Bump version from 0.6.0 to 0.6.1.

Co-authored-by: Cursor <cursoragent@cursor.com>

README.md

@@ -13,6 +13,7 @@ Built on top of [pdmt5](https://github.com/dceoy/pdmt5), a pandas-based data han
 - **Comprehensive data access**: Rates, ticks, account info, symbols, orders, positions, and trading history
 - **Flexible timeframes**: Named timeframes (M1, H1, D1, etc.) and numeric values
 - **Connection management**: Optional credentials, server, and timeout configuration
+- **SQLite rate loading**: Load mt5cli-managed rate tables/views for offline workflows
 
 ## Installation
 
@@ -50,28 +51,33 @@ python -m mt5cli -o account.csv account-info
 
 ## Commands
 
-| Command            | Description                                                                                                  |
-| ------------------ | ------------------------------------------------------------------------------------------------------------ |
-| `rates-from`       | Export rates from a start date                                                                               |
-| `rates-from-pos`   | Export rates from a start position                                                                           |
-| `rates-range`      | Export rates for a date range                                                                                |
-| `ticks-from`       | Export ticks from a start date                                                                               |
-| `ticks-range`      | Export ticks for a date range                                                                                |
-| `account-info`     | Export account information                                                                                   |
-| `terminal-info`    | Export terminal information                                                                                  |
-| `version`          | Export MetaTrader 5 version information                                                                      |
-| `last-error`       | Export the last error information                                                                            |
-| `symbols`          | Export symbol list                                                                                           |
-| `symbol-info`      | Export symbol details                                                                                        |
-| `symbol-info-tick` | Export the last tick for a symbol                                                                            |
-| `market-book`      | Export market depth (order book)                                                                             |
-| `orders`           | Export active orders                                                                                         |
-| `positions`        | Export open positions                                                                                        |
-| `history-orders`   | Export historical orders                                                                                     |
-| `history-deals`    | Export historical deals                                                                                      |
-| `order-check`      | Check funds sufficiency for a trade request                                                                  |
-| `order-send`       | Send a trade request to the trade server (`--yes` required)                                                  |
-| `collect-history`  | Bundle rates, ticks, history-orders, and history-deals for one or more symbols into a single SQLite database |
+| Command                | Description                                                                                                  |
+| ---------------------- | ------------------------------------------------------------------------------------------------------------ |
+| `rates-from`           | Export rates from a start date                                                                               |
+| `rates-from-pos`       | Export rates from a start position                                                                           |
+| `latest-rates`         | Export latest rates from a start position                                                                    |
+| `rates-range`          | Export rates for a date range                                                                                |
+| `ticks-from`           | Export ticks from a start date                                                                               |
+| `ticks-range`          | Export ticks for a date range                                                                                |
+| `ticks-recent`         | Export ticks from a recent trailing window                                                                   |
+| `account-info`         | Export account information                                                                                   |
+| `terminal-info`        | Export terminal information                                                                                  |
+| `version`              | Export MetaTrader 5 version information                                                                      |
+| `last-error`           | Export the last error information                                                                            |
+| `symbols`              | Export symbol list                                                                                           |
+| `symbol-info`          | Export symbol details                                                                                        |
+| `symbol-info-tick`     | Export the last tick for a symbol                                                                            |
+| `minimum-margins`      | Export minimum-volume buy and sell margin requirements                                                       |
+| `market-book`          | Export market depth (order book)                                                                             |
+| `orders`               | Export active orders                                                                                         |
+| `positions`            | Export open positions                                                                                        |
+| `history-orders`       | Export historical orders                                                                                     |
+| `history-deals`        | Export historical deals                                                                                      |
+| `recent-history-deals` | Export historical deals from a recent trailing window                                                        |
+| `mt5-summary`          | Export terminal/account status summary                                                                       |
+| `order-check`          | Check funds sufficiency for a trade request                                                                  |
+| `order-send`           | Send a trade request to the trade server (`--yes` required)                                                  |
+| `collect-history`      | Bundle rates, ticks, history-orders, and history-deals for one or more symbols into a single SQLite database |
 
 Use `order-check` to validate a request payload before running `order-send --yes`.
 
@@ -127,6 +133,31 @@ update_history_with_config(
 - **`update_history`**: incremental append based on existing SQLite `MAX(time)` per symbol (and timeframe for rates); account-level deals use a separate cursor when `include_account_events=True`.
 - **`rates` table**: normalized storage with `symbol` and `timeframe` columns.
 - **Rate compatibility views**: mt5cli manages all `rate_*` views. Naming is `rate_<symbol>__<timeframe>` when a symbol has one timeframe, otherwise `rate_<symbol>__<granularity>_<timeframe>` (for example `rate_EURUSD__M1_1`). Stale `rate_*` views are dropped and recreated when rates change for offline tools such as mteor optimize.
+- **Rate view resolution**: use `resolve_rate_view_name()` / `resolve_rate_view_names()` to map symbols and granularities to existing SQLite compatibility views without creating databases. Both accept `None` (or a missing path) and return deterministic default names unless `require_existing=True`.
+- **Rate view loading**: use `load_rate_data()` / `load_rate_data_from_connection()` to load a SQLite rate table or view into a `DatetimeIndex` DataFrame.
+- **Multi-series rate loading**: use `build_rate_targets()` to build neutral `RateTarget(symbol, timeframe)` pairs, `resolve_rate_tables()` to map them to table/view names (pass `require_existing=True` for strict resolution), and `load_rate_series_from_sqlite()` to load them into a mapping keyed by `(symbol, integer timeframe)`. The loader requires existing managed views unless `explicit_tables` is supplied, and rejects duplicate `(symbol, timeframe)` targets.
+- **Multi-account latest rates**: use `collect_latest_rates_for_accounts()` with `AccountSpec` to read the latest bars for several account groups, merged into a `(symbol, integer timeframe)` mapping. For long-running pollers, `collect_latest_rates_for_accounts_with_retries()` adds bounded exponential backoff that retries only `pdmt5.Mt5TradingError` / `pdmt5.Mt5RuntimeError` and re-raises once `retry_count` is exhausted.
+- **Latest closed bars**: use `collect_latest_closed_rates_for_accounts()` when downstream logic must exclude the still-forming current bar. It fetches `count + 1` bars at `start_pos=0`, drops the last row with `drop_forming_rate_bar()`, and validates each series is non-empty. `collect_latest_closed_rates_by_granularity()` returns the same data keyed by `(symbol, granularity_name)` such as `("EURUSD", "M1")`.
+
+```python
+from mt5cli import AccountSpec, collect_latest_closed_rates_by_granularity
+
+rates = collect_latest_closed_rates_by_granularity(
+    [AccountSpec(symbols=["EURUSD", "GBPUSD"], login=12345)],
+    ["M1", "H1"],
+    count=500,
+    retry_count=3,
+)
+eurusd_m1 = rates["EURUSD", "M1"]  # closed bars only
+```
+
+- **Credential resolution**: use `resolve_account_spec()` / `resolve_account_specs()` to merge explicit override values over `AccountSpec` fields and expand `${ENV_VAR}` placeholders (via `substitute_env_placeholders()`), raising `ValueError` for missing variables. This keeps secrets out of plan/config files without coupling to any strategy code.
+- **Throttled history updates**: use `ThrottledHistoryUpdater` to wrap `update_history()` with a minimum `interval_seconds` between successful runs (monotonic clock). Call `should_update()` / `update(client, symbols)` from an application loop; errors propagate by default, or pass `suppress_errors=True` to swallow recoverable `Mt5*Error`, `sqlite3.Error`, `ValueError`, `OSError`, and MT5 client capability errors for history API methods without advancing the throttle (other `AttributeError` / `TypeError` values always propagate).
+- **Trading session helpers**: use `mt5_trading_session()` for a trading-capable `pdmt5.Mt5TradingClient` that initializes/logs in via `Mt5Config.path` and always shuts down safely. Pair with `detect_position_side()`, `calculate_margin_and_volume()`, and `determine_order_limits()` for generic position and sizing utilities. The read-only `mt5_session()` / `Mt5CliClient` SDK is unchanged.
+- **Granularity-keyed rate loading**: `load_rate_series_by_granularity()` builds targets with `build_rate_targets()`, loads them with `load_rate_series_from_sqlite()`, and returns a mapping keyed by `(symbol | None, granularity_name)` such as `("EURUSD", "M1")` to reduce downstream boilerplate.
+- **MT5 session helper**: use the `mt5_session()` context manager to attach to (or, when `Mt5Config.path` is set, launch) an MT5 terminal, log in, and yield a connected `Mt5CliClient` that shuts down on exit.
+- **SQLite export helpers**: use `export_dataframe_to_sqlite()` for append mode, optional index export, and post-write deduplication by key columns.
+- **Recent ticks and margins**: `recent_ticks()` and `minimum_margins()` SDK helpers (and matching CLI commands) cover common downstream read-only queries.
 
 ## Requirements
 
@@ -134,6 +165,63 @@ update_history_with_config(
 - Windows OS (MetaTrader 5 requirement)
 - MetaTrader 5 platform installed
 
