Add rate view resolution and downstream SDK helpers (#18)

* Add public helpers to resolve rate compatibility view names.

Expose resolve_rate_view_name and resolve_rate_view_names in mt5cli.history so consumers can derive mt5cli-managed SQLite view names from stored rates metadata without reimplementing the naming rules.

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

* Add reusable export, tick-window, and margin helpers for downstream tools.

Expose SQLite append/dedup export, recent tick retrieval, and minimum margin
summary through the SDK and CLI so projects like mteor can depend on mt5cli
instead of duplicating MT5 data plumbing.

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

* Bump version to 0.4.3.

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

* Address PR review feedback for rate view resolution and SDK helpers.

Harden SQLite read-only connections, tighten view discovery, improve recent_ticks
fetch efficiency, default SQLite export to append, and expand tests and docs.

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

* Fix read-only SQLite URI construction on Windows.

Use Path.as_uri() so encoded file URIs work cross-platform with mode=ro.

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

---------

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

README.md

@@ -57,6 +57,7 @@ python -m mt5cli -o account.csv account-info
 | `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                                                                      |
@@ -64,6 +65,7 @@ python -m mt5cli -o account.csv account-info
 | `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                                                                                        |
@@ -87,7 +89,49 @@ mt5cli -o history.db collect-history \
   --timeframe M1 --flags ALL --if-exists append --with-views
 ```
 
-History orders and deals are fetched per symbol and concatenated, so the symbol filter is applied consistently across all datasets. The `cash_events` view is derived from symbol-filtered `history_deals`, so account-level cash events with empty or non-matching symbols may be excluded. The `rates` table records the requested `timeframe` so appended runs at different timeframes remain distinguishable. The `positions_reconstructed` view aggregates trade deals by `position_id`, excludes positions without closing deals, and uses volume-weighted open/close prices; reversal deals (`DEAL_ENTRY_INOUT`) are reported via `volume_reversal` / `reversal_count` columns and do not contribute to the weighted prices.
+History orders and deals are fetched per symbol and concatenated, so the symbol filter is applied consistently across all datasets. The `cash_events` view is derived from symbol-filtered `history_deals`, so account-level cash events with empty or non-matching symbols may be excluded. The `rates` table records the requested `timeframe` so appended runs at different timeframes remain distinguishable. The `positions_reconstructed` view aggregates trade deals by `position_id`, excludes positions without closing-side entries, and uses volume-weighted open/close prices; reversal deals (`DEAL_ENTRY_INOUT`) are reported via `volume_reversal` / `reversal_count` columns.
+
+### Incremental history SDK
+
+For automated pipelines, use the importable incremental API instead of re-fetching fixed date ranges:
+
+```python
+from pdmt5 import Mt5Config, Mt5DataClient
+from mt5cli import Dataset, update_history, update_history_with_config
+
+# Reuse an already-connected pdmt5 client (does not open/close MT5)
+client = Mt5DataClient(config=Mt5Config(login=12345))
+client.initialize_and_login_mt5()
+try:
+    update_history(
+        client=client,
+        output="history.db",
+        symbols=["EURUSD", "GBPUSD"],
+        datasets={Dataset.rates, Dataset.history_deals},
+        timeframes=["M1", "H1"],  # default: all fixed MT5 timeframes
+        lookback_hours=24,
+        create_rate_views=True,
+        with_views=True,
+        include_account_events=True,
+    )
+finally:
+    client.shutdown()
+
+# Standalone wrapper that opens and closes MT5 for you
+update_history_with_config(
+    output="history.db",
+    symbols=["EURUSD"],
+    config=Mt5Config(login=12345),
+)
+```
+
+- **`collect-history`**: explicit date-range export into SQLite.
+- **`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 `mt5cli.history.resolve_rate_view_name()` / `resolve_rate_view_names()` to map symbols and granularities to existing SQLite compatibility views without creating databases.
