - name: Test the C# binding
+        run: dotnet test bindings/csharp/Wickra.Tests/Wickra.Tests.csproj -c Release
+
+      - name: Build the C# examples
+        shell: bash
+        run: |
+          for d in streaming backtest multi_timeframe parallel_assets \
+                   strategy_rsi_mean_reversion strategy_macd_adx strategy_bollinger_squeeze \
+                   fetch_btcusdt live_binance; do
+            dotnet build "examples/csharp/$d" -c Release
+          done
+
+      # Run only the offline examples (fetch_btcusdt / live_binance need network).
+      - name: Run the offline C# examples
+        shell: bash
+        run: |
+          for d in streaming backtest multi_timeframe parallel_assets \
+                   strategy_rsi_mean_reversion strategy_macd_adx strategy_bollinger_squeeze; do
+            dotnet run --project "examples/csharp/$d" -c Release --no-build
+          done
+
+  go:
+    name: Go on ${{ matrix.os }}
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os: [ubuntu-latest, macos-latest, windows-latest]
+    steps:
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false
+
+      # Go is not reliably on PATH on every runner image, so install it
+      # explicitly. cache: false — the cargo build dominates and the modules
+      # have no external Go deps worth caching.
+      - name: Set up Go
+        id: setup-go
+        continue-on-error: true
+        uses: actions/setup-go@40f1582b2485089dde7abd97c1529aa768e1baff # v5
+        with:
+          go-version: "stable"
+          cache: false
+
+      - name: Retry Go setup (CDN flake)
+        if: steps.setup-go.outcome == 'failure'
+        shell: bash
+        run: |
+          echo "::warning::setup-go failed (likely CDN flake), waiting 30s before retry..."
+          sleep 30
+
+      - name: Set up Go (retry)
+        if: steps.setup-go.outcome == 'failure'
+        uses: actions/setup-go@40f1582b2485089dde7abd97c1529aa768e1baff # v5
+        with:
+          go-version: "stable"
+          cache: false
+
+      - name: Install Rust toolchain
+        uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable branch, 2026-03-27
+
+      - name: Cache cargo
+        uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
+        continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
+        timeout-minutes: 6
+
+      # The binding links against the C ABI hub via cgo; build it first and stage
+      # the platform library under bindings/go/lib so cgo's LDFLAGS find it. Go is
+      # preinstalled on the GitHub runners, so no setup-go step is needed.
+      - name: Build the C ABI library
+        run: cargo build -p wickra-c --release
+
+      - name: Stage the native library
+        shell: bash
+        run: |
+          mkdir -p bindings/go/lib
+          case "$RUNNER_OS" in
+            Linux)   cp target/release/libwickra.so    bindings/go/lib/ ;;
+            macOS)   cp target/release/libwickra.dylib  bindings/go/lib/ ;;
+            Windows) cp target/release/wickra.dll       bindings/go/lib/ ;;
+          esac
+
+      - name: Go info
+        run: go version
+
+      - name: Check gofmt
+        shell: bash
+        run: |
+          unformatted="$(gofmt -l bindings/go examples/go)"
+          if [ -n "$unformatted" ]; then
+            echo "gofmt needed on:"; echo "$unformatted"; exit 1
+          fi
+
+      - name: Vet and test the Go binding
+        shell: bash
+        # On Windows there is no rpath; the loader resolves wickra.dll via PATH.
+        run: |
+          export PATH="$PWD/bindings/go/lib:$PATH"
+          cd bindings/go
+          go vet ./...
+          go test ./...
+
+      - name: Build the Go examples
+        shell: bash
+        run: |
+          export PATH="$PWD/bindings/go/lib:$PATH"
+          cd examples/go
+          go build ./...
+
+      # Run only the offline examples (fetch_btcusdt / live_binance need network).
+      - name: Run the offline Go examples
+        shell: bash
+        run: |
+          export PATH="$PWD/bindings/go/lib:$PATH"
+          cd examples/go
+          for d in streaming backtest multi_timeframe parallel_assets \
+                   strategy_rsi_mean_reversion strategy_macd_adx strategy_bollinger_squeeze; do
+            go run "./$d"
+          done
+
+  r:
+    name: R on ${{ matrix.os }}
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os: [ubuntu-latest, macos-latest, windows-latest]
+    env:
+      WICKRA_INCLUDE_DIR: ${{ github.workspace }}/bindings/c/include
+      WICKRA_LIB_DIR: ${{ github.workspace }}/target/release
+    steps:
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false
+
+      - name: Install Rust toolchain
+        uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable branch, 2026-03-27
+
+      - name: Cache cargo
+        uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
+        continue-on-error: true
+        timeout-minutes: 6
+
+      # The binding compiles a thin .Call glue layer against the C ABI hub; build
+      # the library first. On Windows configure.win bundles a renamed copy
+      # (wickra_abi.dll) so the package's own wickra.dll does not collide with it.
+      - name: Build the C ABI library
+        run: cargo build -p wickra-c --release
+
+      - name: Set up R
+        uses: r-lib/actions/setup-r@a51a8012b0aab7c32ef9d19bf54da93f3254335e # v2
+        with:
+          r-version: "release"
+          use-public-rspm: true
+
+      # Use the repos configured by setup-r (use-public-rspm) so Linux installs
+      # binary packages — building testthat's deps from source is slow and flaky.
+      - name: Install test dependency
+        run: Rscript -e 'install.packages("testthat")'
+
+      - name: Install and test the R binding
+        shell: bash
+        # github.workspace is a backslash path on Windows; configure.win (sh) and
+        # mingw need forward slashes. On Linux/macOS the rpath points at
+        # WICKRA_LIB_DIR; export the loader path too as a belt-and-suspenders.
+        run: |
+          export WICKRA_INCLUDE_DIR="${WICKRA_INCLUDE_DIR//\\//}"
+          export WICKRA_LIB_DIR="${WICKRA_LIB_DIR//\\//}"
+          export LD_LIBRARY_PATH="$WICKRA_LIB_DIR:$LD_LIBRARY_PATH"
+          export DYLD_LIBRARY_PATH="$WICKRA_LIB_DIR:$DYLD_LIBRARY_PATH"
+          R CMD INSTALL bindings/r
+          Rscript -e 'library(testthat); library(wickra); test_dir("bindings/r/tests/testthat", stop_on_failure = TRUE)'
+
+      - name: Run the offline R examples
+        shell: bash
+        run: |
+          export WICKRA_LIB_DIR="${WICKRA_LIB_DIR//\\//}"
+          export LD_LIBRARY_PATH="$WICKRA_LIB_DIR:$LD_LIBRARY_PATH"
+          export DYLD_LIBRARY_PATH="$WICKRA_LIB_DIR:$DYLD_LIBRARY_PATH"
+          cd examples/r
+          for f in streaming backtest multi_timeframe parallel_assets \
+                   strategy_rsi_mean_reversion strategy_macd_adx strategy_bollinger_squeeze; do
+            Rscript "$f.R"
+          done
+
+      # fetch_btcusdt / live_binance need the network (and jsonlite / websocket);
+      # build-check that they parse without running them.
+      - name: Parse the network R examples
+        run: Rscript -e 'invisible(lapply(c("examples/r/fetch_btcusdt.R", "examples/r/live_binance.R"), parse)); cat("network R examples parse OK\n")'
+
   # The cross-library benchmark has moved to a dedicated scheduled workflow
   # (.github/workflows/bench.yml) — see audit finding R10. It runs nightly
   # at 03:00 UTC and on-demand via `workflow_dispatch`, and is no longer on

.github/workflows/release.yml

@@ -569,9 +569,146 @@ jobs:
   # the old "publish, then upload provenance" order would have the provenance
   # upload rejected once immutability is enabled.
   # --------------------------------------------------------------------------
+  # --------------------------------------------------------------------------
+  # C ABI native libraries (bindings/c) — built per target on a native runner
+  # (no cross toolchain needed) and attached to the GitHub Release as the
+  # distribution channel. There is no package registry for the C ABI.
+  # --------------------------------------------------------------------------
+  c-abi-build:
+    name: C ABI library (${{ matrix.target }})
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - { host: ubuntu-latest, target: x86_64-unknown-linux-gnu }
+          - { host: ubuntu-24.04-arm, target: aarch64-unknown-linux-gnu }
+          - { host: macos-latest, target: x86_64-apple-darwin }
+          - { host: macos-latest, target: aarch64-apple-darwin }
+          - { host: windows-latest, target: x86_64-pc-windows-msvc }
+          - { host: windows-11-arm, target: aarch64-pc-windows-msvc }
+    runs-on: ${{ matrix.host }}
+    steps:
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false
+
+      - uses: dtolnay/rust-toolchain@29eef336d9b2848a0b548edc03f92a220660cdb8 # stable branch, 2026-03-27
+        with:
+          targets: ${{ matrix.target }}
+
+      - uses: Swatinem/rust-cache@e18b497796c12c097a38f9edb9d0641fb99eee32 # v2
+        continue-on-error: true # cache is an optimisation; never block on a stuck/slow restore
+        timeout-minutes: 6
+
+      - name: Build the C ABI library (cdylib + staticlib)
+        run: cargo build -p wickra-c --release --target ${{ matrix.target }}
+
+      - name: Package header + libraries
+        shell: bash
+        run: |
+          set -e
+          dir="wickra-c-${{ matrix.target }}"
+          mkdir -p "$dir/include" "$dir/lib"
+          cp bindings/c/include/wickra.h bindings/c/include/wickra.hpp "$dir/include/"
+          for f in libwickra.so libwickra.a libwickra.dylib wickra.dll wickra.dll.lib wickra.lib; do
+            src="target/${{ matrix.target }}/release/$f"
+            [ -f "$src" ] && cp "$src" "$dir/lib/"
+          done
+          tar -czf "$dir.tar.gz" "$dir"
+          echo "packaged $dir:"; ls -lR "$dir"
+
+      - name: Upload artifact
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
+        with:
+          name: c-abi-${{ matrix.target }}
+          path: wickra-c-${{ matrix.target }}.tar.gz
+          if-no-files-found: error
+
+  # Pack and publish the .NET binding to NuGet. Independent of the GitHub-release
+  # job so a C# hiccup never blocks the C/C++ asset release. Authentication uses
+  # NuGet Trusted Publishing (OIDC) — no long-lived API key. The 'wickra-release'
+  # trusted-publishing policy on nuget.org (owner KingchenC, repo wickra-lib/wickra,
+  # workflow release.yml) exchanges the GitHub OIDC token for a short-lived key.
+  csharp-publish:
+    name: Publish to NuGet
+    needs: c-abi-build
+    runs-on: ubuntu-latest
+    environment: release
+    permissions:
+      contents: read
+      id-token: write # request the GitHub OIDC token for trusted publishing
+    steps:
+      - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
+        with:
+          persist-credentials: false
+
+      - name: Download the C ABI native libraries
+        uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1
+        with:
+          pattern: c-abi-*
+          path: c-abi-artifacts
+
+      - name: Stage native libraries into runtimes/<rid>/native
+        shell: bash
+        run: |
+          set -e
+          declare -A RID=(
+            [x86_64-unknown-linux-gnu]=linux-x64
+            [aarch64-unknown-linux-gnu]=linux-arm64
+            [x86_64-apple-darwin]=osx-x64
+            [aarch64-apple-darwin]=osx-arm64
+            [x86_64-pc-windows-msvc]=win-x64
+            [aarch64-pc-windows-msvc]=win-arm64
+          )
+          base=bindings/csharp/Wickra/runtimes
+          for target in "${!RID[@]}"; do
+            archive=$(find c-abi-artifacts -name "wickra-c-$target.tar.gz" | head -1)
+            if [ -z "$archive" ]; then
+              echo "::error::missing native artifact for $target"; exit 1
+            fi
+            tmp=$(mktemp -d); tar -xzf "$archive" -C "$tmp"
+            dest="$base/${RID[$target]}/native"; mkdir -p "$dest"
+            for f in libwickra.so libwickra.dylib wickra.dll; do
+              src=$(find "$tmp" -name "$f" | head -1)
+              [ -n "$src" ] && cp "$src" "$dest/"
+            done
+            echo "staged ${RID[$target]}:"; ls -l "$dest"
+          done
+
+      - name: Pack
+        shell: bash
+        run: |
+          version="${GITHUB_REF_NAME#v}"
+          dotnet pack bindings/csharp/Wickra/Wickra.csproj -c Release -p:Version="$version" -o nupkg
+
+      # Exchange the GitHub OIDC token for a short-lived (~1h) NuGet API key.
+      # 'user' is the nuget.org profile name (the package owner), not an email.
+      - name: NuGet login (OIDC -> temporary API key)
+        uses: NuGet/login@8d196754b4036150537f80ac539e15c2f1028841 # v1.2.0
+        id: nuget_login
+        with:
+          user: KingchenC
+
+      # Pass the temporary key through the environment (not string-interpolated
+      # into the script) so it cannot be parsed as shell — avoids template injection.
+      - name: Push to NuGet
+        shell: bash
+        env:
+          NUGET_API_KEY: ${{ steps.nuget_login.outputs.NUGET_API_KEY }}
+        run: |
+          dotnet nuget push "nupkg/*.nupkg" --api-key "$NUGET_API_KEY" \
+            --source https://api.nuget.org/v3/index.json --skip-duplicate
+
+      - name: Upload the NuGet package as a build artifact
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
+        with:
+          name: nuget-package
+          path: nupkg/*.nupkg
+          if-no-files-found: error
+
   github-release:
     name: Attach assets to the draft GitHub Release
-    needs: [cargo-publish, python-publish, node-publish, wasm-publish]
+    needs: [cargo-publish, python-publish, node-publish, wasm-publish, c-abi-build]
     runs-on: ubuntu-latest
     permissions:
       contents: write
@@ -644,7 +781,7 @@ jobs:
           # the provenance bundle is attached (P24, immutability-ready).
           draft: true
           body: |
-            Wickra ${{ github.ref_name }} — streaming-first technical indicators across 4 language registries.
+            Wickra ${{ github.ref_name }} — streaming-first technical indicators across 4 language registries plus a C ABI.
 
             ### Install
 
@@ -665,6 +802,9 @@ jobs:
               darwin-arm64, win32-x64-msvc)
             - `wickra-*.tgz` — npm-pack tarballs (main package + per-platform subpackages + WASM)
             - `*.crate` — cargo source crates (wickra-core, wickra-data, wickra)
+            - `wickra-c-<target>.tar.gz` — C ABI: `include/wickra.h` + `wickra.hpp`
+              and the cdylib/staticlib per target (linux/macos/windows × x64/arm64),
+              the hub for C / C++ / Go / C# / Java / R
 
             ### Auto-generated changelog
 

.github/workflows/sync-about.yml

@@ -9,7 +9,7 @@ name: Sync indicator count
 #   2. GitHub repo "About" description       — synced on push to main / v* tag
 #   3. Docs site: index.md / overview.md / Indicators-Overview.md
 #      (wickra-lib/wickra-docs) — synced on push to main / v* tag*
-#   4. Marketing site count (wickra-lib/webpage: index.md /
+#   4. Marketing site count (wickra-lib/webpage: index.md / about.md /
 #      .vitepress/config.ts) — push to main / v* tag*
 #   5. org profile README count (wickra-lib/.github, profile/README.md)
 #                                            — synced on push to main / v* tag*
@@ -42,10 +42,10 @@ name: Sync indicator count
 # single source of truth for what the bindings reach.
 #
 # Design: on PRs this workflow is a READ-ONLY check. The indicator wiring
-# (ScriptHelpers/_common.py wire_readme_counter) bumps both README.md and
-# docs/README.md inside the author's code commit, so the counter is already
-# correct by the time CI runs. If it is not, the check below fails loud and
-# asks the author to re-run the wiring — it never pushes a fix-up commit.
+# bumps both README.md and docs/README.md inside the author's code commit, so
+# the counter is already correct by the time CI runs. If it is not, the check
+# below fails loud and asks the author to re-run the wiring — it never pushes a
+# fix-up commit.
 #
 # (An earlier version pushed a GITHUB_TOKEN "sync indicator count" commit to
 # the PR head. Because GITHUB_TOKEN pushes trigger no workflows, that commit
@@ -86,10 +86,17 @@ jobs:
       # merge ref) so the counter check validates exactly what will land. On
       # push events we check out the default ref. No push is made, so a shallow
       # checkout is enough.
+      #
+      # Check out by head SHA, not head ref (branch name): a fast `gh pr merge
+      # --squash --delete-branch` deletes the head branch the moment the PR
+      # merges, often before this queued read-only check reaches its checkout.
+      # Fetching the now-gone `refs/heads/<branch>` then fails the run (exit 1).
+      # The head SHA stays reachable via `refs/pull/N/head` after the branch is
+      # gone, so the checkout — and the run — survives an instant merge.
       - uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
         with:
           fetch-depth: 1
-          ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.ref || github.ref }}
+          ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.ref }}
           repository: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.repo.full_name || github.repository }}
 
       - name: Count indicators
@@ -149,7 +156,7 @@ jobs:
           # actually live (Cloudflare Pages, P8.1); merging this PR is therefore
           # gated on the domain resolving, otherwise the About link would 404.
           homepage="https://docs.wickra.org"
-          desc="Streaming-first technical indicators with a Rust core and Python, Node.js, and WebAssembly bindings. ${n} indicators, O(1) per-tick updates, no system dependencies. Drop-in TA-Lib replacement."
+          desc="Streaming-first technical indicators with a Rust core and Python, Node.js, WebAssembly, C ABI, .NET, Go, and R bindings. ${n} indicators, O(1) per-tick updates, no system dependencies. Drop-in TA-Lib replacement."
           # Enforce the homepage unconditionally — it is a constant, so this both
           # corrects the stale kingchenc URL and self-heals any future drift.
           # Same Administration-write permission as --description (no extra scope).
@@ -180,14 +187,14 @@ jobs:
             exit 0
           fi
           cd docs-count
-          sed -i -E "s/[0-9]+ (streaming-first )?indicators/${n} \1indicators/g" index.md overview.md Indicators-Overview.md
+          sed -i -E "s/[0-9]+ (streaming-first )?indicators/${n} \1indicators/g" index.md overview.md Indicators-Overview.md .vitepress/config.ts
           if git diff --quiet; then
             echo "Docs indicator count unchanged."
             exit 0
           fi
           git config user.name "wickra-bot"
           git config user.email "wickra-bot@users.noreply.github.com"
-          git add index.md overview.md Indicators-Overview.md
+          git add index.md overview.md Indicators-Overview.md .vitepress/config.ts
           git commit -m "chore: sync indicator count to ${n}"
           if ! git push 2>/dev/null; then
             echo "::warning::push to wickra-lib/wickra-docs failed — ABOUT_SYNC_TOKEN likely lacks write (findings P10.0a)."
@@ -366,14 +373,14 @@ jobs:
             exit 0
           fi
           cd webpage-count
-          sed -i -E "s/[0-9]+ (streaming-first )?indicators/${n} \1indicators/g" index.md .vitepress/config.ts
+          sed -i -E "s/[0-9]+ (streaming-first )?indicators/${n} \1indicators/g" index.md about.md .vitepress/config.ts
           if git diff --quiet; then
             echo "Webpage indicator count unchanged."
             exit 0
           fi
           git config user.name "wickra-bot"
           git config user.email "wickra-bot@users.noreply.github.com"
-          git add index.md .vitepress/config.ts
+          git add index.md about.md .vitepress/config.ts
           git commit -m "chore: sync indicator count to ${n}"
           if ! git push 2>/dev/null; then
             echo "::warning::push to wickra-lib/webpage failed — ABOUT_SYNC_TOKEN likely lacks write (findings P10.0a)."