+### Migration note for mteor
+
+Replace local MT5 lifecycle and trading helper code with mt5cli imports:
+
+```python
+# Before (local mteor helpers)
+# with local_mt5_trading_session(config) as client:
+#     side = local_detect_position_side(client, symbol)
+#     sizing = local_calculate_margin_and_volume(client, symbol, unit_ratio, preserved_ratio)
+#     limits = local_determine_order_limits(client, symbol, side, sl_ratio, tp_ratio)
+
+# After (mt5cli shared layer)
+from pdmt5 import Mt5Config
+from mt5cli import (
+    calculate_margin_and_volume,
+    detect_position_side,
+    determine_order_limits,
+    mt5_trading_session,
+)
+
+with mt5_trading_session(
+    Mt5Config(path=terminal_path, login=login), retry_count=2
+) as client:
+    side = detect_position_side(client, symbol)
+    sizing = calculate_margin_and_volume(
+        client, symbol, unit_margin_ratio=0.5, preserved_margin_ratio=0.2
+    )
+    if side is not None:
+        limits = determine_order_limits(
+            client,
+            symbol,
+            side,
+            stop_loss_limit_ratio=0.01,
+            take_profit_limit_ratio=0.02,
+        )
+```
+
+Throttled history updates use a separate read-only session:
+
+```python
+from pdmt5 import Mt5Config, Mt5DataClient
+
+from mt5cli import ThrottledHistoryUpdater
+
+updater = ThrottledHistoryUpdater(
+    output="history.db", interval_seconds=60, suppress_errors=True
+)
+client = Mt5DataClient(config=Mt5Config(login=login))
+client.initialize_and_login_mt5()
+try:
+    updater.update(client, ["EURUSD"])
+finally:
+    client.shutdown()
+```
+
+Read-only collectors can keep using `mt5_session()` and `Mt5CliClient` without changes.
+
 ## Development
 
 ```bash

docs/api/history.md

@@ -129,3 +129,101 @@ when required columns are missing.
 The `update_history` SDK path uses the same base tables and optional
 `cash_events` / `positions_reconstructed` views. It additionally maintains
 `rate_<symbol>__<timeframe>` compatibility views when `create_rate_views=True`.
+
+### Rate view resolution
+
+Downstream tools can resolve mt5cli-managed compatibility view names from an
+existing SQLite history database without creating files or guessing naming
+schemes:
+
+```python
+from pathlib import Path
+
+from mt5cli.history import resolve_rate_view_name, resolve_rate_view_names
+
+# Single symbol and granularity
+view = resolve_rate_view_name(Path("history.db"), "EURUSD", "M1")
+
+# Batch resolution in row-major order
+views = resolve_rate_view_names(
+    Path("history.db"),
+    ["EURUSD", "GBPUSD"],
+    ["M1", "H1"],
+)
+```
+
+Resolution rules:
+
+- Returns `rate_<symbol>__<timeframe>` when a symbol stores one timeframe.
+- Returns `rate_<symbol>__<granularity>_<timeframe>` when multiple timeframes
+  are stored for the same symbol.
+- When multiple naming candidates apply, prefers an existing managed
+  `rate_*__*` view from the candidate list.
+- Falls back to single-timeframe naming when the database path is missing or
+  `rates` metadata is unavailable.
+- Pass `require_existing=True` to raise `ValueError` instead of returning a
+  best-guess name when the database or view is missing.
+- Accepts either a SQLite path or an open `sqlite3.Connection`.
+
+### Rate data loading
+
+Use `load_rate_data()` to load a table or view from a SQLite path, or
+`load_rate_data_from_connection()` when you already have a connection:
+
+```python
+from pathlib import Path
+
+from mt5cli import load_rate_data
+from mt5cli.history import resolve_rate_view_name
+
+view = resolve_rate_view_name(Path("history.db"), "EURUSD", "M1", require_existing=True)
+rates = load_rate_data(Path("history.db"), view, count=1000)
+```
+
+The loader accepts close-based OHLC rate data or tick-like bid/ask data. It
+validates that `time` exists, parses timestamps with pandas, and returns a
+DataFrame indexed by ascending `DatetimeIndex` named `time`.
+
+### Multi-series rate loading
+
+For loading many rate series at once, build neutral `RateTarget` pairs and load
+them from SQLite in one call. View names are resolved via the same
+compatibility-view rules, or you can pass `explicit_tables` to bypass resolution:
+
+```python
+from pathlib import Path
+
+from mt5cli import build_rate_targets, load_rate_series_from_sqlite
+
+targets = build_rate_targets(["EURUSD", "GBPUSD"], ["M1", "H1"])
+series = load_rate_series_from_sqlite(Path("history.db"), targets, count=1000)
+frame = series["EURUSD", 1]  # keyed by (symbol, integer timeframe)
+```
+
+- `build_rate_targets()` returns `RateTarget(symbol, timeframe)` pairs in
+  row-major order, normalizing timeframe names such as `"M1"` to their integer
+  values; set `allow_missing_symbol=True` to address series solely by
+  `explicit_tables` (targets carry `symbol=None`).
+- `resolve_rate_tables()` maps targets to table or view names and validates that
+  any `explicit_tables` count matches the target count. Pass
+  `require_existing=True` to raise `ValueError` instead of returning a
+  best-guess name when the database or managed view is missing. When
+  `explicit_tables` is provided, names are returned as-is and
+  `require_existing` is ignored.
+- `load_rate_series_from_sqlite()` returns a mapping keyed by
+  `(symbol, integer timeframe)`. Unless `explicit_tables` is supplied, it
+  requires existing managed `rate_*` compatibility views and raises
+  `ValueError` when they are missing. Duplicate `(symbol, timeframe)` targets
+  are rejected.
+- `load_rate_series_by_granularity()` is a thin wrapper that builds the targets,
+  loads the series, and rekeys the result by granularity name to avoid
+  converting integer timeframes downstream:
+
+  ```python
+  from mt5cli import load_rate_series_by_granularity
+
+  series = load_rate_series_by_granularity(
+      "history.db", ["EURUSD"], ["M1", "H1"], count=1000
+  )
+  frame = series["EURUSD", "M1"]  # keyed by (symbol | None, granularity_name)
+  ```

docs/api/index.md

@@ -18,6 +18,10 @@ Utility module providing constants, enums, Click parameter types, and helper fun
 
 Programmatic SDK for read-only MetaTrader 5 data collection. Returns pandas DataFrames and provides `collect_history` for SQLite bulk collection.
 
+### [Trading](trading.md)
+
+Trading-capable session management and operational helpers built on `pdmt5.Mt5TradingClient`. Complements the read-only SDK without changing existing `Mt5CliClient` behavior.
+
 ### [History Collection (SQLite)](history.md)
 
 SQLite storage helpers for the `collect-history` command schema, incremental updates, deduplication, indexes, and optional views.
@@ -28,8 +32,9 @@ The package follows a simple architecture built on top of pdmt5:
 
 1. **CLI Layer** (`cli.py`): Typer application with subcommands that delegate to the SDK and export results.
 2. **SDK Layer** (`sdk.py`): Read-only data access functions, `Mt5CliClient`, and `collect_history` orchestration.
-3. **Utils Layer** (`utils.py`): Constants, enums, custom Click parameter types, parsing helpers, and format detection/export utilities.
-4. **Data Layer** (via `pdmt5`): Uses `Mt5DataClient` and `Mt5Config` from the pdmt5 package for all MetaTrader 5 data access.
+3. **Trading Layer** (`trading.py`): Trading-capable sessions and operational helpers on `Mt5TradingClient`.
+4. **Utils Layer** (`utils.py`): Constants, enums, custom Click parameter types, parsing helpers, and format detection/export utilities.
+5. **Data Layer** (via `pdmt5`): Uses `Mt5DataClient`, `Mt5TradingClient`, and `Mt5Config` from the pdmt5 package for MetaTrader 5 access.
 
 ## Usage Guidelines
 
@@ -65,12 +70,18 @@ from datetime import UTC, datetime
 from pathlib import Path
 
 from mt5cli import (
+    Dataset,
+    IfExists,
     Mt5CliClient,
     collect_history,
     copy_rates_range,
     detect_format,
     export_dataframe,
+    export_dataframe_to_sqlite,
+    minimum_margins,
+    recent_ticks,
 )
+from mt5cli.history import resolve_rate_view_name
 
 # Fetch rates programmatically
 rates = copy_rates_range(
@@ -86,6 +97,20 @@ fmt = detect_format(Path("output.parquet"))  # Returns "parquet"
 # Export a DataFrame
 export_dataframe(rates, Path("output.csv"), "csv")
 
+# Append to SQLite with deduplication
+export_dataframe_to_sqlite(
+    rates,
+    Path("history.db"),
+    "rates",
+    if_exists=IfExists.APPEND,
+    deduplicate_on=("symbol", "timeframe", "time"),
+)
+
+# Resolve rate compatibility views and fetch recent ticks
+view = resolve_rate_view_name(Path("history.db"), "EURUSD", "M1")
+ticks = recent_ticks("EURUSD", seconds=300)
+margins = minimum_margins("EURUSD")
+
 # Collect history into SQLite
 collect_history(
     Path("history.db"),

docs/api/sdk.md

@@ -1,3 +1,114 @@
 # SDK Module
 
 ::: mt5cli.sdk
+
+## Resilient multi-account orchestration
+
+The SDK ships strategy-agnostic helpers for building long-running collectors on
+top of the read-only client. None of them depend on a particular trading
+application.
+
+### Retrying transient rate collection
+
+`collect_latest_rates_for_accounts_with_retries()` wraps
+`collect_latest_rates_for_accounts()` with bounded exponential backoff. Only
+`pdmt5.Mt5TradingError` and `pdmt5.Mt5RuntimeError` are retried; the final
+failure is re-raised once `retry_count` is exhausted.
+
+```python
+from mt5cli import AccountSpec, collect_latest_rates_for_accounts_with_retries
+
+accounts = [AccountSpec(symbols=["EURUSD"], login=12345)]
+rates = collect_latest_rates_for_accounts_with_retries(
+    accounts,
+    ["M1", "H1"],
+    count=500,
+    retry_count=3,
+    backoff_base=2,  # sleeps 2s, 4s, 8s between attempts
+)
+```
+
+### Latest closed rate bars
+
+MetaTrader 5 `start_pos=0` includes the still-forming current bar as the last
+row. `collect_latest_closed_rates_for_accounts()` fetches `count + 1` bars,
+drops that row with `drop_forming_rate_bar()`, and validates each series is
+non-empty. Use `collect_latest_closed_rates_by_granularity()` when callers
+prefer keys such as `("EURUSD", "M1")` instead of integer timeframes.
+
+```python
+from mt5cli import AccountSpec, collect_latest_closed_rates_by_granularity
+
+rates = collect_latest_closed_rates_by_granularity(
+    [AccountSpec(symbols=["EURUSD"], login=12345)],
+    ["M1", "H1"],
+    count=500,
+    retry_count=3,
+)
+closed_m1 = rates["EURUSD", "M1"]
+```
+
+### Resolving credentials and `${ENV_VAR}` placeholders
+
+`resolve_account_spec()` / `resolve_account_specs()` merge explicit override
+values over `AccountSpec` fields and expand `${ENV_VAR}` placeholders, keeping
+secrets out of plan/config files. A missing environment variable raises
+`ValueError`.
+
+```python
+import os
+
+from mt5cli import AccountSpec, resolve_account_specs
+
+os.environ["MT5_LOGIN"] = "12345"
+os.environ["MT5_PASSWORD"] = "secret"
+accounts = [
+    AccountSpec(symbols=["EURUSD"], login="${MT5_LOGIN}", password="${MT5_PASSWORD}")
+]
+
+resolved = resolve_account_specs(accounts, server="Broker-Demo")
+# resolved[0].login == "12345", resolved[0].server == "Broker-Demo"
+```
+
+### Throttled incremental history updates
+
+`ThrottledHistoryUpdater` wraps `update_history()` with a minimum interval
+between successful runs (using a monotonic clock), so an application loop can
+call it every iteration without over-fetching.
+
+```python
+from pdmt5 import Mt5Config, Mt5DataClient
+
+from mt5cli import Dataset, ThrottledHistoryUpdater
+
+updater = ThrottledHistoryUpdater(
+    output="history.db",
+    datasets={Dataset.rates},
+    timeframes=["M1"],
+    interval_seconds=60,  # <= 0 updates on every call
+)
+
+client = Mt5DataClient(config=Mt5Config(login=12345))
+client.initialize_and_login_mt5()
+try:
+    while True:
+        updater.update(client, ["EURUSD", "GBPUSD"])  # no-op until 60s elapse
+        # ... do other work; break when shutting down ...
+finally:
+    client.shutdown()
+```
+
+By default recoverable errors (`Mt5TradingError`, `Mt5RuntimeError`,
+`sqlite3.Error`, `ValueError`, `OSError`, and MT5 client capability
+`AttributeError` / `TypeError` for history API methods) propagate so the caller
+controls logging; pass `suppress_errors=True` to swallow them and return
+`False` without advancing the throttle. Other `AttributeError` / `TypeError`
+values always propagate. Input validation (`_resolve_update_history_request`)
+runs before any MT5 or SQLite calls, but when `suppress_errors=True` the
+resulting `ValueError` is suppressed along with other recoverable errors.
+
+## Trading-capable sessions
+
+For order placement and trading calculations, use the dedicated
+[Trading module](trading.md). The read-only `Mt5CliClient` and `mt5_session()`
+helpers in this module are unchanged.

docs/api/trading.md

@@ -0,0 +1,70 @@
+# Trading Module
+
+::: mt5cli.trading
+
+## Trading-capable MT5 sessions
+
+`mt5_trading_session()` complements the read-only `mt5_session()` helper in
+`sdk.py`. It yields a connected `pdmt5.Mt5TradingClient`, uses
+`Mt5Config.path` to launch the terminal when configured, and always calls
+`shutdown()` on exit.
+
+```python
+from pdmt5 import Mt5Config
+
+from mt5cli import mt5_trading_session
+
+with mt5_trading_session(
+    Mt5Config(path=r"C:\Program Files\MetaTrader 5\terminal64.exe", login=12345),
+    retry_count=2,
+) as client:
+    positions = client.positions_get_as_df(symbol="EURUSD")
+```
+
+The read-only `Mt5CliClient` / `mt5_session()` API is unchanged.
+
+## Operational trading helpers
+
+These helpers are strategy-agnostic and do not depend on signal detection,
+betting logic, or scheduling code in downstream applications.
+
+```python
+from mt5cli import (
+    calculate_margin_and_volume,
+    detect_position_side,
+    determine_order_limits,
+)
+
+side = detect_position_side(client, "EURUSD")
+sizing = calculate_margin_and_volume(
+    client,
+    "EURUSD",
+    unit_margin_ratio=0.5,
+    preserved_margin_ratio=0.2,
+)
+limits = determine_order_limits(
+    client,
+    "EURUSD",
+    side="long",
+    stop_loss_limit_ratio=0.01,
+    take_profit_limit_ratio=0.02,
+)
+```
+
+Protective ratios must satisfy `0 <= ratio < 1`; `0` omits that level.
+`calculate_margin_and_volume()` clamps negative `margin_free` to `0.0`
+before sizing.
+
+## Migration from mteor-local helpers
+
+| mteor-local concern                                      | mt5cli replacement                              |
+| -------------------------------------------------------- | ----------------------------------------------- |
+| Manual terminal spawn/kill around trading code           | `mt5_trading_session()`                         |
+| Local position-side detection                            | `detect_position_side()`                        |
+| Local margin/volume sizing                               | `calculate_margin_and_volume()`                 |
+| Local SL/TP price derivation                             | `determine_order_limits()`                      |
+| Throttled SQLite history loop with ad-hoc error handling | `ThrottledHistoryUpdater(suppress_errors=True)` |
+
+Keep read-only data collection on `mt5_session()` / `Mt5CliClient`; use
+`mt5_trading_session()` only where order placement or trading calculations are
+required.

docs/index.md

@@ -13,6 +13,7 @@ mt5cli is a CLI application that exports MetaTrader 5 trading data to multiple f
 - **Comprehensive data access**: Rates, ticks, account info, symbols, orders, positions, and trading history
 - **Flexible timeframes**: Named timeframes (M1, H1, D1, etc.) and numeric values
 - **Connection management**: Optional credentials, server, and timeout configuration
+- **SQLite rate loading**: Load mt5cli-managed rate tables/views for offline workflows
 
 ## Installation
 
@@ -22,13 +23,23 @@ pip install mt5cli
 
 ## Programmatic usage / SDK usage
 
-mt5cli can be used as a small Python SDK for read-only MetaTrader 5 data collection. SDK functions return pandas DataFrames without writing files. Use `export_dataframe` when you need to persist results.
+mt5cli can be used as a small Python SDK for read-only MetaTrader 5 data collection. SDK functions return pandas DataFrames without writing files. Use `export_dataframe` or `export_dataframe_to_sqlite` when you need to persist results.
 