+- **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
 

docs/api/history.md

@@ -0,0 +1,166 @@
+# History Collection (SQLite)
+
+::: mt5cli.history
+
+## `collect-history` schema
+
+The `collect-history` command (and the matching `collect_history` SDK function) writes
+selected MT5 datasets into one SQLite database. Each dataset becomes a table; column
+names and types mirror the pdmt5 DataFrame schema for that export, with two additions:
+
+- `symbol` is prepended on every table.
+- `timeframe` is prepended on `rates` so appended runs at different bar sizes stay
+  distinguishable.
+
+SQLite does not declare foreign keys. Rows are linked logically by `symbol`, time
+windows, and (for deals) `position_id` / `order`. Duplicate rows are removed on
+append using dataset-specific keys (for example `ticket` on history tables, or
+`(symbol, timeframe, time)` on rates).
+
+Optional views are created when `--with-views` is set and the `history-deals` dataset
+was written.
+
+### Entity-relationship diagram
+
+Sample layout for a full collection with `--with-views`:
+
+```mermaid
+erDiagram
+    rates {
+        TEXT symbol "dedup key"
+        INTEGER timeframe "dedup key"
+        TEXT time "dedup key"
+        REAL open
+        REAL high
+        REAL low
+        REAL close
+        INTEGER tick_volume
+        INTEGER spread
+        INTEGER real_volume
+    }
+
+    ticks {
+        TEXT symbol "dedup key"
+        TEXT time "dedup key"
+        INTEGER time_msc "dedup key (preferred)"
+        REAL bid
+        REAL ask
+        REAL last
+        INTEGER volume
+        INTEGER flags
+        REAL volume_real
+    }
+
+    history_orders {
+        INTEGER ticket "dedup key"
+        TEXT symbol
+        TEXT time
+        INTEGER type
+        INTEGER state
+        REAL volume_initial
+        REAL price_open
+        REAL price_current
+        INTEGER magic
+    }
+
+    history_deals {
+        INTEGER ticket "dedup key"
+        INTEGER order
+        INTEGER position_id "groups position view"
+        TEXT symbol
+        TEXT time
+        INTEGER type "0/1 trade, else cash event"
+        INTEGER entry "0 IN, 1 OUT, 2 INOUT, 3 OUT_BY"
+        REAL volume
+        REAL price
+        REAL profit
+        REAL commission
+        REAL swap
+        REAL fee
+    }
+
+    cash_events {
+        INTEGER ticket
+        TEXT symbol
+        TEXT time
+        INTEGER type
+        REAL profit
+    }
+
+    positions_reconstructed {
+        INTEGER position_id
+        TEXT symbol
+        TEXT open_time
+        TEXT close_time
+        INTEGER direction
+        REAL volume_open
+        REAL volume_close
+        REAL volume_reversal
+        REAL open_price
+        REAL close_price
+        REAL total_profit
+        INTEGER reversal_count
+        INTEGER deals_count
+    }
+
+    rates ||--o{ history_deals : "symbol (logical)"
+    ticks ||--o{ history_deals : "symbol (logical)"
+    history_orders ||--o{ history_deals : "order ~ ticket (logical)"
+    history_deals ||--|| cash_events : "VIEW: type NOT IN (0,1)"
+    history_deals ||--o{ positions_reconstructed : "VIEW: GROUP BY position_id"
+```
+
+### Tables and views
+
+| Object                    | Kind  | Source               | Notes                                                                                       |
+| ------------------------- | ----- | -------------------- | ------------------------------------------------------------------------------------------- |
+| `rates`                   | table | `copy_rates_range`   | Indexed on `(symbol, timeframe, time)` when columns exist.                                  |
+| `ticks`                   | table | `copy_ticks_range`   | Indexed on `(symbol, time)` when columns exist.                                             |
+| `history_orders`          | table | `history_orders_get` | Fetched per `--symbol`, then concatenated.                                                  |
+| `history_deals`           | table | `history_deals_get`  | Fetched per `--symbol`, then concatenated. Indexed on `(position_id, symbol)` when present. |
+| `cash_events`             | view  | `history_deals`      | Non-trade deal types (deposits, balance ops, etc.). Requires `type` column.                 |
+| `positions_reconstructed` | view  | `history_deals`      | One row per closed `position_id`; volume-weighted prices and reversal stats.                |
+
+Column sets can vary with terminal and pdmt5 version. Views are skipped with a warning
+when required columns are missing.