ARCHITECTURE.md

@@ -27,16 +27,29 @@ or replace lives behind a separate crate boundary.
    │   no I/O, no deps    │            │  optional features │
    └──────────────────────┘            └────────────────────┘
                 ▲
-                │ (every binding wraps the same core)
-                │
-   ┌────────────┴───────────┬─────────────────────┐
-   │                        │                     │
-┌──▼──────┐         ┌───────▼──────┐      ┌───────▼────────┐
-│ Python  │         │     Node     │      │     WASM       │
-│ (PyO3)  │         │ (napi-rs)    │      │ (wasm-bindgen) │
-└─────────┘         └──────────────┘      └────────────────┘
+                │  every binding wraps the same core
+   ┌────────────┼────────────┬────────────────┐
+   │            │            │                │
+┌──▼───────┐ ┌──▼───────┐ ┌──▼───────────┐ ┌──▼──────────────────┐
+│  Python  │ │   Node   │ │     WASM     │ │  C ABI (cbindgen)   │
+│  (PyO3)  │ │ (napi-rs)│ │(wasm-bindgen)│ │   cdylib + header   │
+└──────────┘ └──────────┘ └──────────────┘ └─────────┬───────────┘
+                                                     │  linked by
+                                          ┌──────────▼──────────┐
+                                          │  C · C++ · C# · Go  │
+                                          │     · Java · R      │
+                                          └─────────────────────┘
 ```
 
+Python, Node and WASM are *native* Rust bindings (PyO3 / napi-rs /
+wasm-bindgen). The C ABI is the *hub* every other C-capable language links
+against: it builds to a `cdylib`/`staticlib` plus a generated `wickra.h`, and
+downstream languages link that one artifact rather than each re-wrapping the
+core. C and C++ link it directly; the **C# / .NET** binding (`bindings/csharp`,
+on NuGet), the **Go** binding (`bindings/go`, cgo) and the **R** binding
+(`bindings/r`, `.Call`) are generated from `wickra.h`, with Java planned the
+same way.
+
 | Crate | Path | What it owns | Public deps |
 |---|---|---|---|
 | `wickra-core` | `crates/wickra-core` | every indicator, the `Indicator` trait, `BatchExt`, `Candle`/`Tick` types, `Error` | `thiserror`, `rayon` (parallel batch) |
@@ -45,6 +58,7 @@ or replace lives behind a separate crate boundary.
 | `wickra-python` | `bindings/python` | `_wickra` PyO3 module + Python package | `pyo3`, `numpy`, depends on `wickra-core` |
 | `wickra-node` | `bindings/node` | NAPI-RS native binding | `napi`, depends on `wickra-core` |
 | `wickra-wasm` | `bindings/wasm` | WebAssembly binding | `wasm-bindgen`, depends on `wickra-core` |
+| `wickra-c` | `bindings/c` | C ABI hub — `cdylib`/`staticlib` + generated `wickra.h` (cbindgen) | depends on `wickra-core` |
 | `wickra-examples` | `examples/rust` | runnable binary examples | depends on `wickra`, `wickra-data` |
 
 The `fuzz/` directory is **excluded** from the workspace (it has its own

BENCHMARKS.md

@@ -0,0 +1,96 @@
+# Benchmarks
+
+Read these as **relative** speedups on identical input — absolute µs depend on
+CPU, memory clock and OS scheduler, not a universal contract. **Streaming is the
+headline**: it is where Wickra's design pays off and where the gap is measured in
+orders of magnitude, not percent. The batch numbers come second and are shown
+honestly — the leanest crates edge Wickra out on the simple recurrences, and that
+is a deliberate trade for warmup/NaN semantics, not a ceiling.
+
+- **Reproduced on:** Windows 11 Pro 26200, AMD Ryzen 9 9950X, 64 GB DDR5,
+  Rust 1.92 (release: `lto = "fat"`, `codegen-units = 1`), Python 3.12.
+- **Reproduce yourself:**
+  - Rust core vs Rust crates: `cargo bench -p wickra-bench`
+  - Python vs Python libs: `pip install -e bindings/python[bench]` then
+    `python -m benchmarks.compare_libraries` (auto-detects installed peers).
+
+## 1. Streaming — the structural win
+
+Live trading feeds one tick at a time. Wickra updates every indicator in **O(1)**;
+batch-only libraries (TA-Lib, tulipy, finta, pandas-ta) have no incremental API
+and must recompute the whole history on every tick. Only `talipp` (Python) and
+`ta-rs` / `yata` (Rust) carry real per-tick state. This is the gap the library
+was built to expose.
+
+**Python — per-tick latency** (seed 5 000 bars, then feed ticks one at a time):
+
+| Indicator        | **★ Wickra** | talipp           | TA-Lib (recompute)    |
+|------------------|------------------:|------------------|-----------------------|
+| SMA(20)          | **0.089 µs ★**    | 0.96 µs (11×)    | 422 µs (4 700×)       |
+| EMA(20)          | **0.111 µs ★**    | 1.19 µs (11×)    | 430 µs (3 900×)       |
+| RSI(14)          | **0.061 µs ★**    | 0.95 µs (16×)    | 298 µs (4 900×)       |
+| MACD(12, 26, 9)  | **0.079 µs ★**    | 3.30 µs (42×)    | 327 µs (4 100×)       |
+| Bollinger(20, 2) | **0.089 µs ★**    | 4.97 µs (56×)    | 296 µs (3 300×)       |
+
+Against the only other incremental Python peer Wickra is **11–56× faster**;
+against the recompute-on-every-tick libraries it is **2 800–19 000× faster**
+(`finta` RSI hits 19 000×). tulipy / pandas-ta land in the same recompute band
+as TA-Lib.
+
+**Rust — per-tick latency** (whole 50 000-bar series, lower = faster):
+
+| Indicator        | **★ Wickra** | kand | ta-rs | yata |
+|------------------|------------------:|-----:|------:|-----:|
+| SMA(20)          | 50                | 38   | 47    | 38   |
+| EMA(20)          | 154               | 69   | 56    | 69   |
+| RSI(14)          | 164               | 216  | 74    | —    |
+| MACD(12, 26, 9)  | 275               | 143  | 66    | —    |
+| Bollinger(20, 2) | **128 ★**         | 248  | 168   | —    |
+| ATR(14)          | 152               | 166  | 61    | —    |
+
+`ta-rs` hands back a bare `f64` from the first tick with no warmup and no
+validation; it leads several rows by giving those guarantees up. Against `kand`,
+Wickra wins streaming RSI, Bollinger and ATR. `yata` exposes only SMA/EMA as
+raw-value methods, so its other rows are omitted rather than faked.
+
+## 2. Batch — competitive, not the headline
+
+Whole series in one call. Here hand-tuned C (`tulipy`, TA-Lib) and the leanest
+Rust crate (`kand`) win the simple recurrences — Wickra trades a few µs per pass
+for the `None`-warmup, NaN-safety and bit-exact `batch == streaming` guarantees
+none of them keep. It still wins several rows outright and beats the rest of the
+field everywhere.
+
+**Python** (20 000-bar pass, µs/op, lower = faster):
+
+| Indicator        | Wickra   | TA-Lib   | tulipy   | pandas-ta | finta    |
+|------------------|---------:|---------:|---------:|----------:|---------:|
+| SMA(20)          | 22.2     | **15.6** | 15.9     | 32.7      | 290.1    |
+| EMA(20)          | 30.5     | **30.4** | 30.9     | 46.7      | 198.5    |
+| RSI(14)          | 52.3     | 72.0     | **34.2** | 88.8      | 812.3    |
+| MACD(12, 26, 9)  | 129.8    | 111.1    | **38.4** | 286.8     | 716.7    |
+| Bollinger(20, 2) | 87.2     | 74.6     | **37.9** | 474.3     | 1255.5   |
+| ATR(14)          | 74.7     | 87.3     | **35.5** | —         | 3496.4   |
+
+Wickra beats pandas-ta and finta on every row and TA-Lib on RSI and ATR;
+tulipy's SIMD C (and TA-Lib on SMA/EMA) lead the remaining rows.
+
+**Rust** (50 000-bar pass, µs, lower = faster). Only Wickra and `kand` expose a
+batch API; `ta-rs` and `yata` are streaming-only:
+
+| Indicator        | **★ Wickra** | kand   |
+|------------------|------------------:|-------:|
+| SMA(20)          | 53                | **41** |
+| EMA(20)          | 111               | **71** |
+| RSI(14)          | **221 ★**         | 259    |
+| MACD(12, 26, 9)  | 533               | **327** |
+| Bollinger(20, 2) | **404 ★**         | 460    |
+| ATR(14)          | **122 ★**         | 169    |
+
+Run the suite yourself:
+
+```bash
+cargo bench -p wickra-bench            # Rust core vs kand / ta-rs / yata
+pip install -e bindings/python[bench]  # Python peers
+python -m benchmarks.compare_libraries
+```

CHANGELOG.md

@@ -5,7 +5,198 @@ All notable changes to Wickra are documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
-## [Unreleased]
+## [0.7.8] - 2026-06-09
+### Added
+- **R binding (`bindings/r`)** — an R package reaching the C ABI hub through R's
+  native `.Call` interface, exposing all 514 indicators as constructors that
+  return a `wickra_indicator` object with `update`/`batch`/`reset` methods. The
+  C glue and R wrappers are generated from `wickra.h`; the native handle is freed
+  by a registered finalizer. Ships a full example suite mirroring the C, C# and
+  Go examples; distributed for r-universe / source install.
+
+## [0.7.7] - 2026-06-09
+### Added
+- **Go binding (`bindings/go`)** — a cgo binding over the C ABI hub exposing all
+  514 indicators as idiomatic types with `New<Indicator>` constructors and
+  `Update`/`Batch`/`Reset`/`Close` methods, generated from `wickra.h`. Handles are
+  freed by `Close()` with a `runtime.SetFinalizer` backstop. Ships a full example
+  suite mirroring the C and C# examples; distributed as a subdirectory module
+  (`go get github.com/wickra-lib/wickra/bindings/go`).
+
+## [0.7.6] - 2026-06-09
+### Added
+- **C# / .NET binding (`bindings/csharp`)** — the first language stecker on the
+  C ABI hub. Exposes all 514 indicators as idiomatic `IDisposable` classes via
+  `[LibraryImport]` source-generated P/Invoke, generated from `wickra.h`. Ships
+  on NuGet as `Wickra` with prebuilt native libraries for six target triples
+  (win/linux/osx × x64/arm64), plus a full example suite mirroring the C examples.
+
+## [0.7.5] - 2026-06-09
+### Added
+- **C ABI (`bindings/c`)** — a `cdylib` + `staticlib` plus a generated
+  `include/wickra.h` exposing all 514 indicators and 10 bar builders over an
+  opaque-handle C ABI: the hub any C-capable language (C, C++, Go, C#, Java, R)
+  links against, complementing the native Python/Node/WASM bindings. Ships a
+  full example suite (streaming, backtest, multi-timeframe, OpenMP parallel
+  fan-out, three educational strategies, and Binance fetch/live over `curl`)
+  mirroring the other bindings, plus an optional `wickra.hpp` C++ RAII wrapper.
+
+## [0.7.4] - 2026-06-08
+- **Three-Line Break** — Three-line-break bars (reversal needs N-line break) (`THREE_LINE_BREAK_BARS`).
+- **Run** — Run bars (consecutive same-direction tick runs) (`RUN_BARS`).
+- **Imbalance** — Imbalance bars (tick-rule signed imbalance threshold) (`IMBALANCE_BARS`).
+- **Dollar** — Dollar bars (fixed traded value per bar, Lopez de Prado) (`DOLLAR_BARS`).
+- **Volume** — Volume bars (fixed traded volume per bar) (`VOLUME_BARS`).
+- **Tick** — Tick bars (fixed candle count per bar) (`TICK_BARS`).
+- **Range** — Range bars (fixed price-range bricks) (`RANGE_BARS`).
+
+## [0.7.3] - 2026-06-08
+- **M2Measure** — M2 measure (Modigliani; Sharpe expressed in benchmark return units) (`M2Measure`).
+- **UpsidePotentialRatio** — Upside Potential Ratio (upside mean over downside deviation) (`UpsidePotentialRatio`).
+- **GainToPainRatio** — Gain-to-Pain Ratio (sum of returns over sum of losses) (`GainToPainRatio`).
+- **CommonSenseRatio** — Common Sense Ratio (tail ratio times gain-to-pain) (`CommonSenseRatio`).
+- **KRatio** — K-Ratio (Kestner; equity-curve slope over its standard error) (`KRatio`).
+- **TailRatio** — Tail Ratio (95th over absolute 5th return percentile) (`TailRatio`).
+- **MartinRatio** — Martin Ratio (Ulcer Performance Index; return over RMS drawdown) (`MartinRatio`).
+- **BurkeRatio** — Burke Ratio (return over root-sum-squared drawdowns) (`BurkeRatio`).
+- **SterlingRatio** — Sterling Ratio (mean return over average drawdown) (`SterlingRatio`).
+
+## [0.7.2] - 2026-06-08
+- **Composite Profile** — multi-session composite volume profile exposing POC, VAH and VAL (`CompositeProfile`).
+- **High/Low Volume Nodes** — highest- and lowest-volume price nodes in the profile (`HighLowVolumeNodes`).
+- **Profile Shape** — profile shape classification (b/P/D normal) as a numeric code (`ProfileShape`).
+- **Single Prints** — count of single-print (low-activity) price levels in the profile (`SinglePrints`).
+- **Naked POC** — most recent untouched (naked) point of control level (`NakedPoc`).
+
+## [0.7.1] - 2026-06-08
+- **Open-Interest Momentum** — rate-of-change of open interest over a rolling window (`OpenInterestMomentum`).
+- **Funding-Implied APR** — annualised funding rate (per-interval funding times intervals per year) (`FundingImpliedApr`).
+- **Perpetual Premium Index** — relative premium of the mark price over the index price (`PerpetualPremiumIndex`).
+- **OI-to-Volume Ratio** — open interest divided by taker volume (position turnover proxy) (`OiToVolumeRatio`).
+- **Estimated Leverage Ratio** — open interest divided by aggregate long+short position size (leverage proxy) (`EstimatedLeverageRatio`).
+
+## [0.7.0] - 2026-06-08
+- **Hasbrouck Information Share** — variance-ratio proxy for each venue's share of price discovery (Hasbrouck information share) (`HasbrouckInformationShare`).
+- **PIN** — probability of informed trading from rolling buy/sell imbalance (EKOP single-window estimator) (`Pin`).
+- **Trade-Sign Autocorrelation** — lag-1 autocorrelation of the signed trade aggressor (order-flow persistence) (`TradeSignAutocorrelation`).
+
+## [0.6.9] - 2026-06-08
+- **Tristar** — a three-doji star reversal: three consecutive dojis with the middle gapped above (bearish) or below (bullish) its neighbours (`Tristar`).
+- **Harami Cross** — a Harami whose second candle is a contained doji, a stronger reversal than a plain Harami (`HaramiCross`).
+- **Tower Top/Bottom** — a tall bar, a small pause bar, then a tall opposite bar marking a reversal (`TowerTopBottom`).
+- **Frying Pan Bottom** — a rounded (U-shaped) accumulation base over the lookback window, confirmed when price recovers above the rim (`FryPanBottom`).
+- **Dumpling Top** — a rounded (dome-shaped) distribution top over the lookback window, confirmed when price breaks below the start (`DumplingTop`).
+- **New Price Lines** — flags a run of N consecutive new closing highs (+1) or lows (-1), the eight/ten-new-price-lines exhaustion gauge (`NewPriceLines`).
+
+## [0.6.8] - 2026-06-08
+- **Smoothed Heikin-Ashi** — a Heikin-Ashi candle computed from EMA-smoothed OHLC, damping noise into a cleaner trend candle (`SmoothedHeikinAshi`).
+- **Heikin-Ashi Oscillator** — the Heikin-Ashi candle body (`ha_close − ha_open`), optionally EMA-smoothed, as a zero-line oscillator (`HeikinAshiOscillator`).
+- **Three Line Break** — the trend direction of a line-break chart, reversing only when the close breaks the extreme of the last N lines (`ThreeLineBreak`).
+- **Equivolume** — a chart box whose height is the bar range and whose width is volume-relative, fusing price range with activity (`Equivolume`).
+- **CandleVolume** — a candle whose body is close-minus-open and whose width is volume-relative, a volume-weighted candle chart (`CandleVolume`).
+
+## [0.6.7] - 2026-06-08
+- **TD Camouflage** — a DeMark qualifier flagging hidden intrabar strength or weakness against the prior close (`TDCamouflage`).
+- **TD Clop** — a DeMark two-bar open/close engulfing reversal where the bar opens beyond and closes back across the prior body (`TDClop`).
+- **TD Clopwin** — the inside-body cousin of TD Clop, marking a compression bar whose direction hints at the next move (`TDClopwin`).
+- **TD Propulsion** — a DeMark continuation thrust that opens on the trend side and closes beyond the prior bar's extreme (`TDPropulsion`).
+- **TD Trap** — an inside ("trap") bar followed by a close beyond its range, triggering a directional breakout signal (`TDTrap`).
+- **TD D-Wave** — a streaming Elliott-style swing-wave counter labelling the market's 1–5 impulse / A–C correction sequence (`TDDWave`).
+- **TD Moving Averages** — the DeMark ST1 (fast) and ST2 (slow) median-price trend ribbon whose crossover frames the trend (`TDMovingAverage`).
+
+## [0.6.6] - 2026-06-08
+- **Pivot Reversal** — a breakout signal when price closes through the most recently confirmed swing pivot (`PIVOT_REVERSAL`).
+- **Volume-Weighted Support/Resistance** — a band whose edges are the volume-weighted average of recent highs and lows (`VOLUME_WEIGHTED_SR`).
+- **Andrews Pitchfork** — median line and two parallels projected from the last three swing pivots (`ANDREWS_PITCHFORK`).
+- **Murrey Math Lines** — T. H. Murrey's eighths grid over the recent trading range, each level acting as support/resistance (`MURREY_MATH_LINES`).
+- **Central Pivot Range** — the classic pivot flanked by two central levels gauging the day's expected character (`CENTRAL_PIVOT_RANGE`).
+- **Faster scalar batch paths** — `Ema`, `Rsi`, `BollingerBands`, `MacdIndicator` and `Atr` gained dedicated batch fast paths (used by the Python bindings) that strip per-element `Option`/validation overhead and the intermediate `Vec<Option<_>>` allocation, while staying *bit-for-bit* equal to replaying `update` (including the SMA/Bollinger drift-reseed). Python batch is ~2× faster on EMA/RSI/MACD/ATR; streaming is unchanged.
+- **Cross-library benchmark refresh** — `benchmarks/compare_libraries.py` now measures the median across timing rounds (`--rounds` / `--streaming-rounds`), adds `--skip-batch` / `--skip-streaming`, and drives every peer through the streaming arena (recompute for batch-only libraries). `wickra-bench` compares the batch fast paths against `kand`.
+
+## [0.6.5] - 2026-06-07
+- **Autocorrelation Periodogram** — Ehlers autocorrelation periodogram: dominant cycle period estimate (`AUTOCORRPGRAM`).
+- **Even Better Sinewave** — Ehlers Even Better Sinewave: normalized cycle-phase oscillator (`EVENBETTERSINE`).
+- **Bandpass Filter** — Ehlers bandpass filter: isolates a frequency band around the dominant cycle (`BANDPASS`).
+- **Adaptive CCI** — Adaptive CCI: efficiency-ratio-adaptive CCI on typical price (`ADAPTIVECCI`).
+- **Universal Oscillator** — Ehlers Universal Oscillator: SuperSmoother-based normalized cycle oscillator (`UNIVERSALOSC`).
+- **Adaptive RSI** — Adaptive RSI: dominant-cycle-tuned RSI length (Ehlers) (`ADAPTIVERSI`).
+- **Correlation Trend Indicator** — Ehlers Correlation Trend Indicator: Pearson correlation of price vs time (`CTI`).
+- **Trendflex** — Ehlers Trendflex: trend-following companion to Reflex (`TRENDFLEX`).
+- **Reflex** — Ehlers Reflex: trend-cycle oscillator measuring slope-adjusted displacement (`REFLEX`).
+- **Highpass Filter** — Ehlers highpass filter: removes low-frequency trend, leaving cyclic component (`HIGHPASS`).
+
+## [0.6.4] - 2026-06-07
+- **Kendall Tau** — Kendall rank correlation (tau-b) over a rolling window of paired observations (`KENDALLTAU`).
+- **Sample Entropy** — Sample entropy: regularity/complexity of a rolling series (Richman-Moorman) (`SAMPLEENT`).
+- **Shannon Entropy** — Shannon entropy of a rolling value distribution over fixed bins (`SHANNONENT`).
+- **Rolling Min-Max Scaler** — Rolling min-max scaler mapping the latest value to 0..1 over a rolling window (`ROLLINGMINMAX`).
+- **Jarque-Bera** — Jarque-Bera normality test statistic over a rolling window (`JARQUEBERA`).
+
+## [0.6.3] - 2026-06-07
+- **Volume-Weighted MACD** — Volume-Weighted MACD: MACD computed on VWMA instead of EMA, with signal line and histogram (`VWMACD`).
+- **Better Volume** — Better Volume (VSA): classifies volume against bar spread to surface effort/result imbalance (`BETTERVOL`).
+- **Intraday Intensity Index** — Intraday Intensity Index: volume weighted by close position within the bar range (`INTRADAYINT`).
+- **Trade Volume Index** — Trade Volume Index: accumulates volume by tick direction past a min-tick threshold (distinct from TSV) (`TRADEVOLIDX`).
+- **Twiggs Money Flow** — Twiggs Money Flow: volume-weighted accumulation using true range and Wilder smoothing (distinct from CMF) (`TWIGGSMF`).
+- **Williams Accumulation/Distribution** — Williams Accumulation/Distribution: cumulative price-direction accumulator (distinct from Chaikin A/D) (`WILLIAMSAD`).
+- **Volume RSI** — Volume RSI: Wilder-style RSI computed on signed volume flow (`VOLUMERSI`).
+
+## [0.6.2] - 2026-06-07
+- **Modified MA Stop** — Modified MA Stop — SMMA-ratcheted trailing stop with directional flip (`MODIFIED_MA_STOP`).
+- **Time-Based Stop** — Time-Based Stop — bar-count timer that fires after a fixed holding period (`TIME_BASED_STOP`).
+- **NRTR** — NRTR (Nick Rypock Trailing Reverse) — percentage trailing-reverse stop (`NRTR`).
+- **ATR Ratchet** — ATR Ratchet — Kaufman per-bar tightening volatility trailing stop (`ATR_RATCHET`).
+- **Elder SafeZone** — Elder SafeZone Stop — average noise-penetration trailing stop with directional flip (`ELDER_SAFE_ZONE`).
+- **Kase DevStop** — Kase DevStop volatility trailing stop using standard-deviation of two-bar true range (`KASE_DEV_STOP`).
+
+## [0.6.1] - 2026-06-07
+- **Projection Oscillator** — Widner projection oscillator: close position inside the projection bands, scaled 0..100 (`ProjectionOscillator`).
+- **Projection Bands** — Widner projection bands: forward-projected high/low regression envelope (`ProjectionBands`).
+- **Median Channel** — robust median +/- multiplier*MAD envelope (`MedianChannel`).
+- **Bomar Bands** — adaptive percentage bands containing a target coverage fraction of recent closes (`BomarBands`).
+- **Quartile Bands** — rolling 25th/50th/75th-percentile (Q1/median/Q3) envelope (`QuartileBands`).
+
+## [0.6.0] - 2026-06-06
+- **Volatility Cone** — volatility cone: current realized volatility within its historical min/median/max envelope (`VolatilityCone`).
+- **VolatilityRatio** — Schwager's volatility ratio: true range over the EMA of prior true ranges (`VolatilityRatio`).
+- **BipowerVariation** — jump-robust realized bipower variation (pi/2 sum of adjacent absolute log-return products) (`BipowerVariation`).
+- **VolatilityOfVolatility** — vol-of-vol: sample stddev of a rolling realized-volatility series (`VolatilityOfVolatility`).
+- **Garch11** — GARCH(1,1) conditional volatility with a long-run-variance anchor (`Garch11`).
+- **EwmaVolatility** — RiskMetrics exponentially-weighted volatility of log returns (lambda decay) (`EwmaVolatility`).
+
+## [0.5.9] - 2026-06-06
+
+### Added
+
+- Internal Rust cross-library benchmark harness (`crates/wickra-bench`, not
+  published) comparing Wickra against `kand`, `ta-rs` and `yata` on an identical
+  candle series in both streaming and batch modes; wired into the nightly
+  `cross-library-bench` workflow.
+- `tulipy` runners and expanded per-tick streaming coverage (SMA, EMA, RSI,
+  MACD, Bollinger) in the Python `compare_libraries` benchmark.
+
+### Changed
+
+- Faster streaming and batch updates for SMA, Bollinger Bands, RSI, EMA and ATR
+  (flat ring buffers replacing `VecDeque`, hoisted reciprocals in the Wilder
+  smoothing, leaner hot state) — indicator outputs are unchanged.
+- Rewrote the README benchmark section into honest, tiered tables (Rust core vs
+  the other Rust crates, and Python vs the Python ecosystem) that show where
+  Wickra wins and where it loses, not only the favourable comparisons.
+
+## [0.5.8] - 2026-06-04
+- **TSF Oscillator** — the percentage gap of the close to the one-bar-ahead time-series forecast, a close-relative companion to CFO (`TsfOscillator`).
+- **MACD Histogram** — the standalone macd-minus-signal bar of MACD as a scalar series (`MacdHistogram`).
+- **PPO Histogram** — the Percentage Price Oscillator with its signal EMA and the resulting zero-centered histogram (`PpoHistogram`).
+
+## [0.5.7] - 2026-06-04
+- **Qstick** — Qstick (Chande), the SMA of the candle body (close − open) as a net buying/selling pressure gauge (`QSTICK`).
+- **TTM Trend** — TTM Trend (John Carter), +1/−1 by whether the close sits above the SMA of recent median prices (`TTM_TREND`).
+- **Trend Strength Index** — trend strength index, the signed r² of a linear regression of price against time (`TREND_STRENGTH_INDEX`).
+- **Polarized Fractal Efficiency** — polarized fractal efficiency (Hannula), directional trend efficiency over a fractal lookback (`POLARIZED_FRACTAL_EFFICIENCY`).
+- **Wave PM** — Wave PM (Kase), a variance-normalised peak-momentum statistic (`WAVE_PM`).
+- **Gator Oscillator** — Gator Oscillator (Bill Williams), the Alligator convergence/divergence histogram (`GATOR_OSCILLATOR`).
+- **Kase Permission Stochastic** — Kase Permission Stochastic, a double-smoothed stochastic used as a trade-permission filter (`KASE_PERMISSION_STOCHASTIC`).
 
 ## [0.5.6] - 2026-06-04
 - **QQE** — quantitative qualitative estimation, a smoothed RSI with an ATR-of-RSI trailing line (`QQE`).
@@ -1259,7 +1450,29 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   optional Binance live feed.
 - Bindings for Python, Node.js, and WebAssembly.
 
-[Unreleased]: https://github.com/wickra-lib/wickra/compare/v0.5.6...HEAD
+[Unreleased]: https://github.com/wickra-lib/wickra/compare/v0.7.8...HEAD
+[0.7.8]: https://github.com/wickra-lib/wickra/compare/v0.7.7...v0.7.8
+[0.7.7]: https://github.com/wickra-lib/wickra/compare/v0.7.6...v0.7.7
+[0.7.6]: https://github.com/wickra-lib/wickra/compare/v0.7.5...v0.7.6
+[0.7.5]: https://github.com/wickra-lib/wickra/compare/v0.7.4...v0.7.5
+[0.7.4]: https://github.com/wickra-lib/wickra/compare/v0.7.3...v0.7.4
+[0.7.3]: https://github.com/wickra-lib/wickra/compare/v0.7.2...v0.7.3
+[0.7.2]: https://github.com/wickra-lib/wickra/compare/v0.7.1...v0.7.2
+[0.7.1]: https://github.com/wickra-lib/wickra/compare/v0.7.0...v0.7.1
+[0.7.0]: https://github.com/wickra-lib/wickra/compare/v0.6.9...v0.7.0
+[0.6.9]: https://github.com/wickra-lib/wickra/compare/v0.6.8...v0.6.9
+[0.6.8]: https://github.com/wickra-lib/wickra/compare/v0.6.7...v0.6.8
+[0.6.7]: https://github.com/wickra-lib/wickra/compare/v0.6.6...v0.6.7
+[0.6.6]: https://github.com/wickra-lib/wickra/compare/v0.6.5...v0.6.6
+[0.6.5]: https://github.com/wickra-lib/wickra/compare/v0.6.4...v0.6.5
+[0.6.4]: https://github.com/wickra-lib/wickra/compare/v0.6.3...v0.6.4
+[0.6.3]: https://github.com/wickra-lib/wickra/compare/v0.6.2...v0.6.3
+[0.6.2]: https://github.com/wickra-lib/wickra/compare/v0.6.1...v0.6.2
+[0.6.1]: https://github.com/wickra-lib/wickra/compare/v0.6.0...v0.6.1
+[0.6.0]: https://github.com/wickra-lib/wickra/compare/v0.5.9...v0.6.0
+[0.5.9]: https://github.com/wickra-lib/wickra/compare/v0.5.8...v0.5.9
+[0.5.8]: https://github.com/wickra-lib/wickra/compare/v0.5.7...v0.5.8
+[0.5.7]: https://github.com/wickra-lib/wickra/compare/v0.5.6...v0.5.7
 [0.5.6]: https://github.com/wickra-lib/wickra/compare/v0.5.5...v0.5.6
 [0.5.5]: https://github.com/wickra-lib/wickra/compare/v0.5.4...v0.5.5
 [0.5.4]: https://github.com/wickra-lib/wickra/compare/v0.5.3...v0.5.4

CONTRIBUTING.md

@@ -21,6 +21,10 @@ licensed as above, without any additional terms or conditions.
 | `bindings/python` | PyO3 bindings (`wickra` on PyPI). |
 | `bindings/node` | napi-rs bindings (`wickra` on npm). |
 | `bindings/wasm` | wasm-bindgen bindings (`wickra-wasm` on npm). |
+| `bindings/c` | C ABI — `cdylib` + `staticlib` + generated `include/wickra.h`. The hub for C / C++ and any C-capable language. |
+| `bindings/csharp` | .NET binding over the C ABI (`Wickra` on NuGet) — `[LibraryImport]` P/Invoke generated from `wickra.h`. |
+| `bindings/go` | Go binding over the C ABI via cgo (module tag `bindings/go/vX.Y.Z`) — wrappers generated from `wickra.h`. |
+| `bindings/r` | R binding over the C ABI via `.Call` (R package) — C glue + R wrappers generated from `wickra.h`. |
 | `examples/` | Runnable examples. |
 | `docs/` | Pointer to the documentation site (docs.wickra.org); the docs live in the `wickra-lib/wickra-docs` repo. |
 
@@ -102,7 +106,14 @@ installed. Dependabot also keeps the `.github/requirements` pins current.
 - **Streaming parity.** An indicator's `batch` output must equal the sequence
   of `update` calls.
 - **Bindings.** A change to a public indicator API must be mirrored across the
-  Python, Node, and WASM bindings, including their type stubs / `.d.ts`.
+  Python, Node, and WASM bindings, including their type stubs / `.d.ts`. The C ABI
+  (`bindings/c`) is generated from the core, so regenerate it from the core and
+  commit `src/lib.rs` + `include/wickra.h`. The C# binding (`bindings/csharp`) is
+  generated from `wickra.h`, so regenerate and commit its `Generated/*.g.cs` too.
+  The Go binding (`bindings/go`) is likewise generated from `wickra.h`, so
+  regenerate and commit `indicators_gen.go` (`gofmt`-clean). The R binding
+  (`bindings/r`) is generated from `wickra.h` too, so regenerate and commit
+  `src/wickra.c` + `R/indicators.R`.
 - **Docs.** Update the relevant page on the
   [documentation site](https://docs.wickra.org) and the
   `README.md` when behaviour or the public API changes. The docs live in

Cargo.lock

@@ -702,6 +702,16 @@ dependencies = [
  "wasm-bindgen",
 ]
 
+[[package]]
+name = "kand"
+version = "0.2.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "af1f41590bd014ef6c3dd815b45f07deb4c3198e355a4319bb7521b6a3a6aeb5"
+dependencies = [
+ "num_enum",
+ "thiserror",
+]
+
 [[package]]
 name = "leb128fmt"
 version = "0.1.0"
@@ -911,6 +921,28 @@ dependencies = [
  "libm",
 ]
 
+[[package]]
+name = "num_enum"
+version = "0.7.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "5d0bca838442ec211fa11de3a8b0e0e8f3a4522575b5c4c06ed722e005036f26"
+dependencies = [
+ "num_enum_derive",
+ "rustversion",
+]
+
+[[package]]
+name = "num_enum_derive"
+version = "0.7.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "680998035259dcfcafe653688bf2aa6d3e2dc05e98be6ab46afb089dc84f1df8"
+dependencies = [
+ "proc-macro-crate",
+ "proc-macro2",
+ "quote",
+ "syn",
+]
+
 [[package]]
 name = "numpy"
 version = "0.28.0"
@@ -1081,6 +1113,15 @@ dependencies = [
  "syn",
 ]
 
+[[package]]
+name = "proc-macro-crate"
+version = "3.5.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "e67ba7e9b2b56446f1d419b1d807906278ffa1a658a8a5d8a39dcb1f5a78614f"
+dependencies = [
+ "toml_edit",
+]
+
 [[package]]
 name = "proc-macro2"
 version = "1.0.106"
@@ -1498,6 +1539,12 @@ dependencies = [
  "syn",
 ]
 
+[[package]]
+name = "ta"
+version = "0.5.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "609409d472a0a7d8d4dd9e19891bbdef546b9dce670c3057d0e02192dc541226"
+
 [[package]]
 name = "target-lexicon"
 version = "0.13.5"
@@ -1607,6 +1654,36 @@ dependencies = [
  "tungstenite",
 ]
 
+[[package]]
+name = "toml_datetime"
+version = "1.1.1+spec-1.1.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "3165f65f62e28e0115a00b2ebdd37eb6f3b641855f9d636d3cd4103767159ad7"
+dependencies = [
+ "serde_core",
+]
+
+[[package]]
+name = "toml_edit"
+version = "0.25.12+spec-1.1.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "d2153edc6955a6c354fad8f5efd38b6a8769bdccf9fe50f8e1329f81b0baa5d7"
+dependencies = [
+ "indexmap",
+ "toml_datetime",
+ "toml_parser",
+ "winnow",
+]
+
+[[package]]
+name = "toml_parser"
+version = "1.1.2+spec-1.1.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "a2abe9b86193656635d2411dc43050282ca48aa31c2451210f4202550afb7526"
+dependencies = [
+ "winnow",
+]
+
 [[package]]
 name = "tungstenite"
 version = "0.29.0"
@@ -1867,7 +1944,7 @@ dependencies = [
 
 [[package]]
 name = "wickra"
-version = "0.5.6"
+version = "0.7.8"
 dependencies = [
  "approx",
  "criterion",
@@ -1876,9 +1953,28 @@ dependencies = [
  "wickra-data",
 ]
 
+[[package]]
+name = "wickra-bench"
+version = "0.7.8"
+dependencies = [
+ "criterion",
+ "kand",
+ "ta",
+ "wickra",
+ "wickra-data",
+ "yata",
+]
+
+[[package]]
+name = "wickra-c"
+version = "0.7.8"
+dependencies = [
+ "wickra-core",
+]
+
 [[package]]
 name = "wickra-core"
-version = "0.5.6"
+version = "0.7.8"
 dependencies = [
  "approx",
  "proptest",
@@ -1888,7 +1984,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-data"
-version = "0.5.6"
+version = "0.7.8"
 dependencies = [
  "approx",
  "csv",
@@ -1905,7 +2001,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-examples"
-version = "0.0.0"
+version = "0.7.8"
 dependencies = [
  "serde_json",
  "tokio",
@@ -1915,7 +2011,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-node"
-version = "0.5.6"
+version = "0.7.8"
 dependencies = [
  "napi",
  "napi-build",
@@ -1925,7 +2021,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-python"
-version = "0.5.6"
+version = "0.7.8"
 dependencies = [
  "numpy",
  "pyo3",
@@ -1934,7 +2030,7 @@ dependencies = [
 
 [[package]]
 name = "wickra-wasm"
-version = "0.5.6"
+version = "0.7.8"
 dependencies = [
  "console_error_panic_hook",
  "js-sys",
@@ -1991,6 +2087,15 @@ dependencies = [
  "windows-link",
 ]
 
+[[package]]
+name = "winnow"
+version = "1.0.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "0592e1c9d151f854e6fd382574c3a0855250e1d9b2f99d9281c6e6391af352f1"
+dependencies = [
+ "memchr",
+]
+
 [[package]]
 name = "wit-bindgen"
 version = "0.51.0"
@@ -2091,6 +2196,15 @@ version = "0.6.3"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "1ffae5123b2d3fc086436f8834ae3ab053a283cfac8fe0a0b8eaae044768a4c4"
 
+[[package]]
+name = "yata"
+version = "0.7.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "6b4ef8ddfa3ccd93454262c0e60a43a2bbf403d404174e1815f7581d5028229f"
+dependencies = [
+ "serde",
+]
+
 [[package]]
 name = "yoke"
 version = "0.8.2"

Cargo.toml

@@ -7,12 +7,14 @@ members = [
     "bindings/python",
     "bindings/wasm",
     "bindings/node",
+    "bindings/c",
     "examples/rust",
+    "crates/wickra-bench",
 ]
 exclude = ["fuzz"]
 
 [workspace.package]
-version = "0.5.6"
+version = "0.7.8"
 authors = ["kingchenc <support@wickra.org>"]
 edition = "2021"
 rust-version = "1.86"
@@ -24,7 +26,7 @@ keywords = ["finance", "trading", "indicators", "technical-analysis", "ta"]
 categories = ["finance", "mathematics", "science"]
 
 [workspace.dependencies]
-wickra-core = { path = "crates/wickra-core", version = "0.5.6" }
+wickra-core = { path = "crates/wickra-core", version = "0.7.8" }
 
 thiserror = "2"
 rayon = "1.10"

README.md

@@ -1,25 +1,27 @@
 <p align="center">
-  <a href="https://wickra.org"><img src="https://raw.githubusercontent.com/wickra-lib/.github/main/profile/wickra-banner.webp?v=413" alt="Wickra — streaming-first technical indicators" width="100%"></a>
+  <a href="https://wickra.org"><img src="https://raw.githubusercontent.com/wickra-lib/.github/main/profile/wickra-banner.webp?v=514" alt="Wickra — streaming-first technical indicators" width="100%"></a>
 </p>
 
-[![CI](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
-[![CodeQL](https://github.com/wickra-lib/wickra/actions/workflows/codeql.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/codeql.yml)
-[![codecov](https://codecov.io/gh/wickra-lib/wickra/branch/main/graph/badge.svg)](https://codecov.io/gh/wickra-lib/wickra)
-[![GitHub release](https://img.shields.io/github/v/release/wickra-lib/wickra?logo=github&color=green)](https://github.com/wickra-lib/wickra/releases/latest)
-[![crates.io](https://img.shields.io/crates/v/wickra.svg?logo=rust&color=orange)](https://crates.io/crates/wickra)
-[![PyPI](https://img.shields.io/pypi/v/wickra.svg?logo=pypi&color=blue)](https://pypi.org/project/wickra/)
-[![npm](https://img.shields.io/npm/v/wickra.svg?logo=npm&color=red)](https://www.npmjs.com/package/wickra)
-[![License: MIT OR Apache-2.0](https://img.shields.io/badge/license-MIT_OR_Apache--2.0-blue)](#license)
-[![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/wickra-lib/wickra/badge)](https://scorecard.dev/viewer/?uri=github.com/wickra-lib/wickra)
-[![OpenSSF Best Practices](https://www.bestpractices.dev/projects/13094/badge)](https://www.bestpractices.dev/projects/13094)
-[![Build provenance](https://img.shields.io/badge/provenance-attested-brightgreen?logo=github)](https://github.com/wickra-lib/wickra/attestations)
-[![Docs](https://img.shields.io/badge/docs-docs.wickra.org-0ea5e9?logo=readthedocs&logoColor=white)](https://docs.wickra.org)
+[![CI](https://raw.githubusercontent.com/wickra-lib/.github/main/profile/badges/ci.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
+[![CodeQL](https://raw.githubusercontent.com/wickra-lib/.github/main/profile/badges/codeql.svg)](https://github.com/wickra-lib/wickra/actions/workflows/codeql.yml)
+[![codecov](https://raw.githubusercontent.com/wickra-lib/.github/main/profile/badges/codecov.svg)](https://codecov.io/gh/wickra-lib/wickra)
+[![GitHub release](https://raw.githubusercontent.com/wickra-lib/.github/main/profile/badges/release.svg)](https://github.com/wickra-lib/wickra/releases/latest)
+[![crates.io](https://raw.githubusercontent.com/wickra-lib/.github/main/profile/badges/crates.svg)](https://crates.io/crates/wickra)
+[![PyPI](https://raw.githubusercontent.com/wickra-lib/.github/main/profile/badges/pypi.svg)](https://pypi.org/project/wickra/)
+[![npm](https://raw.githubusercontent.com/wickra-lib/.github/main/profile/badges/npm.svg)](https://www.npmjs.com/package/wickra)
+[![NuGet](https://raw.githubusercontent.com/wickra-lib/.github/main/profile/badges/nuget.svg)](https://www.nuget.org/packages/Wickra)
+[![License: MIT OR Apache-2.0](https://raw.githubusercontent.com/wickra-lib/.github/main/profile/badges/license.svg)](#license)
+[![OpenSSF Scorecard](https://raw.githubusercontent.com/wickra-lib/.github/main/profile/badges/scorecard.svg)](https://scorecard.dev/viewer/?uri=github.com/wickra-lib/wickra)
+[![OpenSSF Best Practices](https://raw.githubusercontent.com/wickra-lib/.github/main/profile/badges/best-practices.svg)](https://www.bestpractices.dev/projects/13094)
+[![Build provenance](https://raw.githubusercontent.com/wickra-lib/.github/main/profile/badges/provenance.svg)](https://github.com/wickra-lib/wickra/attestations)
+[![Docs](https://raw.githubusercontent.com/wickra-lib/.github/main/profile/badges/docs.svg)](https://docs.wickra.org)
 
 **Streaming-first technical indicators. Install with `pip install wickra` — no system dependencies.**
 
 Wickra is a multi-language technical-analysis library with a Rust core and
-bindings for Python, Node.js, and WebAssembly. Every indicator is a state
-machine that updates in O(1) per new data point, so live trading bots and
+native bindings for Python, Node.js and WebAssembly, plus a C ABI that C, C++,
+C# / .NET, Go, R and any other C-capable language links against. Every indicator is a
+state machine that updates in O(1) per new data point, so live trading bots and
 historical backtests share the exact same implementation.
 
 ```python
@@ -46,9 +48,13 @@ Full documentation lives at **[docs.wickra.org](https://docs.wickra.org)**:
 - **Quickstarts** — [Rust](https://docs.wickra.org/Quickstart-Rust),
   [Python](https://docs.wickra.org/Quickstart-Python),
   [Node](https://docs.wickra.org/Quickstart-Node),
-  [WASM](https://docs.wickra.org/Quickstart-WASM).
+  [WASM](https://docs.wickra.org/Quickstart-WASM),
+  [C](https://docs.wickra.org/Quickstart-C),
+  [C#](https://docs.wickra.org/Quickstart-CSharp),
+  [Go](https://docs.wickra.org/Quickstart-Go),
+  [R](https://docs.wickra.org/Quickstart-R).
 - **Indicators** — a per-indicator deep dive (formula, parameters, warmup) for
-  every one of the 413 indicators; start at the
+  every one of the 514 indicators; start at the
   [indicators overview](https://docs.wickra.org/Indicators-Overview).
 - **Reference** — [warmup periods](https://docs.wickra.org/Warmup-Periods),
   [streaming vs batch](https://docs.wickra.org/Streaming-vs-Batch),
@@ -58,85 +64,79 @@ Full documentation lives at **[docs.wickra.org](https://docs.wickra.org)**:
   [TA-Lib migration](https://docs.wickra.org/TA-Lib-Migration),
   [FAQ](https://docs.wickra.org/FAQ).
 
+## Why Wickra
+
+Most TA libraries are fast, *or* multi-language, *or* broad. Wickra refuses to
+pick. It's the streaming-first engine built for the workload the others treat as
+an afterthought — **live, tick-by-tick data** — without giving up the breadth of
+a full batch library, and without making you reimplement your indicators four
+times to get there.
+
+- **The biggest streaming-native catalogue, period.** 514 indicators across 24
+  families — candlesticks, harmonic & chart patterns, market profile, market
+  breadth, Renko/Kagi/Point&Figure bars, Ehlers DSP cycles, risk/performance
+  metrics — every single one updating in **O(1) per tick**. TA-Lib ships ~150 and
+  none of them stream.
+- **One Rust core, five first-class targets.** Native **Python · Node.js ·
+  WebAssembly · Rust** plus a **C ABI** for C / C++, C# / .NET, Go, R and any other C-capable language —
+  identical math, identical results, zero per-language reimplementation and zero
+  GIL bottleneck.
+- **Correct by construction, not by hope.** Every `update` validates its input,
+  runs a real warmup, and returns an `Option` so a single bad tick can't silently
+  poison state. `batch == streaming` is **bit-exact, fuzzed and 100 %-line-covered
+  for all 514 indicators**.
+- **Orders of magnitude faster where it counts.** In streaming Wickra is **11–56×**
+  faster than the only other incremental peer and **thousands of times** faster
+  than recompute-on-every-tick libraries. On batch it wins several rows outright
+  and trades the simple recurrences (SMA, EMA, MACD) for its guarantees — and
+  the losses are shown, not hidden.
+- **Install in one line, anywhere.** `pip install wickra` / `npm install wickra` —
+  precompiled wheels and binaries, **no C toolchain, none of TA-Lib's setup pain**.
+  macOS · Linux · Windows.
+- **Batteries included.** Indicator chaining, a streaming OHLCV CSV reader, and a
+  live Binance kline feed ship in the box.
+- **Truly permissive.** **MIT OR Apache-2.0** — drop it straight into commercial
+  and closed-source work.
+
+Every other library forces one of those compromises. Wickra doesn't:
+
+| Library          | Install     | Streaming   | Languages                   | Indicators | Active |
+|------------------|-------------|-------------|-----------------------------|-----------:|--------|
+| **★&nbsp;Wickra**| **clean**   | **yes, O(1)** | **Rust · Python · Node · WASM** | **514** | **yes** |
+|                  |             |               | **C · C# · Go · R**                 |            |        |
+| kand             | clean       | yes         | Python · WASM · Rust        |       ~60  | yes    |
+| ta-rs            | clean       | yes         | Rust only                   |       ~30  | stale  |
+| yata             | clean       | partial     | Rust only                   |       ~35  | yes    |
+| TA-Lib           | yes (C deps)| no          | many bindings               |      ~150  | barely |
+| pandas-ta        | clean       | no          | Python                      |      ~130  | slow   |
+| finta            | clean       | no          | Python                      |       ~80  | stale  |
+| talipp           | clean       | yes         | Python                      |       ~40  | yes    |
+
+Broad, multi-language, streaming-native **and** honest about its trade-offs — at
+the same time. That's the combination no one else ships.
+
 ## Why Wickra exists
 
-The Python TA ecosystem has plenty of libraries — TA-Lib, pandas-ta, finta,
-talipp, tulipy — and every one of them shares the same blind spot:
+Wickra started as a personal itch. The existing TA libraries never quite fit the
+projects I was building, so I decided to build one from the ground up — partly to
+learn, partly because I genuinely enjoy taking something that already exists and
+trying to do it differently (and, ideally, better). It's open source because the
+useful version of that itch is the one other people can build on too.
 