 ```python
 from datetime import UTC, datetime
 from pathlib import Path
 
-from mt5cli import Mt5CliClient, collect_history, copy_rates_range, export_dataframe
+from mt5cli import (
+    Mt5CliClient,
+    collect_history,
+    copy_rates_range,
+    export_dataframe,
+    export_dataframe_to_sqlite,
+    load_rate_data,
+    minimum_margins,
+    recent_ticks,
+)
+from mt5cli.history import resolve_rate_view_name
 
 # One-off fetch with module-level helpers
 rates = copy_rates_range(
@@ -39,10 +50,21 @@ rates = copy_rates_range(
 )
 export_dataframe(rates, Path("rates.csv"), "csv")
 
+# Resolve SQLite rate compatibility views for downstream tools
+view = resolve_rate_view_name(Path("history.db"), "EURUSD", "M1", require_existing=True)
+offline_rates = load_rate_data(Path("history.db"), view, count=1000)
+
+# Recent tick window and minimum margin summary
+ticks = recent_ticks("EURUSD", seconds=300)
+margins = minimum_margins("EURUSD")
+
 # Reuse one MT5 connection for multiple calls
 with Mt5CliClient(login=12345, password="secret", server="Broker-Demo") as client:
     account = client.account_info()
     positions = client.positions()
+    latest = client.latest_rates("EURUSD", "M1", count=100)
+    summary = client.mt5_summary()
+    summary_table = client.mt5_summary_as_df()
 
 # Bulk SQLite collection (same behavior as the collect-history CLI command)
 collect_history(
@@ -58,6 +80,8 @@ collect_history(
 
 Timeframes, tick flags, and ISO 8601 date strings are accepted wherever noted in the SDK API.
 
