kingchenc
b7ef63400d
Adds an R binding (`bindings/r`) over the C ABI hub — the third language stecker after C# and Go, reaching the hub through R's native `.Call` interface (not extendr). ## What's here - **`bindings/r`** — an R package exposing all 514 indicators as constructors that return a `wickra_indicator` object with generic `update`/`batch`/`reset` methods. The C glue (`src/wickra.c`) and R wrappers (`R/indicators.R`) are generated from `bindings/c/include/wickra.h` (same archetype taxonomy as the C#/Go generators: scalar/batch, multi-output, bars, profile, profile-values, array-input). The opaque handle is an R external pointer freed by a registered finalizer; multi-output returns a named vector (`NA` at warmup), bars a matrix, profiles a list. - **`examples/r`** — the full example suite mirroring C/C#/Go: streaming, backtest, multi_timeframe, parallel_assets (`mclapply`), three strategies, and `fetch_btcusdt`/`live_binance`. - **CI** — an `r` job builds the C ABI library, installs the package, runs the `testthat` suite and the offline examples on Linux, macOS and Windows (`R CMD check` is clean: 0 warnings, 0 notes). - **Docs** — R added to the README languages table, project layout, building/testing, CONTRIBUTING binding table + regenerate note, ARCHITECTURE, examples index, issue/PR templates, the About-description template, and the other binding READMEs. ## Linking / distribution The package compiles a thin `.Call` glue layer against the prebuilt C ABI library (header via `WICKRA_INCLUDE_DIR`, library via `WICKRA_LIB_DIR`). On Windows the package's own `wickra.dll` would collide with the C ABI's `wickra.dll`, so `configure.win` stages a renamed copy (`wickra_abi.dll`) and builds an import library referencing it; `install.libs.R` bundles the DLL and `.onLoad` puts it on the load path. On Linux/macOS the rpath locates the shared library. No `release.yml` change — R is distributed via r-universe / source install (gated). No Rust crate or `Cargo.toml` change — the R package is standalone and additive.
25 lines
1.1 KiB
R
25 lines
1.1 KiB
R
# Run SMA(20) batch over a panel of assets, serial vs parallel::mclapply, with
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# the speedup. mclapply forks on Unix; on Windows it runs serially.
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library(wickra)
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source("_common.R")
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args <- commandArgs(trailingOnly = TRUE)
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assets <- if (length(args) >= 1) as.integer(args[1]) else 200L
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bars <- if (length(args) >= 2) as.integer(args[2]) else 5000L
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panel <- lapply(seq_len(assets), function(a) synthetic_prices(bars, start = 50 + a * 0.1))
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run_one <- function(p) { s <- Sma(20); r <- batch(s, p); r[length(r)] }
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t0 <- Sys.time(); invisible(vapply(panel, run_one, numeric(1)))
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serial <- as.numeric(Sys.time() - t0, units = "secs")
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# mclapply forks on Unix; Windows has no fork, so it must run on a single core.
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cores <- if (.Platform$OS.type == "windows") 1L else max(1L, parallel::detectCores())
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t0 <- Sys.time(); invisible(parallel::mclapply(panel, run_one, mc.cores = cores))
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par <- as.numeric(Sys.time() - t0, units = "secs")
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cat(sprintf("%d assets x %d bars, SMA(20) batch:\n", assets, bars))
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cat(sprintf(" serial %8.1f ms\n", serial * 1000))
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cat(sprintf(" parallel %8.1f ms (%.1fx speedup, %d cores)\n",
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par * 1000, serial / max(par, 1e-9), cores))
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