-| Library                | Install pain    | Streaming | Multi-language | Active |
-|------------------------|-----------------|-----------|----------------|--------|
-| **★&nbsp;Wickra**      | **clean**       | **yes**   | **Python + Node + WASM + Rust** | **yes** |
-| TA-Lib (Python)        | yes (C deps)    | no        | no             | barely |
-| pandas-ta              | clean           | no        | no             | slow   |
-| finta                  | clean           | no        | no             | stale  |
-| ta-lib-python          | yes (C deps)    | no        | no             | barely |
-| talipp                 | clean           | yes       | no             | yes    |
-| Tulip Indicators       | yes (C deps)    | no        | partial        | stale  |
-| ooples (C#)            | clean           | no        | C# only        | yes    |
+## Benchmarks
 
-Wickra is the only library that combines all of: clean install, streaming,
-multi-language reach, and active maintenance.
+Wickra updates every indicator in **O(1)** per tick. In **streaming** — the
+workload it is built for — it is **11–56× faster** than the only other incremental
+peer and **thousands of times** faster than recompute-on-every-tick libraries.
+**Batch** is competitive: it wins several rows outright and trades a few µs
+elsewhere for `None`-warmup, NaN-safety and bit-exact `batch == streaming`.
 
-## Benchmark: how much faster is "streaming-first"?
-
-The numbers below were measured on a single developer workstation and are not
-guaranteed to reproduce identically on different hardware — absolute µs values
-depend on CPU, memory clock and OS scheduler. Read them as **relative
-speedups** between libraries on identical input, not as a universal
-performance contract.
-
-- **Reproduced on:** Windows 11 Pro 26200, AMD Ryzen 9 9950X, 64 GB DDR5,
-  Rust 1.92 (release profile, `lto = "fat"`, `codegen-units = 1`),
-  Python 3.12, Node 20.
-- **Reproduce yourself:** `pip install -e bindings/python[bench]` then
-  `python -m benchmarks.compare_libraries`. The script auto-detects every
-  installed peer library and runs them on the same generated inputs as
-  Wickra. The CI job `cross-library-bench` runs the same script on every
-  push and uploads the raw report as a build artefact.
-
-Lower µs/op = faster. Wickra wins every batch category outright, and the
-streaming gap widens linearly with how much history a batch-only library has
-to recompute on every tick.
-
-### Batch — single full pass over a 20 000-bar series
-
-Reading the table: each cell shows that library's runtime, plus how many times
-slower it is than Wickra in parentheses. **★** marks the winner per row.
-
-| Indicator           | **★&nbsp;Wickra**   | finta                       | talipp                        |
-|---------------------|---------------------|-----------------------------|-------------------------------|
-| SMA(20)             | **95.6 µs ★**       | 343.5 µs (3.6× slower)      | 7 640.6 µs (79.9× slower)     |
-| EMA(20)             | **64.6 µs ★**       | 223.1 µs (3.5× slower)      | 12 160.9 µs (188.2× slower)   |
-| RSI(14)             | **126.2 µs ★**      | 1 107.1 µs (8.8× slower)    | 15 792.2 µs (125.1× slower)   |
-| MACD(12, 26, 9)     | **119.0 µs ★**      | 531.8 µs (4.5× slower)      | 49 788.1 µs (418.2× slower)   |
-| Bollinger(20, 2.0)  | **105.3 µs ★**      | 812.0 µs (7.7× slower)      | 130 938.3 µs (1 243.7× slower)|
-| ATR(14)             | **123.5 µs ★**      | 5 144.8 µs (41.7× slower)   | 28 816.0 µs (233.4× slower)   |
-
-### Streaming — per-tick latency after seeding with 5 000 historical bars
-
-A batch-only library has to re-run its full indicator over the entire history on
-every new tick; Wickra updates state in O(1).
-
-| Indicator | **★&nbsp;Wickra (per tick)** | talipp (per tick)         |
-|-----------|---------------------|---------------------------|
-| RSI(14)   | **0.119 µs ★**      | 1.644 µs (13.8× slower)   |
-
-> TA-Lib and pandas-ta are not included here because both fail to install
-> cleanly on Windows without C build tooling — which is precisely the install
-> pain Wickra was built to remove. The benchmark script auto-detects every
-> peer library it can find and runs them on the same inputs as Wickra; install
-> them in your environment to see those rows light up too.
-
-Run the suite yourself:
-
-```bash
-pip install -e bindings/python[bench]
-python -m benchmarks.compare_libraries
-```
+Full tables (Rust + Python, streaming + batch) and how to reproduce them live in
+**[BENCHMARKS.md](BENCHMARKS.md)**.
 
 ## Indicators
 
-413 streaming-first indicators across twenty-four families. Every one passes the
+514 streaming-first indicators across twenty-four families. Every one passes the
 `batch == streaming` equivalence test, reference-value tests, and reset
 semantics tests. Each has a per-indicator deep dive (formula, parameters,
 warmup) at [docs.wickra.org](https://docs.wickra.org/Indicators-Overview).
@@ -145,25 +145,25 @@ warmup) at [docs.wickra.org](https://docs.wickra.org/Indicators-Overview).
 |--------|-----------|
 | Moving Averages      | SMA, EMA, WMA, DEMA, TEMA, HMA, KAMA, SMMA, TRIMA, ZLEMA, T3, VWMA, ALMA, McGinley Dynamic, FRAMA, VIDYA, JMA, Alligator, EVWMA, SWMA, GMA, EHMA, Median MA, Adaptive Laguerre, GD, Holt-Winters |
 | Momentum Oscillators | RSI (Wilder), Anchored RSI, Stochastic, CCI, ROC, Williams %R, MFI, Awesome Oscillator, MOM, CMO, TSI, PMO, StochRSI, Ultimate Oscillator, RVI, PGO, KST, SMI, Laguerre RSI, Connors RSI, Inertia, ROC Percentage (ROCP), ROC Ratio (ROCR), ROC Ratio 100 (ROCR100), Disparity Index, Fisher RSI, RSX, Dynamic Momentum Index, Stochastic CCI, RMI, Derivative Oscillator, Elder Ray, Intraday Momentum Index, QQE |
-| Trend & Directional  | MACD, MACD Fixed (MACDFIX), MACD Extended (MACDEXT), ADX (+DI/-DI), ADXR, Aroon, TRIX, Aroon Oscillator, Vortex, Random Walk Index, Trend Intensity Index, Wave Trend Oscillator, Mass Index, Choppiness Index, Vertical Horizontal Filter, Plus DM, Minus DM, Plus DI, Minus DI, DX |
-| Price Oscillators    | PPO, DPO, Coppock, Accelerator Oscillator, Balance of Power, APO, AO Histogram, CFO, Zero-Lag MACD, Elder Impulse, STC |
-| Volatility & Bands   | ATR, Bollinger Bands, Keltner Channels, Donchian Channels, NATR, StdDev, Ulcer Index, Historical Volatility, Bollinger Bandwidth, %B, True Range, Chaikin Volatility, RVI (Relative Volatility Index), Parkinson Volatility, Garman-Klass Volatility, Rogers-Satchell Volatility, Yang-Zhang Volatility |
-| Bands & Channels     | MA Envelope, Acceleration Bands, STARC Bands, ATR Bands, Hurst Channel, LinReg Channel, Standard Error Bands, Double Bollinger Bands, TTM Squeeze, Fractal Chaos Bands, VWAP StdDev Bands |
-| Trailing Stops       | Parabolic SAR, Parabolic SAR Extended (SAREXT), SuperTrend, Chandelier Exit, Chande Kroll Stop, ATR Trailing Stop, HiLo Activator, Volty Stop, Yo-Yo Exit, Donchian Channel Stop, Percentage Trailing Stop, Step Trailing Stop, Renko Trailing Stop |
-| Volume               | OBV, VWAP (cumulative + rolling), ADL, Volume-Price Trend, Chaikin Money Flow, Chaikin Oscillator, Force Index, Ease of Movement, Klinger Volume Oscillator, Volume Oscillator, NVI, PVI, Williams A/D, Anchored VWAP, Demand Index, TSV, VZO, Market Facilitation Index |
-| Price Statistics     | Typical Price, Median Price, Weighted Close, Linear Regression, Linear Regression Slope, Z-Score, Linear Regression Angle, Variance, Coefficient of Variation, Skewness, Kurtosis, Standard Error, Detrended StdDev, R², Median Absolute Deviation, Autocorrelation, Hurst Exponent, Pearson Correlation, Beta, Pairwise Beta, Pair Spread Z-Score, Lead-Lag Cross-Correlation, Cointegration, Relative Strength A-vs-B, Spearman Correlation, Mid Price, Mid Point, Average Price, Linear Regression Intercept, Time Series Forecast, Rolling Correlation, Rolling Covariance, OU Half-Life, Spread Hurst, Distance SSD, Beta-Neutral Spread, Variance Ratio, Granger Causality, Kalman Hedge Ratio, Spread Bollinger Bands, Spread AR(1) Coefficient |
-| Ehlers / Cycle (DSP) | MAMA, FAMA, Fisher Transform, Inverse Fisher Transform, SuperSmoother, Hilbert Dominant Cycle, Hilbert Phasor, Hilbert DC Phase, Hilbert Trend Mode, Sine Wave, Decycler, Decycler Oscillator, Roofing Filter, Center of Gravity, Cybernetic Cycle, Adaptive Cycle, Empirical Mode Decomposition, Ehlers Stochastic, Instantaneous Trendline |
-| Pivots & S/R         | Classic Pivots, Fibonacci Pivots, Camarilla, Woodie Pivots, DeMark Pivots, Williams Fractals, ZigZag |
-| DeMark               | TD Setup, TD Sequential, TD DeMarker, TD REI, TD Pressure, TD Combo, TD Countdown, TD Lines, TD Range Projection, TD Differential, TD Open, TD Risk Level |
-| Ichimoku & Charts    | Ichimoku Kinko Hyo (Tenkan, Kijun, Senkou A/B, Chikou), Heikin-Ashi |
-| Alt-Chart Bars       | Renko (box-size bricks), Kagi (reversal-amount lines), Point & Figure (X/O columns) |
-| Candlestick Patterns | Doji, Hammer, Inverted Hammer, Hanging Man, Shooting Star, Engulfing, Harami, Morning/Evening Star, Three White Soldiers/Black Crows, Piercing Line/Dark Cloud Cover, Marubozu, Tweezer, Spinning Top, Three Inside Up/Down, Three Outside Up/Down, Two Crows, Upside Gap Two Crows, Identical Three Crows, Three Line Strike, Three Stars in the South, Abandoned Baby, Advance Block, Belt-hold, Breakaway, Counterattack, Doji Star, Dragonfly Doji, Gravestone Doji, Long-Legged Doji, Rickshaw Man, Evening Doji Star, Morning Doji Star, Gap Side-by-Side White, High-Wave, Hikkake, Modified Hikkake, Homing Pigeon, On-Neck, In-Neck, Thrusting, Separating Lines, Kicking, Kicking by Length, Ladder Bottom, Mat Hold, Matching Low, Long Line, Short Line, Rising Three Methods, Falling Three Methods, Upside Gap Three Methods, Downside Gap Three Methods, Stalled Pattern, Stick Sandwich, Takuri, Closing Marubozu, Opening Marubozu, Tasuki Gap, Unique Three River, Concealing Baby Swallow |
+| Trend & Directional  | MACD, MACD Fixed (MACDFIX), MACD Extended (MACDEXT), ADX (+DI/-DI), ADXR, Aroon, TRIX, Aroon Oscillator, Vortex, Random Walk Index, Trend Intensity Index, Wave Trend Oscillator, Mass Index, Choppiness Index, Vertical Horizontal Filter, Plus DM, Minus DM, Plus DI, Minus DI, DX, TTM Trend, Trend Strength Index, Qstick, Polarized Fractal Efficiency, Wave PM, Gator Oscillator, Kase Permission Stochastic |
+| Price Oscillators    | PPO, DPO, Coppock, Accelerator Oscillator, Balance of Power, APO, AO Histogram, CFO, Zero-Lag MACD, Elder Impulse, STC, TSF Oscillator, MACD Histogram, PPO Histogram |
+| Volatility & Bands   | ATR, Bollinger Bands, Keltner Channels, Donchian Channels, NATR, StdDev, Ulcer Index, Historical Volatility, Bollinger Bandwidth, %B, True Range, Chaikin Volatility, RVI (Relative Volatility Index), Parkinson Volatility, Garman-Klass Volatility, Rogers-Satchell Volatility, Yang-Zhang Volatility, Volatility Cone |
+| Bands & Channels     | MA Envelope, Acceleration Bands, STARC Bands, ATR Bands, Hurst Channel, LinReg Channel, Standard Error Bands, Double Bollinger Bands, TTM Squeeze, Fractal Chaos Bands, VWAP StdDev Bands, Quartile Bands, Bomar Bands, Median Channel, Projection Bands, Projection Oscillator |
+| Trailing Stops       | Parabolic SAR, Parabolic SAR Extended (SAREXT), SuperTrend, Chandelier Exit, Chande Kroll Stop, ATR Trailing Stop, HiLo Activator, Volty Stop, Yo-Yo Exit, Donchian Channel Stop, Percentage Trailing Stop, Step Trailing Stop, Renko Trailing Stop, Kase DevStop, Elder SafeZone, ATR Ratchet, NRTR, Time-Based Stop, Modified MA Stop |
+| Volume               | OBV, VWAP (cumulative + rolling), ADL, Volume-Price Trend, Chaikin Money Flow, Chaikin Oscillator, Force Index, Ease of Movement, Klinger Volume Oscillator, Volume Oscillator, NVI, PVI, Williams A/D, Anchored VWAP, Demand Index, TSV, VZO, Market Facilitation Index, Volume RSI, Williams Accumulation/Distribution, Twiggs Money Flow, Trade Volume Index, Intraday Intensity Index, Better Volume, Volume-Weighted MACD |
+| Price Statistics     | Typical Price, Median Price, Weighted Close, Linear Regression, Linear Regression Slope, Z-Score, Linear Regression Angle, Variance, Coefficient of Variation, Skewness, Kurtosis, Standard Error, Detrended StdDev, R², Median Absolute Deviation, Autocorrelation, Hurst Exponent, Pearson Correlation, Beta, Pairwise Beta, Pair Spread Z-Score, Lead-Lag Cross-Correlation, Cointegration, Relative Strength A-vs-B, Spearman Correlation, Mid Price, Mid Point, Average Price, Linear Regression Intercept, Time Series Forecast, Rolling Correlation, Rolling Covariance, OU Half-Life, Spread Hurst, Distance SSD, Beta-Neutral Spread, Variance Ratio, Granger Causality, Kalman Hedge Ratio, Spread Bollinger Bands, Spread AR(1) Coefficient, Jarque-Bera, Rolling Min-Max Scaler, Shannon Entropy, Sample Entropy, Kendall Tau |
+| Ehlers / Cycle (DSP) | MAMA, FAMA, Fisher Transform, Inverse Fisher Transform, SuperSmoother, Hilbert Dominant Cycle, Hilbert Phasor, Hilbert DC Phase, Hilbert Trend Mode, Sine Wave, Decycler, Decycler Oscillator, Roofing Filter, Center of Gravity, Cybernetic Cycle, Adaptive Cycle, Empirical Mode Decomposition, Ehlers Stochastic, Instantaneous Trendline, Highpass Filter, Reflex, Trendflex, Correlation Trend Indicator, Adaptive RSI, Universal Oscillator, Adaptive CCI, Bandpass Filter, Even Better Sinewave, Autocorrelation Periodogram |
+| Pivots & S/R         | Classic Pivots, Fibonacci Pivots, Camarilla, Woodie Pivots, DeMark Pivots, Williams Fractals, ZigZag, Central Pivot Range, Murrey Math Lines, Andrews Pitchfork, Volume-Weighted Support/Resistance, Pivot Reversal |
+| DeMark               | TD Setup, TD Sequential, TD DeMarker, TD REI, TD Pressure, TD Combo, TD Countdown, TD Lines, TD Range Projection, TD Differential, TD Open, TD Risk Level, TD Camouflage, TD Clop, TD Clopwin, TD Propulsion, TD Trap, TD D-Wave, TD Moving Averages |
+| Ichimoku & Charts    | Ichimoku Kinko Hyo (Tenkan, Kijun, Senkou A/B, Chikou), Heikin-Ashi, Heikin-Ashi Oscillator, Three Line Break, Smoothed Heikin-Ashi, Equivolume, CandleVolume |
+| Alt-Chart Bars       | Renko (box-size bricks), Kagi (reversal-amount lines), Point & Figure (X/O columns), Range, Tick, Volume, Dollar, Imbalance, Run, Three-Line Break |
+| Candlestick Patterns | Doji, Hammer, Inverted Hammer, Hanging Man, Shooting Star, Engulfing, Harami, Morning/Evening Star, Three White Soldiers/Black Crows, Piercing Line/Dark Cloud Cover, Marubozu, Tweezer, Spinning Top, Three Inside Up/Down, Three Outside Up/Down, Two Crows, Upside Gap Two Crows, Identical Three Crows, Three Line Strike, Three Stars in the South, Abandoned Baby, Advance Block, Belt-hold, Breakaway, Counterattack, Doji Star, Dragonfly Doji, Gravestone Doji, Long-Legged Doji, Rickshaw Man, Evening Doji Star, Morning Doji Star, Gap Side-by-Side White, High-Wave, Hikkake, Modified Hikkake, Homing Pigeon, On-Neck, In-Neck, Thrusting, Separating Lines, Kicking, Kicking by Length, Ladder Bottom, Mat Hold, Matching Low, Long Line, Short Line, Rising Three Methods, Falling Three Methods, Upside Gap Three Methods, Downside Gap Three Methods, Stalled Pattern, Stick Sandwich, Takuri, Closing Marubozu, Opening Marubozu, Tasuki Gap, Unique Three River, Concealing Baby Swallow, Tristar, Harami Cross, Tower Top/Bottom, Dumpling Top, New Price Lines, Frying Pan Bottom |
 | Chart Patterns       | Double Top / Bottom, Triple Top / Bottom, Head and Shoulders, Triangle (asc/desc/sym), Wedge (rising/falling), Flag / Pennant, Rectangle / Range, Cup and Handle |
 | Harmonic Patterns    | AB=CD, Gartley, Butterfly, Bat, Crab, Shark, Cypher, Three Drives |
 | Fibonacci            | Fibonacci Retracement, Fibonacci Extension, Fibonacci Projection, Auto-Fibonacci, Golden Pocket, Fibonacci Confluence, Fibonacci Fan, Fibonacci Arcs, Fibonacci Channel, Fibonacci Time Zones |
-| Microstructure       | Order-Book Imbalance (Top-1 / Top-N / Full), Microprice, Quoted Spread, Depth Slope, Signed Volume, Cumulative Volume Delta, Trade Imbalance, Effective Spread, Realized Spread, Kyle's Lambda, Footprint, Order Flow Imbalance, VPIN, Amihud Illiquidity, Roll Measure |
-| Derivatives          | Funding Rate, Funding Rate Mean, Funding Rate Z-Score, Funding Basis, Open-Interest Delta, OI / Price Divergence, OI-Weighted Price, Long/Short Ratio, Taker Buy/Sell Ratio, Liquidation Features, Term-Structure Basis, Calendar Spread |
-| Market Profile       | Value Area (POC / VAH / VAL), Volume Profile (histogram), TPO Profile, Initial Balance, Opening Range |
+| Microstructure       | Order-Book Imbalance (Top-1 / Top-N / Full), Microprice, Quoted Spread, Depth Slope, Signed Volume, Cumulative Volume Delta, Trade Imbalance, Effective Spread, Realized Spread, Kyle's Lambda, Footprint, Order Flow Imbalance, VPIN, Amihud Illiquidity, Roll Measure, Trade-Sign Autocorrelation, Hasbrouck Information Share |
+| Derivatives          | Funding Rate, Funding Rate Mean, Funding Rate Z-Score, Funding Basis, Open-Interest Delta, OI / Price Divergence, OI-Weighted Price, Long/Short Ratio, Taker Buy/Sell Ratio, Liquidation Features, Term-Structure Basis, Calendar Spread, Estimated Leverage Ratio, OI-to-Volume Ratio, Perpetual Premium Index, Funding-Implied APR, Open-Interest Momentum |
+| Market Profile       | Value Area (POC / VAH / VAL), Volume Profile (histogram), TPO Profile, Initial Balance, Opening Range, Naked POC, Single Prints, Profile Shape, High/Low Volume Nodes, Composite Profile |
 | Market Breadth       | Advance/Decline Line, Advance/Decline Ratio, Advance/Decline Volume Line, McClellan Oscillator, McClellan Summation Index, TRIN / Arms Index, Breadth Thrust, New Highs - New Lows, High-Low Index, Percent Above Moving Average, Up/Down Volume Ratio, Bullish Percent Index, Cumulative Volume Index, Absolute Breadth Index, TICK Index |
 | Risk / Performance   | Sharpe Ratio, Sortino Ratio, Calmar Ratio, Omega Ratio, Max Drawdown, Average Drawdown, Drawdown Duration, Pain Index, Value at Risk, Conditional Value at Risk (CVaR), Profit Factor, Gain/Loss Ratio, Recovery Factor, Kelly Criterion, Treynor Ratio, Information Ratio, Alpha (Jensen) |
 | Seasonality & Session | Session VWAP, Session High/Low, Session Range, Average Daily Range, Overnight Gap, Overnight/Intraday Return, Turn-of-Month, Seasonal Z-Score, Time-of-Day Return Profile, Day-of-Week Profile, Intraday Volatility Profile, Volume-by-Time Profile |
@@ -174,8 +174,9 @@ as one column each. `Doji` is direction-less by default (`+1.0` / `0.0`);
 construct it in signed mode (`Doji::new().signed()`, `Doji(signed=True)`,
 `new Doji(true)`) for a dragonfly / gravestone `±1` reading.
 
-Adding a new indicator means implementing one trait in Rust; all four bindings
-inherit it automatically.
+Adding a new indicator means implementing one trait in Rust; every binding
+inherits it automatically (the C ABI — and the C#, Go and R bindings generated from
+it — regenerate from the core).
 
 ## Languages
 
@@ -185,12 +186,17 @@ inherit it automatically.
 | Node.js (napi-rs) | `npm install wickra`                          | `examples/node/backtest.js` |
 | Browser / WASM    | `npm install wickra-wasm`                     | `examples/wasm/index.html` |
 | Rust              | `cargo add wickra`                            | `examples/rust/src/bin/backtest.rs` |
+| C / C++ (C ABI)   | header + library, see [`bindings/c`](bindings/c) | `examples/c/streaming.c` |
+| C# / .NET (C ABI) | `dotnet add package Wickra`, see [`bindings/csharp`](bindings/csharp) | `examples/csharp/streaming` |
+| Go (cgo, C ABI)   | `go get github.com/wickra-lib/wickra/bindings/go`, see [`bindings/go`](bindings/go) | `examples/go/streaming` |
+| R (`.Call`, C ABI) | `R CMD INSTALL bindings/r`, see [`bindings/r`](bindings/r) | `examples/r/streaming.R` |
 
 Each binding ships several runnable examples (streaming, backtest, live feed);
 [`examples/README.md`](examples/README.md) is the full cross-language index.
 
-The wickra-core crate is `unsafe`-forbidden, so every binding inherits a
-memory-safe implementation.
+The wickra-core crate is `unsafe`-forbidden, so the native bindings are
+memory-safe end to end. The C ABI runs the same safe core; only its thin FFI
+boundary uses `unsafe`, and the caller owns handle lifetimes (`_new` / `_free`).
 
 ## Rust API
 
@@ -245,25 +251,35 @@ A Python live-trading example using the public `websockets` package lives at
 ```
 wickra/
 ├── crates/
-│   ├── wickra-core/         core engine + all 413 indicators
+│   ├── wickra-core/         core engine + all 514 indicators
 │   ├── wickra/              top-level facade crate (publishes on crates.io) + benches/
-│   └── wickra-data/         CSV reader, tick aggregator, live exchange feeds
+│   ├── wickra-data/         CSV reader, tick aggregator, live exchange feeds
+│   └── wickra-bench/        internal cross-library benchmark harness (not published)
 ├── bindings/
 │   ├── python/              PyO3 + maturin (publishes on PyPI)
 │   ├── node/                napi-rs (publishes on npm)
-│   └── wasm/                wasm-bindgen (browsers, bundlers, Node)
+│   ├── wasm/                wasm-bindgen (browsers, bundlers, Node)
+│   ├── c/                   C ABI (cdylib + staticlib) + generated include/wickra.h
+│   ├── csharp/              .NET binding over the C ABI (publishes on NuGet)
+│   ├── go/                  Go binding over the C ABI via cgo (module tag)
+│   └── r/                   R binding over the C ABI via .Call (R package)
 ├── examples/                examples/README.md indexes every language
 │   ├── data/                real BTCUSDT OHLCV datasets, one per timeframe
 │   ├── rust/                Rust workspace member (`wickra-examples`)
 │   ├── python/              backtest, live trading, parallel assets, multi-tf
 │   ├── node/                streaming, backtest, live trading (load `wickra`)
-│   └── wasm/                browser demo for `wickra-wasm`
+│   ├── wasm/                browser demo for `wickra-wasm`
+│   ├── c/                   C smoke + streaming, C++ RAII wrapper
+│   ├── csharp/              streaming, backtest, strategies (load `Wickra`)
+│   ├── go/                  streaming, backtest, strategies (cgo binding)
+│   └── r/                   streaming, backtest, strategies (.Call binding)
 └── .github/workflows/       CI and release pipelines
 ```
 
-Rust benchmarks live in `crates/wickra/benches/`; runnable Rust examples live
-in the workspace member crate at `examples/rust/`. There is no top-level
-`benches/` directory.
+Wickra's own regression benchmarks live in `crates/wickra/benches/`; the
+cross-library comparison against kand, ta-rs and yata lives in the internal
+`crates/wickra-bench/` crate. Runnable Rust examples live in the workspace member
+crate at `examples/rust/`. There is no top-level `benches/` directory.
 
 ## Building everything from source
 
@@ -271,7 +287,8 @@ in the workspace member crate at `examples/rust/`. There is no top-level
 # Rust core + tests
 cargo test --workspace
 cargo clippy --workspace --all-targets -- -D warnings
-cargo bench -p wickra
+cargo bench -p wickra           # Wickra's own regression benchmarks
+cargo bench -p wickra-bench     # cross-library comparison (kand, ta-rs, yata)
 
 # Python binding (requires Rust toolchain + maturin)
 cd bindings/python
@@ -283,6 +300,22 @@ wasm-pack build bindings/wasm --target web --release --features panic-hook
 