+`Mt5CliClient.mt5_summary()` returns the SDK structured form as plain nested Python values. Use `Mt5CliClient.mt5_summary_as_df()` when you need a one-row DataFrame for export. The `mt5-summary` CLI command uses this tabular form, so nested terminal/account fields are JSON-encoded strings that are safe for CSV, JSON, Parquet, and SQLite output.
+
 ## Quick Start
 
 ```bash
@@ -88,14 +112,16 @@ mt5cli --login 12345 --password mypass --server MyBroker-Demo \
 | ---------------- | ---------------------------------- |
 | `rates-from`     | Export rates from a start date     |
 | `rates-from-pos` | Export rates from a start position |
+| `latest-rates`   | Export latest rates                |
 | `rates-range`    | Export rates for a date range      |
 
 ### Ticks
 
-| Command       | Description                    |
-| ------------- | ------------------------------ |
-| `ticks-from`  | Export ticks from a start date |
-| `ticks-range` | Export ticks for a date range  |
+| Command        | Description                         |
+| -------------- | ----------------------------------- |
+| `ticks-from`   | Export ticks from a start date      |
+| `ticks-range`  | Export ticks for a date range       |
+| `ticks-recent` | Export ticks from a trailing window |
 
 ### Information
 
@@ -108,18 +134,21 @@ mt5cli --login 12345 --password mypass --server MyBroker-Demo \
 | `symbols`          | Export symbol list                      |
 | `symbol-info`      | Export symbol details                   |
 | `symbol-info-tick` | Export the last tick for a symbol       |
+| `minimum-margins`  | Export minimum-volume margin summary    |
 | `market-book`      | Export market depth (order book)        |
 
 ### Trading
 
-| Command          | Description                                                 |
-| ---------------- | ----------------------------------------------------------- |
-| `orders`         | Export active orders                                        |
-| `positions`      | Export open positions                                       |
-| `history-orders` | Export historical orders                                    |
-| `history-deals`  | Export historical deals                                     |
-| `order-check`    | Check funds sufficiency for a trade request                 |
-| `order-send`     | Send a trade request to the trade server (`--yes` required) |
+| Command                | Description                                                 |
+| ---------------------- | ----------------------------------------------------------- |
+| `orders`               | Export active orders                                        |
+| `positions`            | Export open positions                                       |
+| `history-orders`       | Export historical orders                                    |
+| `history-deals`        | Export historical deals                                     |
+| `recent-history-deals` | Export historical deals from a trailing window              |
+| `mt5-summary`          | Export terminal/account status summary                      |
+| `order-check`          | Check funds sufficiency for a trade request                 |
+| `order-send`           | Send a trade request to the trade server (`--yes` required) |
 
 Use `order-check` to validate a request payload before running `order-send --yes`.
 

mkdocs.yml

@@ -58,6 +58,7 @@ nav:
       - Overview: api/index.md
       - CLI: api/cli.md
       - SDK: api/sdk.md
+      - Trading: api/trading.md
       - History Collection (SQLite): api/history.md
       - Utils: api/utils.md
 

mt5cli/__init__.py

@@ -2,11 +2,34 @@
 
 from importlib.metadata import version
 
+from .history import (
+    RateTarget,
+    build_rate_targets,
+    build_rate_view_name,
+    drop_forming_rate_bar,
+    load_rate_data,
+    load_rate_data_from_connection,
+    load_rate_series_by_granularity,
+    load_rate_series_from_sqlite,
+    resolve_history_datasets,
+    resolve_history_tick_flags,
+    resolve_history_timeframes,
+    resolve_rate_tables,
+    resolve_rate_view_name,
+    resolve_rate_view_names,
+)
 from .sdk import (
+    AccountSpec,
     Mt5CliClient,
+    ThrottledHistoryUpdater,
     account_info,
     build_config,
     collect_history,
+    collect_latest_closed_rates_by_granularity,
+    collect_latest_closed_rates_for_accounts,
+    collect_latest_rates,
+    collect_latest_rates_for_accounts,
+    collect_latest_rates_for_accounts_with_retries,
     copy_rates_from,
     copy_rates_from_pos,
     copy_rates_range,
@@ -15,9 +38,19 @@ from .sdk import (
     history_deals,
     history_orders,
     last_error,
+    latest_rates,
     market_book,
+    minimum_margins,
+    mt5_session,
+    mt5_summary,
+    mt5_summary_as_df,
     orders,
     positions,
+    recent_history_deals,
+    recent_ticks,
+    resolve_account_spec,
+    resolve_account_specs,
+    substitute_env_placeholders,
     symbol_info,
     symbol_info_tick,
     symbols,
@@ -28,31 +61,89 @@ from .sdk import (
 from .sdk import (
     version as mt5_version,
 )
-from .utils import Dataset, IfExists, detect_format, export_dataframe
+from .trading import (
+    calculate_margin_and_volume,
+    detect_position_side,
+    determine_order_limits,
+    mt5_trading_session,
+)
+from .utils import (
+    TICK_FLAG_MAP,
+    TIMEFRAME_MAP,
+    Dataset,
+    IfExists,
+    detect_format,
+    export_dataframe,
+    export_dataframe_to_sqlite,
+    parse_datetime,
+    parse_tick_flags,
+    parse_timeframe,
+)
 
 __version__ = version(__package__) if __package__ else None
 
 __all__ = [
+    "TICK_FLAG_MAP",
+    "TIMEFRAME_MAP",
+    "AccountSpec",
     "Dataset",
     "IfExists",
     "Mt5CliClient",
+    "RateTarget",
+    "ThrottledHistoryUpdater",
     "account_info",
     "build_config",
+    "build_rate_targets",
+    "build_rate_view_name",
+    "calculate_margin_and_volume",
     "collect_history",
+    "collect_latest_closed_rates_by_granularity",
+    "collect_latest_closed_rates_for_accounts",
+    "collect_latest_rates",
+    "collect_latest_rates_for_accounts",
+    "collect_latest_rates_for_accounts_with_retries",
     "copy_rates_from",
     "copy_rates_from_pos",
     "copy_rates_range",
     "copy_ticks_from",
     "copy_ticks_range",
     "detect_format",
+    "detect_position_side",
+    "determine_order_limits",
+    "drop_forming_rate_bar",
     "export_dataframe",
+    "export_dataframe_to_sqlite",
     "history_deals",
     "history_orders",
     "last_error",
+    "latest_rates",
+    "load_rate_data",
+    "load_rate_data_from_connection",
+    "load_rate_series_by_granularity",
+    "load_rate_series_from_sqlite",
     "market_book",
+    "minimum_margins",
+    "mt5_session",
+    "mt5_summary",
+    "mt5_summary_as_df",
+    "mt5_trading_session",
     "mt5_version",
     "orders",
+    "parse_datetime",
+    "parse_tick_flags",
+    "parse_timeframe",
     "positions",
+    "recent_history_deals",
+    "recent_ticks",
+    "resolve_account_spec",
+    "resolve_account_specs",
+    "resolve_history_datasets",
+    "resolve_history_tick_flags",
+    "resolve_history_timeframes",
+    "resolve_rate_tables",
+    "resolve_rate_view_name",
+    "resolve_rate_view_names",
+    "substitute_env_placeholders",
     "symbol_info",
     "symbol_info_tick",
     "symbols",

mt5cli/cli.py

@@ -222,6 +222,31 @@ def rates_from_pos(
     )
 
 
+@app.command()
+def latest_rates(
+    ctx: typer.Context,
+    symbol: Annotated[str, typer.Option(help="Symbol name.")],
+    timeframe: Annotated[
+        int,
+        typer.Option(
+            click_type=TIMEFRAME_TYPE,
+            help="Timeframe.",
+        ),
+    ],
+    count: Annotated[int, typer.Option(help="Number of records.")],
+    start_pos: Annotated[
+        int,
+        typer.Option(help="Start position (0 = current bar)."),
+    ] = 0,
+) -> None:
+    """Export latest rates from a start position."""
+    client = _sdk_client(ctx)
+    _execute_export(
+        ctx,
+        lambda: client.latest_rates(symbol, timeframe, count, start_pos=start_pos),
+    )
+
+
 @app.command()
 def rates_range(
     ctx: typer.Context,
@@ -300,6 +325,44 @@ def ticks_range(
     )
 
 
+@app.command()
+def ticks_recent(
+    ctx: typer.Context,
+    symbol: Annotated[str, typer.Option(help="Symbol name.")],
+    seconds: Annotated[
+        float,
+        typer.Option(help="Lookback window in seconds."),
+    ],
+    date_to: Annotated[
+        datetime | None,
+        typer.Option(click_type=DATETIME_TYPE, help="Window end date."),
+    ] = None,
+    count: Annotated[
+        int,
+        typer.Option(help="Maximum number of ticks to return."),
+    ] = 10000,
+    flags: Annotated[
+        int,
+        typer.Option(
+            click_type=TICK_FLAGS_TYPE,
+            help="Tick flags (ALL, INFO, TRADE, or integer).",
+        ),
+    ] = 1,
+) -> None:
+    """Export ticks from a recent time window."""
+    client = _sdk_client(ctx)
+    _execute_export(
+        ctx,
+        lambda: client.recent_ticks(
+            symbol,
+            seconds,
+            date_to=date_to,
+            count=count,
+            flags=flags,
+        ),
+    )
+
+
 @app.command()
 def account_info(ctx: typer.Context) -> None:
     """Export account information."""
@@ -335,6 +398,16 @@ def symbol_info(
     _execute_export(ctx, lambda: client.symbol_info(symbol))
 
 
+@app.command()
+def minimum_margins(
+    ctx: typer.Context,
+    symbol: Annotated[str, typer.Option(help="Symbol name.")],
+) -> None:
+    """Export minimum-volume buy and sell margin requirements."""
+    client = _sdk_client(ctx)
+    _execute_export(ctx, lambda: client.minimum_margins(symbol))
+
+
 @app.command()
 def orders(
     ctx: typer.Context,
@@ -427,6 +500,37 @@ def history_deals(
     )
 
 
+@app.command()
+def recent_history_deals(
+    ctx: typer.Context,
+    hours: Annotated[float, typer.Option(help="Lookback window in hours.")],
+    date_to: Annotated[
+        datetime | None,
+        typer.Option(click_type=DATETIME_TYPE, help="Window end date."),
+    ] = None,
+    group: Annotated[str | None, typer.Option(help="Group filter.")] = None,
+    symbol: Annotated[str | None, typer.Option(help="Symbol filter.")] = None,
+) -> None:
+    """Export historical deals from a recent trailing window."""
+    client = _sdk_client(ctx)
+    _execute_export(
+        ctx,
+        lambda: client.recent_history_deals(
+            hours,
+            date_to=date_to,
+            group=group,
+            symbol=symbol,
+        ),
+    )
+
+
+@app.command()
+def mt5_summary(ctx: typer.Context) -> None:
+    """Export a compact terminal/account status summary."""
+    client = _sdk_client(ctx)
+    _execute_export(ctx, client.mt5_summary_as_df)
+
+
 @app.command()
 def version(ctx: typer.Context) -> None:
     """Export MetaTrader5 version information."""

mt5cli/history.py

@@ -4,8 +4,10 @@ from __future__ import annotations
 
 import logging
 import sqlite3
+from dataclasses import dataclass
 from datetime import UTC, datetime
-from typing import TYPE_CHECKING, Literal
+from pathlib import Path
+from typing import TYPE_CHECKING, Literal, cast
 
 import pandas as pd
 
@@ -19,7 +21,7 @@ from .utils import (
 )
 
 if TYPE_CHECKING:
-    from collections.abc import Callable, Sequence
+    from collections.abc import Callable, Mapping, Sequence
 
     from pdmt5 import Mt5DataClient
 
@@ -104,6 +106,23 @@ def resolve_granularity_name(timeframe: int) -> str:
     return str(timeframe)
 
 
+def drop_forming_rate_bar(df_rate: pd.DataFrame) -> pd.DataFrame:
+    """Return closed bars from chronologically ordered MT5 rate data.
+
+    MetaTrader 5 ``copy_rates_from_pos(start_pos=0)`` includes the still-forming
+    current bar as the last row. Slice it off so downstream logic only sees
+    completed bars. Empty frames and single-row frames return empty results.
+
+    Args:
+        df_rate: Rate data ordered oldest-to-newest with the forming bar last.
+
+    Returns:
+        A new DataFrame with all rows except the last. Index and columns are
+        preserved. The input frame is not modified.
+    """
+    return df_rate.iloc[:-1].copy()
+
+
 def build_rate_view_name(
     *,
     symbol: str,
@@ -122,9 +141,641 @@ def build_rate_view_name(
     return f"rate_{symbol}__{granularity}_{timeframe}"
 
 
+SqliteConnOrPath = sqlite3.Connection | Path | str
+
+
+def _require_non_empty_identifier(identifier: str, kind: str) -> str:
+    value = identifier.strip()
+    if not value:
+        msg = f"SQLite {kind} name must not be empty."
+        raise ValueError(msg)
+    return value
+
+
+def _open_history_connection(
+    conn_or_path: SqliteConnOrPath | None,
+) -> tuple[sqlite3.Connection | None, bool]:
+    """Open a read-only SQLite connection when given a path.
+
+    Returns:
+        A connection and whether the caller should close it. When ``conn_or_path``
+        is None or the path does not exist, returns ``(None, False)`` without
+        creating a database file.
+    """
+    if conn_or_path is None:
+        return None, False
+    if isinstance(conn_or_path, sqlite3.Connection):
+        return conn_or_path, False
+    path = Path(conn_or_path)
+    if not path.exists():
+        return None, False
+    conn = sqlite3.connect(f"{path.resolve().as_uri()}?mode=ro", uri=True)
+    return conn, True
+
+
+def _open_existing_sqlite_database(
+    conn_or_path: SqliteConnOrPath,
+) -> tuple[sqlite3.Connection, bool]:
+    """Open a read-only SQLite database or reuse an existing connection.
+
+    Returns:
+        Tuple of connection and whether the caller should close it.
+
+    Raises:
+        ValueError: If the database path does not exist or is not a file.
+    """
+    if isinstance(conn_or_path, sqlite3.Connection):
+        return conn_or_path, False
+    path = Path(conn_or_path)
+    if not path.exists():
+        msg = f"SQLite database not found: {path}"
+        raise ValueError(msg)
+    if not path.is_file():
+        msg = f"SQLite database path is not a file: {path}"
+        raise ValueError(msg)
+    conn = sqlite3.connect(f"{path.resolve().as_uri()}?mode=ro", uri=True)
+    return conn, True
+
+
+def _validate_rate_load_request(table: str, count: int | None) -> str:
+    table_name = _require_non_empty_identifier(table, "table or view")
+    if count is not None and count <= 0:
+        msg = "count must be positive when provided."
+        raise ValueError(msg)
+    return table_name
+
+
+def _ensure_rate_columns(columns: set[str], table: str) -> None:
+    if not columns:
+        msg = f"SQLite table or view not found: {table}"
+        raise ValueError(msg)
+    if "time" not in columns:
+        msg = f"SQLite table or view {table!r} must include a time column."
+        raise ValueError(msg)
+    if "close" not in columns and not {"ask", "bid"}.issubset(columns):
+        msg = (
+            f"SQLite table or view {table!r} must include close, "
+            "or both ask and bid columns."
+        )
+        raise ValueError(msg)
+
+
+def _parse_rate_time_index(frame: pd.DataFrame, table: str) -> pd.DataFrame:
+    parsed = frame["time"].map(parse_sqlite_timestamp)
+    if parsed.isna().any():