+
+### Incremental collection
+
+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 legacy
+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`.

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.
 
+### [History Collection (SQLite)](history.md)
+
+SQLite storage helpers for the `collect-history` command schema, incremental updates, deduplication, indexes, and optional views.
+
 ## Architecture Overview
 
 The package follows a simple architecture built on top of pdmt5:
@@ -61,12 +65,18 @@ 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(
@@ -82,6 +92,20 @@ 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/index.md

@@ -22,13 +22,22 @@ 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,
+    minimum_margins,
+    recent_ticks,
+)
+from mt5cli.history import resolve_rate_view_name
 
 # One-off fetch with module-level helpers
 rates = copy_rates_range(
@@ -39,6 +48,13 @@ 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")
+
+# 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()
@@ -92,10 +108,11 @@ mt5cli --login 12345 --password mypass --server MyBroker-Demo \
 
 ### 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
 
@@ -108,6 +125,7 @@ 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
@@ -152,6 +170,8 @@ mt5cli -o history.db collect-history \
 
 History orders and deals are fetched per symbol and concatenated, so the symbol filter is applied consistently across all datasets. The `cash_events` view is derived from symbol-filtered `history_deals`, so account-level cash events with empty or non-matching symbols may be excluded. The `positions_reconstructed` view excludes positions with no closing deal, uses volume-weighted open/close prices, and reports reversal deals (`DEAL_ENTRY_INOUT`) via `volume_reversal` / `reversal_count`.
 
+See the [History schema diagram](api/history.md#entity-relationship-diagram) for a sample ER layout of the resulting database.
+
 ## Global Options
 
 | Option         | Description                                             |

mkdocs.yml

@@ -24,6 +24,7 @@ theme:
   features:
     - content.code.annotate
     - content.code.copy
+    - content.code.mermaid
     - navigation.indexes
     - navigation.sections
     - navigation.tabs
@@ -57,6 +58,7 @@ nav:
       - Overview: api/index.md
       - CLI: api/cli.md
       - SDK: api/sdk.md
+      - History Collection (SQLite): api/history.md
       - Utils: api/utils.md
 
 markdown_extensions:

mt5cli/__init__.py

@@ -16,21 +16,33 @@ from .sdk import (
     history_orders,
     last_error,
     market_book,
+    minimum_margins,
     orders,
     positions,
+    recent_ticks,
     symbol_info,
     symbol_info_tick,
     symbols,
     terminal_info,
+    update_history,
+    update_history_with_config,
 )
 from .sdk import (
     version as mt5_version,
 )
-from .utils import detect_format, export_dataframe
+from .utils import (
+    Dataset,
+    IfExists,
+    detect_format,
+    export_dataframe,
+    export_dataframe_to_sqlite,
+)
 
 __version__ = version(__package__) if __package__ else None
 
 __all__ = [
+    "Dataset",
+    "IfExists",
     "Mt5CliClient",
     "account_info",
     "build_config",
@@ -42,15 +54,20 @@ __all__ = [
     "copy_ticks_range",
     "detect_format",
     "export_dataframe",
+    "export_dataframe_to_sqlite",
     "history_deals",
     "history_orders",
     "last_error",
     "market_book",
+    "minimum_margins",
     "mt5_version",
     "orders",
     "positions",
+    "recent_ticks",
     "symbol_info",
     "symbol_info_tick",
     "symbols",
     "terminal_info",
+    "update_history",
+    "update_history_with_config",
 ]

mt5cli/cli.py

@@ -300,6 +300,44 @@ 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 +373,16 @@ 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,

mt5cli/sdk.py

@@ -5,12 +5,24 @@ from __future__ import annotations
 import logging
 import sqlite3
 from contextlib import contextmanager
-from datetime import datetime
-from pathlib import Path  # noqa: TC003
+from dataclasses import dataclass
+from datetime import UTC, datetime, timedelta
+from pathlib import Path
 from typing import TYPE_CHECKING, Self, TypeVar
 
+import pandas as pd
 from pdmt5 import Mt5Config, Mt5DataClient
 
+from .history import (
+    create_cash_events_view,
+    create_history_indexes,
+    create_positions_reconstructed_view,
+    resolve_history_datasets,
+    resolve_history_tick_flags,
+    resolve_history_timeframes,
+    write_collected_datasets,
+    write_incremental_datasets,
+)
 from .utils import (
     Dataset,