 # Node binding (requires @napi-rs/cli)
 cd bindings/node && npm install && npm run build && npm test
+
+# C ABI (cdylib + staticlib + generated header)
+cargo build -p wickra-c --release
+cmake -S examples/c -B examples/c/build -DWICKRA_LIB_DIR="$PWD/target/release"
+cmake --build examples/c/build && ctest --test-dir examples/c/build --output-on-failure
+
+# C# / .NET binding (requires the .NET 8 SDK; links the C ABI above)
+dotnet test bindings/csharp/Wickra.Tests/Wickra.Tests.csproj
+
+# Go binding (requires a C compiler for cgo; links the C ABI above)
+cp target/release/libwickra.so bindings/go/lib/   # .dylib on macOS, wickra.dll on Windows
+cd bindings/go && go test ./...
+
+# R binding (requires a C toolchain / Rtools; links the C ABI above)
+WICKRA_INCLUDE_DIR="$PWD/bindings/c/include" WICKRA_LIB_DIR="$PWD/target/release" \
+  R CMD INSTALL bindings/r
 ```
 
 ## Testing
@@ -302,6 +335,10 @@ Every layer is covered; run the suites with the commands in
   values across all indicators.
 - `bindings/wasm`: `wasm-bindgen-test` cases for constructors, equivalence,
   and reference values.
+- `bindings/go`: `go test` cases covering one indicator per FFI archetype
+  (scalar/batch, multi-output, bars, profile, array input), reset, and lifecycle.
+- `bindings/r`: `testthat` cases covering one indicator per FFI archetype
+  (scalar/batch, multi-output, bars, profile, array input), reset, and validation.
 
 ## Contributing
 
@@ -371,3 +408,10 @@ The library is provided **as is**, without warranty of any kind; see
 <p align="center">
   If Wickra saved you time, the cheapest way to say thanks is to ⭐ the repo.
 </p>
+
+<p align="center">
+  <a href="https://star-history.com/#wickra-lib/wickra&Date">
+    <img alt="Wickra star history" width="640"
+         src="https://api.star-history.com/svg?repos=wickra-lib/wickra&type=Date&theme=dark">
+  </a>
+</p>

ROADMAP.md

@@ -21,8 +21,9 @@ minor releases; breaking changes are called out in the changelog.
   versioning stability for a 1.0 release.
 - **Performance.** Keep per-tick updates O(1) and maintain the benchmark suite;
   investigate further allocation and cache improvements.
-- **Bindings parity.** Keep the Python, Node.js and WebAssembly bindings in
-  lockstep with the Rust core, including type stubs and platform coverage.
+- **Bindings parity.** Keep the Python, Node.js and WebAssembly bindings — plus
+  the C ABI and the C# / .NET, Go and R bindings generated from it — in lockstep with the
+  Rust core, including type stubs and platform coverage.
 - **Documentation.** Maintain a deep-dive page per indicator on
   <https://docs.wickra.org>, plus quickstarts and cookbook material.
 - **Project health.** Maintain test coverage, static and dynamic analysis,

SECURITY.md

@@ -58,7 +58,11 @@ artifacts, and (4) a healthy dependency supply chain.
 
 - *Memory safety* — the core and all bindings are written in Rust. The crates
   forbid or minimise `unsafe`, so the compiler guarantees memory and thread
-  safety for the indicator logic.
+  safety for the indicator logic. The one exception is the C ABI
+  ([`bindings/c`](bindings/c)), whose thin FFI shim is necessarily `unsafe`
+  because it dereferences caller-supplied pointers; it adds no indicator logic,
+  validates every handle for NULL, and never lets a panic cross the boundary, so
+  the safe core's guarantees still cover all computation.
 - *Input robustness* — every indicator validates its parameters and rejects
   non-finite inputs at construction; behaviour on edge cases (flat markets,
   warmup, reset) is pinned by unit tests, and the public update paths are

SUPPORT.md

@@ -7,8 +7,8 @@ Thanks for using Wickra! Here is where to get help, depending on what you need.
 Most questions are answered in the documentation:
 
 - **Docs site:** <https://docs.wickra.org> — quickstarts for Rust, Python,
-  Node.js and WebAssembly, a per-indicator reference, warmup periods, the data
-  layer, and an FAQ.
+  Node.js, WebAssembly, C, C#, Go and R, a per-indicator reference, warmup periods, the
+  data layer, and an FAQ.
 - **README:** <https://github.com/wickra-lib/wickra#readme> — installation and a
   quick overview.
 - **API docs (Rust):** <https://docs.rs/wickra>.

THREAT_MODEL.md

@@ -3,8 +3,10 @@
 This document describes Wickra's attack surface and the threats considered,
 together with their mitigations. It complements the security assurance case in
 [`SECURITY.md`](SECURITY.md). Wickra is a computational technical-analysis
-library (a Rust core with Python, Node.js and WebAssembly bindings), not a
-network service or trading system; the attack surface is correspondingly small.
+library (a Rust core with Python, Node.js and WebAssembly bindings plus a C ABI
+and the .NET, Go and R bindings built on it),
+not a network service or trading system; the attack surface is correspondingly
+small.
 
 ## Assets
 
@@ -31,6 +33,7 @@ network service or trading system; the attack surface is correspondingly small.
 | Threat | Mitigation |
 | --- | --- |
 | Memory-safety exploit (buffer overflow, UAF) via crafted input | Pure safe Rust; `unsafe` is forbidden/minimised, so the compiler precludes these classes. |
+| Misuse of the C ABI FFI boundary (invalid/dangling handle, undersized batch buffer) | The C ABI (`bindings/c`) is the sole `unsafe` surface. Its shim adds no logic, NULL-checks every handle (returning `NaN`/no-op), writes only into caller-sized buffers, and catches panics so none cross the boundary. A caller passing a non-NULL but dangling pointer is undefined behaviour by C's own contract — out of scope, the same as any C library. |
 | Denial of service via malformed/degenerate input (NaN, infinities, extreme magnitudes) | Indicators reject non-finite inputs and validate parameters at construction; update paths are exercised by coverage-guided fuzzing and unit tests for edge cases. |
 | Silently incorrect results | 100% line coverage on the core crate; reference-value tests against known-good sources; streaming/batch parity tests. |
 | Integer overflow / panics | `clippy::pedantic` with `-D warnings`; debug assertions and overflow checks enabled in test/fuzz builds. |

bindings/c/Cargo.toml

@@ -0,0 +1,46 @@
+[package]
+name = "wickra-c"
+description = "C ABI (cdylib + staticlib) for the Wickra streaming-first technical indicators library — the hub every C-capable language (C, C++, Go, C#, Java, R) links against."
+version.workspace = true
+authors.workspace = true
+edition.workspace = true
+rust-version.workspace = true
+license.workspace = true
+repository.workspace = true
+homepage.workspace = true
+readme = "README.md"
+keywords.workspace = true
+categories.workspace = true
+publish = false
+
+[lib]
+name = "wickra"
+crate-type = ["cdylib", "staticlib"]
+
+# The C ABI inherently needs `unsafe` (raw pointers across the FFI boundary,
+# `#[export_name]` symbol control). The workspace forbids `unsafe_code`, so this
+# crate cannot inherit `workspace = true`; it mirrors every workspace lint and
+# only relaxes `unsafe_code` to `allow` (parity with how the proc-macro bindings
+# emit their unsafe). The Rust core stays `unsafe`-forbidden — this is the one
+# crate where the boundary lives.
+[lints.rust]
+unsafe_code = "allow"
+missing_debug_implementations = "warn"
+unreachable_pub = "warn"
+unused_must_use = "deny"
+
+[lints.clippy]
+all = { level = "warn", priority = -1 }
+pedantic = { level = "warn", priority = -1 }
+module_name_repetitions = "allow"
+must_use_candidate = "allow"
+missing_errors_doc = "allow"
+missing_panics_doc = "allow"
+cast_precision_loss = "allow"
+cast_possible_truncation = "allow"
+cast_sign_loss = "allow"
+similar_names = "allow"
+float_cmp = "allow"
+
+[dependencies]
+wickra-core = { workspace = true }

bindings/c/README.md

@@ -0,0 +1,80 @@
+# Wickra — C / C++
+
+[![CI](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
+[![codecov](https://codecov.io/gh/wickra-lib/wickra/branch/main/graph/badge.svg)](https://codecov.io/gh/wickra-lib/wickra)
+[![GitHub release](https://img.shields.io/github/v/release/wickra-lib/wickra?logo=github&color=green)](https://github.com/wickra-lib/wickra/releases/latest)
+[![License: MIT OR Apache-2.0](https://img.shields.io/badge/license-MIT_OR_Apache--2.0-blue)](https://github.com/wickra-lib/wickra#license)
+
+**Streaming-first technical indicators for C and C++. A prebuilt shared/static
+library plus a generated `wickra.h` — no system dependencies.**
+
+Wickra is a multi-language technical-analysis library with a Rust core and
+bindings for Python, Node.js and WebAssembly, plus a C ABI for C/C++, C#, Go, R and any
+other C-capable language. Every indicator is an O(1)
+streaming state machine, so live trading bots and historical backtests share
+the exact same implementation. This package is the **C ABI hub**: it compiles the
+core to a C-compatible shared/static library plus a generated header, so any
+C-capable language (C, C++, Go, C#, Java, R) links against one artifact instead
+of re-wrapping every indicator natively.
+
+## Install
+
+Grab the prebuilt header + library for your platform from the
+[GitHub releases](https://github.com/wickra-lib/wickra/releases) — each archive
+has `wickra.h`, the optional `wickra.hpp` C++ wrapper, and the shared/static
+library — or build from source:
+
+```bash
+cargo build -p wickra-c --release
+# -> target/release/libwickra.{so,dylib} or wickra.dll (+ import lib) + a staticlib
+```
+
+Then compile against the header and link the library
+(`cc app.c -I include -L lib -lwickra -lm -o app`).
+
+## Quick start
+
+```c
+#include "wickra.h"
+
+struct Rsi *rsi = wickra_rsi_new(14);              /* NULL on invalid params */
+for (size_t i = 0; i < n; ++i) {
+    double v = wickra_rsi_update(rsi, prices[i]);  /* NaN during warmup       */
+    if (v == v && v > 70.0)                        /* v == v is the NaN check */
+        printf("overbought\n");
+}
+wickra_rsi_free(rsi);                              /* exactly once per _new   */
+```
+
+Every indicator is an opaque handle with the same five functions —
+`_new` / `_update` / `_batch` / `_reset` / `_free`. `update` is O(1); there is no
+RAII across the C boundary, so each `_new` needs exactly one `_free`, and every
+function is NULL-safe (a NULL handle yields `NaN` or a no-op, never a crash).
+Multi-output indicators (MACD, Bollinger, ADX, …) take a pointer to a `#[repr(C)]`
+struct and return a `bool`. The optional `wickra.hpp` wraps any handle in a
+move-only `wickra::Handle` for exception-safe C++ lifetimes.
+
+## Documentation
+
+The full indicator catalogue, guides, quickstarts, and API reference live in
+the main repository and documentation site:
+
+- **Repository & full indicator list:** <https://github.com/wickra-lib/wickra>
+- **Docs** (C quickstart, cookbook, TA-Lib migration): <https://docs.wickra.org/Quickstart-C>
+- **Runnable examples:** [`examples/c/`](https://github.com/wickra-lib/wickra/tree/main/examples/c)
+
+Wickra ships native bindings for Python, Node.js, WebAssembly and Rust, plus this
+C ABI hub that any C-capable language (C, C++, Go, C#, Java, R) links against —
+all exposing the same indicators from the shared Rust core.
+
+## Disclaimer
+
+Wickra is an indicator toolkit, not a trading system. The values it computes
+are deterministic transforms of the input data — they are not financial advice
+and do not predict the market. Any use in a live trading context is at your own
+risk. The library is provided **as is**, without warranty of any kind.
+
+## License
+
+Licensed under either of [Apache-2.0](https://github.com/wickra-lib/wickra/blob/main/LICENSE-APACHE)
+or [MIT](https://github.com/wickra-lib/wickra/blob/main/LICENSE-MIT) at your option.

bindings/c/cbindgen.toml

@@ -0,0 +1,20 @@
+language = "C"
+header = "/* Wickra C ABI — generated by cbindgen. Do not edit by hand. */"
+include_guard = "WICKRA_H"
+pragma_once = true
+# Wrap the declarations in `extern "C"` under __cplusplus so the header is usable
+# from C++ (the optional wickra.hpp RAII layer and any C++ consumer).
+cpp_compat = true
+tab_width = 4
+# Off: cbindgen copies the Rust struct/fn doc comments verbatim, and some core
+# indicator docs contain markdown (e.g. `**1/8**/**7/8**`) whose `*/` would close
+# the C block comment early and break the header. Usage docs live in the crate
+# README and examples; the header is a pure declaration contract.
+documentation = false
+
+[parse]
+# Parse wickra-core too so the opaque indicator handle types (Sma, Ema, …) are
+# discovered and emitted as forward-declared opaque structs. Their fields are
+# never exposed — only `T *` handles cross the boundary.
+parse_deps = true
+include = ["wickra-core"]

bindings/c/include/wickra.hpp

@@ -0,0 +1,66 @@
+// Optional C++ convenience layer over the Wickra C ABI (`wickra.h`).
+//
+// The C ABI hands out raw handles that must be released exactly once with the
+// matching `wickra_<ind>_free`. `wickra::Handle` wraps that in a move-only RAII
+// owner so the free happens automatically at scope exit:
+//
+//     #include "wickra.hpp"
+//
+//     wickra::Handle<Sma, wickra_sma_free> sma(wickra_sma_new(14));
+//     if (sma) {
+//         double v = wickra_sma_update(sma.get(), 42.0);  // NaN during warmup
+//     }
+//     // sma is freed here
+//
+// This is header-only and adds no runtime cost beyond the C calls themselves.
+
+#ifndef WICKRA_HPP
+#define WICKRA_HPP
+
+#include "wickra.h"
+
+#include <utility>
+
+namespace wickra {
+
+/// Move-only RAII owner of a Wickra handle. `T` is the opaque indicator type and
+/// `Free` its `wickra_<ind>_free` function.
+template <typename T, void (*Free)(T *)>
+class Handle {
+public:
+    explicit Handle(T *ptr) noexcept : ptr_(ptr) {}
+
+    ~Handle() {
+        if (ptr_ != nullptr) {
+            Free(ptr_);
+        }
+    }
+
+    Handle(const Handle &) = delete;
+    Handle &operator=(const Handle &) = delete;
+
+    Handle(Handle &&other) noexcept : ptr_(std::exchange(other.ptr_, nullptr)) {}
+
+    Handle &operator=(Handle &&other) noexcept {
+        if (this != &other) {
+            if (ptr_ != nullptr) {
+                Free(ptr_);
+            }
+            ptr_ = std::exchange(other.ptr_, nullptr);
+        }
+        return *this;
+    }
+
+    /// The raw handle, for passing to the `wickra_<ind>_*` functions.
+    T *get() const noexcept { return ptr_; }
+
+    /// True if the handle is non-null (construction succeeded).
+    explicit operator bool() const noexcept { return ptr_ != nullptr; }
+
+private:
+    T *ptr_;
+};
+
+}  // namespace wickra
+
+#endif  // WICKRA_HPP

bindings/csharp/.gitignore

@@ -0,0 +1,12 @@
+# .NET build output
+bin/
+obj/
+*.user
+
+# NuGet packaging output
+*.nupkg
+*.snupkg
+
+# Native libraries staged for packaging (produced by the release pipeline from
+# the wickra-c-<triple>.tar.gz assets; never committed to source).
+Wickra/runtimes/

bindings/csharp/README.md

@@ -0,0 +1,78 @@
+# Wickra — .NET
+
+[![CI](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
+[![codecov](https://codecov.io/gh/wickra-lib/wickra/branch/main/graph/badge.svg)](https://codecov.io/gh/wickra-lib/wickra)
+[![NuGet](https://img.shields.io/nuget/v/Wickra.svg?logo=nuget&color=blue)](https://www.nuget.org/packages/Wickra)
+[![License: MIT OR Apache-2.0](https://img.shields.io/badge/license-MIT_OR_Apache--2.0-blue)](https://github.com/wickra-lib/wickra#license)
+
+**Streaming-first technical indicators for .NET. `dotnet add package Wickra` —
+prebuilt native library, no system dependencies.**
+
+Wickra is a multi-language technical-analysis library with a Rust core and
+bindings for Python, Node.js and WebAssembly, plus a C ABI for C/C++, C#, Go, R and any
+other C-capable language. Every indicator is an O(1)
+streaming state machine, so live trading bots and historical backtests share
+the exact same implementation. This package is the .NET binding; it consumes the
+C ABI hub through `[LibraryImport]` P/Invoke and exposes all 514 streaming-first
+indicators as idiomatic `IDisposable` classes.
+
+## Install
+
+```bash
+dotnet add package Wickra
+```
+
+The native library ships prebuilt per platform (Linux, macOS, Windows — x64 and
+arm64) under `runtimes/<rid>/native/`, selected automatically. There is nothing
+to compile. Targets .NET 8 and later.
+
+## Quick start
+
+```csharp
+using Wickra;
+
+// Batch: run an indicator over a whole series (NaN at warmup positions).
+var prices = Enumerable.Range(0, 1000).Select(i => 100.0 + i * 0.1).ToArray();
+using var sma = new Sma(20);
+double[] values = sma.Batch(prices);
+
+// Streaming: the same indicator, fed tick by tick in O(1).
+using var rsi = new Rsi(14);
+foreach (var price in liveFeed)
+{
+    var value = rsi.Update(price); // NaN during warmup, no recomputation
+    if (double.IsFinite(value) && value > 70)
+    {
+        Console.WriteLine("overbought");
+    }
+}
+```
+
+`Batch(prices)` and feeding the same prices through `Update()` produce identical
+values — the equivalence is enforced by the test suite. Multi-output indicators
+(MACD, Bollinger, ADX, …) return a nullable `record struct`, `null` while warming up.
+
+## Documentation
+
+The full indicator catalogue, guides, quickstarts, and API reference live in
+the main repository and documentation site:
+
+- **Repository & full indicator list:** <https://github.com/wickra-lib/wickra>
+- **Docs** (quickstarts, cookbook, TA-Lib migration): <https://docs.wickra.org>
+- **Runnable examples:** [`examples/csharp/`](https://github.com/wickra-lib/wickra/tree/main/examples/csharp)
+
+Wickra ships native bindings for Python, Node.js, WebAssembly and Rust, plus a
+C ABI hub that any C-capable language (C, C++, Go, C#, Java, R) links against —
+all exposing the same indicators from the shared, `unsafe`-forbidden Rust core.
+
+## Disclaimer
+
+Wickra is an indicator toolkit, not a trading system. The values it computes
+are deterministic transforms of the input data — they are not financial advice
+and do not predict the market. Any use in a live trading context is at your own
+risk. The library is provided **as is**, without warranty of any kind.
+
+## License
+
+Licensed under either of [Apache-2.0](https://github.com/wickra-lib/wickra/blob/main/LICENSE-APACHE)
+or [MIT](https://github.com/wickra-lib/wickra/blob/main/LICENSE-MIT) at your option.

bindings/csharp/Wickra.Tests/ArchetypeTests.cs

@@ -0,0 +1,144 @@
+using Wickra;
+using Xunit;
+
+namespace Wickra.Tests;
+
+/// <summary>
+/// One representative per FFI archetype, exercising every marshalling path the
+/// generator produces (scalar, candle, pairwise, multi-output, bars, profile,
+/// values-profile, array-input). Garbage marshalling surfaces as NaN, wild
+/// values, or crashes — so finite/sane assertions are the real check.
+/// </summary>
+public class ArchetypeTests
+{
+    private static (double open, double high, double low, double close, double volume, long ts) Candle(int i)
+    {
+        var close = 100.0 + 10.0 * Math.Sin(i * 0.3);
+        var open = 100.0 + 10.0 * Math.Sin((i - 1) * 0.3);
+        var high = Math.Max(open, close) + 1.0;
+        var low = Math.Min(open, close) - 1.0;
+        return (open, high, low, close, 1_000.0, i * 60_000L);
+    }
+
+    [Fact]
+    public void Scalar_Ema_IsFiniteAfterWarmup()
+    {
+        using var ema = new Ema(3);
+        double last = double.NaN;
+        for (var i = 1; i <= 10; i++)
+        {
+            last = ema.Update(i);
+        }
+
+        Assert.True(double.IsFinite(last));
+        Assert.InRange(last, 1.0, 10.0);
+    }
+
+    [Fact]
+    public void Candle_Atr_IsFinitePositive()
+    {
+        using var atr = new Atr(3);
+        double last = double.NaN;
+        for (var i = 0; i < 20; i++)
+        {
+            var (o, h, l, c, v, ts) = Candle(i);
+            last = atr.Update(o, h, l, c, v, ts);
+        }
+
+        Assert.True(double.IsFinite(last));
+        Assert.True(last > 0.0);
+    }
+
+    [Fact]
+    public void Pairwise_Beta_IsFinite()
+    {
+        using var beta = new Beta(5);
+        double last = double.NaN;
+        for (var i = 0; i < 30; i++)
+        {
+            var market = 100.0 + 10.0 * Math.Sin(i * 0.5);
+            var asset = 50.0 + 6.0 * Math.Sin(i * 0.5 + 0.2);
+            last = beta.Update(market, asset);
+        }
+
+        Assert.True(double.IsFinite(last));
+    }
+
+    [Fact]
+    public void MultiOutput_Adx_ReturnsFiniteStruct()
+    {
+        using var adx = new Adx(5);
+        AdxOutput? result = null;
+        for (var i = 0; i < 60; i++)
+        {
+            var (o, h, l, c, v, ts) = Candle(i);
+            result = adx.Update(o, h, l, c, v, ts);
+        }
+
+        Assert.NotNull(result);
+        Assert.True(double.IsFinite(result!.Value.Adx));
+        Assert.True(double.IsFinite(result.Value.PlusDi));
+        Assert.True(double.IsFinite(result.Value.MinusDi));
+    }
+
+    [Fact]
+    public void Bars_DollarBars_EmitsBars()
+    {
+        using var bars = new DollarBars(5_000.0);
+        var total = 0;
+        for (var i = 0; i < 200; i++)
+        {
+            var (o, h, l, c, v, ts) = Candle(i);
+            total += bars.Update(o, h, l, c, v, ts).Length;
+        }
+
+        Assert.True(total > 0);
+    }
+
+    [Fact]
+    public void Profile_VolumeProfile_ReturnsValues()
+    {
+        using var profile = new VolumeProfile(20, 8);
+        VolumeProfileOutputScalars? result = null;
+        for (var i = 0; i < 60; i++)
+        {
+            var (o, h, l, c, v, ts) = Candle(i);
+            result = profile.Update(o, h, l, c, v, ts);
+        }
+
+        Assert.NotNull(result);
+        Assert.NotNull(result!.Value.Values);
+        Assert.True(result.Value.PriceLow <= result.Value.PriceHigh);
+    }
+
+    [Fact]
+    public void ProfileValues_DayOfWeekProfile_NoCrash()
+    {
+        using var profile = new DayOfWeekProfile(0);
+        double[]? result = null;
+        for (var i = 0; i < 60; i++)
+        {
+            var close = 100.0 + 5.0 * Math.Sin(i * 0.2);
+            // one day apart so the day-of-week buckets fill
+            result = profile.Update(close, close + 1, close - 1, close, 1_000.0, i * 86_400_000L);
+        }
+
+        if (result is not null)
+        {
+            Assert.All(result, v => Assert.True(double.IsFinite(v)));
+        }
+    }
+
+    [Fact]
+    public void ArrayInput_DepthSlope_IsFinite()
+    {
+        using var slope = new DepthSlope();
+        ReadOnlySpan<double> bidPrice = stackalloc double[] { 99.0, 98.0, 97.0 };
+        ReadOnlySpan<double> bidSize = stackalloc double[] { 10.0, 20.0, 30.0 };
+        ReadOnlySpan<double> askPrice = stackalloc double[] { 101.0, 102.0, 103.0 };
+        ReadOnlySpan<double> askSize = stackalloc double[] { 12.0, 22.0, 32.0 };
+
+        var result = slope.Update(bidPrice, bidSize, askPrice, askSize);
+        Assert.True(double.IsFinite(result));
+    }
+}

bindings/csharp/Wickra.Tests/SmaTests.cs

@@ -0,0 +1,51 @@
+using Wickra;
+using Xunit;
+
+namespace Wickra.Tests;
+
+public class SmaTests
+{
+    [Fact]
+    public void StreamingMatchesReference()
+    {
+        using var sma = new Sma(3);
+        Assert.True(double.IsNaN(sma.Update(1)));
+        Assert.True(double.IsNaN(sma.Update(2)));
+        Assert.Equal(2.0, sma.Update(3), 9);
+        Assert.Equal(3.0, sma.Update(4), 9);
+        Assert.Equal(4.0, sma.Update(5), 9);
+    }
+
+    [Fact]
+    public void BatchMatchesStreaming()
+    {
+        using var sma = new Sma(3);
+        var output = sma.Batch(new double[] { 1, 2, 3, 4, 5 });
+
+        Assert.True(double.IsNaN(output[0]));
+        Assert.True(double.IsNaN(output[1]));
+        Assert.Equal(2.0, output[2], 9);
+        Assert.Equal(3.0, output[3], 9);
+        Assert.Equal(4.0, output[4], 9);
+    }
+
+    [Fact]
+    public void ResetClearsState()
+    {
+        using var sma = new Sma(3);
+        sma.Update(1);
+        sma.Update(2);
+        sma.Update(3);
+        sma.Reset();
+        Assert.True(double.IsNaN(sma.Update(10)));
+    }
+
+    [Fact]
+    public void ZeroPeriodThrows()
+    {
+        // Zero is rejected by the native constructor (returns NULL) -> ArgumentException;
+        // a negative period is caught earlier by the wrapper guard.
+        Assert.Throws<ArgumentException>(() => new Sma(0));
+        Assert.Throws<ArgumentOutOfRangeException>(() => new Sma(-1));
+    }
+}

bindings/csharp/Wickra.Tests/Wickra.Tests.csproj

@@ -0,0 +1,21 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <TargetFramework>net8.0</TargetFramework>
+    <LangVersion>latest</LangVersion>
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <IsPackable>false</IsPackable>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Microsoft.NET.Test.Sdk" Version="17.11.1" />
+    <PackageReference Include="xunit" Version="2.9.2" />
+    <PackageReference Include="xunit.runner.visualstudio" Version="2.8.2" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\Wickra\Wickra.csproj" />
+  </ItemGroup>
+
+</Project>

bindings/csharp/Wickra/Wickra.csproj

@@ -0,0 +1,57 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <TargetFramework>net8.0</TargetFramework>
+    <LangVersion>latest</LangVersion>
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <AllowUnsafeBlocks>true</AllowUnsafeBlocks>
+    <RootNamespace>Wickra</RootNamespace>
+    <AssemblyName>Wickra</AssemblyName>
+
+    <!-- NuGet package metadata -->
+    <PackageId>Wickra</PackageId>
+    <Version>0.7.8</Version>
+    <Authors>kingchenc</Authors>
+    <Description>High-performance streaming technical-analysis indicators (514 indicators) for .NET, backed by the native Rust core via the Wickra C ABI.</Description>
+    <PackageLicenseExpression>MIT OR Apache-2.0</PackageLicenseExpression>
+    <PackageProjectUrl>https://github.com/wickra-lib/wickra</PackageProjectUrl>
+    <RepositoryUrl>https://github.com/wickra-lib/wickra</RepositoryUrl>
+    <RepositoryType>git</RepositoryType>
+    <PackageTags>technical-analysis;indicators;trading;finance;streaming;ffi;native</PackageTags>
+    <PackageReadmeFile>README.md</PackageReadmeFile>
+    <IncludeSymbols>true</IncludeSymbols>
+    <SymbolPackageFormat>snupkg</SymbolPackageFormat>
+    <GenerateDocumentationFile>true</GenerateDocumentationFile>
+    <!-- A managed package carrying per-RID native assets; not built per-RID itself. -->
+    <IncludeBuildOutput>true</IncludeBuildOutput>
+    <!-- NU5128: managed package carrying only per-RID native assets.
+         CS1591: generated members are self-descriptive; hand-written API is documented. -->
+    <NoWarn>$(NoWarn);NU5128;CS1591</NoWarn>
+  </PropertyGroup>
+
+  <!--
+    Supported native runtime identifiers. The release pipeline builds the C ABI
+    per target triple and stages the libraries under
+    Wickra/runtimes/<rid>/native/ before `dotnet pack`:
+      win-x64   win-arm64   linux-x64   linux-arm64   osx-x64   osx-arm64
+  -->
+  <PropertyGroup>
+    <WickraRuntimeIdentifiers>win-x64;win-arm64;linux-x64;linux-arm64;osx-x64;osx-arm64</WickraRuntimeIdentifiers>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <None Include="..\README.md" Pack="true" PackagePath="\" />
+  </ItemGroup>
+
+  <!--
+    Native libraries are packed under runtimes/<rid>/native/ by the release pipeline,
+    which unpacks the wickra-c-<triple>.tar.gz assets into the matching RID folders.
+    For local development and tests the natives are resolved from the cargo target dir
+    via WickraNative's DllImportResolver.
+  -->
+  <ItemGroup>
+    <None Include="runtimes/**/native/*" Pack="true" PackagePath="runtimes" Condition="Exists('runtimes')" />
+  </ItemGroup>
+
+</Project>

bindings/csharp/Wickra/WickraHandle.cs

@@ -0,0 +1,26 @@
+using Microsoft.Win32.SafeHandles;
+
+namespace Wickra;
+
+/// <summary>
+/// Owns an opaque native indicator handle and releases it via the indicator's
+/// <c>_free</c> function. One generic handle type backs every indicator; the
+/// correct free routine is captured at construction time.
+/// </summary>
+internal sealed class WickraHandle : SafeHandleZeroOrMinusOneIsInvalid
+{
+    private readonly Action<nint> _free;
+
+    internal WickraHandle(nint handle, Action<nint> free)
+        : base(ownsHandle: true)
+    {
+        _free = free;
+        SetHandle(handle);
+    }
+
+    protected override bool ReleaseHandle()
+    {
+        _free(handle);
+        return true;
+    }
+}

bindings/csharp/Wickra/WickraNative.cs

@@ -0,0 +1,87 @@
+using System.Runtime.CompilerServices;
+using System.Runtime.InteropServices;
+
+namespace Wickra;
+
+/// <summary>
+/// Native library resolution for the Wickra C ABI.
+/// </summary>
+/// <remarks>
+/// When consumed as a NuGet package the native library ships under
+/// <c>runtimes/&lt;rid&gt;/native/</c> and the default runtime resolver finds it
+/// automatically. For local development (project reference against a cargo build)
+/// the resolver additionally walks up the directory tree to locate
+/// <c>target/release</c> or <c>target/debug</c>. Every candidate is validated to
+/// actually export the Wickra ABI before it is accepted, so an unrelated library
+/// of the same name cannot shadow the real one.
+/// </remarks>
+internal static class WickraNative
+{
+    /// <summary>The library name passed to <c>[LibraryImport]</c>.</summary>
+    internal const string LibraryName = "wickra";
+
+    // Any exported symbol works as a fingerprint; sma_new exists in every build.
+    private const string SentinelSymbol = "wickra_sma_new";
+
+    [ModuleInitializer]
+    internal static void Register()
+    {
+        NativeLibrary.SetDllImportResolver(typeof(WickraNative).Assembly, Resolve);
+    }
+
+    private static nint Resolve(string libraryName, System.Reflection.Assembly assembly, DllImportSearchPath? searchPath)
+    {
+        if (libraryName != LibraryName)
+        {
+            return nint.Zero;
+        }
+
+        // 1. Default resolution (NuGet runtimes/ layout, app-local copies). Accept
+        //    only if it is genuinely the Wickra ABI; otherwise discard and fall through.
+        if (NativeLibrary.TryLoad(libraryName, assembly, searchPath, out var handle))
+        {
+            if (Exports(handle))
+            {
+                return handle;
+            }
+
+            NativeLibrary.Free(handle);
+        }
+
+        // 2. Development fallback: locate the cargo build output.
+        var fileName = NativeFileName();
+        var dir = AppContext.BaseDirectory;
+        for (var i = 0; i < 16 && dir is not null; i++)
+        {