+        msg = f"SQLite table or view {table!r} contains unparsable time values."
+        raise ValueError(msg)
+    result = frame.drop(columns=["time"])
+    result.index = pd.DatetimeIndex(parsed, name="time")
+    return result.sort_index(kind="stable")
+
+
+def load_rate_data_from_connection(
+    connection: sqlite3.Connection,
+    table: str,
+    count: int | None = None,
+) -> pd.DataFrame:
+    """Load rate-like data from a SQLite table or view.
+
+    Args:
+        connection: Open SQLite connection.
+        table: Source table or view name.
+        count: Optional number of most recent rows to load.
+
+    Returns:
+        DataFrame indexed by ascending ``time``.
+
+    Raises:
+        ValueError: If inputs, schema, timestamps are invalid, or the table
+            or view contains no rows.
+    """
+    table_name = _validate_rate_load_request(table, count)
+    columns = get_table_columns(connection, table_name)
+    _ensure_rate_columns(columns, table_name)
+    quoted_table = quote_sqlite_identifier(table_name)
+    if count is None:
+        frame = cast(
+            "pd.DataFrame",
+            pd.read_sql_query(  # type: ignore[reportUnknownMemberType]
+                f"SELECT * FROM {quoted_table} ORDER BY time ASC",  # noqa: S608
+                connection,
+            ),
+        )
+    else:
+        frame = cast(
+            "pd.DataFrame",
+            pd.read_sql_query(  # type: ignore[reportUnknownMemberType]
+                f"SELECT * FROM {quoted_table} ORDER BY time DESC LIMIT ?",  # noqa: S608
+                connection,
+                params=(count,),
+            ),
+        )
+    if frame.empty:
+        msg = f"SQLite table or view {table_name!r} contains no rows."
+        raise ValueError(msg)
+    return _parse_rate_time_index(frame, table_name)
+
+
+def load_rate_data(
+    conn_or_path: SqliteConnOrPath,
+    table: str,
+    count: int | None = None,
+) -> pd.DataFrame:
+    """Load rate-like data from a SQLite database path or connection.
+
+    Args:
+        conn_or_path: SQLite database path or open connection.
+        table: Source table or view name.
+        count: Optional number of most recent rows to load.
+
+    Returns:
+        DataFrame indexed by ascending ``time``.
+
+    """
+    conn, should_close = _open_existing_sqlite_database(conn_or_path)
+    try:
+        return load_rate_data_from_connection(conn, table, count=count)
+    finally:
+        if should_close:
+            conn.close()
+
+
+def _load_rates_timeframe_counts(conn: sqlite3.Connection) -> dict[str, int] | None:
+    """Return distinct timeframe counts per symbol from the normalized rates table."""
+    columns = get_table_columns(conn, Dataset.rates.table_name)
+    if not {"symbol", "timeframe"}.issubset(columns):
+        return None
+    rows = conn.execute(
+        "SELECT symbol, COUNT(DISTINCT timeframe) FROM rates GROUP BY symbol",
+    ).fetchall()
+    return {str(symbol): int(count) for symbol, count in rows}
+
+
+def _load_existing_rate_views(conn: sqlite3.Connection) -> set[str]:
+    """Return mt5cli-managed ``rate_*__*`` compatibility view names."""
+    rows = conn.execute(
+        "SELECT name FROM sqlite_master WHERE type = 'view' AND name GLOB 'rate_*__*'",
+    ).fetchall()
+    return {str(row[0]) for row in rows}
+
+
+def _rate_view_name_candidates(
+    *,
+    symbol: str,
+    granularity: str,
+    granularity_count: int,
+    timeframe: int,
+) -> list[str]:
+    """Return candidate view names in preference order."""
+    single = build_rate_view_name(
+        symbol=symbol,
+        granularity=granularity,
+        granularity_count=1,
+        timeframe=timeframe,
+    )
+    if granularity_count <= 1:
+        return [single]
+    multi = build_rate_view_name(
+        symbol=symbol,
+        granularity=granularity,
+        granularity_count=granularity_count,
+        timeframe=timeframe,
+    )
+    return [multi, single]
+
+
+def _resolve_rate_view_name_from_context(
+    *,
+    symbol: str,
+    timeframe: int,
+    granularity_name: str,
+    timeframe_counts: dict[str, int] | None,
+    existing_views: set[str],
+    require_existing: bool = False,
+) -> str:
+    """Resolve one rate view name using preloaded SQLite metadata.
+
+    Returns:
+        Preferred mt5cli-managed rate compatibility view name.
+
+    Raises:
+        ValueError: If ``require_existing`` is True and no managed view exists.
+    """
+    if timeframe_counts is None or symbol not in timeframe_counts:
+        candidates = [
+            build_rate_view_name(
+                symbol=symbol,
+                granularity=granularity_name,
+                granularity_count=1,
+                timeframe=timeframe,
+            ),
+            build_rate_view_name(
+                symbol=symbol,
+                granularity=granularity_name,
+                granularity_count=2,
+                timeframe=timeframe,
+            ),
+        ]
+    else:
+        candidates = _rate_view_name_candidates(
+            symbol=symbol,
+            granularity=granularity_name,
+            granularity_count=timeframe_counts[symbol],
+            timeframe=timeframe,
+        )
+    for candidate in candidates:
+        if candidate in existing_views:
+            return candidate
+    if require_existing:
+        msg = (
+            f"No rate compatibility view exists for symbol {symbol!r} "
+            f"and granularity {granularity_name!r}; "
+            f"candidates: {', '.join(candidates)}."
+        )
+        raise ValueError(msg)
+    return candidates[0]
+
+
+def resolve_rate_view_name(
+    conn_or_path: SqliteConnOrPath | None,
+    symbol: str,
+    granularity: str,
+    *,
+    require_existing: bool = False,
+) -> str:
+    """Resolve the mt5cli-managed rate compatibility view name.
+
+    Args:
+        conn_or_path: SQLite database path or open connection. When None or a
+            non-existing path and ``require_existing`` is False, the deterministic
+            default view name is returned without creating a database file.
+        symbol: Symbol stored in the normalized ``rates`` table.
+        granularity: Timeframe name (for example ``M1``) or integer string.
+        require_existing: When True, require the database and a managed view to exist.
+
+    Returns:
+        View name such as ``rate_EURUSD__1`` or ``rate_EURUSD__M1_1``.
+
+    Raises:
+        ValueError: If ``require_existing`` is True and the database or view is missing.
+    """
+    timeframe = parse_timeframe(granularity)
+    granularity_name = resolve_granularity_name(timeframe)
+    conn, should_close = _open_history_connection(conn_or_path)
+    try:
+        if conn is None:
+            if require_existing:
+                path = (
+                    conn_or_path
+                    if isinstance(conn_or_path, (Path, str))
+                    else "database"
+                )
+                msg = f"SQLite database not found: {path}"
+                raise ValueError(msg)
+            return build_rate_view_name(
+                symbol=symbol,
+                granularity=granularity_name,
+                granularity_count=1,
+                timeframe=timeframe,
+            )
+        return _resolve_rate_view_name_from_context(
+            symbol=symbol,
+            timeframe=timeframe,
+            granularity_name=granularity_name,
+            timeframe_counts=_load_rates_timeframe_counts(conn),
+            existing_views=_load_existing_rate_views(conn),
+            require_existing=require_existing,
+        )
+    finally:
+        if should_close and conn is not None:
+            conn.close()
+
+
+def resolve_rate_view_names(
+    conn_or_path: SqliteConnOrPath | None,
+    symbols: Sequence[str],
+    granularities: Sequence[str],
+    *,
+    require_existing: bool = False,
+) -> list[str]:
+    """Resolve rate compatibility view names for symbol and granularity pairs.
+
+    Args:
+        conn_or_path: SQLite database path or open connection. When None or a
+            non-existing path and ``require_existing`` is False, deterministic
+            default view names are returned without creating a database file.
+        symbols: Symbols stored in the normalized ``rates`` table.
+        granularities: Timeframe names (for example ``M1``) or integer strings.
+        require_existing: When True, require the database and managed views to exist.
+
+    Returns:
+        View names in row-major order: every ``granularity`` for the first
+        symbol, then every granularity for the next symbol, and so on.
+    """
+    conn, should_close = _open_history_connection(conn_or_path)
+    try:
+        if conn is None:
+            return [
+                resolve_rate_view_name(
+                    conn_or_path,
+                    symbol,
+                    granularity,
+                    require_existing=require_existing,
+                )
+                for symbol in symbols
+                for granularity in granularities
+            ]
+        timeframe_counts = _load_rates_timeframe_counts(conn)
+        existing_views = _load_existing_rate_views(conn)
+        resolved: list[str] = []
+        for symbol in symbols:
+            for granularity in granularities:
+                timeframe = parse_timeframe(granularity)
+                resolved.append(
+                    _resolve_rate_view_name_from_context(
+                        symbol=symbol,
+                        timeframe=timeframe,
+                        granularity_name=resolve_granularity_name(timeframe),
+                        timeframe_counts=timeframe_counts,
+                        existing_views=existing_views,
+                        require_existing=require_existing,
+                    ),
+                )
+        return resolved
+    finally:
+        if should_close and conn is not None:
+            conn.close()
+
+
+@dataclass(frozen=True)
+class RateTarget:
+    """A single rate series identified by symbol and timeframe.
+
+    Attributes:
+        symbol: MT5 symbol name, or None when the rate series is addressed only
+            by an explicit table (for example a custom SQLite view).
+        timeframe: MT5 timeframe as an integer or name (for example ``M1``).
+    """
+
+    symbol: str | None
+    timeframe: int | str
+
+    def __post_init__(self) -> None:
+        """Normalize accepted timeframe aliases to the stored integer value."""
+        if not isinstance(self.timeframe, int):
+            object.__setattr__(self, "timeframe", parse_timeframe(self.timeframe))
+
+    @property
+    def timeframe_int(self) -> int:
+        """Return the timeframe as its integer MT5 value."""
+        return cast("int", self.timeframe)
+
+
+def build_rate_targets(
+    symbols: Sequence[str],
+    timeframes: Sequence[int | str],
+    *,
+    allow_missing_symbol: bool = False,
+) -> list[RateTarget]:
+    """Build rate targets for every symbol and timeframe combination.
+
+    Args:
+        symbols: MT5 symbol names. May be empty when ``allow_missing_symbol``.
+        timeframes: MT5 timeframes as integers or names (for example ``M1``).
+        allow_missing_symbol: When True and ``symbols`` is empty, build targets
+            with ``symbol=None`` for each timeframe instead of raising.
+
+    Returns:
+        Targets in row-major order: every timeframe for the first symbol, then
+        every timeframe for the next symbol, and so on.
+
+    Raises:
+        ValueError: If ``timeframes`` is empty, or ``symbols`` is empty and
+            ``allow_missing_symbol`` is False.
+    """
+    if not timeframes:
+        msg = "At least one timeframe is required."
+        raise ValueError(msg)
+    if not symbols:
+        if not allow_missing_symbol:
+            msg = "At least one symbol is required."
+            raise ValueError(msg)
+        return [RateTarget(symbol=None, timeframe=tf) for tf in timeframes]
+    return [
+        RateTarget(symbol=symbol, timeframe=tf)
+        for symbol in symbols
+        for tf in timeframes
+    ]
+
+
+def resolve_rate_tables(
+    conn_or_path: SqliteConnOrPath | None,
+    targets: Sequence[RateTarget],
+    explicit_tables: Sequence[str] | None = None,
+    *,
+    require_existing: bool = False,
+) -> list[str]:
+    """Resolve SQLite table or view names for rate targets.
+
+    Args:
+        conn_or_path: SQLite database path or open connection. May be None when
+            ``explicit_tables`` is provided, or when ``require_existing`` is
+            False and deterministic default view names are sufficient.
+        targets: Rate targets to resolve.
+        explicit_tables: Optional explicit table or view names. When provided,
+            they are used as-is and must match the number of targets.
+        require_existing: When True, require the database and managed views to
+            exist for each symbol target. Ignored when ``explicit_tables`` is
+            provided.
+
+    Returns:
+        Table or view names aligned with ``targets``.
+
+    Raises:
+        ValueError: If ``targets`` is empty, ``explicit_tables`` length does not
+            match the target count, a target without a symbol is resolved
+            without an explicit table, or ``require_existing`` is True and the
+            database or a managed view is missing.
+    """
+    target_list = list(targets)
+    if not target_list:
+        msg = "At least one rate target is required."
+        raise ValueError(msg)
+    if explicit_tables is not None:
+        tables = list(explicit_tables)
+        if len(tables) != len(target_list):
+            msg = (
+                f"Expected {len(target_list)} explicit table(s) "
+                f"to match the targets, got {len(tables)}."
+            )
+            raise ValueError(msg)
+        return tables
+    if any(target.symbol is None for target in target_list):
+        msg = (
+            "Cannot resolve a rate table for a target without a symbol; "
+            "provide explicit_tables."
+        )
+        raise ValueError(msg)
+    conn, should_close = _open_history_connection(conn_or_path)
+    try:
+        if conn is None:
+            if require_existing:
+                path = (
+                    conn_or_path
+                    if isinstance(conn_or_path, (Path, str))
+                    else "database"
+                )
+                msg = f"SQLite database not found: {path}"
+                raise ValueError(msg)
+            timeframe_counts = None
+            existing_views: set[str] = set()
+        else:
+            timeframe_counts = _load_rates_timeframe_counts(conn)
+            existing_views = _load_existing_rate_views(conn)
+        resolved: list[str] = []
+        for target in target_list:
+            symbol = cast("str", target.symbol)
+            timeframe = target.timeframe_int
+            resolved.append(
+                _resolve_rate_view_name_from_context(
+                    symbol=symbol,
+                    timeframe=timeframe,
+                    granularity_name=resolve_granularity_name(timeframe),
+                    timeframe_counts=timeframe_counts,
+                    existing_views=existing_views,