     IfExists,
@@ -20,9 +32,7 @@ from .utils import (
 )
 
 if TYPE_CHECKING:
-    from collections.abc import Callable, Iterator
-
-    import pandas as pd
+    from collections.abc import Callable, Iterator, Sequence
 
 T = TypeVar("T")
 
@@ -42,28 +52,19 @@ __all__ = [
     "history_orders",
     "last_error",
     "market_book",
+    "minimum_margins",
     "orders",
     "positions",
+    "recent_ticks",
     "symbol_info",
     "symbol_info_tick",
     "symbols",
     "terminal_info",
+    "update_history",
+    "update_history_with_config",
     "version",
 ]
 
-_TRADE_DEAL_TYPES: tuple[int, int] = (0, 1)
-_TRADE_DEAL_TYPES_SQL = f"({', '.join(str(value) for value in _TRADE_DEAL_TYPES)})"
-_POSITIONS_VIEW_REQUIRED_COLUMNS: frozenset[str] = frozenset({
-    "position_id",
-    "symbol",
-    "time",
-    "type",
-    "entry",
-    "volume",
-    "price",
-    "profit",
-})
-
 
 def _coerce_timeframe(timeframe: int | str) -> int:
     if isinstance(timeframe, int):
@@ -89,6 +90,89 @@ def _coerce_datetime(value: datetime | str | None) -> datetime | None:
     return parse_datetime(value)
 
 
+def _coerce_tick_time(value: object) -> datetime:
+    if isinstance(value, datetime):
+        return value
+    if isinstance(value, str):
+        return parse_datetime(value)
+    if isinstance(value, (int, float)):
+        return datetime.fromtimestamp(value, tz=UTC)
+    msg = f"Unsupported tick time value: {value!r}"
+    raise TypeError(msg)
+
+
+def _filter_ticks_to_end(frame: pd.DataFrame, end: datetime) -> pd.DataFrame:
+    if frame.empty or "time" not in frame.columns:
+        return frame
+    times = pd.to_datetime(frame["time"], utc=True)
+    return frame.loc[times <= end].reset_index(drop=True)
+
+
+def _fetch_recent_ticks(
+    client: Mt5DataClient,
+    symbol: str,
+    seconds: float,
+    date_to: datetime | None,
+    count: int,
+    flags: int,
+) -> pd.DataFrame:
+    if date_to is not None:
+        end = date_to
+    else:
+        tick = client.symbol_info_tick(symbol)
+        end = _coerce_tick_time(tick.time)
+    start = end - timedelta(seconds=seconds)
+    if count > 0:
+        from_frame = _filter_ticks_to_end(
+            client.copy_ticks_from_as_df(
+                symbol=symbol,
+                date_from=start,
+                count=count,
+                flags=flags,
+            ),
+            end,
+        )
+        if len(from_frame) < count:
+            return from_frame
+    frame = client.copy_ticks_range_as_df(
+        symbol=symbol,
+        date_from=start,
+        date_to=end,
+        flags=flags,
+    )
+    if count > 0 and len(frame) > count:
+        return frame.tail(count).reset_index(drop=True)
+    return frame
+
+
+def _fetch_minimum_margins(client: Mt5DataClient, symbol: str) -> pd.DataFrame:
+    sym = client.symbol_info(symbol)
+    account = client.account_info()
+    tick = client.symbol_info_tick(symbol)
+    volume_min = sym.volume_min
+    buy_margin = client.order_calc_margin(
+        client.mt5.ORDER_TYPE_BUY,
+        symbol,
+        volume_min,
+        tick.ask,
+    )
+    sell_margin = client.order_calc_margin(
+        client.mt5.ORDER_TYPE_SELL,
+        symbol,
+        volume_min,
+        tick.bid,
+    )
+    return pd.DataFrame([
+        {
+            "symbol": symbol,
+            "account_currency": account.currency,
+            "volume_min": volume_min,
+            "buy_margin": buy_margin,
+            "sell_margin": sell_margin,
+        }
+    ])
+
+
 def build_config(
     *,
     path: str | None = None,
@@ -418,326 +502,271 @@ class Mt5CliClient:
         """Return market depth for a symbol."""
         return self._fetch(lambda c: c.market_book_get_as_df(symbol=symbol))
 
+    def recent_ticks(
+        self,
+        symbol: str,
+        seconds: float,
+        *,
+        date_to: datetime | str | None = None,
+        count: int = 10000,
+        flags: int | str = "ALL",
+    ) -> pd.DataFrame:
+        """Return ticks from a recent time window.
 
-def _create_cash_events_view(
-    conn: sqlite3.Connection,
-    deals_columns: set[str],
-) -> bool:
-    """Create the cash_events SQLite view derived from history_deals.
+        Args:
+            symbol: Symbol name.
+            seconds: Lookback window in seconds ending at ``date_to``.
+            date_to: Window end time. When ``None``, uses the latest
+                ``symbol_info_tick().time`` rather than wall-clock now.
+            count: Maximum ticks to return. Values ``<= 0`` return the full