+            foreach (var profile in new[] { "release", "debug" })
+            {
+                var candidate = Path.Combine(dir, "target", profile, fileName);
+                if (File.Exists(candidate) && NativeLibrary.TryLoad(candidate, out var devHandle))
+                {
+                    if (Exports(devHandle))
+                    {
+                        return devHandle;
+                    }
+
+                    NativeLibrary.Free(devHandle);
+                }
+            }
+
+            dir = Path.GetDirectoryName(dir.TrimEnd(Path.DirectorySeparatorChar, Path.AltDirectorySeparatorChar));
+        }
+
+        return nint.Zero;
+    }
+
+    private static bool Exports(nint handle) => NativeLibrary.TryGetExport(handle, SentinelSymbol, out _);
+
+    private static string NativeFileName()
+    {
+        if (OperatingSystem.IsWindows())
+        {
+            return "wickra.dll";
+        }
+
+        return OperatingSystem.IsMacOS() ? "libwickra.dylib" : "libwickra.so";
+    }
+}

bindings/go/README.md

@@ -0,0 +1,100 @@
+# Wickra — Go
+
+[![CI](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
+[![codecov](https://codecov.io/gh/wickra-lib/wickra/branch/main/graph/badge.svg)](https://codecov.io/gh/wickra-lib/wickra)
+[![Go Reference](https://pkg.go.dev/badge/github.com/wickra-lib/wickra/bindings/go.svg)](https://pkg.go.dev/github.com/wickra-lib/wickra/bindings/go)
+[![License: MIT OR Apache-2.0](https://img.shields.io/badge/license-MIT_OR_Apache--2.0-blue)](https://github.com/wickra-lib/wickra#license)
+
+**Streaming-first technical indicators for Go, over the Wickra C ABI hub via cgo.**
+
+Wickra is a multi-language technical-analysis library with a Rust core and
+bindings for Python, Node.js and WebAssembly, plus a C ABI for C/C++, C#, Go and
+any other C-capable language. Every indicator is an O(1) streaming state machine,
+so live trading bots and historical backtests share the exact same
+implementation. This package is the Go binding; it consumes the C ABI hub through
+cgo and exposes all 514 streaming-first indicators as idiomatic types.
+
+## Install
+
+```bash
+go get github.com/wickra-lib/wickra/bindings/go
+```
+
+The binding uses cgo, so a C compiler is required, and it links against the
+prebuilt Wickra C ABI library. Build that library from the workspace and stage
+it under this package's `lib/` directory:
+
+```bash
+cargo build -p wickra-c --release
+cp target/release/libwickra.so    bindings/go/lib/   # Linux
+cp target/release/libwickra.dylib bindings/go/lib/   # macOS
+cp target/release/wickra.dll      bindings/go/lib/   # Windows (also on PATH at run time)
+```
+
+On Linux and macOS the library path is baked in via rpath; on Windows the DLL
+must be discoverable at run time (next to the executable or on `PATH`).
+
+## Quick start
+
+```go
+package main
+
+import (
+	"fmt"
+
+	wickra "github.com/wickra-lib/wickra/bindings/go"
+)
+
+func main() {
+	// Batch: run an indicator over a whole series (NaN at warmup positions).
+	prices := make([]float64, 1000)
+	for i := range prices {
+		prices[i] = 100.0 + float64(i)*0.1
+	}
+	sma, _ := wickra.NewSma(20)
+	defer sma.Close()
+	values := sma.Batch(prices)
+
+	// Streaming: the same indicator, fed tick by tick in O(1).
+	rsi, _ := wickra.NewRsi(14)
+	defer rsi.Close()
+	for _, price := range prices {
+		value := rsi.Update(price) // NaN during warmup, no recomputation
+		if value > 70 {
+			fmt.Println("overbought")
+		}
+	}
+	_ = values
+}
+```
+
+`Batch(prices)` and feeding the same prices through `Update()` produce identical
+values — the equivalence is enforced by the test suite. Multi-output indicators
+(MACD, Bollinger, ADX, …) return `(Output, bool)`, with `false` while warming up.
+Every indicator owns a native handle freed by `Close()`; a finalizer is wired as
+a backstop, but call `Close()` (e.g. with `defer`) to release memory promptly.
+
+## Documentation
+
+The full indicator catalogue, guides, quickstarts, and API reference live in the
+main repository and documentation site:
+
+- **Repository & full indicator list:** <https://github.com/wickra-lib/wickra>
+- **Docs** (quickstarts, cookbook, TA-Lib migration): <https://docs.wickra.org>
+- **Runnable examples:** [`examples/go/`](https://github.com/wickra-lib/wickra/tree/main/examples/go)
+
+Wickra ships native bindings for Python, Node.js, WebAssembly and Rust, plus a
+C ABI hub that any C-capable language (C, C++, C#, Go, Java, R) links against —
+all exposing the same indicators from the shared, `unsafe`-forbidden Rust core.
+
+## Disclaimer
+
+Wickra is an indicator toolkit, not a trading system. The values it computes are
+deterministic transforms of the input data — they are not financial advice and
+do not predict the market. Any use in a live trading context is at your own risk.
+The library is provided **as is**, without warranty of any kind.
+
+## License
+
+Licensed under either of [Apache-2.0](https://github.com/wickra-lib/wickra/blob/main/LICENSE-APACHE)
+or [MIT](https://github.com/wickra-lib/wickra/blob/main/LICENSE-MIT) at your option.

bindings/go/go.mod

@@ -0,0 +1,3 @@
+module github.com/wickra-lib/wickra/bindings/go
+
+go 1.23

bindings/go/lib/.gitignore

@@ -0,0 +1,7 @@
+# Prebuilt Wickra C ABI libraries are provisioned locally / in CI, not committed.
+*.so
+*.dylib
+*.dll
+*.a
+*.lib
+*.exp

bindings/go/wickra.go

@@ -0,0 +1,25 @@
+// Package wickra provides idiomatic Go bindings for the Wickra
+// technical-analysis library over its C ABI hub.
+//
+// Each indicator is an opaque-handle type with a New<Indicator> constructor and
+// Update/Batch/Reset/Close methods. Handles are freed by Close and, as a
+// backstop, by a finalizer; call Close explicitly to release native memory
+// promptly. The binding links against the prebuilt Wickra C ABI library
+// (libwickra.so/.dylib or wickra.dll) staged under ./lib — see the package
+// README for how to provision it.
+package wickra
+
+/*
+#cgo CFLAGS: -I${SRCDIR}/../c/include
+#cgo linux LDFLAGS: -L${SRCDIR}/lib -lwickra -Wl,-rpath,${SRCDIR}/lib
+#cgo darwin LDFLAGS: -L${SRCDIR}/lib -lwickra -Wl,-rpath,${SRCDIR}/lib
+#cgo windows LDFLAGS: -L${SRCDIR}/lib -l:wickra.dll
+#include "wickra.h"
+*/
+import "C"
+
+import "errors"
+
+// ErrInvalidParams is returned by a New<Indicator> constructor when the native
+// constructor rejects the supplied parameters (for example a zero period).
+var ErrInvalidParams = errors.New("wickra: invalid indicator parameters")

bindings/go/wickra_test.go

@@ -0,0 +1,151 @@
+package wickra
+
+import (
+	"math"
+	"testing"
+)
+
+// One indicator per FFI archetype, exercising the full New/Update/Batch/Reset/
+// Close surface against the real native library.
+
+func TestScalarKnownValue(t *testing.T) {
+	s, err := NewSma(3)
+	if err != nil {
+		t.Fatalf("NewSma: %v", err)
+	}
+	defer s.Close()
+
+	var last float64
+	for _, v := range []float64{1, 2, 3, 4, 5} {
+		last = s.Update(v)
+	}
+	if math.Abs(last-4.0) > 1e-9 {
+		t.Fatalf("sma(3) last = %v, want 4.0", last)
+	}
+}
+
+func TestScalarBatchMatchesStreaming(t *testing.T) {
+	input := []float64{1, 2, 3, 4, 5, 6, 7, 8}
+
+	stream, _ := NewSma(3)
+	defer stream.Close()
+	want := make([]float64, len(input))
+	for i, v := range input {
+		want[i] = stream.Update(v)
+	}
+
+	batchInd, _ := NewSma(3)
+	defer batchInd.Close()
+	got := batchInd.Batch(input)
+
+	if len(got) != len(want) {
+		t.Fatalf("batch len = %d, want %d", len(got), len(want))
+	}
+	for i := range want {
+		if math.IsNaN(want[i]) && math.IsNaN(got[i]) {
+			continue
+		}
+		if math.Abs(got[i]-want[i]) > 1e-9 {
+			t.Fatalf("batch[%d] = %v, streaming = %v", i, got[i], want[i])
+		}
+	}
+}
+
+func TestMultiOutput(t *testing.T) {
+	m, err := NewMacdIndicator(3, 6, 3)
+	if err != nil {
+		t.Fatalf("NewMacdIndicator: %v", err)
+	}
+	defer m.Close()
+
+	var ok bool
+	var out MacdOutput
+	for i := 0; i < 30; i++ {
+		out, ok = m.Update(100 + float64(i))
+	}
+	if !ok {
+		t.Fatal("macd never produced a value after warmup")
+	}
+	if math.IsNaN(out.Macd) {
+		t.Fatal("macd value is NaN after warmup")
+	}
+}
+
+func TestBars(t *testing.T) {
+	rb, err := NewRangeBars(2.0)
+	if err != nil {
+		t.Fatalf("NewRangeBars: %v", err)
+	}
+	defer rb.Close()
+
+	total := 0
+	for _, p := range []float64{100, 101, 103, 104, 99, 96, 102, 108, 95, 110} {
+		bars := rb.Update(p, p, p, p, 1, 0)
+		total += len(bars)
+	}
+	if total == 0 {
+		t.Fatal("range bars produced no bars over a 15-point move")
+	}
+}
+
+func TestProfile(t *testing.T) {
+	vp, err := NewVolumeProfile(10, 24)
+	if err != nil {
+		t.Fatalf("NewVolumeProfile: %v", err)
+	}
+	defer vp.Close()
+
+	var ok bool
+	var snap VolumeProfileOutputScalars
+	for i := 0; i < 50; i++ {
+		price := 100 + 5*math.Sin(float64(i)*0.3)
+		snap, ok = vp.Update(price, price+1, price-1, price, 1000, int64(i))
+	}
+	if !ok {
+		t.Fatal("volume profile never produced a snapshot")
+	}
+	if len(snap.Values) == 0 {
+		t.Fatal("volume profile returned an empty values buffer")
+	}
+}
+
+func TestArrayInput(t *testing.T) {
+	ob, err := NewOrderBookImbalanceFull()
+	if err != nil {
+		t.Fatalf("NewOrderBookImbalanceFull: %v", err)
+	}
+	defer ob.Close()
+
+	bidPrice := []float64{99.9, 99.8, 99.7}
+	bidSize := []float64{5, 3, 2}
+	askPrice := []float64{100.1, 100.2, 100.3}
+	askSize := []float64{1, 1, 1}
+	v := ob.Update(bidPrice, bidSize, askPrice, askSize)
+	if math.IsNaN(v) {
+		t.Fatal("order-book imbalance is NaN on a populated book")
+	}
+}
+
+func TestResetReturnsToWarmup(t *testing.T) {
+	s, _ := NewSma(3)
+	defer s.Close()
+	for _, v := range []float64{1, 2, 3} {
+		s.Update(v)
+	}
+	s.Reset()
+	if got := s.Update(10); !math.IsNaN(got) {
+		t.Fatalf("after reset first update = %v, want NaN (warmup)", got)
+	}
+}
+
+func TestInvalidParams(t *testing.T) {
+	if _, err := NewSma(0); err == nil {
+		t.Fatal("NewSma(0) should return ErrInvalidParams")
+	}
+}
+
+func TestCloseIsIdempotent(t *testing.T) {
+	s, _ := NewSma(3)
+	s.Close()
+	s.Close() // must not panic or double-free
+}

bindings/node/README.md

@@ -9,7 +9,8 @@
 prebuilt native binary, no system dependencies.**
 
 Wickra is a multi-language technical-analysis library with a Rust core and
-bindings for Python, Node.js, and WebAssembly. Every indicator is an O(1)
+bindings for Python, Node.js and WebAssembly, plus a C ABI for C/C++, C#, Go, R and any
+other C-capable language. Every indicator is an O(1)
 streaming state machine, so live trading bots and historical backtests share
 the exact same implementation. This package is the Node.js binding (napi-rs);
 it exposes 200+ streaming-first indicators across sixteen families.
@@ -55,8 +56,9 @@ the main repository and documentation site:
 - **Docs** (quickstarts, cookbook, TA-Lib migration): <https://docs.wickra.org>
 - **Runnable examples:** [`examples/node/`](https://github.com/wickra-lib/wickra/tree/main/examples/node)
 
-Wickra ships four bindings — Python, Node.js, WebAssembly, and Rust — that all
-expose the same indicators from the shared, `unsafe`-forbidden Rust core.
+Wickra ships native bindings for Python, Node.js, WebAssembly and Rust, plus a
+C ABI hub that any C-capable language (C, C++, Go, C#, Java, R) links against —
+all exposing the same indicators from the shared, `unsafe`-forbidden Rust core.
 
 ## Disclaimer
 

bindings/node/__tests__/completeness.test.js

@@ -14,7 +14,18 @@ const wickra = require('..');
 // but intentionally not isReady/warmupPeriod, so they are excluded from the
 // Indicator completeness contract below (their interface is covered by the
 // dedicated bar-builder tests).
-const BAR_BUILDERS = new Set(['RenkoBars', 'KagiBars', 'PointAndFigureBars']);
+const BAR_BUILDERS = new Set([
+  'RenkoBars',
+  'KagiBars',
+  'PointAndFigureBars',
+  'RangeBars',
+  'TickBars',
+  'VolumeBars',
+  'DollarBars',
+  'ImbalanceBars',
+  'RunBars',
+  'ThreeLineBreakBars',
+]);
 
 // An "indicator class" is an exported constructor whose prototype carries the
 // streaming `update` method. This excludes `version` (a plain function), the bar

bindings/node/__tests__/indicators.test.js

@@ -28,6 +28,38 @@ function num(v) {
 // --- Scalar indicators: update(value) vs batch(prices) ---
 
 const scalarFactories = {
+  M2Measure: () => new wickra.M2Measure(20, 0.0, 0.02),
+  UpsidePotentialRatio: () => new wickra.UpsidePotentialRatio(20, 0.0),
+  GainToPainRatio: () => new wickra.GainToPainRatio(12),
+  CommonSenseRatio: () => new wickra.CommonSenseRatio(20),
+  KRatio: () => new wickra.KRatio(30),
+  TailRatio: () => new wickra.TailRatio(20),
+  MartinRatio: () => new wickra.MartinRatio(14),
+  BurkeRatio: () => new wickra.BurkeRatio(12),
+  SterlingRatio: () => new wickra.SterlingRatio(12),
+  AUTOCORRPGRAM: () => new wickra.AUTOCORRPGRAM(10, 48),
+  EVENBETTERSINE: () => new wickra.EVENBETTERSINE(40, 10),
+  BANDPASS: () => new wickra.BANDPASS(20, 0.3),
+  UNIVERSALOSC: () => new wickra.UNIVERSALOSC(20),
+  ADAPTIVERSI: () => new wickra.ADAPTIVERSI(14),
+  CTI: () => new wickra.CTI(20),
+  TRENDFLEX: () => new wickra.TRENDFLEX(20),
+  REFLEX: () => new wickra.REFLEX(20),
+  HIGHPASS: () => new wickra.HIGHPASS(48),
+  SAMPLEENT: () => new wickra.SAMPLEENT(20, 2, 0.2),
+  SHANNONENT: () => new wickra.SHANNONENT(20, 8),
+  ROLLINGMINMAX: () => new wickra.ROLLINGMINMAX(20),
+  JARQUEBERA: () => new wickra.JARQUEBERA(20),
+  BipowerVariation: () => new wickra.BipowerVariation(20),
+  VolatilityOfVolatility: () => new wickra.VolatilityOfVolatility(20, 20),
+  Garch11: () => new wickra.Garch11(0.000002, 0.1, 0.88),
+  EwmaVolatility: () => new wickra.EwmaVolatility(0.94),
+  PpoHistogram: () => new wickra.PpoHistogram(3, 6, 3),
+  MacdHistogram: () => new wickra.MacdHistogram(3, 6, 3),
+  TsfOscillator: () => new wickra.TsfOscillator(3),
+  WAVE_PM: () => new wickra.WAVE_PM(32, 3),
+  POLARIZED_FRACTAL_EFFICIENCY: () => new wickra.POLARIZED_FRACTAL_EFFICIENCY(10, 5),
+  TREND_STRENGTH_INDEX: () => new wickra.TREND_STRENGTH_INDEX(20),
   DerivativeOscillator: () => new wickra.DerivativeOscillator(14, 5, 3, 9),
   RMI: () => new wickra.RMI(14, 5),
   DynamicMomentumIndex: () => new wickra.DynamicMomentumIndex(14),
@@ -342,6 +374,36 @@ const candleScalar = {
   HighLowRange: { make: () => new wickra.HighLowRange(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
   StochasticCCI: { make: () => new wickra.StochasticCCI(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
   IMI: { make: () => new wickra.IMI(14), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  TTM_TREND: { make: () => new wickra.TTM_TREND(6), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  Qstick: { make: () => new wickra.Qstick(10), step: (ind, i) => ind.update(open[i], close[i]), batch: (ind) => ind.batch(open, close) },
+  VolatilityRatio: { make: () => new wickra.VolatilityRatio(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  ProjectionOscillator: { make: () => new wickra.ProjectionOscillator(14), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  TimeBasedStop: { make: () => new wickra.TimeBasedStop(5), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  VolumeRsi: { make: () => new wickra.VolumeRsi(14), step: (ind, i) => ind.update(close[i], volume[i]), batch: (ind) => ind.batch(close, volume) },
+  Wad: { make: () => new wickra.Wad(), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  TwiggsMoneyFlow: { make: () => new wickra.TwiggsMoneyFlow(21), step: (ind, i) => ind.update(high[i], low[i], close[i], volume[i]), batch: (ind) => ind.batch(high, low, close, volume) },
+  TradeVolumeIndex: { make: () => new wickra.TradeVolumeIndex(0.25), step: (ind, i) => ind.update(close[i], volume[i]), batch: (ind) => ind.batch(close, volume) },
+  IntradayIntensity: { make: () => new wickra.IntradayIntensity(), step: (ind, i) => ind.update(high[i], low[i], close[i], volume[i]), batch: (ind) => ind.batch(high, low, close, volume) },
+  BetterVolume: { make: () => new wickra.BetterVolume(14), step: (ind, i) => ind.update(high[i], low[i], close[i], volume[i]), batch: (ind) => ind.batch(high, low, close, volume) },
+  ADAPTIVECCI: { make: () => new wickra.ADAPTIVECCI(20), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  PivotReversal: { make: () => new wickra.PivotReversal(1, 1), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  TDCamouflage: { make: () => new wickra.TDCamouflage(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  TDClop: { make: () => new wickra.TDClop(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  TDClopwin: { make: () => new wickra.TDClopwin(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  TDPropulsion: { make: () => new wickra.TDPropulsion(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  TDTrap: { make: () => new wickra.TDTrap(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  TDDWave: { make: () => new wickra.TDDWave(2), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  HeikinAshiOscillator: { make: () => new wickra.HeikinAshiOscillator(5), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  ThreeLineBreak: { make: () => new wickra.ThreeLineBreak(3), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  Tristar: { make: () => new wickra.Tristar(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  HaramiCross: { make: () => new wickra.HaramiCross(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  TowerTopBottom: { make: () => new wickra.TowerTopBottom(), step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  DumplingTop: { make: () => new wickra.DumplingTop(9), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  NewPriceLines: { make: () => new wickra.NewPriceLines(5), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  FryPanBottom: { make: () => new wickra.FryPanBottom(9), step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  NakedPoc: { make: () => new wickra.NakedPoc(20, 24), step: (ind, i) => ind.update(high[i], low[i], close[i], volume[i]), batch: (ind) => ind.batch(high, low, close, volume) },
+  SinglePrints: { make: () => new wickra.SinglePrints(20, 24), step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  ProfileShape: { make: () => new wickra.ProfileShape(20, 24), step: (ind, i) => ind.update(high[i], low[i], volume[i]), batch: (ind) => ind.batch(high, low, volume) },
 };
 
 for (const [name, d] of Object.entries(candleScalar)) {
@@ -426,6 +488,29 @@ const multi = {
   FibTimeZones: { make: () => new wickra.FibTimeZones(), fields: ['onZone', 'barsToNext'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
   ElderRay: { make: () => new wickra.ElderRay(13), fields: ['bullPower', 'bearPower'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
   QQE: { make: () => new wickra.QQE(14, 5, 4.236), fields: ['rsiMa', 'trailingLine'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  GatorOscillator: { make: () => new wickra.GatorOscillator(13, 8, 5), fields: ['upper', 'lower'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  KasePermissionStochastic: { make: () => new wickra.KasePermissionStochastic(9, 3), fields: ['fast', 'slow'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  VolatilityCone: { make: () => new wickra.VolatilityCone(20, 60), fields: ['current', 'min', 'median', 'max', 'percentile'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  QuartileBands: { make: () => new wickra.QuartileBands(4), fields: ['upper', 'middle', 'lower'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  BomarBands: { make: () => new wickra.BomarBands(4, 0.85), fields: ['upper', 'middle', 'lower'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  MedianChannel: { make: () => new wickra.MedianChannel(5, 2.0), fields: ['upper', 'middle', 'lower'], step: (ind, i) => ind.update(close[i]), batch: (ind) => ind.batch(close) },
+  ProjectionBands: { make: () => new wickra.ProjectionBands(3), fields: ['upper', 'middle', 'lower'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  KaseDevStop: { make: () => new wickra.KaseDevStop(3, 1.0), fields: ['value', 'direction'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  ElderSafeZone: { make: () => new wickra.ElderSafeZone(14, 2.0), fields: ['value', 'direction'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  AtrRatchet: { make: () => new wickra.AtrRatchet(14, 4.0, 0.1), fields: ['value', 'direction'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  Nrtr: { make: () => new wickra.Nrtr(2.0), fields: ['value', 'direction'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  ModifiedMaStop: { make: () => new wickra.ModifiedMaStop(14), fields: ['value', 'direction'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  VolumeWeightedMacd: { make: () => new wickra.VolumeWeightedMacd(12, 26, 9), fields: ['macd', 'signal', 'histogram'], step: (ind, i) => ind.update(close[i], volume[i]), batch: (ind) => ind.batch(close, volume) },
+  CentralPivotRange: { make: () => new wickra.CentralPivotRange(), fields: ['pivot', 'tc', 'bc'], step: (ind, i) => ind.update(high[i], low[i], close[i]), batch: (ind) => ind.batch(high, low, close) },
+  MurreyMathLines: { make: () => new wickra.MurreyMathLines(4), fields: ['mm8_8', 'mm7_8', 'mm6_8', 'mm5_8', 'mm4_8', 'mm3_8', 'mm2_8', 'mm1_8', 'mm0_8'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  AndrewsPitchfork: { make: () => new wickra.AndrewsPitchfork(2), fields: ['median', 'upper', 'lower'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  VolumeWeightedSr: { make: () => new wickra.VolumeWeightedSr(3), fields: ['support', 'resistance'], step: (ind, i) => ind.update(high[i], low[i], volume[i]), batch: (ind) => ind.batch(high, low, volume) },
+  TDMovingAverage: { make: () => new wickra.TDMovingAverage(5, 13), fields: ['st1', 'st2'], step: (ind, i) => ind.update(high[i], low[i]), batch: (ind) => ind.batch(high, low) },
+  SmoothedHeikinAshi: { make: () => new wickra.SmoothedHeikinAshi(5), fields: ['open', 'high', 'low', 'close'], step: (ind, i) => ind.update(open[i], high[i], low[i], close[i]), batch: (ind) => ind.batch(open, high, low, close) },
+  Equivolume: { make: () => new wickra.Equivolume(20), fields: ['height', 'width'], step: (ind, i) => ind.update(high[i], low[i], volume[i]), batch: (ind) => ind.batch(high, low, volume) },
+  CandleVolume: { make: () => new wickra.CandleVolume(20), fields: ['body', 'width'], step: (ind, i) => ind.update(open[i], close[i], volume[i]), batch: (ind) => ind.batch(open, close, volume) },
+  HighLowVolumeNodes: { make: () => new wickra.HighLowVolumeNodes(20, 24), fields: ['hvn', 'lvn'], step: (ind, i) => ind.update(high[i], low[i], volume[i]), batch: (ind) => ind.batch(high, low, volume) },
+  CompositeProfile: { make: () => new wickra.CompositeProfile(20, 24, 0.7), fields: ['poc', 'vah', 'val'], step: (ind, i) => ind.update(high[i], low[i], volume[i]), batch: (ind) => ind.batch(high, low, volume) },
 };
 
 for (const [name, d] of Object.entries(multi)) {
@@ -595,6 +680,8 @@ const pairFactories = {
   VarianceRatio: () => new wickra.VarianceRatio(60, 2),
   GrangerCausality: () => new wickra.GrangerCausality(60, 1),
   SpreadAr1Coefficient: () => new wickra.SpreadAr1Coefficient(40),
+  KendallTau: () => new wickra.KendallTau(20),
+  HasbrouckInformationShare: () => new wickra.HasbrouckInformationShare(2),
 };
 
 for (const [name, make] of Object.entries(pairFactories)) {
@@ -1198,7 +1285,7 @@ test('vpin / amihud / roll reference + streaming matches batch', () => {
   const price = Array.from({ length: n }, (_, i) => 100 + Math.sin(i * 0.25) * 4);
   const size = Array.from({ length: n }, (_, i) => 1 + (i % 5));
   const isBuy = Array.from({ length: n }, (_, i) => i % 2 === 0);
-  for (const make of [() => new wickra.Vpin(8, 5), () => new wickra.AmihudIlliquidity(14), () => new wickra.RollMeasure(14)]) {
+  for (const make of [() => new wickra.Vpin(8, 5), () => new wickra.AmihudIlliquidity(14), () => new wickra.RollMeasure(14), () => new wickra.TradeSignAutocorrelation(10), () => new wickra.Pin(10)]) {
     const batch = make().batch(price, size, isBuy);
     const streamer = make();
     assert.equal(batch.length, n);
@@ -1207,6 +1294,16 @@ test('vpin / amihud / roll reference + streaming matches batch', () => {
       assert.ok((Number.isNaN(batch[i]) && s === null) || Math.abs(s - batch[i]) < 1e-9, `mismatch at ${i}`);
     }
   }
+  // Trade-sign autocorrelation: alternating signs -> -1, all buys -> +1.
+  let tsac = null;
+  const tsacInd = new wickra.TradeSignAutocorrelation(10);
+  for (let i = 0; i < 20; i++) tsac = tsacInd.update(100, 1, i % 2 === 0);
+  assert.ok(Math.abs(tsac - -1.0) < 1e-12);
+  // PIN: one-sided flow -> 1, balanced flow -> 0.
+  let pin = null;
+  const pinInd = new wickra.Pin(10);
+  for (let i = 0; i < 20; i++) pin = pinInd.update(100, 1, true);
+  assert.ok(Math.abs(pin - 1.0) < 1e-12);
 });
 
 test('price-impact indicators reference values', () => {
@@ -1360,6 +1457,56 @@ test('derivatives reject bad input', () => {
   assert.throws(() => new wickra.FundingBasis().update(100, 0));
 });
 
+test('B16 derivatives reference values', () => {
+  // Estimated leverage: oi / (long + short) = 200 / 100 = 2.
+  assert.ok(Math.abs(new wickra.EstimatedLeverageRatio().update(200, 60, 40) - 2.0) < 1e-12);
+  // OI-to-volume: oi / (buy + sell) = 100 / 50 = 2.
+  assert.ok(Math.abs(new wickra.OiToVolumeRatio().update(100, 30, 20) - 2.0) < 1e-12);
+  // Perpetual premium: (mark - index) / index = 0.5 / 100 = 0.005.
+  assert.ok(Math.abs(new wickra.PerpetualPremiumIndex().update(100.5, 100.0) - 0.005) < 1e-12);
+  // Funding-implied APR: rate * intervals = 0.0001 * 1095 = 0.1095.
+  assert.ok(Math.abs(new wickra.FundingImpliedApr(1095).update(0.0001) - 0.1095) < 1e-12);
+  // Open-interest momentum (period 2): warmup then ROC% = 100*(120 - 100)/100 = 20.
+  const oim = new wickra.OpenInterestMomentum(2);
+  assert.equal(oim.update(100), null);
+  assert.equal(oim.update(110), null);
+  assert.ok(Math.abs(oim.update(120) - 20.0) < 1e-12);
+});
+
+test('B16 derivatives streaming matches batch', () => {
+  const n = 30;
+  const oi = Array.from({ length: n }, (_, i) => 1000 + 50 * Math.sin(i * 0.3));
+  const longSz = Array.from({ length: n }, (_, i) => 600 + 20 * Math.cos(i * 0.2));
+  const shortSz = Array.from({ length: n }, (_, i) => 400 + 15 * Math.sin(i * 0.4));
+  const buy = Array.from({ length: n }, (_, i) => 300 + 10 * Math.sin(i * 0.5));
+  const sell = Array.from({ length: n }, (_, i) => 250 + 12 * Math.cos(i * 0.35));
+  const index = Array.from({ length: n }, (_, i) => 100 + Math.sin(i * 0.2));
+  const mark = Array.from({ length: n }, (_, i) => index[i] + 0.05 * Math.cos(i * 0.3));
+  const rate = Array.from({ length: n }, (_, i) => 0.0001 * Math.sin(i * 0.3));
+  const cmp = (batch, s, i) =>
+    assert.ok((s === null && Number.isNaN(batch[i])) || Math.abs(s - batch[i]) < 1e-12, `mismatch at ${i}`);
+
+  let b = new wickra.EstimatedLeverageRatio().batch(oi, longSz, shortSz);
+  let st = new wickra.EstimatedLeverageRatio();
+  for (let i = 0; i < n; i++) cmp(b, st.update(oi[i], longSz[i], shortSz[i]), i);
+
+  b = new wickra.OiToVolumeRatio().batch(oi, buy, sell);
+  st = new wickra.OiToVolumeRatio();
+  for (let i = 0; i < n; i++) cmp(b, st.update(oi[i], buy[i], sell[i]), i);
+
+  b = new wickra.PerpetualPremiumIndex().batch(mark, index);
+  st = new wickra.PerpetualPremiumIndex();
+  for (let i = 0; i < n; i++) cmp(b, st.update(mark[i], index[i]), i);
+
+  b = new wickra.FundingImpliedApr(1095).batch(rate);
+  st = new wickra.FundingImpliedApr(1095);
+  for (let i = 0; i < n; i++) cmp(b, st.update(rate[i]), i);
+
+  b = new wickra.OpenInterestMomentum(10).batch(oi);
+  st = new wickra.OpenInterestMomentum(10);
+  for (let i = 0; i < n; i++) cmp(b, st.update(oi[i]), i);
+});
+
 test('market breadth: AdvanceDecline reference values', () => {
   // A breadth tick is the universe as parallel arrays; the sign of `change`
   // classifies each symbol as advancing / declining / unchanged.
@@ -1622,3 +1769,72 @@ test('PointAndFigureBars closes a column on a 3-box reversal', () => {
   assert.equal(col[0].direction, 1);
   assert.ok(Math.abs(col[0].high - 15) < 1e-9 && Math.abs(col[0].low - 10) < 1e-9);
 });
+
+test('RangeBars prints aligned bars on an up move', () => {
+  const rb = new wickra.RangeBars(1.0);
+  assert.deepEqual(rb.update(10), []); // seed
+  const up = rb.update(13);
+  assert.equal(up.length, 3);
+  assert.ok(Math.abs(up[0].open - 10) < 1e-9 && Math.abs(up[2].close - 13) < 1e-9);
+  assert.ok(up.every((b) => b.direction === 1));
+});
+
+test('TickBars groups a fixed number of candles', () => {
+  const tb = new wickra.TickBars(2);
+  assert.deepEqual(tb.update(10, 11, 9, 10.5, 100), []);
+  const out = tb.update(10.5, 12, 10, 11, 150);
+  assert.equal(out.length, 1);
+  assert.ok(Math.abs(out[0].open - 10) < 1e-9);
+  assert.ok(Math.abs(out[0].high - 12) < 1e-9);
+  assert.ok(Math.abs(out[0].low - 9) < 1e-9);
+  assert.ok(Math.abs(out[0].close - 11) < 1e-9);
+  assert.ok(Math.abs(out[0].volume - 250) < 1e-9);
+});
+
+test('VolumeBars closes when accumulated volume crosses the threshold', () => {
+  const vb = new wickra.VolumeBars(100);
+  assert.deepEqual(vb.update(10, 10, 10, 10, 60), []);
+  const out = vb.update(10.5, 10.5, 10.5, 10.5, 60);
+  assert.equal(out.length, 1);
+  assert.ok(Math.abs(out[0].volume - 120) < 1e-9);
+});
+
+test('DollarBars closes when traded value crosses the threshold', () => {
+  const db = new wickra.DollarBars(1000);
+  assert.deepEqual(db.update(10, 10, 10, 10, 60), []);
+  const out = db.update(10, 10, 10, 10, 60);
+  assert.equal(out.length, 1);
+  assert.ok(Math.abs(out[0].dollar - 1200) < 1e-9);
+  assert.ok(Math.abs(out[0].volume - 120) < 1e-9);
+});
+
+test('ImbalanceBars closes a buy bar at the threshold', () => {
+  const ib = new wickra.ImbalanceBars(3.0);
+  ib.update(10, 10, 10, 10);
+  ib.update(11, 11, 11, 11);
+  ib.update(12, 12, 12, 12);
+  const out = ib.update(13, 13, 13, 13);
+  assert.equal(out.length, 1);
+  assert.equal(out[0].direction, 1);
+  assert.ok(Math.abs(out[0].imbalance - 3) < 1e-9);
+});
+
+test('RunBars closes a buy run at the run length', () => {
+  const rb = new wickra.RunBars(3);
+  rb.update(10, 10, 10, 10);
+  rb.update(11, 11, 11, 11);
+  rb.update(12, 12, 12, 12);
+  const out = rb.update(13, 13, 13, 13);
+  assert.equal(out.length, 1);
+  assert.equal(out[0].direction, 1);
+  assert.equal(out[0].length, 3);
+});
+
+test('ThreeLineBreakBars draws a rising line', () => {
+  const tlb = new wickra.ThreeLineBreakBars(3);
+  assert.deepEqual(tlb.update(10), []); // seed
+  const out = tlb.update(11);
+  assert.equal(out.length, 1);
+  assert.equal(out[0].direction, 1);