+                    require_existing=require_existing,
+                ),
+            )
+        return resolved
+    finally:
+        if should_close and conn is not None:
+            conn.close()
+
+
+def load_rate_series_from_sqlite(
+    conn_or_path: SqliteConnOrPath,
+    targets: Sequence[RateTarget],
+    count: int,
+    explicit_tables: Sequence[str] | None = None,
+) -> dict[tuple[str | None, int], pd.DataFrame]:
+    """Load multiple rate series from a SQLite database.
+
+    Args:
+        conn_or_path: SQLite database path or open connection.
+        targets: Rate targets to load. Each ``(symbol, timeframe_int)`` pair
+            must be unique.
+        count: Number of most recent rows to load per series.
+        explicit_tables: Optional explicit table or view names matching targets.
+            When omitted, managed ``rate_*`` compatibility views must already
+            exist in the database.
+
+    Returns:
+        Mapping keyed by ``(symbol, timeframe_int)`` to each rate DataFrame.
+
+    Raises:
+        ValueError: If ``count`` is not positive, targets are empty, duplicate
+            ``(symbol, timeframe_int)`` pairs are present, or table resolution
+            fails.
+    """
+    if count <= 0:
+        msg = "count must be positive."
+        raise ValueError(msg)
+    target_list = list(targets)
+    if not target_list:
+        msg = "At least one rate target is required."
+        raise ValueError(msg)
+    if explicit_tables is None and any(target.symbol is None for target in target_list):
+        msg = (
+            "Cannot resolve a rate table for a target without a symbol; "
+            "provide explicit_tables."
+        )
+        raise ValueError(msg)
+    seen_keys: set[tuple[str | None, int]] = set()
+    for target in target_list:
+        key = (target.symbol, target.timeframe_int)
+        if key in seen_keys:
+            symbol_repr = repr(target.symbol)
+            msg = f"Duplicate rate target: ({symbol_repr}, {target.timeframe_int})"
+            raise ValueError(msg)
+        seen_keys.add(key)
+    tables = (
+        resolve_rate_tables(None, target_list, explicit_tables)
+        if explicit_tables is not None
+        else None
+    )
+    conn, should_close = _open_existing_sqlite_database(conn_or_path)
+    try:
+        resolved_tables = tables or resolve_rate_tables(
+            conn,
+            target_list,
+            require_existing=True,
+        )
+        return {
+            (target.symbol, target.timeframe_int): load_rate_data_from_connection(
+                conn,
+                table,
+                count=count,
+            )
+            for target, table in zip(target_list, resolved_tables, strict=True)
+        }
+    finally:
+        if should_close:
+            conn.close()
+
+
+def load_rate_series_by_granularity(
+    conn_or_path: SqliteConnOrPath,
+    symbols: Sequence[str],
+    granularities: Sequence[int | str],
+    count: int,
+    *,
+    explicit_tables: Sequence[str] | None = None,
+    allow_missing_symbol: bool = False,
+) -> dict[tuple[str | None, str], pd.DataFrame]:
+    """Load rate series keyed by symbol and string granularity name.
+
+    Builds targets with :func:`build_rate_targets` and loads them with
+    :func:`load_rate_series_from_sqlite`, then rekeys the result by granularity
+    name (for example ``M1``) instead of the integer timeframe to reduce
+    downstream boilerplate.
+
+    Args:
+        conn_or_path: SQLite database path or open connection.
+        symbols: MT5 symbol names. May be empty when ``allow_missing_symbol``.
+        granularities: MT5 timeframes as integers or names (for example ``M1``).
+        count: Number of most recent rows to load per series.
+        explicit_tables: Optional explicit table or view names matching the
+            built targets in row-major order. Required when symbols are omitted.
+        allow_missing_symbol: When True and ``symbols`` is empty, build targets
+            with ``symbol=None`` for each granularity instead of raising.
+
+    Returns:
+        Mapping keyed by ``(symbol | None, granularity_name)`` to each rate
+        DataFrame. Propagates ``ValueError`` (via :func:`build_rate_targets` and
+        :func:`load_rate_series_from_sqlite`) when inputs are empty or invalid,
+        table resolution fails, or duplicate targets are present.
+    """
+    targets = build_rate_targets(
+        symbols,
+        granularities,
+        allow_missing_symbol=allow_missing_symbol,
+    )
+    series = load_rate_series_from_sqlite(
+        conn_or_path,
+        targets,
+        count,
+        explicit_tables=explicit_tables,
+    )
+    return {
+        (symbol, resolve_granularity_name(timeframe)): frame
+        for (symbol, timeframe), frame in series.items()
+    }
+
+
 def get_table_columns(conn: sqlite3.Connection, table: str) -> set[str]:
     """Return existing SQLite columns for a table."""
-    rows = conn.execute(f"PRAGMA table_info({table})").fetchall()
+    quoted_table = quote_sqlite_identifier(table)
+    rows = conn.execute(f"PRAGMA table_info({quoted_table})").fetchall()
     return {str(row[1]) for row in rows}
 
 
@@ -404,7 +1055,20 @@ def drop_duplicates_in_table(
     )
 
 
-DedupScope = tuple[str, tuple[object, ...]]
+@dataclass(frozen=True)
+class DedupScope:
+    """Scoped deduplication predicate and the columns it references.
+
+    Attributes:
+        where: SQL predicate appended to the duplicate-removal query.
+        params: Parameters bound to the scope predicate.
+        required_columns: Columns that must be present in the written table for
+            the scope to run.
+    """
+
+    where: str
+    params: tuple[object, ...]
+    required_columns: frozenset[str]
 
 
 def _record_dedup_scope(
@@ -412,17 +1076,25 @@ def _record_dedup_scope(
     dataset: Dataset,
     scope_where: str,
     scope_params: tuple[object, ...],
+    required_columns: frozenset[str],
 ) -> None:
-    dedup_scopes.setdefault(dataset, []).append((scope_where, scope_params))
+    dedup_scopes.setdefault(dataset, []).append(
+        DedupScope(scope_where, scope_params, required_columns),
+    )
 
 
 def deduplicate_history_tables(
     conn: sqlite3.Connection,
     written_columns: dict[Dataset, set[str]],
     written_tables: set[Dataset],
-    dedup_scopes: dict[Dataset, list[DedupScope]] | None = None,
+    dedup_scopes: Mapping[Dataset, Sequence[DedupScope]] | None = None,
 ) -> None:
-    """Deduplicate appended history tables by stable identifiers."""
+    """Deduplicate appended history tables by stable identifiers.
+
+    Scopes whose required columns are not present in the written table are
+    skipped. If all scopes for a dataset are skipped, the table receives one
+    unscoped deduplication pass instead.
+    """
     cursor = conn.cursor()
     for dataset in written_tables:
         columns = written_columns.get(dataset, set())
@@ -441,16 +1113,19 @@ def deduplicate_history_tables(
                 table,
             )
             continue
-        scopes = dedup_scopes.get(dataset, []) if dedup_scopes else []
+        raw_scopes: Sequence[DedupScope] = (
+            dedup_scopes.get(dataset, ()) if dedup_scopes else ()
+        )
+        scopes = [scope for scope in raw_scopes if scope.required_columns <= columns]
         if scopes:
-            for scope_where, scope_params in scopes:
+            for scope in scopes:
                 drop_duplicates_in_table(
                     cursor,
                     table,
                     list(keys),
                     keep="last",
-                    scope_where=scope_where,
-                    scope_params=scope_params,
+                    scope_where=scope.where,
+                    scope_params=scope.params,
                 )
             continue
         drop_duplicates_in_table(cursor, table, list(keys), keep="last")
@@ -817,6 +1492,7 @@ def _write_incremental_rates(
                     Dataset.rates,
                     "symbol = ? AND timeframe = ? AND time >= ?",
                     (symbol, timeframe, start_date),
+                    frozenset({"symbol", "timeframe", "time"}),
                 )
 
 
@@ -855,6 +1531,7 @@ def _write_incremental_ticks(
                 Dataset.ticks,
                 "symbol = ? AND time >= ?",
                 (symbol, start_date),
+                frozenset({"symbol", "time"}),
             )
 
 
@@ -893,6 +1570,7 @@ def _write_incremental_history_orders(
                 Dataset.history_orders,
                 "symbol = ? AND time >= ?",
                 (symbol, start_date),
+                frozenset({"symbol", "time"}),
             )
 
 
@@ -946,6 +1624,7 @@ def _write_incremental_history_deals(
                         Dataset.history_deals,
                         "symbol = ? AND time >= ?",
                         (symbol, start_by_symbol[symbol, None]),
+                        frozenset({"symbol", "time"}),
                     )
             if "type" in columns:
                 _record_dedup_scope(
@@ -953,6 +1632,7 @@ def _write_incremental_history_deals(
                     Dataset.history_deals,
                     f"type NOT IN {_TRADE_DEAL_TYPES_SQL} AND time >= ?",
                     (account_event_start,),
+                    frozenset({"type", "time"}),
                 )
             if "type" not in columns and "symbol" in columns:
                 _record_dedup_scope(
@@ -960,6 +1640,7 @@ def _write_incremental_history_deals(
                     Dataset.history_deals,
                     "(symbol IS NULL OR symbol = '') AND time >= ?",
                     (account_event_start,),
+                    frozenset({"symbol", "time"}),
                 )
         return
     start_by_symbol = load_incremental_start_datetimes(
@@ -987,6 +1668,7 @@ def _write_incremental_history_deals(
                 Dataset.history_deals,
                 "symbol = ? AND time >= ?",
                 (symbol, start_date),
+                frozenset({"symbol", "time"}),
             )
 
 

mt5cli/trading.py

@@ -0,0 +1,210 @@
+"""Trading-capable MetaTrader 5 session helpers and operational utilities."""
+
+from __future__ import annotations
+
+from contextlib import contextmanager
+from typing import TYPE_CHECKING, Literal
+
+from pdmt5 import Mt5Config, Mt5TradingClient
+
+from .sdk import build_config
+
+if TYPE_CHECKING:
+    from collections.abc import Iterator
+
+    import pandas as pd
+
+PositionSide = Literal["long", "short"]
+OrderSide = Literal["long", "short"]
+
+__all__ = [
+    "OrderSide",
+    "PositionSide",
+    "calculate_margin_and_volume",
+    "detect_position_side",
+    "determine_order_limits",
+    "mt5_trading_session",
+]
+
+
+def _require_unit_ratio(value: float, name: str) -> None:
+    if not 0.0 <= value <= 1.0:
+        msg = f"{name} must be between 0 and 1 inclusive."
+        raise ValueError(msg)
+
+
+def _require_protective_ratio(value: float, name: str) -> None:
+    if not 0.0 <= value < 1.0:
+        msg = f"{name} must be at least 0 and less than 1."
+        raise ValueError(msg)
+
+
+def _sum_position_volume(positions: pd.DataFrame, position_type: object) -> float:
+    matched = positions.loc[positions["type"] == position_type, "volume"]
+    if matched.empty:
+        return 0.0
+    return float(matched.to_numpy(dtype=float).sum())
+
+
+def _normalize_order_side(side: str) -> OrderSide:
+    normalized = side.lower()
+    if normalized in {"long", "buy"}:
+        return "long"
+    if normalized in {"short", "sell"}:
+        return "short"
+    msg = (
+        f"Unsupported order side: {side!r}. Expected 'long', 'short', 'buy', or 'sell'."
+    )
+    raise ValueError(msg)
+
+
+def detect_position_side(
+    client: Mt5TradingClient,
+    symbol: str,
+) -> PositionSide | None:
+    """Detect the net open position side for a symbol.
+
+    Args:
+        client: Connected ``Mt5TradingClient`` instance.
+        symbol: Symbol to inspect.
+
+    Returns:
+        ``"long"`` when net buy volume exceeds sell volume, ``"short"`` when
+        net sell volume exceeds buy volume, or ``None`` when no positions exist
+        or buy/sell volumes are exactly balanced.
+    """
+    positions = client.positions_get_as_df(symbol=symbol)
+    if positions.empty:
+        return None
+
+    buy_type = client.mt5.POSITION_TYPE_BUY
+    sell_type = client.mt5.POSITION_TYPE_SELL
+    buy_volume = _sum_position_volume(positions, buy_type)
+    sell_volume = _sum_position_volume(positions, sell_type)
+    net_volume = buy_volume - sell_volume
+    if net_volume > 0:
+        return "long"
+    if net_volume < 0:
+        return "short"
+    return None
+
+
+def calculate_margin_and_volume(
+    client: Mt5TradingClient,
+    symbol: str,
+    unit_margin_ratio: float,
+    preserved_margin_ratio: float,
+) -> dict[str, float]:
+    """Calculate tradable margin and volumes from account free margin.
+
+    Applies ``preserved_margin_ratio`` to keep a reserve off ``margin_free``,
+    then allocates ``unit_margin_ratio`` of the remainder as the margin budget
+    for volume sizing on both buy and sell sides.
+
+    Args:
+        client: Connected ``Mt5TradingClient`` instance.
+        symbol: Symbol used for minimum-lot margin and volume calculations.
+        unit_margin_ratio: Fraction of post-reserve margin to allocate per unit.
+        preserved_margin_ratio: Fraction of ``margin_free`` to preserve.
+
+    Returns:
+        Dictionary with ``margin_free``, ``available_margin``, ``trade_margin``,
+        ``buy_volume``, and ``sell_volume``. Negative ``margin_free`` values are
+        clamped to ``0.0`` before sizing.
+    """
+    _require_unit_ratio(unit_margin_ratio, "unit_margin_ratio")
+    _require_unit_ratio(preserved_margin_ratio, "preserved_margin_ratio")
+
+    account = client.account_info_as_dict()
+    margin_free = max(0.0, float(account.get("margin_free") or 0.0))
+    available_margin = margin_free * (1.0 - preserved_margin_ratio)
+    trade_margin = available_margin * unit_margin_ratio
+    buy_volume = client.calculate_volume_by_margin(symbol, trade_margin, "BUY")
+    sell_volume = client.calculate_volume_by_margin(symbol, trade_margin, "SELL")
+    return {
+        "margin_free": margin_free,
+        "available_margin": available_margin,
+        "trade_margin": trade_margin,
+        "buy_volume": buy_volume,
+        "sell_volume": sell_volume,
+    }
+
+
+def determine_order_limits(
+    client: Mt5TradingClient,
+    symbol: str,
+    side: OrderSide | str,
+    stop_loss_limit_ratio: float,
+    take_profit_limit_ratio: float,
+) -> dict[str, float | None]:
+    """Derive entry and protective order prices from current market quotes.
+
+    Args:
+        client: Connected ``Mt5TradingClient`` instance.
+        symbol: Symbol used for the quote lookup.
+        side: Position side as ``"long"``/``"short"`` (``"buy"``/``"sell"``
+            aliases are accepted).
+        stop_loss_limit_ratio: Relative distance from entry for stop loss in
+            ``[0, 1)``. A value of ``0`` omits the stop loss.
+        take_profit_limit_ratio: Relative distance from entry for take profit in