+                window without trimming. Positive values keep the most recent
+                ticks; when the window is sparse, ``copy_ticks_from`` avoids
+                fetching the entire range.
+            flags: Tick flags as ``ALL``, ``INFO``, ``TRADE``, or an integer.
+
+        Returns:
+            Tick DataFrame with MT5 tick columns such as ``time``, ``bid``,
+            ``ask``, ``last``, and ``volume``.
+        """
+        tick_flags = _coerce_tick_flags(flags)
+        end = _coerce_datetime(date_to)
+        return self._fetch(
+            lambda c: _fetch_recent_ticks(
+                c,
+                symbol,
+                seconds,
+                end,
+                count,
+                tick_flags,
+            ),
+        )
+
+    def minimum_margins(self, symbol: str) -> pd.DataFrame:
+        """Return minimum-volume buy and sell margin requirements.
+
+        Args:
+            symbol: Symbol name.
+
+        Returns:
+            One-row DataFrame with columns ``symbol``, ``account_currency``,
+            ``volume_min``, ``buy_margin``, and ``sell_margin``.
+        """
+        return self._fetch(lambda c: _fetch_minimum_margins(c, symbol))
+
+
+def _resolve_incremental_settings(
+    selected_datasets: set[Dataset],
+    timeframes: Sequence[int | str] | None,
+    flags: int | str,
+) -> tuple[list[int], int]:
+    """Resolve dataset-specific incremental update settings.
 
     Returns:
-        True if the view was created, False if required columns are missing.
+        Tuple of resolved rate timeframes and tick copy flags.
+
+    Raises:
+        ValueError: If timeframe or tick flag values are invalid.
     """
-    if "type" not in deals_columns:
-        logger.warning("Skipping cash_events view: history_deals.type is missing")
-        return False
-    conn.execute("DROP VIEW IF EXISTS cash_events")
-    conn.execute(
-        "CREATE VIEW cash_events AS"  # noqa: S608
-        f" SELECT * FROM history_deals WHERE type NOT IN {_TRADE_DEAL_TYPES_SQL}",
-    )
-    return True
+    resolved_timeframes: list[int] = []
+    if Dataset.rates in selected_datasets:
+        try:
+            resolved_timeframes = resolve_history_timeframes(timeframes)
+        except ValueError as exc:
+            msg = str(exc)
+            raise ValueError(msg) from exc
+    resolved_tick_flags = 0
+    if Dataset.ticks in selected_datasets:
+        try:
+            resolved_tick_flags = resolve_history_tick_flags(flags)
+        except ValueError as exc:
+            msg = str(exc)
+            raise ValueError(msg) from exc
+    return resolved_timeframes, resolved_tick_flags
 
 
-def _create_positions_reconstructed_view(
-    conn: sqlite3.Connection,
-    deals_columns: set[str],
-) -> bool:
-    """Create the positions_reconstructed SQLite view derived from history_deals.
+@dataclass(frozen=True)
+class _UpdateHistoryRequest:
+    selected: set[Dataset]
+    end: datetime
+    fallback_start: datetime
+    resolved_timeframes: list[int]
+    resolved_tick_flags: int
+    output_path: Path
+
+
+def _resolve_update_history_request(
+    *,
+    output: Path | str,
+    symbols: Sequence[str],
+    datasets: set[Dataset] | None,
+    timeframes: Sequence[int | str] | None,
+    flags: int | str,
+    lookback_hours: float,
+    date_to: datetime | str | None,
+) -> _UpdateHistoryRequest | None:
+    """Validate and resolve incremental history update inputs.
 
     Returns:
-        True if the view was created, False if required columns are missing.
+        Resolved request parameters, or None when no datasets are selected.
+
+    Raises:
+        ValueError: If symbols are empty, lookback_hours is not positive, or
+            timeframe/flag values are invalid.
     """
-    if not _POSITIONS_VIEW_REQUIRED_COLUMNS.issubset(deals_columns):
-        missing = ", ".join(sorted(_POSITIONS_VIEW_REQUIRED_COLUMNS - deals_columns))
-        logger.warning(
-            "Skipping positions_reconstructed view: history_deals missing columns: %s",
-            missing,
-        )
-        return False
-    conn.execute("DROP VIEW IF EXISTS positions_reconstructed")
-    conn.execute(
-        "CREATE VIEW positions_reconstructed AS"  # noqa: S608
-        " SELECT"
-        " position_id,"
-        " symbol,"
-        " MIN(CASE WHEN entry = 0 THEN time END) AS open_time,"
-        " MAX(CASE WHEN entry IN (1, 2, 3) THEN time END) AS close_time,"
-        " MIN(CASE WHEN entry = 0 THEN type END) AS direction,"
-        " SUM(CASE WHEN entry = 0 THEN volume ELSE 0 END) AS volume_open,"