+  assert.ok(Math.abs(out[0].open - 10) < 1e-9 && Math.abs(out[0].close - 11) < 1e-9);
+});

bindings/node/npm/darwin-arm64/package.json

@@ -1,6 +1,6 @@
 {
   "name": "wickra-darwin-arm64",
-  "version": "0.5.6",
+  "version": "0.7.8",
   "description": "Native binding for wickra (macOS Apple Silicon). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.darwin-arm64.node",
   "files": [

bindings/node/npm/darwin-x64/package.json

@@ -1,6 +1,6 @@
 {
   "name": "wickra-darwin-x64",
-  "version": "0.5.6",
+  "version": "0.7.8",
   "description": "Native binding for wickra (macOS Intel). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.darwin-x64.node",
   "files": [

bindings/node/npm/linux-arm64-gnu/package.json

@@ -1,6 +1,6 @@
 {
   "name": "wickra-linux-arm64-gnu",
-  "version": "0.5.6",
+  "version": "0.7.8",
   "description": "Native binding for wickra (linux arm64 GNU). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.linux-arm64-gnu.node",
   "files": [

bindings/node/npm/linux-x64-gnu/package.json

@@ -1,6 +1,6 @@
 {
   "name": "wickra-linux-x64-gnu",
-  "version": "0.5.6",
+  "version": "0.7.8",
   "description": "Native binding for wickra (linux x64 GNU). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.linux-x64-gnu.node",
   "files": [

bindings/node/npm/win32-arm64-msvc/package.json

@@ -1,6 +1,6 @@
 {
   "name": "wickra-win32-arm64-msvc",
-  "version": "0.5.6",
+  "version": "0.7.8",
   "description": "Native binding for wickra (Windows arm64 MSVC). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.win32-arm64-msvc.node",
   "files": [

bindings/node/npm/win32-x64-msvc/package.json

@@ -1,6 +1,6 @@
 {
   "name": "wickra-win32-x64-msvc",
-  "version": "0.5.6",
+  "version": "0.7.8",
   "description": "Native binding for wickra (Windows x64 MSVC). Installed automatically as an optional dependency of wickra on matching platforms.",
   "main": "wickra.win32-x64-msvc.node",
   "files": [

bindings/node/package-lock.json

@@ -1,12 +1,12 @@
 {
   "name": "wickra",
-  "version": "0.5.6",
+  "version": "0.7.8",
   "lockfileVersion": 3,
   "requires": true,
   "packages": {
     "": {
       "name": "wickra",
-      "version": "0.5.6",
+      "version": "0.7.8",
       "license": "MIT OR Apache-2.0",
       "devDependencies": {
         "@napi-rs/cli": "^2.18.0"
@@ -15,12 +15,12 @@
         "node": ">= 18"
       },
       "optionalDependencies": {
-        "wickra-darwin-arm64": "0.5.6",
-        "wickra-darwin-x64": "0.5.6",
-        "wickra-linux-arm64-gnu": "0.5.6",
-        "wickra-linux-x64-gnu": "0.5.6",
-        "wickra-win32-arm64-msvc": "0.5.6",
-        "wickra-win32-x64-msvc": "0.5.6"
+        "wickra-darwin-arm64": "0.7.8",
+        "wickra-darwin-x64": "0.7.8",
+        "wickra-linux-arm64-gnu": "0.7.8",
+        "wickra-linux-x64-gnu": "0.7.8",
+        "wickra-win32-arm64-msvc": "0.7.8",
+        "wickra-win32-x64-msvc": "0.7.8"
       }
     },
     "node_modules/@napi-rs/cli": {
@@ -41,8 +41,8 @@
       }
     },
     "node_modules/wickra-darwin-arm64": {
-      "version": "0.5.6",
-      "resolved": "https://registry.npmjs.org/wickra-darwin-arm64/-/wickra-darwin-arm64-0.5.6.tgz",
+      "version": "0.7.8",
+      "resolved": "https://registry.npmjs.org/wickra-darwin-arm64/-/wickra-darwin-arm64-0.7.8.tgz",
       "integrity": "sha512-4eZiBR/yGUdr4nzhEUFy2i69XgNx64iI2ax/LPamsThgylC0KpHOZKK19QzJ2d9KbK4C8nMjME5FLuR+4GNEwQ==",
       "cpu": [
         "arm64"
@@ -57,8 +57,8 @@
       }
     },
     "node_modules/wickra-darwin-x64": {
-      "version": "0.5.6",
-      "resolved": "https://registry.npmjs.org/wickra-darwin-x64/-/wickra-darwin-x64-0.5.6.tgz",
+      "version": "0.7.8",
+      "resolved": "https://registry.npmjs.org/wickra-darwin-x64/-/wickra-darwin-x64-0.7.8.tgz",
       "integrity": "sha512-6hf8zI3QPjTFp4zCpmgUwDvNtu6jHqNUHKD5e55POo0CgA52HkpyxSPtVm8TGTIZDI7kPjlbOdBM8CJ76mmXwA==",
       "cpu": [
         "x64"
@@ -73,8 +73,8 @@
       }
     },
     "node_modules/wickra-linux-arm64-gnu": {
-      "version": "0.5.6",
-      "resolved": "https://registry.npmjs.org/wickra-linux-arm64-gnu/-/wickra-linux-arm64-gnu-0.5.6.tgz",
+      "version": "0.7.8",
+      "resolved": "https://registry.npmjs.org/wickra-linux-arm64-gnu/-/wickra-linux-arm64-gnu-0.7.8.tgz",
       "integrity": "sha512-kSe6y0xBMSiqdPLXNjwop5WZdHtvdBNKSEBCwZ4hFq33p4apW25/wrlzv9/oDuyD4kuPabJEhCCnFOplh58CUg==",
       "cpu": [
         "arm64"
@@ -89,8 +89,8 @@
       }
     },
     "node_modules/wickra-linux-x64-gnu": {
-      "version": "0.5.6",
-      "resolved": "https://registry.npmjs.org/wickra-linux-x64-gnu/-/wickra-linux-x64-gnu-0.5.6.tgz",
+      "version": "0.7.8",
+      "resolved": "https://registry.npmjs.org/wickra-linux-x64-gnu/-/wickra-linux-x64-gnu-0.7.8.tgz",
       "integrity": "sha512-tWBWS4qz7hxM4xnpFb59bhf6TaLwXq0Z3jEa/2l7r8PiHA94g8r8S53NRMiT+4yiL5hSWe/nUiC/YXdRrhEZ4g==",
       "cpu": [
         "x64"
@@ -105,8 +105,8 @@
       }
     },
     "node_modules/wickra-win32-arm64-msvc": {
-      "version": "0.5.6",
-      "resolved": "https://registry.npmjs.org/wickra-win32-arm64-msvc/-/wickra-win32-arm64-msvc-0.5.6.tgz",
+      "version": "0.7.8",
+      "resolved": "https://registry.npmjs.org/wickra-win32-arm64-msvc/-/wickra-win32-arm64-msvc-0.7.8.tgz",
       "integrity": "sha512-EXIckHxAtF75PUGDKRzXyqMe9ldP0JjSdu68WFN6iJfp+McYrGu6h40TEJlQ/oUEIoPqiZB/xhVyo/el5Lg7zw==",
       "cpu": [
         "arm64"
@@ -121,8 +121,8 @@
       }
     },
     "node_modules/wickra-win32-x64-msvc": {
-      "version": "0.5.6",
-      "resolved": "https://registry.npmjs.org/wickra-win32-x64-msvc/-/wickra-win32-x64-msvc-0.5.6.tgz",
+      "version": "0.7.8",
+      "resolved": "https://registry.npmjs.org/wickra-win32-x64-msvc/-/wickra-win32-x64-msvc-0.7.8.tgz",
       "integrity": "sha512-Yfsqq1Xwp6hdxMyLze411vNdo7BDwI6+lPSe7A9XdqyPecNDbtKwYLpsal2r8EHbNzqM+R8XnuRtUaEQS5VlUQ==",
       "cpu": [
         "x64"

bindings/node/package.json

@@ -1,6 +1,6 @@
 {
   "name": "wickra",
-  "version": "0.5.6",
+  "version": "0.7.8",
   "description": "Streaming-first technical indicators: incremental, fast, install-free. Node bindings powered by Rust.",
   "author": "kingchenc <support@wickra.org>",
   "main": "index.js",
@@ -47,12 +47,12 @@
     "node": ">= 18"
   },
   "optionalDependencies": {
-    "wickra-linux-x64-gnu": "0.5.6",
-    "wickra-linux-arm64-gnu": "0.5.6",
-    "wickra-darwin-x64": "0.5.6",
-    "wickra-darwin-arm64": "0.5.6",
-    "wickra-win32-x64-msvc": "0.5.6",
-    "wickra-win32-arm64-msvc": "0.5.6"
+    "wickra-linux-x64-gnu": "0.7.8",
+    "wickra-linux-arm64-gnu": "0.7.8",
+    "wickra-darwin-x64": "0.7.8",
+    "wickra-darwin-arm64": "0.7.8",
+    "wickra-win32-x64-msvc": "0.7.8",
+    "wickra-win32-arm64-msvc": "0.7.8"
   },
   "scripts": {
     "build": "napi build --platform --release",

bindings/python/README.md

@@ -9,7 +9,8 @@
 system dependencies, no C build tooling.**
 
 Wickra is a multi-language technical-analysis library with a Rust core and
-bindings for Python, Node.js, and WebAssembly. Every indicator is an O(1)
+bindings for Python, Node.js and WebAssembly, plus a C ABI for C/C++, C#, Go, R and any
+other C-capable language. Every indicator is an O(1)
 streaming state machine, so live trading bots and historical backtests share
 the exact same implementation. This package is the Python binding (PyO3); it
 exposes 200+ streaming-first indicators across sixteen families.
@@ -54,8 +55,9 @@ the main repository and documentation site:
 - **Docs** (quickstarts, cookbook, TA-Lib migration): <https://docs.wickra.org>
 - **Runnable examples:** [`examples/python/`](https://github.com/wickra-lib/wickra/tree/main/examples/python)
 
-Wickra ships four bindings — Python, Node.js, WebAssembly, and Rust — that all
-expose the same indicators from the shared, `unsafe`-forbidden Rust core.
+Wickra ships native bindings for Python, Node.js, WebAssembly and Rust, plus a
+C ABI hub that any C-capable language (C, C++, Go, C#, Java, R) links against —
+all exposing the same indicators from the shared, `unsafe`-forbidden Rust core.
 
 ## Disclaimer
 

bindings/python/benchmarks/compare_libraries.py

@@ -49,6 +49,7 @@ TALIB = _try_import("talib")
 PANDAS_TA = _try_import("pandas_ta")
 TALIPP = _try_import("talipp.indicators") or _try_import("talipp")
 FINTA = _try_import("finta")
+TULIPY = _try_import("tulipy")
 PD = _try_import("pandas")
 import wickra as WICKRA  # noqa: E402  -- the library under test must be importable
 
@@ -71,13 +72,23 @@ class Sample:
         return (self.seconds / self.iterations) * 1_000_000
 
 
-def time_call(fn: Callable[[], None], iterations: int) -> float:
-    """Time ``fn`` over ``iterations`` calls, returning total wall seconds."""
+def time_call(fn: Callable[[], None], iterations: int, rounds: int = 5) -> float:
+    """Time ``fn`` over ``iterations`` calls per round, across ``rounds`` rounds.
+
+    Returns the *median* round's wall seconds for one round of ``iterations``
+    calls. Taking the median across several rounds damps the OS scheduling and
+    GC jitter that a single timing pass would otherwise bake into the result,
+    so the per-iteration figure is stable run-to-run. Callers keep dividing the
+    return value by ``iterations``.
+    """
     fn()  # one warmup call to populate caches
-    start = time.perf_counter()
-    for _ in range(iterations):
-        fn()
-    return time.perf_counter() - start
+    rounds_s: List[float] = []
+    for _ in range(rounds):
+        start = time.perf_counter()
+        for _ in range(iterations):
+            fn()
+        rounds_s.append(time.perf_counter() - start)
+    return statistics.median(rounds_s)
 
 
 def gen_prices(n: int, seed: int = 0xC0FFEE) -> np.ndarray:
@@ -275,6 +286,34 @@ def talipp_bollinger_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
     return lambda: BB(period=20, std_dev_mult=2.0, input_values=list(prices))
 
 
+# tulipy wraps the C "Tulip Indicators" library; it takes contiguous float64
+# arrays and indicator options as positional arguments.
+
+
+def tulipy_sma_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.sma(prices, 20))
+
+
+def tulipy_ema_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.ema(prices, 20))
+
+
+def tulipy_rsi_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.rsi(prices, 14))
+
+
+def tulipy_macd_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.macd(prices, 12, 26, 9))
+
+
+def tulipy_bollinger_batch(prices: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.bbands(prices, 20, 2.0))
+
+
+def tulipy_atr_batch(high: np.ndarray, low: np.ndarray, close: np.ndarray) -> Optional[Callable[[], None]]:
+    return None if TULIPY is None else (lambda: TULIPY.atr(high, low, close, 14))
+
+
 # --------------------------------------------------------------------------- #
 # Streaming scenario: per-tick latency
 # --------------------------------------------------------------------------- #
@@ -329,6 +368,260 @@ def talipp_rsi_streaming(seed: np.ndarray, live: np.ndarray) -> Optional[Callabl
     return run
 
 
+# Scalar streaming peers: Wickra and talipp both update incrementally in O(1),
+# so this is the like-for-like per-tick comparison (batch-only libs are covered
+# by the batch tables and the recompute contrast on RSI above).
+
+
+def wickra_sma_streaming(seed: np.ndarray, live: np.ndarray) -> Callable[[], None]:
+    def run() -> None:
+        sma = WICKRA.SMA(20)
+        sma.batch(seed)
+        for p in live:
+            sma.update(float(p))
+
+    return run
+
+
+def talipp_sma_streaming(seed: np.ndarray, live: np.ndarray) -> Optional[Callable[[], None]]:
+    if TALIPP is None:
+        return None
+    from talipp.indicators import SMA  # type: ignore
+
+    def run() -> None:
+        sma = SMA(period=20, input_values=list(seed))
+        for p in live:
+            sma.add(float(p))
+
+    return run
+
+
+def wickra_ema_streaming(seed: np.ndarray, live: np.ndarray) -> Callable[[], None]:
+    def run() -> None:
+        ema = WICKRA.EMA(20)
+        ema.batch(seed)
+        for p in live:
+            ema.update(float(p))
+
+    return run
+
+
+def talipp_ema_streaming(seed: np.ndarray, live: np.ndarray) -> Optional[Callable[[], None]]:
+    if TALIPP is None:
+        return None
+    from talipp.indicators import EMA  # type: ignore
+
+    def run() -> None:
+        ema = EMA(period=20, input_values=list(seed))
+        for p in live:
+            ema.add(float(p))
+
+    return run
+
+
+def wickra_macd_streaming(seed: np.ndarray, live: np.ndarray) -> Callable[[], None]:
+    def run() -> None:
+        macd = WICKRA.MACD()
+        macd.batch(seed)
+        for p in live:
+            macd.update(float(p))
+
+    return run
+
+
+def talipp_macd_streaming(seed: np.ndarray, live: np.ndarray) -> Optional[Callable[[], None]]:
+    if TALIPP is None:
+        return None
+    from talipp.indicators import MACD  # type: ignore
+
+    def run() -> None:
+        macd = MACD(
+            fast_period=12, slow_period=26, signal_period=9, input_values=list(seed)
+        )
+        for p in live:
+            macd.add(float(p))
+
+    return run
+
+
+def wickra_bollinger_streaming(seed: np.ndarray, live: np.ndarray) -> Callable[[], None]:
+    def run() -> None:
+        bb = WICKRA.BollingerBands(20, 2.0)
+        bb.batch(seed)
+        for p in live:
+            bb.update(float(p))
+
+    return run
+
+
+def talipp_bollinger_streaming(seed: np.ndarray, live: np.ndarray) -> Optional[Callable[[], None]]:
+    if TALIPP is None:
+        return None
+    from talipp.indicators import BB  # type: ignore
+
+    def run() -> None:
+        bb = BB(period=20, std_dev_mult=2.0, input_values=list(seed))
+        for p in live:
+            bb.add(float(p))
+
+    return run
+
+
+# Recompute streaming peers: batch-only libraries have no incremental API, so
+# the only honest way to drive them tick-by-tick is to re-run the full batch
+# over the grown history on every new price. These runners expose exactly that
+# cost — the gap Wickra's O(1) update closes.
+
+
+def _talib_recompute_streaming(seed, live, fn):
+    def run() -> None:
+        history = list(seed)
+        for p in live:
+            history.append(float(p))
+            fn(np.asarray(history))
+
+    return run
+
+
+def _pandas_ta_recompute_streaming(seed, live, fn):
+    def run() -> None:
+        history = list(seed)
+        for p in live:
+            history.append(float(p))
+            fn(PD.Series(history))
+
+    return run
+
+
+def _tulipy_recompute_streaming(seed, live, fn):
+    def run() -> None:
+        history = list(seed)
+        for p in live:
+            history.append(float(p))
+            fn(np.asarray(history, dtype=np.float64))
+
+    return run
+
+
+def _finta_recompute_streaming(seed, live, fn):
+    def run() -> None:
+        history = list(seed)
+        for p in live:
+            history.append(float(p))
+            arr = np.asarray(history)
+            fn(PD.DataFrame({"open": arr, "high": arr, "low": arr, "close": arr, "volume": np.ones_like(arr)}))
+
+    return run
+
+
+def talib_sma_streaming(seed, live):
+    if TALIB is None:
+        return None
+    return _talib_recompute_streaming(seed, live, lambda a: TALIB.SMA(a, timeperiod=20))
+
+
+def pandas_ta_sma_streaming(seed, live):
+    if PANDAS_TA is None or PD is None:
+        return None
+    return _pandas_ta_recompute_streaming(seed, live, lambda s: PANDAS_TA.sma(s, length=20))
+
+
+def tulipy_sma_streaming(seed, live):
+    if TULIPY is None:
+        return None
+    return _tulipy_recompute_streaming(seed, live, lambda a: TULIPY.sma(a, 20))
+
+
+def finta_sma_streaming(seed, live):
+    if FINTA is None or PD is None:
+        return None
+    return _finta_recompute_streaming(seed, live, lambda df: FINTA.TA.SMA(df, period=20))
+
+
+def talib_ema_streaming(seed, live):
+    if TALIB is None:
+        return None
+    return _talib_recompute_streaming(seed, live, lambda a: TALIB.EMA(a, timeperiod=20))
+
+
+def pandas_ta_ema_streaming(seed, live):
+    if PANDAS_TA is None or PD is None:
+        return None
+    return _pandas_ta_recompute_streaming(seed, live, lambda s: PANDAS_TA.ema(s, length=20))
+
+
+def tulipy_ema_streaming(seed, live):
+    if TULIPY is None:
+        return None
+    return _tulipy_recompute_streaming(seed, live, lambda a: TULIPY.ema(a, 20))
+
+
+def finta_ema_streaming(seed, live):
+    if FINTA is None or PD is None:
+        return None
+    return _finta_recompute_streaming(seed, live, lambda df: FINTA.TA.EMA(df, period=20))
+
+
+def tulipy_rsi_streaming(seed, live):
+    if TULIPY is None:
+        return None
+    return _tulipy_recompute_streaming(seed, live, lambda a: TULIPY.rsi(a, 14))
+
+
+def finta_rsi_streaming(seed, live):
+    if FINTA is None or PD is None:
+        return None
+    return _finta_recompute_streaming(seed, live, lambda df: FINTA.TA.RSI(df, period=14))
+
+
+def talib_macd_streaming(seed, live):
+    if TALIB is None:
+        return None
+    return _talib_recompute_streaming(seed, live, lambda a: TALIB.MACD(a))
+
+
+def pandas_ta_macd_streaming(seed, live):
+    if PANDAS_TA is None or PD is None:
+        return None
+    return _pandas_ta_recompute_streaming(seed, live, lambda s: PANDAS_TA.macd(s))
+
+
+def tulipy_macd_streaming(seed, live):
+    if TULIPY is None:
+        return None
+    return _tulipy_recompute_streaming(seed, live, lambda a: TULIPY.macd(a, 12, 26, 9))
+
+
+def finta_macd_streaming(seed, live):
+    if FINTA is None or PD is None:
+        return None
+    return _finta_recompute_streaming(seed, live, lambda df: FINTA.TA.MACD(df))
+
+
+def talib_bollinger_streaming(seed, live):
+    if TALIB is None:
+        return None
+    return _talib_recompute_streaming(seed, live, lambda a: TALIB.BBANDS(a, timeperiod=20, nbdevup=2, nbdevdn=2))
+
+
+def pandas_ta_bollinger_streaming(seed, live):
+    if PANDAS_TA is None or PD is None:
+        return None
+    return _pandas_ta_recompute_streaming(seed, live, lambda s: PANDAS_TA.bbands(s, length=20, std=2.0))
+
+
+def tulipy_bollinger_streaming(seed, live):
+    if TULIPY is None:
+        return None
+    return _tulipy_recompute_streaming(seed, live, lambda a: TULIPY.bbands(a, 20, 2.0))
+
+
+def finta_bollinger_streaming(seed, live):
+    if FINTA is None or PD is None:
+        return None
+    return _finta_recompute_streaming(seed, live, lambda df: FINTA.TA.BBANDS(df, period=20, std_multiplier=2.0))
+
+
 # --------------------------------------------------------------------------- #
 # Runner
 # --------------------------------------------------------------------------- #
@@ -339,6 +632,7 @@ BATCH_INDICATORS = [
         ("Wickra", wickra_sma_batch),
         ("TA-Lib", talib_sma_batch),
         ("pandas-ta", pandas_ta_sma_batch),
+        ("tulipy", tulipy_sma_batch),
         ("finta", finta_sma_batch),
         ("talipp", talipp_sma_batch),
     ]),
@@ -346,6 +640,7 @@ BATCH_INDICATORS = [
         ("Wickra", wickra_ema_batch),
         ("TA-Lib", talib_ema_batch),
         ("pandas-ta", pandas_ta_ema_batch),
+        ("tulipy", tulipy_ema_batch),
         ("finta", finta_ema_batch),
         ("talipp", talipp_ema_batch),
     ]),
@@ -353,6 +648,7 @@ BATCH_INDICATORS = [
         ("Wickra", wickra_rsi_batch),
         ("TA-Lib", talib_rsi_batch),
         ("pandas-ta", pandas_ta_rsi_batch),
+        ("tulipy", tulipy_rsi_batch),
         ("finta", finta_rsi_batch),
         ("talipp", talipp_rsi_batch),
     ]),
@@ -360,6 +656,7 @@ BATCH_INDICATORS = [
         ("Wickra", wickra_macd_batch),
         ("TA-Lib", talib_macd_batch),
         ("pandas-ta", pandas_ta_macd_batch),
+        ("tulipy", tulipy_macd_batch),
         ("finta", finta_macd_batch),
         ("talipp", talipp_macd_batch),
     ]),
@@ -367,6 +664,7 @@ BATCH_INDICATORS = [
         ("Wickra", wickra_bollinger_batch),
         ("TA-Lib", talib_bollinger_batch),
         ("pandas-ta", pandas_ta_bollinger_batch),
+        ("tulipy", tulipy_bollinger_batch),
         ("finta", finta_bollinger_batch),
         ("talipp", talipp_bollinger_batch),
     ]),
@@ -376,29 +674,64 @@ OHLC_INDICATORS = [
     ("ATR(14)", [
         ("Wickra", wickra_atr_batch),
         ("TA-Lib", talib_atr_batch),
+        ("tulipy", tulipy_atr_batch),
         ("finta", finta_atr_batch),
         ("talipp", talipp_atr_batch),
     ]),
 ]
 
 STREAMING_INDICATORS = [
+    ("SMA(20)", [
+        ("Wickra", wickra_sma_streaming),
+        ("talipp", talipp_sma_streaming),
+        ("TA-Lib", talib_sma_streaming),
+        ("pandas-ta", pandas_ta_sma_streaming),
+        ("tulipy", tulipy_sma_streaming),
+        ("finta", finta_sma_streaming),
+    ]),
+    ("EMA(20)", [
+        ("Wickra", wickra_ema_streaming),
+        ("talipp", talipp_ema_streaming),
+        ("TA-Lib", talib_ema_streaming),
+        ("pandas-ta", pandas_ta_ema_streaming),
+        ("tulipy", tulipy_ema_streaming),
+        ("finta", finta_ema_streaming),
+    ]),
     ("RSI(14)", [
         ("Wickra", wickra_rsi_streaming),
+        ("talipp", talipp_rsi_streaming),
         ("TA-Lib", talib_rsi_streaming),
         ("pandas-ta", pandas_ta_rsi_streaming),
-        ("talipp", talipp_rsi_streaming),
+        ("tulipy", tulipy_rsi_streaming),
+        ("finta", finta_rsi_streaming),
+    ]),
+    ("MACD(12, 26, 9)", [
+        ("Wickra", wickra_macd_streaming),
+        ("talipp", talipp_macd_streaming),
+        ("TA-Lib", talib_macd_streaming),
+        ("pandas-ta", pandas_ta_macd_streaming),
+        ("tulipy", tulipy_macd_streaming),
+        ("finta", finta_macd_streaming),
+    ]),
+    ("Bollinger(20, 2.0)", [
+        ("Wickra", wickra_bollinger_streaming),
+        ("talipp", talipp_bollinger_streaming),
+        ("TA-Lib", talib_bollinger_streaming),
+        ("pandas-ta", pandas_ta_bollinger_streaming),
+        ("tulipy", tulipy_bollinger_streaming),
+        ("finta", finta_bollinger_streaming),
     ]),
 ]
 
 
-def run_batch(prices: np.ndarray, iterations: int) -> List[Sample]:
+def run_batch(prices: np.ndarray, iterations: int, rounds: int) -> List[Sample]:
     out: List[Sample] = []
     for indicator_name, libs in BATCH_INDICATORS:
         for lib_name, factory in libs:
             runner = factory(prices)
             if runner is None:
                 continue
-            secs = time_call(runner, iterations)
+            secs = time_call(runner, iterations, rounds)
             out.append(Sample(lib_name, indicator_name, "batch", secs, iterations))
     return out
 
@@ -408,6 +741,7 @@ def run_ohlc(
     low: np.ndarray,
     close: np.ndarray,
     iterations: int,
+    rounds: int,
 ) -> List[Sample]:
     out: List[Sample] = []
     for indicator_name, libs in OHLC_INDICATORS:
@@ -415,12 +749,12 @@ def run_ohlc(
             runner = factory(high, low, close)
             if runner is None:
                 continue
-            secs = time_call(runner, iterations)
+            secs = time_call(runner, iterations, rounds)
             out.append(Sample(lib_name, indicator_name, "batch", secs, iterations))
     return out
 
 
-def run_streaming(prices: np.ndarray, streaming_window: int, iterations: int) -> List[Sample]:
+def run_streaming(prices: np.ndarray, streaming_window: int, iterations: int, rounds: int) -> List[Sample]:
     out: List[Sample] = []
     seed = prices[:streaming_window]
     live = prices[streaming_window:]
@@ -431,7 +765,7 @@ def run_streaming(prices: np.ndarray, streaming_window: int, iterations: int) ->
             runner = factory(seed, live)
             if runner is None:
                 continue
-            secs = time_call(runner, iterations)
+            secs = time_call(runner, iterations, rounds)
             sample = Sample(lib_name, indicator_name, "streaming", secs, iterations)
             sample.iterations = iterations * len(live)  # per-tick normalization
             out.append(sample)
@@ -479,6 +813,12 @@ def parse_args() -> argparse.Namespace:
     parser = argparse.ArgumentParser(description=__doc__.splitlines()[0] if __doc__ else None)
     parser.add_argument("--size", type=int, default=20_000, help="number of prices")
     parser.add_argument("--iterations", type=int, default=20, help="batch repetitions per timing")
+    parser.add_argument(
+        "--rounds",
+        type=int,
+        default=5,
+        help="batch timing rounds; the median round is reported to damp jitter",
+    )
     parser.add_argument(
         "--streaming-window",
         type=int,
@@ -491,6 +831,14 @@ def parse_args() -> argparse.Namespace:
         default=3,
         help="repetitions of the streaming workload (each iteration replays all live ticks)",
     )
+    parser.add_argument(
+        "--streaming-rounds",
+        type=int,
+        default=2,
+        help="streaming timing rounds; the median round is reported",
+    )
+    parser.add_argument("--skip-batch", action="store_true", help="skip the batch tables")
+    parser.add_argument("--skip-streaming", action="store_true", help="skip the streaming tables")
     return parser.parse_args()
 
 
@@ -501,6 +849,7 @@ def main() -> None:
     available = []
     if TALIB is not None: available.append("TA-Lib")
     if PANDAS_TA is not None: available.append("pandas-ta")
+    if TULIPY is not None: available.append("tulipy")
     if FINTA is not None: available.append("finta")
     if TALIPP is not None: available.append("talipp")
     print(f"Wickra benchmark suite — wickra=v{WICKRA.__version__}")
@@ -509,11 +858,14 @@ def main() -> None:
     print(f"Streaming window: {args.streaming_window} seed, {args.size - args.streaming_window} live")
 
     high, low, close, _ = gen_ohlc(args.size)
-    batch_rows = run_batch(prices, args.iterations)
-    ohlc_rows = run_ohlc(high, low, close, args.iterations)
-    streaming_rows = run_streaming(prices, args.streaming_window, args.streaming_iterations)
+    rows: List[Sample] = []
+    if not args.skip_batch:
+        rows += run_batch(prices, args.iterations, args.rounds)
+        rows += run_ohlc(high, low, close, args.iterations, args.rounds)
+    if not args.skip_streaming:
+        rows += run_streaming(prices, args.streaming_window, args.streaming_iterations, args.streaming_rounds)
 
-    print(render_table(batch_rows + ohlc_rows + streaming_rows))
+    print(render_table(rows))
 
 
 if __name__ == "__main__":

bindings/python/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "maturin"
 
 [project]
 name = "wickra"
-version = "0.5.6"
+version = "0.7.8"
 description = "Streaming-first technical indicators: incremental, fast, install-free."
 readme = "README.md"
 license = "MIT OR Apache-2.0"
@@ -39,6 +39,7 @@ bench = [
     "pytest-benchmark>=4",
     "TA-Lib; platform_system != 'Windows'",
     "pandas-ta>=0.3.14b",
+    "tulipy>=0.4; platform_system != 'Windows'",
     "talipp>=2",
     "finta>=1.3",
     "pandas>=2",

bindings/python/python/wickra/__init__.py

@@ -25,6 +25,47 @@ from __future__ import annotations
 
 from ._wickra import (
     __version__,
+    M2Measure,
+    UpsidePotentialRatio,
+    GainToPainRatio,
+    CommonSenseRatio,
+    KRatio,
+    TailRatio,
+    MartinRatio,
+    BurkeRatio,
+    SterlingRatio,
+    AUTOCORRPGRAM,
+    EVENBETTERSINE,
+    BANDPASS,
+    ADAPTIVECCI,
+    UNIVERSALOSC,
+    ADAPTIVERSI,
+    CTI,
+    TRENDFLEX,
+    REFLEX,
+    HIGHPASS,
+    SAMPLEENT,
+    SHANNONENT,
+    ROLLINGMINMAX,
+    JARQUEBERA,
+    TimeBasedStop,
+    ProjectionOscillator,
+    VolatilityCone,
+    VolatilityRatio,
+    BipowerVariation,
+    VolatilityOfVolatility,
+    Garch11,
+    EwmaVolatility,
+    PpoHistogram,
+    MacdHistogram,
+    TsfOscillator,
+    Qstick,
+    GatorOscillator,
+    KasePermissionStochastic,
+    WAVE_PM,
+    POLARIZED_FRACTAL_EFFICIENCY,
+    TREND_STRENGTH_INDEX,
+    TTM_TREND,
     QQE,
     IMI,
     ElderRay,
@@ -151,6 +192,11 @@ from ._wickra import (
     HistoricalVolatility,
     BollingerBandwidth,
     PercentB,
+    # Trailing Stops
+    ModifiedMaStop,
+    Nrtr,
+    AtrRatchet,
+    ElderSafeZone,
     SuperTrend,
     ChandelierExit,
     ChandeKrollStop,
@@ -162,6 +208,7 @@ from ._wickra import (
     PercentageTrailingStop,
     StepTrailingStop,
     RenkoTrailingStop,
+    KaseDevStop,
     TrueRange,
     ChaikinVolatility,
     RVIVolatility,
@@ -170,6 +217,13 @@ from ._wickra import (
     RogersSatchellVolatility,
     YangZhangVolatility,
     # Volume
+    VolumeWeightedMacd,
+    BetterVolume,
+    IntradayIntensity,
+    TradeVolumeIndex,
+    TwiggsMoneyFlow,
+    Wad,
+    VolumeRsi,
     OBV,
     VWAP,
     RollingVWAP,
@@ -190,6 +244,7 @@ from ._wickra import (
     MarketFacilitationIndex,
     EaseOfMovement,
     # Statistics
+    KendallTau,
     SpreadBollingerBands,
     KalmanHedgeRatio,
     GrangerCausality,
@@ -247,6 +302,10 @@ from ._wickra import (
     MAMA,
     FAMA,
     # Bands & Channels
+    ProjectionBands,
+    MedianChannel,
+    BomarBands,
+    QuartileBands,
     MaEnvelope,
     AccelerationBands,
     StarcBands,
@@ -259,6 +318,11 @@ from ._wickra import (
     FractalChaosBands,
     VwapStdDevBands,
     # Pivots & S/R
+    PivotReversal,
+    VolumeWeightedSr,
+    AndrewsPitchfork,
+    MurreyMathLines,
+    CentralPivotRange,
     ClassicPivots,
     FibonacciPivots,
     Camarilla,
@@ -267,6 +331,13 @@ from ._wickra import (
     WilliamsFractals,
     ZigZag,
     # DeMark
+    TDMovingAverage,
+    TDDWave,
+    TDTrap,
+    TDPropulsion,
+    TDClopwin,
+    TDClop,
+    TDCamouflage,
     TDSetup,
     TDSequential,
     TDDeMarker,
@@ -282,17 +353,40 @@ from ._wickra import (
     # Ichimoku & alternative charts
     Ichimoku,
     HeikinAshi,
+    SmoothedHeikinAshi,
+    HeikinAshiOscillator,
+    ThreeLineBreak,
+    Equivolume,
+    CandleVolume,
     # Market Profile
+    CompositeProfile,
+    HighLowVolumeNodes,
+    ProfileShape,
+    SinglePrints,
+    NakedPoc,
     ValueArea,
     VolumeProfile,
     TpoProfile,
     InitialBalance,
     OpeningRange,
     # Alt-Chart Bars
+    ThreeLineBreakBars,
+    RunBars,
+    ImbalanceBars,
+    DollarBars,
+    VolumeBars,
+    TickBars,
+    RangeBars,
     RenkoBars,
     KagiBars,
     PointAndFigureBars,
     # Candlestick patterns
+    TowerTopBottom,
+    HaramiCross,
+    Tristar,
+    FryPanBottom,
+    DumplingTop,
+    NewPriceLines,
     Doji,
     Hammer,
     InvertedHammer,
@@ -391,6 +485,8 @@ from ._wickra import (
     QuotedSpread,
     DepthSlope,
     # Microstructure: trade flow
+    Pin,
+    TradeSignAutocorrelation,