+            ``[0, 1)``. A value of ``0`` omits the take profit.
+
+    Returns:
+        Dictionary with ``entry``, ``stop_loss``, and ``take_profit`` keys.
+        Omitted protective levels are returned as ``None``.
+    """
+    _require_protective_ratio(stop_loss_limit_ratio, "stop_loss_limit_ratio")
+    _require_protective_ratio(take_profit_limit_ratio, "take_profit_limit_ratio")
+    normalized_side = _normalize_order_side(side)
+    tick = client.symbol_info_tick_as_dict(symbol=symbol)
+    entry = float(tick["ask"] if normalized_side == "long" else tick["bid"])
+
+    stop_loss: float | None = None
+    if stop_loss_limit_ratio > 0:
+        if normalized_side == "long":
+            stop_loss = entry * (1.0 - stop_loss_limit_ratio)
+        else:
+            stop_loss = entry * (1.0 + stop_loss_limit_ratio)
+
+    take_profit: float | None = None
+    if take_profit_limit_ratio > 0:
+        if normalized_side == "long":
+            take_profit = entry * (1.0 + take_profit_limit_ratio)
+        else:
+            take_profit = entry * (1.0 - take_profit_limit_ratio)
+
+    return {
+        "entry": entry,
+        "stop_loss": stop_loss,
+        "take_profit": take_profit,
+    }
+
+
+@contextmanager
+def mt5_trading_session(
+    config: Mt5Config | None = None,
+    retry_count: int = 0,
+) -> Iterator[Mt5TradingClient]:
+    """Open a trading-capable MT5 session and always shut down safely.
+
+    Launches the MetaTrader 5 terminal using ``Mt5Config.path`` when set,
+    initializes and logs in via ``initialize_and_login_mt5()``, yields a
+    connected :class:`~pdmt5.Mt5TradingClient`, and calls ``shutdown()`` on
+    exit even when an error is raised inside the context.
+
+    Args:
+        config: MT5 connection configuration. Defaults to an empty config that
+            attaches to a running terminal.
+        retry_count: Number of initialization retries passed to
+            ``Mt5TradingClient``.
+
+    Yields:
+        Connected ``Mt5TradingClient`` bound to the session.
+    """
+    mt5_config = config or build_config()
+    client = Mt5TradingClient(config=mt5_config, retry_count=retry_count)
+    try:
+        client.initialize_and_login_mt5()
+        yield client
+    finally:
+        client.shutdown()

mt5cli/utils.py

@@ -2,16 +2,18 @@
 
 from __future__ import annotations
 
-import importlib
 import json
+import sqlite3
 from datetime import UTC, datetime
 from enum import StrEnum
 from pathlib import Path
-from typing import TYPE_CHECKING, Any, TypeGuard, cast
+from typing import TYPE_CHECKING, Any, TypeGuard
 
 import click
 
 if TYPE_CHECKING:
+    from collections.abc import Sequence
+
     import pandas as pd
 
 # ---------------------------------------------------------------------------
@@ -260,6 +262,50 @@ def detect_format(
     raise ValueError(msg)
 
 
+def export_dataframe_to_sqlite(
+    df: pd.DataFrame,
+    output_path: Path,
+    table_name: str = "data",
+    *,
+    if_exists: IfExists = IfExists.APPEND,
+    index: bool = False,
+    index_label: str | None = None,
+    deduplicate_on: Sequence[str] | None = None,
+) -> None:
+    """Write a DataFrame to SQLite with configurable append and deduplication.
+
+    Args:
+        df: DataFrame to export.
+        output_path: SQLite database path.
+        table_name: Target table name.
+        if_exists: Conflict behavior when the table already exists.
+        index: Whether to write the DataFrame index as a column.
+        index_label: Column name for the index when ``index=True``.
+        deduplicate_on: Optional key columns to deduplicate after writing,
+            keeping the latest ``ROWID`` per key group. Deduplication scans the
+            full table, so repeated appends cost O(table size); index the key
+            columns when appending frequently.
+    """
+    with sqlite3.connect(output_path) as conn:
+        df.to_sql(  # type: ignore[reportUnknownMemberType]
+            table_name,
+            conn,
+            if_exists=if_exists.value,
+            index=index,
+            index_label=index_label,
+        )
+        if deduplicate_on:
+            from .history import drop_duplicates_in_table  # noqa: PLC0415
+
+            drop_duplicates_in_table(
+                conn.cursor(),
+                table_name,
+                list(deduplicate_on),
+                keep="last",
+            )
+            conn.commit()
+
+
 def export_dataframe(
     df: pd.DataFrame,
     output_path: Path,
@@ -289,14 +335,13 @@ def export_dataframe(
     elif output_format == "parquet":
         df.to_parquet(output_path, index=False)
     elif output_format == "sqlite3":
-        sqlite3 = cast("Any", importlib.import_module("sqlite3"))
-        with sqlite3.connect(output_path) as conn:
-            df.to_sql(  # type: ignore[reportUnknownMemberType]
-                table_name,
-                conn,
-                if_exists="replace",
-                index=False,
-            )
+        export_dataframe_to_sqlite(
+            df,
+            output_path,
+            table_name,
+            if_exists=IfExists.REPLACE,
+            index=False,
+        )
     else:
         msg = f"Unsupported output format: {output_format}"
         raise ValueError(msg)

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "mt5cli"
-version = "0.4.2"
+version = "0.6.1"
 description = "Command-line tool for MetaTrader 5"
 authors = [{name = "dceoy", email = "dceoy@users.noreply.github.com"}]
 maintainers = [{name = "dceoy", email = "dceoy@users.noreply.github.com"}]

tests/test_cli.py

@@ -6,7 +6,7 @@ import json
 import logging
 import re
 import sqlite3
-from datetime import UTC, datetime
+from datetime import UTC, datetime, timedelta
 from typing import TYPE_CHECKING
 from unittest.mock import MagicMock
 
@@ -93,6 +93,10 @@ def mock_client(mocker: MockerFixture) -> MagicMock:
     client.market_book_get_as_df.return_value = sample_df
     client.order_check_as_df.return_value = sample_df
     client.order_send_as_df.return_value = sample_df
+    client.version.return_value = (5, 0, 1)
+    client.terminal_info.return_value = {"connected": True, "paths": ["terminal.exe"]}
+    client.account_info.return_value = {"login": 123, "limits": {"modes": ["demo"]}}
+    client.symbols_total.return_value = 42
     mocker.patch("mt5cli.sdk.Mt5DataClient", return_value=client)
     return client
 
@@ -223,6 +227,37 @@ class TestCommands:
             count=50,
         )
 
+    def test_latest_rates(
+        self,
+        tmp_path: Path,
+        mock_client: MagicMock,
+    ) -> None:
+        """Test latest-rates command."""
+        output = tmp_path / "out.csv"
+        result = runner.invoke(
+            app,
+            [
+                "-o",
+                str(output),
+                "latest-rates",
+                "--symbol",
+                "GBPUSD",
+                "--timeframe",
+                "H1",
+                "--count",
+                "50",
+                "--start-pos",
+                "2",
+            ],
+        )
+        assert result.exit_code == 0, result.output
+        mock_client.copy_rates_from_pos_as_df.assert_called_once_with(
+            symbol="GBPUSD",
+            timeframe=16385,
+            start_pos=2,
+            count=50,
+        )
+
     def test_rates_range(
         self,
         tmp_path: Path,
@@ -316,6 +351,65 @@ class TestCommands:
             flags=2,
         )
 
+    def test_ticks_recent(
+        self,
+        tmp_path: Path,
+        mock_client: MagicMock,
+    ) -> None:
+        """Test ticks-recent command."""
+        output = tmp_path / "out.csv"
+        result = runner.invoke(
+            app,
+            [
+                "-o",
+                str(output),
+                "ticks-recent",
+                "--symbol",
+                "EURUSD",
+                "--seconds",
+                "120",
+                "--date-to",
+                "2024-01-02",
+                "--count",
+                "500",
+                "--flags",
+                "ALL",
+            ],
+        )
+        assert result.exit_code == 0, result.output
+        mock_client.copy_ticks_from_as_df.assert_called_once_with(
+            symbol="EURUSD",
+            date_from=datetime(2024, 1, 2, tzinfo=UTC) - timedelta(seconds=120),
+            count=500,
+            flags=1,
+        )
+        mock_client.copy_ticks_range_as_df.assert_not_called()
+
+    def test_minimum_margins(
+        self,
+        tmp_path: Path,
+        mock_client: MagicMock,
+    ) -> None:
+        """Test minimum-margins command."""
+        sym = MagicMock(volume_min=0.01)
+        account = MagicMock(currency="USD")
+        tick = MagicMock(ask=1.1010, bid=1.1000)
+        mock_client.symbol_info.return_value = sym
+        mock_client.account_info.return_value = account
+        mock_client.symbol_info_tick.return_value = tick
+        mock_client.order_calc_margin.side_effect = [12.5, 12.4]
+        mock_client.mt5.ORDER_TYPE_BUY = 0
+        mock_client.mt5.ORDER_TYPE_SELL = 1
+        output = tmp_path / "out.csv"
+        result = runner.invoke(
+            app,
+            ["-o", str(output), "minimum-margins", "--symbol", "EURUSD"],
+        )
+        assert result.exit_code == 0, result.output
+        mock_client.symbol_info.assert_called_once_with("EURUSD")
+        mock_client.order_calc_margin.assert_any_call(0, "EURUSD", 0.01, 1.1010)
+        mock_client.order_calc_margin.assert_any_call(1, "EURUSD", 0.01, 1.1000)
+
     def test_orders(
         self,
         tmp_path: Path,
@@ -392,6 +486,84 @@ class TestCommands:
         assert result.exit_code == 0, result.output
         mock_client.history_deals_get_as_df.assert_called_once()
 
+    def test_recent_history_deals(
+        self,
+        tmp_path: Path,
+        mock_client: MagicMock,
+    ) -> None:
+        """Test recent-history-deals command."""
+        output = tmp_path / "out.csv"
+        result = runner.invoke(
+            app,
+            [
+                "-o",
+                str(output),
+                "recent-history-deals",
+                "--hours",
+                "6",
+                "--date-to",
+                "2024-01-02",
+                "--symbol",
+                "EURUSD",
+            ],
+        )
+        assert result.exit_code == 0, result.output
+        mock_client.history_deals_get_as_df.assert_called_once_with(
+            date_from=datetime(2024, 1, 1, 18, tzinfo=UTC),
+            date_to=datetime(2024, 1, 2, tzinfo=UTC),
+            group=None,
+            symbol="EURUSD",
+            ticket=None,
+            position=None,
+        )
+
+    @pytest.mark.parametrize(
+        ("filename", "reader"),
+        [
+            ("summary.csv", "csv"),
+            ("summary.json", "json"),
+            ("summary.db", "sqlite3"),
+            ("summary.parquet", "parquet"),
+        ],
+    )
+    def test_mt5_summary_export_formats(
+        self,
+        tmp_path: Path,
+        mock_client: MagicMock,
+        filename: str,
+        reader: str,
+    ) -> None:
+        """Test mt5-summary writes export-safe files for supported formats."""
+        output = tmp_path / filename
+        result = runner.invoke(app, ["-o", str(output), "mt5-summary"])
+        assert result.exit_code == 0, result.output
+        assert output.exists()
+        mock_client.version.assert_called_once()
+        mock_client.terminal_info.assert_called_once()
+        mock_client.account_info.assert_called_once()
+        mock_client.symbols_total.assert_called_once()
+        if reader == "csv":
+            frame = pd.read_csv(output)
+        elif reader == "json":
+            with output.open() as f:
+                records = json.load(f)
+            frame = pd.DataFrame(records)
+        elif reader == "sqlite3":
+            with sqlite3.connect(output) as conn:
+                frame = pd.read_sql(  # type: ignore[reportUnknownMemberType]
+                    "SELECT * FROM data",
+                    conn,
+                )
+        else:
+            frame = pd.read_parquet(output)
+        assert len(frame) == 1
+        assert frame.iloc[0].to_dict() == {
+            "version": "[5,0,1]",
+            "terminal_info": '{"connected":true,"paths":["terminal.exe"]}',
+            "account_info": '{"limits":{"modes":["demo"]},"login":123}',
+            "symbols_total": 42,
+        }
+
     def test_version(
         self,
         tmp_path: Path,

tests/test_trading.py

@@ -0,0 +1,356 @@
+"""Tests for trading session helpers and operational utilities."""
+
+from __future__ import annotations
+
+from unittest.mock import MagicMock
+
+import pandas as pd
+import pytest
+from pdmt5 import Mt5RuntimeError
+from pytest_mock import MockerFixture  # noqa: TC002
+
+from mt5cli.sdk import build_config
+from mt5cli.trading import (
+    calculate_margin_and_volume,
+    detect_position_side,
+    determine_order_limits,
+    mt5_trading_session,
+)
+
+
+class TestDetectPositionSide:
+    """Tests for detect_position_side."""
+
+    def test_returns_none_when_no_positions(self) -> None:
+        """Test None is returned when no open positions exist."""
+        client = MagicMock()
+        client.positions_get_as_df.return_value = pd.DataFrame()
+
+        assert detect_position_side(client, "EURUSD") is None
+
+    def test_returns_long_for_net_buy_volume(self) -> None:
+        """Test long is returned when buy volume exceeds sell volume."""
+        client = MagicMock()
+        client.mt5.POSITION_TYPE_BUY = 0
+        client.mt5.POSITION_TYPE_SELL = 1
+        client.positions_get_as_df.return_value = pd.DataFrame(
+            {
+                "type": [0, 0, 1],
+                "volume": [0.2, 0.1, 0.05],
+            },
+        )
+
+        assert detect_position_side(client, "EURUSD") == "long"
+
+    def test_returns_short_for_net_sell_volume(self) -> None:
+        """Test short is returned when sell volume exceeds buy volume."""
+        client = MagicMock()
+        client.mt5.POSITION_TYPE_BUY = 0
+        client.mt5.POSITION_TYPE_SELL = 1
+        client.positions_get_as_df.return_value = pd.DataFrame(
+            {
+                "type": [1, 1],
+                "volume": [0.3, 0.1],
+            },
+        )
+
+        assert detect_position_side(client, "EURUSD") == "short"
+
+    def test_returns_none_for_balanced_hedged_positions(self) -> None:
+        """Test None is returned when buy and sell volumes net to zero."""
+        client = MagicMock()
+        client.mt5.POSITION_TYPE_BUY = 0
+        client.mt5.POSITION_TYPE_SELL = 1
+        client.positions_get_as_df.return_value = pd.DataFrame(
+            {
+                "type": [0, 1],
+                "volume": [0.2, 0.2],
+            },
+        )
+
+        assert detect_position_side(client, "EURUSD") is None
+
+
+class TestCalculateMarginAndVolume:
+    """Tests for calculate_margin_and_volume."""
+
+    def test_calculates_margin_budget_and_volumes(self) -> None:
+        """Test margin budget and buy/sell volumes are derived from ratios."""
+        client = MagicMock()
+        client.account_info_as_dict.return_value = {"margin_free": 1000.0}