-        " SUM(CASE WHEN entry IN (1, 3) THEN volume ELSE 0 END) AS volume_close,"
-        " SUM(CASE WHEN entry = 2 THEN volume ELSE 0 END) AS volume_reversal,"
-        " CASE"
-        " WHEN SUM(CASE WHEN entry = 0 THEN volume ELSE 0 END) > 0"
-        " THEN SUM(CASE WHEN entry = 0 THEN price * volume ELSE 0 END)"
-        " / SUM(CASE WHEN entry = 0 THEN volume ELSE 0 END)"
-        " END AS open_price,"
-        " CASE"
-        " WHEN SUM(CASE WHEN entry IN (1, 3) THEN volume ELSE 0 END) > 0"
-        " THEN SUM(CASE WHEN entry IN (1, 3) THEN price * volume ELSE 0 END)"
-        " / SUM(CASE WHEN entry IN (1, 3) THEN volume ELSE 0 END)"
-        " END AS close_price,"
-        " SUM(profit) AS total_profit,"
-        " SUM(CASE WHEN entry = 2 THEN 1 ELSE 0 END) AS reversal_count,"
-        " COUNT(*) AS deals_count"
-        " FROM history_deals"
-        f" WHERE type IN {_TRADE_DEAL_TYPES_SQL} AND position_id != 0"
-        " GROUP BY position_id, symbol"
-        " HAVING SUM(CASE WHEN entry IN (1, 3) THEN 1 ELSE 0 END) > 0",
-    )
-    return True
+    if lookback_hours <= 0:
+        msg = "lookback_hours must be positive."
+        raise ValueError(msg)
+    selected = resolve_history_datasets(datasets)
+    if not selected:
+        logger.info("Skipping SQLite history update: no datasets selected.")
+        return None
+    if not symbols:
+        msg = "At least one symbol is required."
+        raise ValueError(msg)
 
-
-def _write_frame_to_sqlite(
-    conn: sqlite3.Connection,
-    frame: pd.DataFrame,
-    table_name: str,
-    if_exists: IfExists,
-) -> bool:
-    """Write a non-empty-schema frame to SQLite.
-
-    Returns:
-        True if a table was written, False if the frame had no columns.
-    """
-    if len(frame.columns) == 0:
-        logger.warning("Skipping %s: dataset returned no columns", table_name)
-        return False
-    frame.to_sql(  # type: ignore[reportUnknownMemberType]
-        table_name,
-        conn,
-        if_exists=if_exists.value,
-        index=False,
-        chunksize=50_000,
-        method="multi",
-    )
-    return True
-
-
-def _create_collect_history_indexes(
-    conn: sqlite3.Connection,
-    written_columns: dict[Dataset, set[str]],
-) -> None:
-    """Create useful indexes for collected history tables when present."""
-    if {"symbol", "time"}.issubset(written_columns.get(Dataset.rates, set())):
-        conn.execute(
-            "CREATE INDEX IF NOT EXISTS idx_rates_symbol_time ON rates(symbol, time)",
-        )
-    if {"symbol", "time"}.issubset(written_columns.get(Dataset.ticks, set())):
-        conn.execute(
-            "CREATE INDEX IF NOT EXISTS idx_ticks_symbol_time ON ticks(symbol, time)",
-        )
-    if {"position_id", "symbol"}.issubset(
-        written_columns.get(Dataset.history_deals, set())
-    ):
-        conn.execute(
-            "CREATE INDEX IF NOT EXISTS idx_history_deals_position_symbol"
-            " ON history_deals(position_id, symbol)",
-        )
-
-
-def _record_written_columns(
-    written_columns: dict[Dataset, set[str]],
-    dataset: Dataset,
-    frame: pd.DataFrame,
-) -> None:
-    """Remember columns for datasets written during streaming collection."""
-    columns = set(frame.columns)
-    if dataset in written_columns:
-        written_columns[dataset].update(columns)
+    if date_to is not None:
+        resolved_end = _coerce_datetime(date_to)
     else:
-        written_columns[dataset] = columns
-
-
-def _write_streamed_frame(
-    conn: sqlite3.Connection,
-    frame: pd.DataFrame,
-    dataset: Dataset,
-    table_exists: bool,
-    if_exists: IfExists,
-    written_columns: dict[Dataset, set[str]],
-) -> bool:
-    """Write one streamed dataset frame and track table state.
-
-    Returns:
-        True if the dataset table exists after this write attempt.
-    """
-    write_mode = IfExists.APPEND if table_exists else if_exists
-    if _write_frame_to_sqlite(
-        conn,
-        frame,
-        dataset.table_name,
-        write_mode,
-    ):
-        _record_written_columns(written_columns, dataset, frame)
-        return True
-    return table_exists
-
-
-def _write_rates_dataset(
-    conn: sqlite3.Connection,
-    client: Mt5DataClient,
-    symbols: list[str],
-    timeframe: int,
-    date_from: datetime,
-    date_to: datetime,
-    if_exists: IfExists,
-    written_columns: dict[Dataset, set[str]],
-) -> bool:
-    """Stream rates frames into SQLite.
-
-    Returns:
-        True if the rates table was written.
-    """