     RollMeasure,
     AmihudIlliquidity,
     Vpin,
@@ -398,12 +494,18 @@ from ._wickra import (
     CumulativeVolumeDelta,
     TradeImbalance,
     # Microstructure: price impact
+    HasbrouckInformationShare,
     EffectiveSpread,
     RealizedSpread,
     KylesLambda,
     # Microstructure: footprint
     Footprint,
     # Derivatives
+    OpenInterestMomentum,
+    FundingImpliedApr,
+    PerpetualPremiumIndex,
+    OiToVolumeRatio,
+    EstimatedLeverageRatio,
     FundingRate,
     FundingRateMean,
     FundingRateZScore,
@@ -466,6 +568,47 @@ from ._wickra import (
 )
 
 __all__ = [
+    "M2Measure",
+    "UpsidePotentialRatio",
+    "GainToPainRatio",
+    "CommonSenseRatio",
+    "KRatio",
+    "TailRatio",
+    "MartinRatio",
+    "BurkeRatio",
+    "SterlingRatio",
+    "AUTOCORRPGRAM",
+    "EVENBETTERSINE",
+    "BANDPASS",
+    "ADAPTIVECCI",
+    "UNIVERSALOSC",
+    "ADAPTIVERSI",
+    "CTI",
+    "TRENDFLEX",
+    "REFLEX",
+    "HIGHPASS",
+    "SAMPLEENT",
+    "SHANNONENT",
+    "ROLLINGMINMAX",
+    "JARQUEBERA",
+    "TimeBasedStop",
+    "ProjectionOscillator",
+    "VolatilityCone",
+    "VolatilityRatio",
+    "BipowerVariation",
+    "VolatilityOfVolatility",
+    "Garch11",
+    "EwmaVolatility",
+    "PpoHistogram",
+    "MacdHistogram",
+    "TsfOscillator",
+    "Qstick",
+    "GatorOscillator",
+    "KasePermissionStochastic",
+    "WAVE_PM",
+    "POLARIZED_FRACTAL_EFFICIENCY",
+    "TREND_STRENGTH_INDEX",
+    "TTM_TREND",
     "QQE",
     "IMI",
     "ElderRay",
@@ -593,6 +736,11 @@ __all__ = [
     "HistoricalVolatility",
     "BollingerBandwidth",
     "PercentB",
+    # Trailing Stops
+    "ModifiedMaStop",
+    "Nrtr",
+    "AtrRatchet",
+    "ElderSafeZone",
     "SuperTrend",
     "ChandelierExit",
     "ChandeKrollStop",
@@ -604,6 +752,7 @@ __all__ = [
     "PercentageTrailingStop",
     "StepTrailingStop",
     "RenkoTrailingStop",
+    "KaseDevStop",
     "TrueRange",
     "ChaikinVolatility",
     "RVIVolatility",
@@ -612,6 +761,13 @@ __all__ = [
     "RogersSatchellVolatility",
     "YangZhangVolatility",
     # Volume
+    "VolumeWeightedMacd",
+    "BetterVolume",
+    "IntradayIntensity",
+    "TradeVolumeIndex",
+    "TwiggsMoneyFlow",
+    "Wad",
+    "VolumeRsi",
     "OBV",
     "VWAP",
     "RollingVWAP",
@@ -632,6 +788,7 @@ __all__ = [
     "MarketFacilitationIndex",
     "EaseOfMovement",
     # Statistics
+    "KendallTau",
     "SpreadBollingerBands",
     "KalmanHedgeRatio",
     "GrangerCausality",
@@ -689,6 +846,10 @@ __all__ = [
     "MAMA",
     "FAMA",
     # Bands & Channels
+    "ProjectionBands",
+    "MedianChannel",
+    "BomarBands",
+    "QuartileBands",
     "MaEnvelope",
     "AccelerationBands",
     "StarcBands",
@@ -701,6 +862,11 @@ __all__ = [
     "FractalChaosBands",
     "VwapStdDevBands",
     # Pivots & S/R
+    "PivotReversal",
+    "VolumeWeightedSr",
+    "AndrewsPitchfork",
+    "MurreyMathLines",
+    "CentralPivotRange",
     "ClassicPivots",
     "FibonacciPivots",
     "Camarilla",
@@ -709,6 +875,13 @@ __all__ = [
     "WilliamsFractals",
     "ZigZag",
     # DeMark
+    "TDMovingAverage",
+    "TDDWave",
+    "TDTrap",
+    "TDPropulsion",
+    "TDClopwin",
+    "TDClop",
+    "TDCamouflage",
     "TDSetup",
     "TDSequential",
     "TDDeMarker",
@@ -724,17 +897,40 @@ __all__ = [
     # Ichimoku & alternative charts
     "Ichimoku",
     "HeikinAshi",
+    "SmoothedHeikinAshi",
+    "HeikinAshiOscillator",
+    "ThreeLineBreak",
+    "Equivolume",
+    "CandleVolume",
     # Market Profile
+    "CompositeProfile",
+    "HighLowVolumeNodes",
+    "ProfileShape",
+    "SinglePrints",
+    "NakedPoc",
     "ValueArea",
     "VolumeProfile",
     "TpoProfile",
     "InitialBalance",
     "OpeningRange",
     # Alt-Chart Bars
+    "ThreeLineBreakBars",
+    "RunBars",
+    "ImbalanceBars",
+    "DollarBars",
+    "VolumeBars",
+    "TickBars",
+    "RangeBars",
     "RenkoBars",
     "KagiBars",
     "PointAndFigureBars",
     # Candlestick patterns
+    "TowerTopBottom",
+    "HaramiCross",
+    "Tristar",
+    "FryPanBottom",
+    "DumplingTop",
+    "NewPriceLines",
     "Doji",
     "Hammer",
     "InvertedHammer",
@@ -833,6 +1029,8 @@ __all__ = [
     "QuotedSpread",
     "DepthSlope",
     # Microstructure: trade flow
+    "Pin",
+    "TradeSignAutocorrelation",
     "RollMeasure",
     "AmihudIlliquidity",
     "Vpin",
@@ -840,12 +1038,18 @@ __all__ = [
     "CumulativeVolumeDelta",
     "TradeImbalance",
     # Microstructure: price impact
+    "HasbrouckInformationShare",
     "EffectiveSpread",
     "RealizedSpread",
     "KylesLambda",
     # Microstructure: footprint
     "Footprint",
     # Derivatives
+    "OpenInterestMomentum",
+    "FundingImpliedApr",
+    "PerpetualPremiumIndex",
+    "OiToVolumeRatio",
+    "EstimatedLeverageRatio",
     "FundingRate",
     "FundingRateMean",
     "FundingRateZScore",

bindings/python/tests/test_new_indicators.py

@@ -45,6 +45,38 @@ def ohlcv() -> tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:
 # --- Scalar (f64 -> f64) indicators ---------------------------------------
 
 SCALAR = [
+    (ta.M2Measure, (20, 0.0, 0.02)),
+    (ta.UpsidePotentialRatio, (20, 0.0)),
+    (ta.GainToPainRatio, (12,)),
+    (ta.CommonSenseRatio, (20,)),
+    (ta.KRatio, (30,)),
+    (ta.TailRatio, (20,)),
+    (ta.MartinRatio, (14,)),
+    (ta.BurkeRatio, (12,)),
+    (ta.SterlingRatio, (12,)),
+    (ta.AUTOCORRPGRAM, (10, 48)),
+    (ta.EVENBETTERSINE, (40, 10)),
+    (ta.BANDPASS, (20, 0.3)),
+    (ta.UNIVERSALOSC, (20,)),
+    (ta.ADAPTIVERSI, (14,)),
+    (ta.CTI, (20,)),
+    (ta.TRENDFLEX, (20,)),
+    (ta.REFLEX, (20,)),
+    (ta.HIGHPASS, (48,)),
+    (ta.SAMPLEENT, (20, 2, 0.2)),
+    (ta.SHANNONENT, (20, 8)),
+    (ta.ROLLINGMINMAX, (20,)),
+    (ta.JARQUEBERA, (20,)),
+    (ta.BipowerVariation, (20,)),
+    (ta.VolatilityOfVolatility, (20, 20)),
+    (ta.Garch11, (0.000002, 0.1, 0.88)),
+    (ta.EwmaVolatility, (0.94,)),
+    (ta.PpoHistogram, (3, 6, 3)),
+    (ta.MacdHistogram, (3, 6, 3)),
+    (ta.TsfOscillator, (3,)),
+    (ta.WAVE_PM, (32, 3)),
+    (ta.POLARIZED_FRACTAL_EFFICIENCY, (10, 5)),
+    (ta.TREND_STRENGTH_INDEX, (20,)),
     (ta.DerivativeOscillator, (14, 5, 3, 9)),
     (ta.RMI, (14, 5)),
     (ta.DynamicMomentumIndex, (14,)),
@@ -163,6 +195,9 @@ SCALAR = [
 # Family 05 band/channel indicators with scalar input and multi-output.
 # `cols` is the expected number of band columns from `batch`.
 SCALAR_MULTI = {
+    "MedianChannel": (lambda: ta.MedianChannel(5, 2.0), 3),
+    "BomarBands": (lambda: ta.BomarBands(4, 0.85), 3),
+    "QuartileBands": (lambda: ta.QuartileBands(4), 3),
     "Qqe": (lambda: ta.QQE(14, 5, 4.236), 2),
     "MaEnvelope": (lambda: ta.MaEnvelope(20, 0.025), 3),
     "LinRegChannel": (lambda: ta.LinRegChannel(20, 2.0), 3),
@@ -191,6 +226,8 @@ def test_scalar_streaming_matches_batch(cls, args, sine_prices):
 # --- Two-series (asset, benchmark) indicators -----------------------------
 
 PAIR = [
+    (ta.HasbrouckInformationShare, (2,)),
+    (ta.KendallTau, (20,)),
     (ta.SpreadAr1Coefficient, (40,)),
     (ta.GrangerCausality, (60, 1)),
     (ta.VarianceRatio, (60, 2)),
@@ -355,6 +392,107 @@ def test_relative_strength_streaming_matches_batch():
 # 6-tuple candle; the batch helper takes only the columns it needs.
 
 CANDLE_SCALAR = {
+    "ProfileShape": (
+        lambda: ta.ProfileShape(20, 24),
+        lambda ind, h, l, c, v: ind.batch(h, l, v),
+    ),
+    "SinglePrints": (
+        lambda: ta.SinglePrints(20, 24),
+        lambda ind, h, l, c, v: ind.batch(h, l),
+    ),
+    "NakedPoc": (
+        lambda: ta.NakedPoc(20, 24),
+        lambda ind, h, l, c, v: ind.batch(h, l, c, v),
+    ),
+    "FryPanBottom": (
+        lambda: ta.FryPanBottom(9),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+    ),
+    "NewPriceLines": (
+        lambda: ta.NewPriceLines(5),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+    ),
+    "DumplingTop": (
+        lambda: ta.DumplingTop(9),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+    ),
+    "TowerTopBottom": (
+        lambda: ta.TowerTopBottom(),
+        lambda ind, h, l, c, v: ind.batch(c, h, l, c),
+    ),
+    "HaramiCross": (
+        lambda: ta.HaramiCross(),
+        lambda ind, h, l, c, v: ind.batch(c, h, l, c),
+    ),
+    "Tristar": (
+        lambda: ta.Tristar(),
+        lambda ind, h, l, c, v: ind.batch(c, h, l, c),
+    ),
+    "ThreeLineBreak": (
+        lambda: ta.ThreeLineBreak(3),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+    ),
+    "HeikinAshiOscillator": (
+        lambda: ta.HeikinAshiOscillator(5),
+        lambda ind, h, l, c, v: ind.batch(c, h, l, c),
+    ),
+    "TDDWave": (
+        lambda: ta.TDDWave(2),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+    ),
+    "TDTrap": (
+        lambda: ta.TDTrap(),
+        lambda ind, h, l, c, v: ind.batch(c, h, l, c),
+    ),
+    "TDPropulsion": (
+        lambda: ta.TDPropulsion(),
+        lambda ind, h, l, c, v: ind.batch(c, h, l, c),
+    ),
+    "TDClopwin": (
+        lambda: ta.TDClopwin(),
+        lambda ind, h, l, c, v: ind.batch(c, h, l, c),
+    ),
+    "TDClop": (
+        lambda: ta.TDClop(),
+        lambda ind, h, l, c, v: ind.batch(c, h, l, c),
+    ),
+    "TDCamouflage": (
+        lambda: ta.TDCamouflage(),
+        lambda ind, h, l, c, v: ind.batch(c, h, l, c),
+    ),
+    "PivotReversal": (
+        lambda: ta.PivotReversal(1, 1),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+    ),
+    "ADAPTIVECCI": (lambda: ta.ADAPTIVECCI(20), lambda ind, h, l, c, v: ind.batch(h, l, c)),
+    "BetterVolume": (
+        lambda: ta.BetterVolume(14),
+        lambda ind, h, l, c, v: ind.batch(h, l, c, v),
+    ),
+    "IntradayIntensity": (
+        lambda: ta.IntradayIntensity(),
+        lambda ind, h, l, c, v: ind.batch(h, l, c, v),
+    ),
+    "TradeVolumeIndex": (
+        lambda: ta.TradeVolumeIndex(0.25),
+        lambda ind, h, l, c, v: ind.batch(c, v),
+    ),
+    "TwiggsMoneyFlow": (
+        lambda: ta.TwiggsMoneyFlow(21),
+        lambda ind, h, l, c, v: ind.batch(h, l, c, v),
+    ),
+    "Wad": (
+        lambda: ta.Wad(),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+    ),
+    "VolumeRsi": (
+        lambda: ta.VolumeRsi(14),
+        lambda ind, h, l, c, v: ind.batch(c, v),
+    ),
+    "TimeBasedStop": (lambda: ta.TimeBasedStop(5), lambda ind, h, l, c, v: ind.batch(h, l, c)),
+    "ProjectionOscillator": (lambda: ta.ProjectionOscillator(14), lambda ind, h, l, c, v: ind.batch(h, l, c)),
+    "VolatilityRatio": (lambda: ta.VolatilityRatio(14), lambda ind, h, l, c, v: ind.batch(h, l, c)),
+    "TTM_TREND": (lambda: ta.TTM_TREND(6), lambda ind, h, l, c, v: ind.batch(h, l, c)),
     "StochasticCCI": (lambda: ta.StochasticCCI(14), lambda ind, h, l, c, v: ind.batch(h, l, c)),
     # Per-bar OHLC transforms (open matters). The streaming harness feeds
     # open == close, so batch passes the close column in for open to match.
@@ -892,6 +1030,106 @@ def test_candle_scalar_streaming_matches_batch(name, ohlcv):
 # --- Candle-input, multi-output indicators --------------------------------
 
 MULTI = {
+    "CompositeProfile": (
+        lambda: ta.CompositeProfile(20, 24, 0.7),
+        lambda ind, h, l, c, v: ind.batch(h, l, v),
+        3,
+    ),
+    "HighLowVolumeNodes": (
+        lambda: ta.HighLowVolumeNodes(20, 24),
+        lambda ind, h, l, c, v: ind.batch(h, l, v),
+        2,
+    ),
+    "CandleVolume": (
+        lambda: ta.CandleVolume(20),
+        lambda ind, h, l, c, v: ind.batch(c, c, v),
+        2,
+    ),
+    "Equivolume": (
+        lambda: ta.Equivolume(20),
+        lambda ind, h, l, c, v: ind.batch(h, l, v),
+        2,
+    ),
+    "SmoothedHeikinAshi": (
+        lambda: ta.SmoothedHeikinAshi(5),
+        lambda ind, h, l, c, v: ind.batch(c, h, l, c),
+        4,
+    ),
+    "TDMovingAverage": (
+        lambda: ta.TDMovingAverage(5, 13),
+        lambda ind, h, l, c, v: ind.batch(h, l),
+        2,
+    ),
+    "VolumeWeightedSr": (
+        lambda: ta.VolumeWeightedSr(3),
+        lambda ind, h, l, c, v: ind.batch(h, l, v),
+        2,
+    ),
+    "AndrewsPitchfork": (
+        lambda: ta.AndrewsPitchfork(2),
+        lambda ind, h, l, c, v: ind.batch(h, l),
+        3,
+    ),
+    "MurreyMathLines": (
+        lambda: ta.MurreyMathLines(4),
+        lambda ind, h, l, c, v: ind.batch(h, l),
+        9,
+    ),
+    "CentralPivotRange": (
+        lambda: ta.CentralPivotRange(),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+        3,
+    ),
+    "VolumeWeightedMacd": (
+        lambda: ta.VolumeWeightedMacd(12, 26, 9),
+        lambda ind, h, l, c, v: ind.batch(c, v),
+        3,
+    ),
+    "ModifiedMaStop": (
+        lambda: ta.ModifiedMaStop(14),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+        2,
+    ),
+    "Nrtr": (
+        lambda: ta.Nrtr(2.0),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+        2,
+    ),
+    "AtrRatchet": (
+        lambda: ta.AtrRatchet(14, 4.0, 0.1),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+        2,
+    ),
+    "ElderSafeZone": (
+        lambda: ta.ElderSafeZone(14, 2.0),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+        2,
+    ),
+    "KaseDevStop": (
+        lambda: ta.KaseDevStop(3, 1.0),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+        2,
+    ),
+    "ProjectionBands": (
+        lambda: ta.ProjectionBands(3),
+        lambda ind, h, l, c, v: ind.batch(h, l),
+        3,
+    ),
+    "VolatilityCone": (
+        lambda: ta.VolatilityCone(20, 60),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+        5,
+    ),
+    "KasePermissionStochastic": (
+        lambda: ta.KasePermissionStochastic(9, 3),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+        2,
+    ),
+    "GatorOscillator": (
+        lambda: ta.GatorOscillator(13, 8, 5),
+        lambda ind, h, l, c, v: ind.batch(h, l, c),
+        2,
+    ),
     "ElderRay": (
         lambda: ta.ElderRay(13),
         lambda ind, h, l, c, v: ind.batch(h, l, c),
@@ -1518,7 +1756,7 @@ def test_kvo_constant_series_is_zero():
         assert v == pytest.approx(0.0, abs=1e-12)
 
 
-def test_williams_ad_reference():
+def test_wad_reference():
     # bar 0 seeds prev_close = 10.
     # bar 1: prev=10, today high=13, low=8, close=12 (up day).
     #   TR_l = min(10, 8) = 8 -> delta = 12 - 8 = 4. AD = 4.
@@ -2779,6 +3017,371 @@ def test_imi_reference():
     assert math.isnan(out[1])
     assert out[2] == pytest.approx(75.0)
 
+
+def test_qstick_reference():
+    q = ta.Qstick(3)
+    open_ = np.array([10.0, 10.0, 10.0])
+    close = np.array([11.0, 11.0, 11.0])
+    out = q.batch(open_, close)
+    # Each body is close - open = 1; SMA(3) of [1, 1, 1] = 1.
+    assert math.isnan(out[0])
+    assert math.isnan(out[1])
+    assert out[2] == pytest.approx(1.0)
+
+
+def test_ttm_trend_reference():
+    t = ta.TTM_TREND(3)
+    high = np.array([13.0, 13.0, 13.0])
+    low = np.array([9.0, 9.0, 9.0])
+    close = np.array([12.0, 12.0, 12.0])
+    out = t.batch(high, low, close)
+    # Median (13 + 9) / 2 = 11; close 12 is above the SMA(3) reference -> +1.
+    assert math.isnan(out[0])
+    assert out[2] == pytest.approx(1.0)
+
+
+def test_trend_strength_index_reference():
+    tsi = ta.TREND_STRENGTH_INDEX(10)
+    closes = np.arange(10, dtype=float)
+    out = tsi.batch(closes)
+    # A clean ramp is a perfect uptrend -> signed r^2 = +1.
+    assert math.isclose(out[-1], 1.0, abs_tol=1e-9)
+
+
+def test_polarized_fractal_efficiency_reference():
+    pfe = ta.POLARIZED_FRACTAL_EFFICIENCY(5, 3)
+    closes = np.arange(20, dtype=float)
+    out = pfe.batch(closes)
+    # On a straight ramp the path equals the diagonal -> efficiency 1 -> +100.
+    assert math.isclose(out[-1], 100.0, abs_tol=1e-9)
+
+
+def test_wave_pm_reference():
+    wpm = ta.WAVE_PM(10, 3)
+    closes = np.arange(60, dtype=float) * 5.0
+    out = wpm.batch(closes)
+    # Constant-slope ramp: momentum equals its energy -> 100 * (1 - e^-0.5).
+    baseline = 100.0 * (1.0 - math.exp(-0.5))
+    assert math.isclose(out[-1], baseline, abs_tol=1e-9)
+
+
+def test_gator_oscillator_reference():
+    g = ta.GatorOscillator(13, 8, 5)
+    n = 40
+    high = np.full(n, 11.0)
+    low = np.full(n, 9.0)
+    close = np.full(n, 10.0)
+    out = g.batch(high, low, close)
+    # Constant median collapses all three Alligator lines -> both bars zero.
+    assert out[-1][0] == pytest.approx(0.0)
+    assert out[-1][1] == pytest.approx(0.0)
+
+
+def test_kase_permission_stochastic_reference():
+    k = ta.KasePermissionStochastic(4, 2)
+    n = 20
+    flat = np.full(n, 10.0)
+    out = k.batch(flat, flat, flat)
+    # HH == LL -> raw %K defaults to the neutral 50 -> both lines at 50.
+    assert out[-1][0] == pytest.approx(50.0)
+    assert out[-1][1] == pytest.approx(50.0)
+
+
+def test_tsf_oscillator_reference():
+    t = ta.TsfOscillator(3)
+    assert t.update(1.0) is None
+    assert t.update(2.0) is None
+    assert t.update(9.0) == pytest.approx(-33.33333333333333)
+
+
+def test_macd_histogram_reference():
+    # On a constant-slope ramp the MACD line is flat once seeded, so the
+    # signal EMA catches up and the histogram collapses to 0.
+    t = ta.MacdHistogram(3, 6, 3)
+    for i in range(7):
+        assert t.update(100.0 + i * 2.0) is None
+    assert t.update(100.0 + 7 * 2.0) == pytest.approx(0.0, abs=1e-9)
+
+
+def test_ppo_histogram_reference():
+    # PPO divides the EMA gap by the slow EMA, so on the same ramp the ratio
+    # keeps drifting and the histogram stays non-zero.
+    t = ta.PpoHistogram(3, 6, 3)
+    for i in range(7):
+        assert t.update(100.0 + i * 2.0) is None
+    assert t.update(100.0 + 7 * 2.0) == pytest.approx(-0.052098, abs=1e-6)
+
+
+def test_ewma_volatility_reference():
+    t = ta.EwmaVolatility(0.94)
+    assert t.update(100.0) is None
+    assert t.update(110.0) == pytest.approx(0.09531017980432493)
+    assert t.update(99.0) == pytest.approx(0.0959428936787596)
+
+
+def test_garch11_reference():
+    t = ta.Garch11(0.000002, 0.1, 0.88)
+    assert t.update(100.0) is None
+    assert t.update(110.0) == pytest.approx(0.009999999999999995)
+    assert t.update(99.0) == pytest.approx(0.031597516317477786)
+
+
+def test_volatility_cone_reference():
+    t = ta.VolatilityCone(20, 60)
+
+
+def test_quartile_bands_reference():
+    t = ta.QuartileBands(4)
+    assert t.update(40.0) is None
+    assert t.update(30.0) is None
+    assert t.update(20.0) is None
+    assert t.update(10.0) == pytest.approx((32.5, 25.0, 17.5))
+
+
+def test_bomar_bands_reference():
+    t = ta.BomarBands(4, 0.85)
+    assert t.update(100.0) is None
+    assert t.update(102.0) is None
+    assert t.update(98.0) is None
+    assert t.update(104.0) == pytest.approx((104.0, 101.0, 98.0))
+
+
+def test_median_channel_reference():
+    t = ta.MedianChannel(5, 2.0)
+    assert t.update(1.0) is None
+    assert t.update(2.0) is None
+    assert t.update(3.0) is None
+    assert t.update(4.0) is None
+    assert t.update(5.0) == pytest.approx((5.0, 3.0, 1.0))
+
+
+def test_projection_bands_reference():
+    t = ta.ProjectionBands(3)
+    assert t.update((8.0, 10.0, 8.0, 9.0, 1.0, 0)) is None
+    assert t.update((9.0, 12.0, 9.0, 11.0, 1.0, 1)) is None
+    assert t.update((10.0, 11.0, 10.0, 11.0, 1.0, 2)) == pytest.approx((12.5, 11.25, 10.0))
+
+
+def test_projection_oscillator_reference():
+    # Same window as ProjectionBands: upper 12.5, lower 10; close 11 -> 40.
+    t = ta.ProjectionOscillator(3)
+    assert t.update((8.0, 10.0, 8.0, 9.0, 1.0, 0)) is None
+    assert t.update((9.0, 12.0, 9.0, 11.0, 1.0, 1)) is None
+    assert t.update((10.0, 11.0, 10.0, 11.0, 1.0, 2)) == pytest.approx(40.0)
+
+
+def test_kase_devstop_reference():
+    t = ta.KaseDevStop(3, 1.0)
+    assert t.update((100.0, 101.0, 99.0, 100.0, 1.0, 0)) is None
+    assert t.update((101.0, 102.0, 100.0, 101.0, 1.0, 1)) is None
+    assert t.update((102.0, 103.0, 101.0, 102.0, 1.0, 2)) is None
+    assert t.update((102.5, 104.0, 102.0, 103.0, 1.0, 3)) == pytest.approx((101.0, 1.0))
+
+
+def _stop_candles(n):
+    # Gently rising, valid OHLC: high >= open/close, low <= open/close.
+    return [(100.0 + i, 101.5 + i, 98.5 + i, 100.5 + i, 1.0, i) for i in range(n)]
+
+
+def test_elder_safezone_reference():
+    t = ta.ElderSafeZone(14, 2.0)
+    candles = _stop_candles(15)
+    for c in candles[:14]:
+        assert t.update(c) is None
+    assert t.update(candles[14]) == pytest.approx((112.5, 1.0))
+
+
+def test_atr_ratchet_reference():
+    t = ta.AtrRatchet(14, 4.0, 0.1)
+    candles = _stop_candles(14)
+    for c in candles[:13]:
+        assert t.update(c) is None
+    assert t.update(candles[13]) == pytest.approx((101.5, 1.0))
+
+
+def test_nrtr_reference():
+    t = ta.Nrtr(2.0)
+    assert t.update((100.0, 100.0, 100.0, 100.0, 1.0, 0)) == pytest.approx((98.0, 1.0))
+
+
+def test_time_based_stop_reference():
+    t = ta.TimeBasedStop(5)
+    assert t.update((100.0, 101.0, 99.0, 100.0, 1.0, 0)) == pytest.approx(0.2)
+
+
+def test_modified_ma_stop_reference():
+    t = ta.ModifiedMaStop(14)
+    candles = _stop_candles(14)
+    for c in candles[:13]:
+        assert t.update(c) is None
+    assert t.update(candles[13]) == pytest.approx((107.0, 1.0))
+
+
+def test_volume_rsi_reference():
+    t = ta.VolumeRsi(14)
+
+
+def test_twiggs_money_flow_reference():
+    t = ta.TwiggsMoneyFlow(21)
+
+
+def test_trade_volume_index_reference():
+    t = ta.TradeVolumeIndex(0.25)
+
+
+def test_intraday_intensity_reference():
+    t = ta.IntradayIntensity()
+
+
+def test_better_volume_reference():
+    t = ta.BetterVolume(14)
+
+
+def test_volume_weighted_macd_reference():
+    t = ta.VolumeWeightedMacd(12, 26, 9)
+
+
+def test_kendall_tau_reference():
+    t = ta.KendallTau(20)
+
+
+def test_central_pivot_range_reference():
+    t = ta.CentralPivotRange()
+    assert t.update((105.0, 110.0, 90.0, 105.0, 1.0, 0)) == pytest.approx((101.66666666666667, 103.33333333333334, 100.0))
+
+
+def test_murrey_math_lines_reference():
+    t = ta.MurreyMathLines(4)
+    assert t.update((140.0, 180.0, 100.0, 140.0, 1.0, 0)) is None
+    assert t.update((140.0, 180.0, 100.0, 140.0, 1.0, 1)) is None
+    assert t.update((140.0, 180.0, 100.0, 140.0, 1.0, 2)) is None
+    assert t.update((140.0, 180.0, 100.0, 140.0, 1.0, 3)) == pytest.approx((180.0, 170.0, 160.0, 150.0, 140.0, 130.0, 120.0, 110.0, 100.0))
+
+
+def test_andrews_pitchfork_reference():
+    t = ta.AndrewsPitchfork(2)
+    # Warmup: no pitchfork until three alternating swing pivots are confirmed.
+    assert t.update((100.0, 101.0, 99.0, 100.0, 1.0, 0)) is None
+
+
+def test_volume_weighted_sr_reference():
+    t = ta.VolumeWeightedSr(3)
+    assert t.update((100.0, 102.0, 98.0, 100.0, 1.0, 0)) is None
+    assert t.update((100.0, 104.0, 96.0, 100.0, 1.0, 1)) is None
+    assert t.update((100.0, 106.0, 94.0, 100.0, 1.0, 2)) == pytest.approx((96.0, 104.0))
+
+
+def test_pivot_reversal_reference():
+    t = ta.PivotReversal(1, 1)
+    assert t.update((9.5, 10.0, 9.0, 9.5, 1.0, 0)) is None
+    assert t.update((11.5, 12.0, 11.0, 11.5, 1.0, 1)) is None
+    # Pivot high = 12 confirmed; close 9.5 has not crossed it.
+    assert t.update((9.5, 10.0, 9.0, 9.5, 1.0, 2)) == pytest.approx(0.0)
+    assert t.update((9.0, 11.0, 9.0, 9.0, 1.0, 3)) == pytest.approx(0.0)
+    # Close 13 > pivot high 12 with prev close 9 below it -> bullish reversal.
+    assert t.update((13.0, 14.0, 12.5, 13.0, 1.0, 4)) == pytest.approx(1.0)
+
+
+
+def test_td_camouflage_reference():
+    t = ta.TDCamouflage()
+    assert t.update((10.0, 11.0, 8.0, 10.0, 1.0, 0)) == pytest.approx(0.0)
+    assert t.update((9.0, 10.0, 7.0, 9.5, 1.0, 1)) == pytest.approx(1.0)
+
+
+def test_td_clop_reference():
+    t = ta.TDClop()
+    assert t.update((10.0, 12.0, 9.0, 11.0, 1.0, 0)) == pytest.approx(0.0)
+    assert t.update((9.0, 13.0, 8.0, 12.0, 1.0, 1)) == pytest.approx(1.0)
+
+
+def test_td_clopwin_reference():
+    t = ta.TDClopwin()
+    assert t.update((10.0, 15.0, 9.0, 14.0, 1.0, 0)) == pytest.approx(0.0)
+    assert t.update((11.0, 14.0, 10.0, 13.0, 1.0, 1)) == pytest.approx(1.0)
+
+
+def test_td_propulsion_reference():
+    t = ta.TDPropulsion()
+    assert t.update((9.5, 11.0, 9.0, 10.0, 1.0, 0)) == pytest.approx(0.0)
+    assert t.update((10.5, 12.0, 10.0, 11.5, 1.0, 1)) == pytest.approx(1.0)
+
+
+def test_td_trap_reference():
+    t = ta.TDTrap()
+    assert t.update((100.0, 110.0, 90.0, 100.0, 1.0, 0)) == pytest.approx(0.0)
+    assert t.update((101.5, 108.0, 95.0, 102.0, 1.0, 1)) == pytest.approx(0.0)
+    assert t.update((106.0, 112.0, 100.0, 109.0, 1.0, 2)) == pytest.approx(1.0)
+
+
+
+def test_heikin_ashi_oscillator_reference():
+    t = ta.HeikinAshiOscillator(5)
+
+
+def test_three_line_break_reference():
+    t = ta.ThreeLineBreak(3)
+
+
+def test_smoothed_heikin_ashi_reference():
+    t = ta.SmoothedHeikinAshi(5)
+
+
+def test_equivolume_reference():
+    t = ta.Equivolume(20)
+
+
+def test_candle_volume_reference():
+    t = ta.CandleVolume(20)
+
+
+def test_tristar_reference():
+    t = ta.Tristar()
+    assert t.update((100.0, 101.0, 99.0, 100.02, 1.0, 0)) == pytest.approx(0.0)
+    assert t.update((105.0, 106.0, 104.0, 105.02, 1.0, 1)) == pytest.approx(0.0)
+    assert t.update((100.0, 101.0, 99.0, 100.02, 1.0, 2)) == pytest.approx(-1.0)
+
+
+def test_harami_cross_reference():
+    t = ta.HaramiCross()
+    assert t.update((110.0, 110.2, 99.8, 100.0, 1.0, 0)) == pytest.approx(0.0)
+    assert t.update((105.0, 106.0, 104.0, 105.02, 1.0, 1)) == pytest.approx(1.0)
+
+
+def test_tower_top_bottom_reference():
+    t = ta.TowerTopBottom()
+    assert t.update((100.0, 110.1, 99.9, 110.0, 1.0, 0)) == pytest.approx(0.0)
+    assert t.update((105.0, 107.0, 103.0, 105.1, 1.0, 1)) == pytest.approx(0.0)
+    assert t.update((110.0, 110.1, 99.9, 100.0, 1.0, 2)) == pytest.approx(-1.0)
+
+
+
+def test_hasbrouck_information_share_reference():
+    t = ta.HasbrouckInformationShare(2)
+    assert t.update(7.0, 9.0) is None
+    assert t.update(7.0, 9.0) is None
+    assert t.update(7.0, 9.0) == pytest.approx(0.5)
+
+
+def test_naked_poc_reference():
+    t = ta.NakedPoc(20, 24)
+
+
+def test_single_prints_reference():
+    t = ta.SinglePrints(20, 24)
+
+
+def test_profile_shape_reference():
+    t = ta.ProfileShape(20, 24)
+
+
+def test_high_low_volume_nodes_reference():
+    t = ta.HighLowVolumeNodes(20, 24)
+
+
+def test_composite_profile_reference():
+    t = ta.CompositeProfile(20, 24, 0.7)
+
 # --- Lifecycle ------------------------------------------------------------
 
 
@@ -3119,6 +3722,8 @@ def test_tradeflow_indicators_streaming_equals_batch():
         lambda: ta.Vpin(8.0, 5),
         lambda: ta.AmihudIlliquidity(14),
         lambda: ta.RollMeasure(14),
+        lambda: ta.TradeSignAutocorrelation(10),
+        lambda: ta.Pin(10),
     ):
         batch = make().batch(price, size, is_buy)
         streamer = make()
@@ -3130,6 +3735,34 @@ def test_tradeflow_indicators_streaming_equals_batch():
         assert _eq_nan(batch, streamed)
 
 
+def test_trade_sign_autocorrelation_reference():
+    # Perfectly alternating aggressor signs -> lag-1 autocorrelation -1.
+    t = ta.TradeSignAutocorrelation(10)
+    last = None
+    for i in range(20):
+        last = t.update(100.0, 1.0, i % 2 == 0)
+    assert last == pytest.approx(-1.0)
+    # All buys -> perfectly persistent flow -> +1.
+    t2 = ta.TradeSignAutocorrelation(10)
+    for _ in range(20):
+        last2 = t2.update(100.0, 1.0, True)
+    assert last2 == pytest.approx(1.0)
+
+
+def test_pin_reference():
+    # One-sided flow (all buys) -> maximally informed -> PIN 1.
+    p = ta.Pin(10)
+    last = None
+    for _ in range(20):
+        last = p.update(100.0, 1.0, True)
+    assert last == pytest.approx(1.0)
+    # Balanced flow -> uninformed -> PIN 0.
+    p2 = ta.Pin(10)
+    for i in range(20):
+        last2 = p2.update(100.0, 1.0, i % 2 == 0)
+    assert last2 == pytest.approx(0.0)
+
+
 def test_price_impact_indicators_streaming_equals_batch():
     n = 40
     mid = np.array([100.0 + 0.5 * math.sin(i * 0.4) for i in range(n)], dtype=np.float64)
@@ -3500,6 +4133,71 @@ def test_basis_indicators_streaming_equals_batch():
     assert _eq_nan(batch, streamed)
 
 
+def test_b16_derivatives_reference():
+    # Estimated leverage: oi / (long + short) = 200 / 100 = 2.
+    assert ta.EstimatedLeverageRatio().update(200.0, 60.0, 40.0) == pytest.approx(2.0)
+    # OI-to-volume: oi / (buy + sell) = 100 / 50 = 2.
+    assert ta.OiToVolumeRatio().update(100.0, 30.0, 20.0) == pytest.approx(2.0)
+    # Perpetual premium: (mark - index) / index = 0.5 / 100 = 0.005.
+    assert ta.PerpetualPremiumIndex().update(100.5, 100.0) == pytest.approx(0.005)
+    # Funding-implied APR: rate * intervals = 0.0001 * 1095 = 0.1095.
+    assert ta.FundingImpliedApr(1095.0).update(0.0001) == pytest.approx(0.1095)
+    # Open-interest momentum (period 2): warmup then ROC% = 100*(120-100)/100 = 20.
+    oim = ta.OpenInterestMomentum(2)
+    assert oim.update(100.0) is None
+    assert oim.update(110.0) is None
+    assert oim.update(120.0) == pytest.approx(20.0)
+
+
+def test_b16_derivatives_streaming_equals_batch():
+    n = 40
+    oi = np.array([1000.0 + 50.0 * math.sin(i * 0.3) for i in range(n)], dtype=np.float64)
+    long_sz = np.array([600.0 + 20.0 * math.cos(i * 0.2) for i in range(n)], dtype=np.float64)
+    short_sz = np.array([400.0 + 15.0 * math.sin(i * 0.4) for i in range(n)], dtype=np.float64)
+    buy = np.array([300.0 + 10.0 * math.sin(i * 0.5) for i in range(n)], dtype=np.float64)
+    sell = np.array([250.0 + 12.0 * math.cos(i * 0.35) for i in range(n)], dtype=np.float64)
+    index = np.array([100.0 + math.sin(i * 0.2) for i in range(n)], dtype=np.float64)
+    mark = np.array([index[i] + 0.05 * math.cos(i * 0.3) for i in range(n)], dtype=np.float64)
+    rate = np.array([0.0001 * math.sin(i * 0.3) for i in range(n)], dtype=np.float64)
+
+    # EstimatedLeverageRatio; update(open_interest, long_size, short_size).
+    batch = ta.EstimatedLeverageRatio().batch(oi, long_sz, short_sz)
+    streamer = ta.EstimatedLeverageRatio()
+    streamed = np.array(
+        [streamer.update(oi[i], long_sz[i], short_sz[i]) for i in range(n)], dtype=np.float64
+    )
+    assert batch.shape == (n,)
+    assert _eq_nan(batch, streamed)
+
+    # OiToVolumeRatio; update(open_interest, taker_buy_volume, taker_sell_volume).
+    batch = ta.OiToVolumeRatio().batch(oi, buy, sell)
+    streamer = ta.OiToVolumeRatio()
+    streamed = np.array(