+        client.calculate_volume_by_margin.side_effect = [0.3, 0.2]
+
+        result = calculate_margin_and_volume(
+            client,
+            "EURUSD",
+            unit_margin_ratio=0.5,
+            preserved_margin_ratio=0.2,
+        )
+
+        assert result == {
+            "margin_free": 1000.0,
+            "available_margin": 800.0,
+            "trade_margin": 400.0,
+            "buy_volume": 0.3,
+            "sell_volume": 0.2,
+        }
+        client.calculate_volume_by_margin.assert_any_call("EURUSD", 400.0, "BUY")
+        client.calculate_volume_by_margin.assert_any_call("EURUSD", 400.0, "SELL")
+
+    @pytest.mark.parametrize(
+        ("account_dict", "expected_margin_free"),
+        [
+            ({"margin_free": 0.0}, 0.0),
+            ({}, 0.0),
+            ({"margin_free": None}, 0.0),
+        ],
+    )
+    def test_zero_or_missing_margin_free(
+        self,
+        account_dict: dict[str, float | None],
+        expected_margin_free: float,
+    ) -> None:
+        """Test missing or zero margin_free yields zero trade margin."""
+        client = MagicMock()
+        client.account_info_as_dict.return_value = account_dict
+        client.calculate_volume_by_margin.return_value = 0.0
+
+        result = calculate_margin_and_volume(
+            client,
+            "EURUSD",
+            unit_margin_ratio=0.5,
+            preserved_margin_ratio=0.2,
+        )
+
+        assert result["margin_free"] == expected_margin_free
+        client.calculate_volume_by_margin.assert_any_call("EURUSD", 0.0, "BUY")
+        client.calculate_volume_by_margin.assert_any_call("EURUSD", 0.0, "SELL")
+
+    def test_clamps_negative_margin_free_to_zero(self) -> None:
+        """Test negative margin_free is clamped to zero before sizing."""
+        client = MagicMock()
+        client.account_info_as_dict.return_value = {"margin_free": -500.0}
+        client.calculate_volume_by_margin.return_value = 0.0
+
+        result = calculate_margin_and_volume(
+            client,
+            "EURUSD",
+            unit_margin_ratio=0.5,
+            preserved_margin_ratio=0.2,
+        )
+
+        expected_margin_free = 0.0
+        assert result["margin_free"] == expected_margin_free
+        client.calculate_volume_by_margin.assert_any_call("EURUSD", 0.0, "BUY")
+        client.calculate_volume_by_margin.assert_any_call("EURUSD", 0.0, "SELL")
+
+    @pytest.mark.parametrize(
+        ("unit_ratio", "preserved_ratio"),
+        [
+            (-0.1, 0.0),
+            (1.1, 0.0),
+            (0.5, -0.1),
+            (0.5, 1.1),
+        ],
+    )
+    def test_rejects_invalid_ratios(
+        self,
+        unit_ratio: float,
+        preserved_ratio: float,
+    ) -> None:
+        """Test invalid ratio values raise ValueError."""
+        with pytest.raises(ValueError, match="must be between 0 and 1"):
+            calculate_margin_and_volume(
+                MagicMock(),
+                "EURUSD",
+                unit_margin_ratio=unit_ratio,
+                preserved_margin_ratio=preserved_ratio,
+            )
+
+
+class TestDetermineOrderLimits:
+    """Tests for determine_order_limits."""
+
+    @pytest.mark.parametrize(
+        ("side", "expected_entry_key"),
+        [
+            ("long", "ask"),
+            ("short", "bid"),
+            ("buy", "ask"),
+            ("sell", "bid"),
+        ],
+    )
+    def test_uses_expected_quote_for_entry(
+        self,
+        side: str,
+        expected_entry_key: str,
+    ) -> None:
+        """Test entry price is taken from ask for long/buy and bid for short/sell."""
+        client = MagicMock()
+        client.symbol_info_tick_as_dict.return_value = {"ask": 1.1010, "bid": 1.1000}
+
+        result = determine_order_limits(
+            client,
+            "EURUSD",
+            side,
+            stop_loss_limit_ratio=0.0,
+            take_profit_limit_ratio=0.0,
+        )
+
+        assert (
+            result["entry"]
+            == client.symbol_info_tick_as_dict.return_value[expected_entry_key]
+        )
+        assert result["stop_loss"] is None
+        assert result["take_profit"] is None
+
+    def test_calculates_long_protective_levels(self) -> None:
+        """Test long stop loss and take profit are placed below/above entry."""
+        client = MagicMock()
+        client.symbol_info_tick_as_dict.return_value = {"ask": 100.0, "bid": 99.0}
+
+        result = determine_order_limits(
+            client,
+            "EURUSD",
+            "long",
+            stop_loss_limit_ratio=0.02,
+            take_profit_limit_ratio=0.03,
+        )
+
+        assert result == {
+            "entry": 100.0,
+            "stop_loss": 98.0,
+            "take_profit": 103.0,
+        }
+
+    def test_calculates_short_protective_levels(self) -> None:
+        """Test short stop loss and take profit are placed above/below entry."""
+        client = MagicMock()
+        client.symbol_info_tick_as_dict.return_value = {"ask": 100.0, "bid": 99.0}
+
+        result = determine_order_limits(
+            client,
+            "EURUSD",
+            "short",
+            stop_loss_limit_ratio=0.02,
+            take_profit_limit_ratio=0.03,
+        )
+
+        assert result == {
+            "entry": 99.0,
+            "stop_loss": 100.98,
+            "take_profit": 96.03,
+        }
+
+    def test_rejects_unknown_side(self) -> None:
+        """Test unsupported side values raise ValueError."""
+        with pytest.raises(ValueError, match="Unsupported order side"):
+            determine_order_limits(
+                MagicMock(),
+                "EURUSD",
+                "flat",
+                stop_loss_limit_ratio=0.01,
+                take_profit_limit_ratio=0.01,
+            )
+
+    @pytest.mark.parametrize(
+        ("stop_loss_ratio", "take_profit_ratio"),
+        [
+            (-0.05, 0.01),
+            (0.01, 2.0),
+        ],
+    )
+    def test_rejects_invalid_protective_ratios(
+        self,
+        stop_loss_ratio: float,
+        take_profit_ratio: float,
+    ) -> None:
+        """Test out-of-range protective ratios raise ValueError."""
+        with pytest.raises(ValueError, match="must be at least 0 and less than 1"):
+            determine_order_limits(
+                MagicMock(),
+                "EURUSD",
+                "long",
+                stop_loss_limit_ratio=stop_loss_ratio,
+                take_profit_limit_ratio=take_profit_ratio,
+            )
+
+    @pytest.mark.parametrize(
+        ("field", "ratio"),
+        [
+            ("stop_loss_limit_ratio", 1.0),
+            ("take_profit_limit_ratio", 1.0),
+        ],
+    )
+    def test_rejects_unit_boundary_protective_ratios(
+        self,
+        field: str,
+        ratio: float,
+    ) -> None:
+        """Test protective ratios of exactly 1.0 are rejected."""
+        kwargs = {
+            "stop_loss_limit_ratio": 0.01,
+            "take_profit_limit_ratio": 0.01,
+            field: ratio,
+        }
+        with pytest.raises(ValueError, match="must be at least 0 and less than 1"):
+            determine_order_limits(
+                MagicMock(),
+                "EURUSD",
+                "long",
+                **kwargs,
+            )
+
+
+class TestMt5TradingSession:
+    """Tests for the mt5_trading_session context manager."""
+
+    def test_yields_connected_client_and_shuts_down(
+        self,
+        mocker: MockerFixture,
+    ) -> None:
+        """Test mt5_trading_session connects, yields a client, and shuts down."""
+        mock_client = MagicMock()
+        trading_client = mocker.patch(
+            "mt5cli.trading.Mt5TradingClient",
+            return_value=mock_client,
+        )
+
+        with mt5_trading_session(
+            build_config(path="/opt/mt5/terminal64.exe"),
+            retry_count=2,
+        ) as client:
+            mock_client.initialize_and_login_mt5.assert_called_once()
+            assert client is mock_client
+
+        trading_client.assert_called_once()
+        assert trading_client.call_args.kwargs["retry_count"] == 2
+        assert (
+            trading_client.call_args.kwargs["config"].path == "/opt/mt5/terminal64.exe"
+        )
+        mock_client.shutdown.assert_called_once()
+
+    def test_shuts_down_when_initialize_raises(
+        self,
+        mocker: MockerFixture,
+    ) -> None:
+        """Test shutdown is called when initialization fails."""
+        mock_client = MagicMock()
+        mock_client.initialize_and_login_mt5.side_effect = Mt5RuntimeError("boom")
+        mocker.patch("mt5cli.trading.Mt5TradingClient", return_value=mock_client)
+
+        with pytest.raises(Mt5RuntimeError, match="boom"), mt5_trading_session():
+            pass
+
+        mock_client.shutdown.assert_called_once()
+
+    def test_shuts_down_when_body_raises(self, mocker: MockerFixture) -> None:
+        """Test shutdown is called when the context body raises."""
+        mock_client = MagicMock()
+        mocker.patch("mt5cli.trading.Mt5TradingClient", return_value=mock_client)
+
+        body_error = "body error"
+        with pytest.raises(RuntimeError, match=body_error), mt5_trading_session():
+            raise RuntimeError(body_error)
+
+        mock_client.shutdown.assert_called_once()

tests/test_utils.py

@@ -21,8 +21,10 @@ from mt5cli.utils import (
     TIMEFRAME_MAP,
     TIMEFRAME_TYPE,
     Dataset,
+    IfExists,
     detect_format,
     export_dataframe,
+    export_dataframe_to_sqlite,
     parse_datetime,
     parse_request,
     parse_tick_flags,
@@ -130,6 +132,112 @@ class TestExportDataframe:
             export_dataframe(sample_df, tmp_path / "out.txt", "xml")
 
 
+class TestExportDataframeToSqlite:
+    """Tests for export_dataframe_to_sqlite."""
+
+    def test_append_preserves_existing_rows(self, tmp_path: Path) -> None:
+        """Test append mode keeps prior rows in the SQLite table."""
+        output = tmp_path / "append.db"
+        first = pd.DataFrame({"id": [1], "value": ["a"]})
+        second = pd.DataFrame({"id": [2], "value": ["b"]})
+        export_dataframe_to_sqlite(first, output, "items", if_exists=IfExists.REPLACE)
+        export_dataframe_to_sqlite(second, output, "items", if_exists=IfExists.APPEND)
+        with sqlite3.connect(output) as conn:
+            result = pd.read_sql(  # type: ignore[reportUnknownMemberType]
+                "SELECT id, value FROM items ORDER BY id",
+                conn,
+            )
+        pd.testing.assert_frame_equal(
+            result,
+            pd.DataFrame({"id": [1, 2], "value": ["a", "b"]}),
+        )
+
+    def test_deduplicate_keeps_latest_row(self, tmp_path: Path) -> None:
+        """Test deduplication keeps the latest ROWID for key columns."""
+        output = tmp_path / "dedup.db"
+        first = pd.DataFrame({
+            "symbol": ["EURUSD", "EURUSD"],
+            "time": ["2024-01-01", "2024-01-01"],
+            "bid": [1.0, 1.1],
+        })
+        second = pd.DataFrame({
+            "symbol": ["EURUSD"],
+            "time": ["2024-01-01"],
+            "bid": [1.2],
+        })
+        export_dataframe_to_sqlite(
+            first,
+            output,
+            "ticks",
+            if_exists=IfExists.REPLACE,
+            deduplicate_on=("symbol", "time"),
+        )
+        export_dataframe_to_sqlite(
+            second,
+            output,
+            "ticks",
+            if_exists=IfExists.APPEND,
+            deduplicate_on=("symbol", "time"),
+        )
+        with sqlite3.connect(output) as conn:
+            result = pd.read_sql(  # type: ignore[reportUnknownMemberType]
+                "SELECT symbol, time, bid FROM ticks",
+                conn,
+            )
+        pd.testing.assert_frame_equal(
+            result.reset_index(drop=True),
+            pd.DataFrame({
+                "symbol": ["EURUSD"],
+                "time": ["2024-01-01"],
+                "bid": [1.2],
+            }),
+        )
+
+    def test_default_if_exists_appends_without_dropping_rows(
+        self,
+        tmp_path: Path,
+    ) -> None:
+        """Test the default append mode keeps prior rows."""
+        output = tmp_path / "default-append.db"
+        first = pd.DataFrame({"id": [1], "value": ["a"]})
+        second = pd.DataFrame({"id": [2], "value": ["b"]})
+        export_dataframe_to_sqlite(first, output, "items")
+        export_dataframe_to_sqlite(second, output, "items")
+        with sqlite3.connect(output) as conn:
+            result = pd.read_sql(  # type: ignore[reportUnknownMemberType]
+                "SELECT id, value FROM items ORDER BY id",
+                conn,
+            )
+        pd.testing.assert_frame_equal(
+            result,
+            pd.DataFrame({"id": [1, 2], "value": ["a", "b"]}),
+        )
+
+    def test_writes_index_with_label(self, tmp_path: Path) -> None:
+        """Test optional index export with a custom label."""
+        output = tmp_path / "index.db"
+        frame = pd.DataFrame(
+            {"value": [1.0]}, index=pd.Index(["EURUSD"], name="symbol")
+        )
+        export_dataframe_to_sqlite(
+            frame,
+            output,
+            "margins",
+            if_exists=IfExists.REPLACE,
+            index=True,
+            index_label="symbol",
+        )
+        with sqlite3.connect(output) as conn:
+            result = pd.read_sql(  # type: ignore[reportUnknownMemberType]
+                "SELECT symbol, value FROM margins",
+                conn,
+            )
+        pd.testing.assert_frame_equal(
+            result,
+            pd.DataFrame({"symbol": ["EURUSD"], "value": [1.0]}),
+        )
+
+
 # ---------------------------------------------------------------------------
 # Parse helpers
 # ---------------------------------------------------------------------------

uv.lock

@@ -487,7 +487,7 @@ wheels = [
 
 [[package]]
 name = "mt5cli"
-version = "0.4.2"
+version = "0.6.1"
 source = { editable = "." }
 dependencies = [
     { name = "click" },
@@ -836,11 +836,11 @@ wheels = [
 
 [[package]]
 name = "pygments"
-version = "2.19.2"
+version = "2.20.0"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/b0/77/a5b8c569bf593b0140bde72ea885a803b82086995367bf2037de0159d924/pygments-2.19.2.tar.gz", hash = "sha256:636cb2477cec7f8952536970bc533bc43743542f70392ae026374600add5b887", size = 4968631, upload-time = "2025-06-21T13:39:12.283Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/c3/b2/bc9c9196916376152d655522fdcebac55e66de6603a76a02bca1b6414f6c/pygments-2.20.0.tar.gz", hash = "sha256:6757cd03768053ff99f3039c1a36d6c0aa0b263438fcab17520b30a303a82b5f", size = 4955991, upload-time = "2026-03-29T13:29:33.898Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl", hash = "sha256:86540386c03d588bb81d44bc3928634ff26449851e99741617ecb9037ee5ec0b", size = 1225217, upload-time = "2025-06-21T13:39:07.939Z" },
+    { url = "https://files.pythonhosted.org/packages/f4/7e/a72dd26f3b0f4f2bf1dd8923c85f7ceb43172af56d63c7383eb62b332364/pygments-2.20.0-py3-none-any.whl", hash = "sha256:81a9e26dd42fd28a23a2d169d86d7ac03b46e2f8b59ed4698fb4785f946d0176", size = 1231151, upload-time = "2026-03-29T13:29:30.038Z" },
 ]
 
 [[package]]