-    table_exists = False
-    for sym in symbols:
-        frame = client.copy_rates_range_as_df(
-            symbol=sym,
-            timeframe=timeframe,
-            date_from=date_from,
-            date_to=date_to,
-        )
-        frame.insert(0, "symbol", sym)
-        frame.insert(1, "timeframe", timeframe)
-        table_exists = _write_streamed_frame(
-            conn,
-            frame,
-            Dataset.rates,
-            table_exists,
-            if_exists,
-            written_columns,
-        )
-    return table_exists
-
-
-def _write_ticks_dataset(
-    conn: sqlite3.Connection,
-    client: Mt5DataClient,
-    symbols: list[str],
-    flags: int,
-    date_from: datetime,
-    date_to: datetime,
-    if_exists: IfExists,
-    written_columns: dict[Dataset, set[str]],
-) -> bool:
-    """Stream ticks frames into SQLite.
-
-    Returns:
-        True if the ticks table was written.
-    """
-    table_exists = False
-    for sym in symbols:
-        frame = client.copy_ticks_range_as_df(
-            symbol=sym,
-            date_from=date_from,
-            date_to=date_to,
-            flags=flags,
-        )
-        frame.insert(0, "symbol", sym)
-        table_exists = _write_streamed_frame(
-            conn,
-            frame,
-            Dataset.ticks,
-            table_exists,
-            if_exists,
-            written_columns,
-        )
-    return table_exists
-
-
-def _write_history_dataset(
-    conn: sqlite3.Connection,
-    fetch: Callable[..., pd.DataFrame],
-    dataset: Dataset,
-    symbols: list[str],
-    date_from: datetime,
-    date_to: datetime,
-    if_exists: IfExists,
-    written_columns: dict[Dataset, set[str]],
-) -> bool:
-    """Stream a history dataset into SQLite with exact symbol filtering.
-
-    Returns:
-        True if the history table was written.
-    """
-    table_exists = False
-    for sym in symbols:
-        frame = fetch(date_from=date_from, date_to=date_to, symbol=sym)
-        if "symbol" in frame.columns:
-            frame = frame[frame["symbol"] == sym]
-        table_exists = _write_streamed_frame(
-            conn,
-            frame,
-            dataset,
-            table_exists,
-            if_exists,
-            written_columns,
-        )
-    return table_exists
-
-
-def _write_collected_datasets(
-    conn: sqlite3.Connection,
-    client: Mt5DataClient,
-    symbols: list[str],
-    datasets: set[Dataset],
-    timeframe: int,
-    flags: int,
-    date_from: datetime,
-    date_to: datetime,
-    if_exists: IfExists,
-) -> tuple[set[Dataset], dict[Dataset, set[str]]]:
-    """Collect selected datasets and stream each symbol frame into SQLite.
-
-    Returns:
-        Written datasets and their columns.
-    """
-    written_columns: dict[Dataset, set[str]] = {}
-    written_tables: set[Dataset] = set()
-    if Dataset.rates in datasets and _write_rates_dataset(
-        conn,
-        client,
-        symbols,
-        timeframe,
-        date_from,
-        date_to,
-        if_exists,
-        written_columns,
-    ):
-        written_tables.add(Dataset.rates)
-    if Dataset.ticks in datasets and _write_ticks_dataset(
-        conn,
-        client,
-        symbols,
+        resolved_end = datetime.now(UTC)
+    end = resolved_end if resolved_end is not None else datetime.now(UTC)
+    fallback_start = end - timedelta(hours=lookback_hours)
+    resolved_timeframes, resolved_tick_flags = _resolve_incremental_settings(
+        selected,
+        timeframes,
         flags,
-        date_from,
-        date_to,
-        if_exists,
-        written_columns,
-    ):
-        written_tables.add(Dataset.ticks)
-    if Dataset.history_orders in datasets and _write_history_dataset(
-        conn,
-        client.history_orders_get_as_df,
-        Dataset.history_orders,
-        symbols,
-        date_from,
-        date_to,
-        if_exists,
-        written_columns,
-    ):
-        written_tables.add(Dataset.history_orders)
-    if Dataset.history_deals in datasets and _write_history_dataset(
-        conn,
-        client.history_deals_get_as_df,
-        Dataset.history_deals,
-        symbols,
-        date_from,
-        date_to,
-        if_exists,
-        written_columns,
-    ):
-        written_tables.add(Dataset.history_deals)
-    return written_tables, written_columns
+    )
+    return _UpdateHistoryRequest(
+        selected=selected,
+        end=end,
+        fallback_start=fallback_start,
+        resolved_timeframes=resolved_timeframes,
+        resolved_tick_flags=resolved_tick_flags,