+        [streamer.update(oi[i], buy[i], sell[i]) for i in range(n)], dtype=np.float64
+    )
+    assert _eq_nan(batch, streamed)
+
+    # PerpetualPremiumIndex; update(mark_price, index_price).
+    batch = ta.PerpetualPremiumIndex().batch(mark, index)
+    streamer = ta.PerpetualPremiumIndex()
+    streamed = np.array(
+        [streamer.update(mark[i], index[i]) for i in range(n)], dtype=np.float64
+    )
+    assert _eq_nan(batch, streamed)
+
+    # FundingImpliedApr; update(funding_rate).
+    batch = ta.FundingImpliedApr(1095.0).batch(rate)
+    streamer = ta.FundingImpliedApr(1095.0)
+    streamed = np.array([streamer.update(rate[i]) for i in range(n)], dtype=np.float64)
+    assert _eq_nan(batch, streamed)
+
+    # OpenInterestMomentum; update(open_interest).
+    batch = ta.OpenInterestMomentum(10).batch(oi)
+    streamer = ta.OpenInterestMomentum(10)
+    streamed = np.array([streamer.update(oi[i]) for i in range(n)], dtype=np.float64)
+    assert _eq_nan(batch, streamed)
+
+
 # --- Alt-Chart Bars ------------------------------------------------------
 
 
@@ -3539,3 +4237,83 @@ def test_bar_builders_reset():
     r.update(15.0)
     r.reset()
     assert r.update(50.0) == []  # re-seeds after reset
+
+
+def test_range_bars_reference():
+    rb = ta.RangeBars(1.0)
+    assert rb.update(10.0) == []  # seed
+    assert rb.update(13.0) == [(10.0, 11.0, 1), (11.0, 12.0, 1), (12.0, 13.0, 1)]
+
+
+def test_range_bars_batch_shape():
+    rb = ta.RangeBars(1.0)
+    out = rb.batch(np.array([10.0, 11.0, 12.0, 13.0]))
+    assert out.shape == (3, 3)
+    np.testing.assert_allclose(out[:, 2], [1.0, 1.0, 1.0])
+
+
+def test_tick_bars_reference():
+    tb = ta.TickBars(2)
+    assert tb.update(10.0, 11.0, 9.0, 10.5, 100.0) == []
+    out = tb.update(10.5, 12.0, 10.0, 11.0, 150.0)
+    assert len(out) == 1
+    assert out[0] == (10.0, 12.0, 9.0, 11.0, 250.0)
+
+
+def test_tick_bars_batch_shape():
+    tb = ta.TickBars(2)
+    col = np.array([10.0, 10.0, 10.0, 10.0])
+    vol = np.array([1.0, 1.0, 1.0, 1.0])
+    out = tb.batch(col, col, col, col, vol)
+    assert out.shape == (2, 5)
+
+
+def test_volume_bars_reference():
+    vb = ta.VolumeBars(100.0)
+    assert vb.update(10.0, 10.0, 10.0, 10.0, 60.0) == []
+    out = vb.update(10.5, 10.5, 10.5, 10.5, 60.0)
+    assert len(out) == 1
+    assert out[0][4] == 120.0  # accumulated volume
+
+
+def test_dollar_bars_reference():
+    db = ta.DollarBars(1000.0)
+    assert db.update(10.0, 10.0, 10.0, 10.0, 60.0) == []  # 600
+    out = db.update(10.0, 10.0, 10.0, 10.0, 60.0)  # 1200 >= 1000
+    assert len(out) == 1
+    assert out[0][4] == 120.0  # volume
+    assert out[0][5] == 1200.0  # traded value
+
+
+def test_imbalance_bars_reference():
+    ib = ta.ImbalanceBars(3.0)
+    assert ib.update(10.0, 10.0, 10.0, 10.0) == []  # seed
+    ib.update(11.0, 11.0, 11.0, 11.0)  # +1
+    ib.update(12.0, 12.0, 12.0, 12.0)  # +2
+    out = ib.update(13.0, 13.0, 13.0, 13.0)  # +3 -> close
+    assert len(out) == 1
+    assert out[0][4] == 3.0  # imbalance
+    assert out[0][5] == 1  # direction
+
+
+def test_run_bars_reference():
+    rb = ta.RunBars(3)
+    assert rb.update(10.0, 10.0, 10.0, 10.0) == []  # seed
+    rb.update(11.0, 11.0, 11.0, 11.0)  # run 1
+    rb.update(12.0, 12.0, 12.0, 12.0)  # run 2
+    out = rb.update(13.0, 13.0, 13.0, 13.0)  # run 3 -> close
+    assert len(out) == 1
+    assert out[0][4] == 3  # length
+    assert out[0][5] == 1  # direction
+
+
+def test_three_line_break_bars_reference():
+    tlb = ta.ThreeLineBreakBars(3)
+    assert tlb.update(10.0) == []  # seed
+    assert tlb.update(11.0) == [(10.0, 11.0, 1)]
+
+
+def test_three_line_break_bars_batch_shape():
+    tlb = ta.ThreeLineBreakBars(3)
+    out = tlb.batch(np.array([10.0, 11.0, 12.0, 13.0]))
+    assert out.shape[1] == 3

bindings/r/.Rbuildignore

@@ -0,0 +1,8 @@
+^src/wickra_abi\.dll$
+^src/wickra_abi\.def$
+^src/libwickra_abi\.dll\.a$
+^src/.*\.o$
+^src/wickra\.dll$
+^src/wickra\.so$
+^src/symbols\.rds$
+^\.gitignore$

bindings/r/DESCRIPTION

@@ -0,0 +1,20 @@
+Package: wickra
+Type: Package
+Title: Streaming-First Technical Indicators
+Version: 0.7.8
+Authors@R: person("Wickra contributors", role = c("aut", "cre"), email = "support@wickra.org")
+Description: R bindings for the Wickra technical-analysis library over its C ABI
+    hub. Exposes 514 indicators, each an O(1) streaming state machine shared with
+    the Rust core and the other language bindings, so that live and historical
+    evaluation use the exact same implementation.
+License: MIT + file LICENSE | Apache License 2.0
+URL: https://github.com/wickra-lib/wickra, https://docs.wickra.org
+BugReports: https://github.com/wickra-lib/wickra/issues
+Encoding: UTF-8
+NeedsCompilation: yes
+SystemRequirements: the Wickra C ABI library (libwickra); set WICKRA_INCLUDE_DIR
+    and WICKRA_LIB_DIR when installing from source.
+Roxygen: list(markdown = TRUE)
+Suggests: testthat (>= 3.0.0)
+Config/testthat/edition: 3
+Config/roxygen2/version: 8.0.0

bindings/r/LICENSE

@@ -0,0 +1,2 @@
+YEAR: 2026
+COPYRIGHT HOLDER: Wickra contributors

bindings/r/NAMESPACE

@@ -0,0 +1,522 @@
+# Generated by roxygen2: do not edit by hand
+
+S3method(batch,wickra_indicator)
+S3method(reset,wickra_indicator)
+S3method(update,wickra_indicator)
+export(AbandonedBaby)
+export(Abcd)
+export(AbsoluteBreadthIndex)
+export(AccelerationBands)
+export(AcceleratorOscillator)
+export(AdOscillator)
+export(AdVolumeLine)
+export(AdaptiveCci)
+export(AdaptiveCycle)
+export(AdaptiveLaguerreFilter)
+export(AdaptiveRsi)
+export(Adl)
+export(AdvanceBlock)
+export(AdvanceDecline)
+export(AdvanceDeclineRatio)
+export(Adx)
+export(Adxr)
+export(Alligator)
+export(Alma)
+export(Alpha)
+export(AmihudIlliquidity)
+export(AnchoredRsi)
+export(AnchoredVwap)
+export(AndrewsPitchfork)
+export(Apo)
+export(Aroon)
+export(AroonOscillator)
+export(Atr)
+export(AtrBands)
+export(AtrRatchet)
+export(AtrTrailingStop)
+export(AutoFib)
+export(Autocorrelation)
+export(AutocorrelationPeriodogram)
+export(AverageDailyRange)
+export(AverageDrawdown)
+export(AvgPrice)
+export(AwesomeOscillator)
+export(AwesomeOscillatorHistogram)
+export(BalanceOfPower)
+export(BandpassFilter)
+export(Bat)
+export(BeltHold)
+export(Beta)
+export(BetaNeutralSpread)
+export(BetterVolume)
+export(BipowerVariation)
+export(BodySizePct)
+export(BollingerBands)
+export(BollingerBandwidth)
+export(BomarBands)
+export(BreadthThrust)
+export(Breakaway)
+export(BullishPercentIndex)
+export(BurkeRatio)
+export(Butterfly)
+export(CalendarSpread)
+export(CalmarRatio)
+export(Camarilla)
+export(CandleVolume)
+export(Cci)
+export(CenterOfGravity)
+export(CentralPivotRange)
+export(Cfo)
+export(ChaikinMoneyFlow)
+export(ChaikinOscillator)
+export(ChaikinVolatility)
+export(ChandeKrollStop)
+export(ChandelierExit)
+export(ChoppinessIndex)
+export(ClassicPivots)
+export(CloseVsOpen)
+export(ClosingMarubozu)
+export(Cmo)
+export(CoefficientOfVariation)
+export(Cointegration)
+export(CommonSenseRatio)
+export(CompositeProfile)
+export(ConcealingBabySwallow)
+export(ConditionalValueAtRisk)
+export(ConnorsRsi)
+export(Coppock)
+export(CorrelationTrendIndicator)
+export(Counterattack)
+export(Crab)
+export(CumulativeVolumeDelta)
+export(CumulativeVolumeIndex)
+export(CupAndHandle)
+export(CyberneticCycle)
+export(Cypher)
+export(DayOfWeekProfile)
+export(Decycler)
+export(DecyclerOscillator)
+export(Dema)
+export(DemandIndex)
+export(DemarkPivots)
+export(DepthSlope)
+export(DerivativeOscillator)
+export(DetrendedStdDev)
+export(DisparityIndex)
+export(DistanceSsd)
+export(Doji)
+export(DojiStar)
+export(DollarBars)
+export(Donchian)
+export(DonchianStop)
+export(DoubleBollinger)
+export(DoubleTopBottom)
+export(DownsideGapThreeMethods)
+export(Dpo)
+export(DragonflyDoji)
+export(DrawdownDuration)
+export(DumplingTop)
+export(Dx)
+export(DynamicMomentumIndex)
+export(EaseOfMovement)
+export(EffectiveSpread)
+export(EhlersStochastic)
+export(Ehma)
+export(ElderImpulse)
+export(ElderRay)
+export(ElderSafeZone)
+export(Ema)
+export(EmpiricalModeDecomposition)
+export(Engulfing)
+export(Equivolume)
+export(EstimatedLeverageRatio)
+export(EvenBetterSinewave)
+export(EveningDojiStar)
+export(Evwma)
+export(EwmaVolatility)
+export(Expectancy)
+export(FallingThreeMethods)
+export(Fama)
+export(FibArcs)
+export(FibChannel)
+export(FibConfluence)
+export(FibExtension)
+export(FibFan)
+export(FibProjection)
+export(FibRetracement)
+export(FibTimeZones)
+export(FibonacciPivots)
+export(FisherRsi)
+export(FisherTransform)
+export(FlagPennant)
+export(Footprint)
+export(ForceIndex)
+export(FractalChaosBands)
+export(Frama)
+export(FryPanBottom)
+export(FundingBasis)
+export(FundingImpliedApr)
+export(FundingRate)
+export(FundingRateMean)
+export(FundingRateZScore)
+export(GainLossRatio)
+export(GainToPainRatio)
+export(GapSideBySideWhite)
+export(Garch11)
+export(GarmanKlassVolatility)
+export(Gartley)
+export(GatorOscillator)
+export(GeneralizedDema)
+export(GeometricMa)
+export(GoldenPocket)
+export(GrangerCausality)
+export(GravestoneDoji)
+export(Hammer)
+export(HangingMan)
+export(Harami)
+export(HaramiCross)
+export(HasbrouckInformationShare)
+export(HeadAndShoulders)
+export(HeikinAshi)
+export(HeikinAshiOscillator)
+export(HiLoActivator)
+export(HighLowIndex)
+export(HighLowRange)
+export(HighLowVolumeNodes)
+export(HighWave)
+export(HighpassFilter)
+export(Hikkake)
+export(HikkakeModified)
+export(HilbertDominantCycle)
+export(HistoricalVolatility)
+export(Hma)
+export(HoltWinters)
+export(HomingPigeon)
+export(HtDcPhase)
+export(HtPhasor)
+export(HtTrendMode)
+export(HurstChannel)
+export(HurstExponent)
+export(Ichimoku)
+export(IdenticalThreeCrows)
+export(ImbalanceBars)
+export(InNeck)
+export(Inertia)
+export(InformationRatio)
+export(InitialBalance)
+export(InstantaneousTrendline)
+export(IntradayIntensity)
+export(IntradayMomentumIndex)
+export(IntradayVolatilityProfile)
+export(InverseFisherTransform)
+export(InvertedHammer)
+export(JarqueBera)
+export(Jma)
+export(JumpIndicator)
+export(KRatio)
+export(KagiBars)
+export(KalmanHedgeRatio)
+export(Kama)
+export(KaseDevStop)
+export(KasePermissionStochastic)
+export(KellyCriterion)
+export(Keltner)
+export(KendallTau)
+export(Kicking)
+export(KickingByLength)
+export(Kst)
+export(Kurtosis)
+export(Kvo)
+export(KylesLambda)
+export(LadderBottom)
+export(LaguerreRsi)
+export(LeadLagCrossCorrelation)
+export(LinRegAngle)
+export(LinRegChannel)
+export(LinRegIntercept)
+export(LinRegSlope)
+export(LinearRegression)
+export(LiquidationFeatures)
+export(LogReturn)
+export(LongLeggedDoji)
+export(LongLine)
+export(LongShortRatio)
+export(M2Measure)
+export(MaEnvelope)
+export(MacdExt)
+export(MacdFix)
+export(MacdHistogram)
+export(MacdIndicator)
+export(Mama)
+export(MarketFacilitationIndex)
+export(MartinRatio)
+export(Marubozu)
+export(MassIndex)
+export(MatHold)
+export(MatchingLow)
+export(MaxDrawdown)
+export(McClellanOscillator)
+export(McClellanSummationIndex)
+export(McGinleyDynamic)
+export(MedianAbsoluteDeviation)
+export(MedianChannel)
+export(MedianMa)
+export(MedianPrice)
+export(Mfi)
+export(Microprice)
+export(MidPoint)
+export(MidPrice)
+export(MinusDi)
+export(MinusDm)
+export(ModifiedMaStop)
+export(Mom)
+export(MorningDojiStar)
+export(MorningEveningStar)
+export(MurreyMathLines)
+export(NakedPoc)
+export(Natr)
+export(NewHighsNewLows)
+export(NewPriceLines)
+export(Nrtr)
+export(Nvi)
+export(OIPriceDivergence)
+export(OIWeighted)
+export(Obv)
+export(OiToVolumeRatio)
+export(OmegaRatio)
+export(OnNeck)
+export(OpenInterestDelta)
+export(OpenInterestMomentum)
+export(OpeningMarubozu)
+export(OpeningRange)
+export(OrderBookImbalanceFull)
+export(OrderBookImbalanceTop1)
+export(OrderBookImbalanceTopN)
+export(OrderFlowImbalance)
+export(OuHalfLife)
+export(OvernightGap)
+export(OvernightIntradayReturn)
+export(PainIndex)
+export(PairSpreadZScore)
+export(PairwiseBeta)
+export(ParkinsonVolatility)
+export(PearsonCorrelation)
+export(PercentAboveMa)
+export(PercentB)
+export(PercentageTrailingStop)
+export(PerpetualPremiumIndex)
+export(Pgo)
+export(PiercingDarkCloud)
+export(Pin)
+export(PivotReversal)
+export(PlusDi)
+export(PlusDm)
+export(Pmo)
+export(PointAndFigureBars)
+export(PolarizedFractalEfficiency)
+export(Ppo)
+export(PpoHistogram)
+export(ProfileShape)
+export(ProfitFactor)
+export(ProjectionBands)
+export(ProjectionOscillator)
+export(Psar)
+export(Pvi)
+export(Qqe)
+export(Qstick)
+export(QuartileBands)
+export(QuotedSpread)
+export(RSquared)
+export(RangeBars)
+export(RealizedSpread)
+export(RealizedVolatility)
+export(RecoveryFactor)
+export(RectangleRange)
+export(Reflex)
+export(RegimeLabel)
+export(RelativeStrengthAB)
+export(RenkoBars)
+export(RenkoTrailingStop)
+export(RickshawMan)
+export(RisingThreeMethods)
+export(Rmi)
+export(Roc)
+export(Rocp)
+export(Rocr)
+export(Rocr100)
+export(RogersSatchellVolatility)
+export(RollMeasure)
+export(RollingCorrelation)
+export(RollingCovariance)
+export(RollingIqr)
+export(RollingMinMaxScaler)
+export(RollingPercentileRank)
+export(RollingQuantile)
+export(RollingVwap)
+export(RoofingFilter)
+export(Rsi)
+export(Rsx)
+export(RunBars)
+export(Rvi)
+export(RviVolatility)
+export(Rwi)
+export(SampleEntropy)
+export(SarExt)
+export(SeasonalZScore)
+export(SeparatingLines)
+export(SessionHighLow)
+export(SessionRange)
+export(SessionVwap)
+export(ShannonEntropy)
+export(Shark)
+export(SharpeRatio)
+export(ShootingStar)
+export(ShortLine)
+export(SignedVolume)
+export(SineWave)
+export(SineWeightedMa)
+export(SinglePrints)
+export(Skewness)
+export(Sma)
+export(Smi)
+export(Smma)
+export(SmoothedHeikinAshi)
+export(SortinoRatio)
+export(SpearmanCorrelation)
+export(SpinningTop)
+export(SpreadAr1Coefficient)
+export(SpreadBollingerBands)
+export(SpreadHurst)
+export(StalledPattern)
+export(StandardError)
+export(StandardErrorBands)
+export(StarcBands)
+export(Stc)
+export(StdDev)
+export(StepTrailingStop)
+export(SterlingRatio)
+export(StickSandwich)
+export(StochRsi)
+export(Stochastic)
+export(StochasticCci)
+export(SuperSmoother)
+export(SuperTrend)
+export(T3)
+export(TailRatio)
+export(TakerBuySellRatio)
+export(Takuri)
+export(TasukiGap)
+export(TdCamouflage)
+export(TdClop)
+export(TdClopwin)
+export(TdCombo)
+export(TdCountdown)
+export(TdDWave)
+export(TdDeMarker)
+export(TdDifferential)
+export(TdLines)
+export(TdMovingAverage)
+export(TdOpen)
+export(TdPressure)
+export(TdPropulsion)
+export(TdRangeProjection)
+export(TdRei)
+export(TdRiskLevel)
+export(TdSequential)
+export(TdSetup)
+export(TdTrap)
+export(Tema)
+export(TermStructureBasis)
+export(ThreeDrives)
+export(ThreeInside)
+export(ThreeLineBreak)
+export(ThreeLineBreakBars)
+export(ThreeLineStrike)
+export(ThreeOutside)
+export(ThreeSoldiersOrCrows)
+export(ThreeStarsInSouth)
+export(Thrusting)
+export(TickBars)
+export(TickIndex)
+export(Tii)
+export(TimeBasedStop)
+export(TimeOfDayReturnProfile)
+export(TowerTopBottom)
+export(TpoProfile)
+export(TradeImbalance)
+export(TradeSignAutocorrelation)
+export(TradeVolumeIndex)
+export(TrendLabel)
+export(TrendStrengthIndex)
+export(Trendflex)
+export(TreynorRatio)
+export(Triangle)
+export(Trima)
+export(Trin)
+export(TripleTopBottom)
+export(Tristar)
+export(Trix)
+export(TrueRange)
+export(Tsf)
+export(TsfOscillator)
+export(Tsi)
+export(Tsv)
+export(TtmSqueeze)
+export(TtmTrend)
+export(TurnOfMonth)
+export(Tweezer)
+export(TwiggsMoneyFlow)
+export(TwoCrows)
+export(TypicalPrice)
+export(UlcerIndex)
+export(UltimateOscillator)
+export(UniqueThreeRiver)
+export(UniversalOscillator)
+export(UpDownVolumeRatio)
+export(UpsideGapThreeMethods)
+export(UpsideGapTwoCrows)
+export(UpsidePotentialRatio)
+export(ValueArea)
+export(ValueAtRisk)
+export(Variance)
+export(VarianceRatio)
+export(VerticalHorizontalFilter)
+export(Vidya)
+export(VolatilityCone)
+export(VolatilityOfVolatility)
+export(VolatilityRatio)
+export(VoltyStop)
+export(VolumeBars)
+export(VolumeByTimeProfile)
+export(VolumeOscillator)
+export(VolumePriceTrend)
+export(VolumeProfile)
+export(VolumeRsi)
+export(VolumeWeightedMacd)
+export(VolumeWeightedSr)
+export(Vortex)
+export(Vpin)
+export(Vwap)
+export(VwapStdDevBands)
+export(Vwma)
+export(Vzo)
+export(Wad)
+export(WavePm)
+export(WaveTrend)
+export(Wedge)
+export(WeightedClose)
+export(WickRatio)
+export(WilliamsFractals)
+export(WilliamsR)
+export(WinRate)
+export(Wma)
+export(WoodiePivots)
+export(YangZhangVolatility)
+export(YoyoExit)
+export(ZScore)
+export(ZeroLagMacd)
+export(ZigZag)
+export(Zlema)
+export(batch)
+export(reset)
+importFrom(stats,update)

bindings/r/R/methods.R

@@ -0,0 +1,78 @@
+#' wickra: streaming-first technical indicators
+#'
+#' R bindings for the Wickra technical-analysis library over its C ABI hub. Each
+#' indicator is a constructor (for example [Sma()], [Rsi()], [MacdIndicator()])
+#' returning a `wickra_indicator` object; feed it one observation at a time with
+#' [update()], run a whole series in one call with [batch()], and clear its
+#' state with [reset()]. The native handle is freed automatically when the object
+#' is garbage-collected.
+#'
+#' @keywords internal
+#' @importFrom stats update
+"_PACKAGE"
+
+#' Update an indicator with one observation
+#'
+#' @param object A `wickra_indicator` created by an indicator constructor.
+#' @param ... The observation: a single value for scalar indicators, the OHLCV
+#'   fields plus a timestamp for candle indicators, or two values for pairwise
+#'   indicators.
+#' @return The indicator value: a numeric scalar; a named numeric vector for
+#'   multi-output indicators (`NA` during warmup); a matrix of completed bars for
+#'   bar builders; or a list / numeric vector for profile indicators
+#'   (`NULL` during warmup).
+#' @examples
+#' sma <- Sma(3)
+#' for (x in c(1, 2, 3, 4, 5)) v <- update(sma, x)
+#' v # 4
+#' @export
+update.wickra_indicator <- function(object, ...) {
+  args <- list(object$ptr, ...)
+  if (!is.na(object$values_cap)) {
+    args <- c(args, object$values_cap)
+  }
+  do.call(".Call", c(list(paste0("wk_", object$prefix, "_update")), args,
+                     list(PACKAGE = "wickra")))
+}
+
+#' Run an indicator over a whole series in one call
+#'
+#' Available for scalar indicators. The result is identical to feeding the same
+#' inputs through [update()] one at a time, with `NA` at warmup positions.
+#'
+#' @param object A `wickra_indicator`.
+#' @param ... The input vector(s).
+#' @return A numeric vector the same length as the input.
+#' @examples
+#' batch(Sma(3), c(1, 2, 3, 4, 5)) # NA NA 2 3 4
+#' @export
+batch <- function(object, ...) {
+  UseMethod("batch")
+}
+
+#' @rdname batch
+#' @export
+batch.wickra_indicator <- function(object, ...) {
+  do.call(".Call", c(list(paste0("wk_", object$prefix, "_batch"), object$ptr),
+                     list(...), list(PACKAGE = "wickra")))
+}
+
+#' Reset an indicator to its warmup state
+#'
+#' @param object A `wickra_indicator`.
+#' @return The indicator, invisibly.
+#' @examples
+#' sma <- Sma(3)
+#' update(sma, 1)
+#' reset(sma)
+#' @export
+reset <- function(object) {
+  UseMethod("reset")
+}
+
+#' @rdname reset
+#' @export
+reset.wickra_indicator <- function(object) {
+  .Call(paste0("wk_", object$prefix, "_reset"), object$ptr, PACKAGE = "wickra")
+  invisible(object)
+}

bindings/r/R/zzz.R

@@ -0,0 +1,18 @@
+.onLoad <- function(libname, pkgname) {
+  # On Windows the package's wickra.dll depends on the bundled C ABI
+  # wickra_abi.dll; the loader searches PATH for it, so prepend the package's own
+  # libs directory. On Linux/macOS the rpath baked at build time locates the
+  # shared library, so no PATH change is needed.
+  if (.Platform$OS.type == "windows") {
+    libs <- system.file(paste0("libs", .Platform$r_arch),
+                        package = pkgname, lib.loc = libname)
+    if (nzchar(libs)) {
+      Sys.setenv(PATH = paste(libs, Sys.getenv("PATH"), sep = .Platform$path.sep))
+    }
+  }
+  library.dynam("wickra", pkgname, libname)
+}
+
+.onUnload <- function(libpath) {
+  library.dynam.unload("wickra", libpath)
+}

bindings/r/README.md

@@ -0,0 +1,85 @@
+# Wickra — R
+
+[![CI](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
+[![codecov](https://codecov.io/gh/wickra-lib/wickra/branch/main/graph/badge.svg)](https://codecov.io/gh/wickra-lib/wickra)
+[![License: MIT OR Apache-2.0](https://img.shields.io/badge/license-MIT_OR_Apache--2.0-blue)](https://github.com/wickra-lib/wickra#license)
+
+**Streaming-first technical indicators for R, over the Wickra C ABI hub via `.Call`.**
+
+Wickra is a multi-language technical-analysis library with a Rust core and
+bindings for Python, Node.js and WebAssembly, plus a C ABI for C/C++, C#, Go, R
+and any other C-capable language. Every indicator is an O(1) streaming state
+machine, so live trading and historical backtests share the exact same
+implementation. This package is the R binding; it reaches the C ABI hub through
+R's native `.Call` interface and exposes all 514 indicators as constructors that
+return a lightweight `wickra_indicator` object.
+
+## Install
+
+The package compiles a thin C glue layer (`.Call`) against the prebuilt Wickra
+C ABI library, so a C toolchain (Rtools on Windows) is required, plus the C ABI
+header and library. Build the library from the workspace, then install the
+package pointing at it:
+
+```bash
+cargo build -p wickra-c --release
+WICKRA_INCLUDE_DIR="$PWD/bindings/c/include" \
+WICKRA_LIB_DIR="$PWD/target/release" \
+R CMD INSTALL bindings/r
+```
+
+On Windows the C ABI DLL is bundled into the package and put on the load path
+automatically; on Linux and macOS the library path is baked in via rpath.
+
+## Quick start
+
+```r
+library(wickra)
+
+# Batch: run an indicator over a whole series (NaN at warmup positions).
+prices <- 100 + (0:999) * 0.1
+sma <- Sma(20)
+values <- batch(sma, prices)
+
+# Streaming: the same indicator, fed one observation at a time in O(1).
+rsi <- Rsi(14)
+for (price in prices) {
+  v <- update(rsi, price) # NaN during warmup
+  if (!is.na(v) && v > 70) message("overbought")
+}
+
+# Multi-output indicators return a named vector (NA while warming up).
+macd <- MacdIndicator(12, 26, 9)
+update(macd, 42) # c(macd = NA, signal = NA, histogram = NA)
+```
+
+`batch(ind, prices)` and feeding the same prices through `update()` produce
+identical values — the equivalence is enforced by the test suite. Candle-input
+indicators take the OHLCV fields plus a timestamp, e.g.
+`update(atr, open, high, low, close, volume, timestamp)`. The native handle is
+freed automatically when the object is garbage-collected.
+
+## Documentation
+
+The full indicator catalogue, guides, quickstarts, and API reference live in the
+main repository and documentation site:
+
+- **Repository & full indicator list:** <https://github.com/wickra-lib/wickra>
+- **Docs** (quickstarts, cookbook, TA-Lib migration): <https://docs.wickra.org>
+- **Runnable examples:** [`examples/r/`](https://github.com/wickra-lib/wickra/tree/main/examples/r)
+
+Wickra ships native bindings for Python, Node.js, WebAssembly and Rust, plus a
+C ABI hub that any C-capable language (C, C++, C#, Go, Java, R) links against —
+all exposing the same indicators from the shared, `unsafe`-forbidden Rust core.
+
+## Disclaimer
+
+Wickra is an indicator toolkit, not a trading system. The values it computes are
+deterministic transforms of the input data — they are not financial advice and
+do not predict the market. Any use in a live trading context is at your own risk.
+The library is provided **as is**, without warranty of any kind.
+
+## License
+
+Licensed under either of [Apache-2.0](https://github.com/wickra-lib/wickra/blob/main/LICENSE-APACHE)
+or [MIT](https://github.com/wickra-lib/wickra/blob/main/LICENSE-MIT) at your option.

bindings/r/configure.win

@@ -0,0 +1,17 @@
+#!/bin/sh
+# Windows build: the package compiles to wickra.dll, which would collide with the
+# C ABI's own wickra.dll (the loader would resolve the import to the package
+# itself). Stage a renamed copy, wickra_abi.dll, into src/ and build a mingw
+# import library that references it by that name (objdump + dlltool, both shipped
+# with Rtools — no gendef/pexports needed). install.libs.R then bundles the DLL.
+set -e
+: "${WICKRA_LIB_DIR:?set WICKRA_LIB_DIR to the directory containing wickra.dll}"
+cp "${WICKRA_LIB_DIR}/wickra.dll" src/wickra_abi.dll
+{
+  echo 'LIBRARY wickra_abi.dll'
+  echo 'EXPORTS'
+  objdump -p src/wickra_abi.dll | awk '/\[ *[0-9]+\]/ {print $NF}' | grep '^wickra_'
+} > src/wickra_abi.def
+dlltool --input-def src/wickra_abi.def --dllname wickra_abi.dll \
+  --output-lib src/libwickra_abi.dll.a
+exit 0

bindings/r/man/AbandonedBaby.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{AbandonedBaby}
+\alias{AbandonedBaby}
+\title{AbandonedBaby indicator}
+\usage{
+AbandonedBaby()
+}
+\description{
+AbandonedBaby indicator
+}
+\keyword{internal}

bindings/r/man/Abcd.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{Abcd}
+\alias{Abcd}
+\title{Abcd indicator}
+\usage{
+Abcd()
+}
+\description{
+Abcd indicator
+}
+\keyword{internal}

bindings/r/man/AbsoluteBreadthIndex.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{AbsoluteBreadthIndex}
+\alias{AbsoluteBreadthIndex}
+\title{AbsoluteBreadthIndex indicator}
+\usage{
+AbsoluteBreadthIndex()
+}
+\description{
+AbsoluteBreadthIndex indicator
+}
+\keyword{internal}

bindings/r/man/AccelerationBands.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{AccelerationBands}
+\alias{AccelerationBands}
+\title{AccelerationBands indicator}
+\usage{
+AccelerationBands(period, factor)
+}
+\description{
+AccelerationBands indicator
+}
+\keyword{internal}

bindings/r/man/AcceleratorOscillator.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{AcceleratorOscillator}
+\alias{AcceleratorOscillator}
+\title{AcceleratorOscillator indicator}
+\usage{
+AcceleratorOscillator(ao_fast, ao_slow, signal_period)
+}
+\description{
+AcceleratorOscillator indicator
+}
+\keyword{internal}

bindings/r/man/AdOscillator.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{AdOscillator}
+\alias{AdOscillator}
+\title{AdOscillator indicator}
+\usage{
+AdOscillator()
+}
+\description{
+AdOscillator indicator
+}
+\keyword{internal}

bindings/r/man/AdVolumeLine.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{AdVolumeLine}
+\alias{AdVolumeLine}
+\title{AdVolumeLine indicator}
+\usage{
+AdVolumeLine()
+}
+\description{
+AdVolumeLine indicator
+}
+\keyword{internal}

bindings/r/man/AdaptiveCci.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{AdaptiveCci}
+\alias{AdaptiveCci}
+\title{AdaptiveCci indicator}
+\usage{
+AdaptiveCci(period)
+}
+\description{
+AdaptiveCci indicator
+}
+\keyword{internal}

bindings/r/man/AdaptiveCycle.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{AdaptiveCycle}
+\alias{AdaptiveCycle}
+\title{AdaptiveCycle indicator}
+\usage{
+AdaptiveCycle()
+}
+\description{
+AdaptiveCycle indicator
+}
+\keyword{internal}

bindings/r/man/AdaptiveLaguerreFilter.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{AdaptiveLaguerreFilter}
+\alias{AdaptiveLaguerreFilter}
+\title{AdaptiveLaguerreFilter indicator}
+\usage{
+AdaptiveLaguerreFilter(period)
+}
+\description{
+AdaptiveLaguerreFilter indicator
+}
+\keyword{internal}

bindings/r/man/AdaptiveRsi.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{AdaptiveRsi}
+\alias{AdaptiveRsi}
+\title{AdaptiveRsi indicator}
+\usage{
+AdaptiveRsi(period)
+}
+\description{
+AdaptiveRsi indicator
+}
+\keyword{internal}

bindings/r/man/Adl.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{Adl}
+\alias{Adl}
+\title{Adl indicator}
+\usage{
+Adl()
+}
+\description{
+Adl indicator
+}
+\keyword{internal}

bindings/r/man/AdvanceBlock.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{AdvanceBlock}
+\alias{AdvanceBlock}
+\title{AdvanceBlock indicator}
+\usage{
+AdvanceBlock()
+}
+\description{
+AdvanceBlock indicator
+}
+\keyword{internal}

bindings/r/man/AdvanceDecline.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{AdvanceDecline}
+\alias{AdvanceDecline}
+\title{AdvanceDecline indicator}
+\usage{
+AdvanceDecline()
+}
+\description{
+AdvanceDecline indicator
+}
+\keyword{internal}

bindings/r/man/AdvanceDeclineRatio.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{AdvanceDeclineRatio}
+\alias{AdvanceDeclineRatio}
+\title{AdvanceDeclineRatio indicator}
+\usage{
+AdvanceDeclineRatio()
+}
+\description{
+AdvanceDeclineRatio indicator
+}
+\keyword{internal}

bindings/r/man/Adx.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{Adx}
+\alias{Adx}
+\title{Adx indicator}
+\usage{
+Adx(period)
+}
+\description{
+Adx indicator
+}
+\keyword{internal}

bindings/r/man/Adxr.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{Adxr}
+\alias{Adxr}
+\title{Adxr indicator}
+\usage{
+Adxr(period)
+}
+\description{
+Adxr indicator
+}
+\keyword{internal}

bindings/r/man/Alligator.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{Alligator}
+\alias{Alligator}
+\title{Alligator indicator}
+\usage{
+Alligator(jaw_period, teeth_period, lips_period)
+}
+\description{
+Alligator indicator
+}
+\keyword{internal}

bindings/r/man/Alma.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{Alma}
+\alias{Alma}
+\title{Alma indicator}
+\usage{
+Alma(period, offset, sigma)
+}
+\description{
+Alma indicator
+}
+\keyword{internal}

bindings/r/man/Alpha.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{Alpha}
+\alias{Alpha}
+\title{Alpha indicator}
+\usage{
+Alpha(period, risk_free)
+}
+\description{
+Alpha indicator
+}
+\keyword{internal}

bindings/r/man/AmihudIlliquidity.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{AmihudIlliquidity}
+\alias{AmihudIlliquidity}
+\title{AmihudIlliquidity indicator}
+\usage{
+AmihudIlliquidity(period)
+}
+\description{
+AmihudIlliquidity indicator
+}
+\keyword{internal}

bindings/r/man/AnchoredRsi.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{AnchoredRsi}
+\alias{AnchoredRsi}
+\title{AnchoredRsi indicator}
+\usage{
+AnchoredRsi()
+}
+\description{
+AnchoredRsi indicator
+}
+\keyword{internal}

bindings/r/man/AnchoredVwap.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{AnchoredVwap}
+\alias{AnchoredVwap}
+\title{AnchoredVwap indicator}
+\usage{
+AnchoredVwap()
+}
+\description{
+AnchoredVwap indicator
+}
+\keyword{internal}

bindings/r/man/AndrewsPitchfork.Rd

@@ -0,0 +1,12 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/indicators.R
+\name{AndrewsPitchfork}
+\alias{AndrewsPitchfork}
+\title{AndrewsPitchfork indicator}
+\usage{
+AndrewsPitchfork(strength)
+}
+\description{
+AndrewsPitchfork indicator
+}
+\keyword{internal}