+        output_path=Path(output),
+    )
+
+
+def update_history(  # noqa: PLR0913
+    *,
+    client: Mt5DataClient,
+    output: Path | str,
+    symbols: Sequence[str],
+    datasets: set[Dataset] | None = None,
+    timeframes: Sequence[int | str] | None = None,
+    flags: int | str = "ALL",
+    lookback_hours: float = 24.0,
+    date_to: datetime | str | None = None,
+    deduplicate: bool = True,
+    create_rate_views: bool = True,
+    with_views: bool = False,
+    include_account_events: bool = True,
+) -> None:
+    """Incrementally append MT5 history into a SQLite database.
+
+    Uses an already-connected ``Mt5DataClient`` and does not create or close
+    the MT5 connection. For first-time tables, data is fetched from
+    ``date_to - lookback_hours``. Subsequent runs resume from existing
+    ``MAX(time)`` per symbol (and timeframe for rates); when
+    ``include_account_events=True``, account-level deals use a separate cursor
+    over ``type NOT IN (0, 1)`` / empty-symbol rows.
+
+    Args:
+        client: Connected MT5 data client.
+        output: SQLite database path.
+        symbols: Symbols to update.
+        datasets: Datasets to include (defaults to all).
+        timeframes: Rate timeframes to update (defaults to all fixed MT5
+            timeframes when None).
+        flags: Tick copy flags as integer or name (e.g. ``ALL``).
+        lookback_hours: First-run lookback when a table has no prior rows.
+        date_to: Optional update end datetime. Defaults to now (UTC).
+        deduplicate: Remove duplicate rows after append, keeping latest ROWID.
+        create_rate_views: Create ``rate_<symbol>__<timeframe>`` views.
+        with_views: Create ``cash_events`` and ``positions_reconstructed`` views.
+        include_account_events: Include account-level cash events in
+            ``history_deals`` when True.
+    """
+    request = _resolve_update_history_request(
+        output=output,
+        symbols=symbols,
+        datasets=datasets,
+        timeframes=timeframes,
+        flags=flags,
+        lookback_hours=lookback_hours,
+        date_to=date_to,
+    )
+    if request is None:
+        return
+    logger.info(
+        "Updating history in SQLite: symbols=%s, datasets=%s, path=%s",
+        list(symbols),
+        sorted(dataset.value for dataset in request.selected),
+        request.output_path,
+    )
+    with sqlite3.connect(request.output_path) as conn:
+        conn.execute("PRAGMA journal_mode=WAL")
+        conn.execute("PRAGMA synchronous=NORMAL")
+        write_incremental_datasets(
+            conn,
+            client,
+            symbols,
+            request.selected,
+            request.resolved_timeframes,
+            request.resolved_tick_flags,
+            request.fallback_start,
+            request.end,
+            deduplicate=deduplicate,
+            create_rate_views=create_rate_views,
+            with_views=with_views,
+            include_account_events=include_account_events,
+        )
+
+
+def update_history_with_config(  # noqa: PLR0913
+    *,
+    output: Path | str,
+    symbols: Sequence[str],
+    config: Mt5Config | None = None,
+    datasets: set[Dataset] | None = None,
+    timeframes: Sequence[int | str] | None = None,
+    flags: int | str = "ALL",
+    lookback_hours: float = 24.0,
+    date_to: datetime | str | None = None,
+    deduplicate: bool = True,
+    create_rate_views: bool = True,
+    with_views: bool = False,
+    include_account_events: bool = True,
+) -> None:
+    """Incrementally append MT5 history, opening and closing the MT5 connection.
+
+    Convenience wrapper around :func:`update_history` for standalone use.
+    """
+    request = _resolve_update_history_request(
+        output=output,
+        symbols=symbols,
+        datasets=datasets,
+        timeframes=timeframes,
+        flags=flags,
+        lookback_hours=lookback_hours,
+        date_to=date_to,
+    )
+    if request is None:
+        return
+    mt5_config = config or build_config()
+    with _connected_client(mt5_config) as client:
+        update_history(
+            client=client,
+            output=output,
+            symbols=symbols,
+            datasets=datasets,
+            timeframes=timeframes,
+            flags=flags,
+            lookback_hours=lookback_hours,
+            date_to=date_to,
+            deduplicate=deduplicate,
+            create_rate_views=create_rate_views,
+            with_views=with_views,
+            include_account_events=include_account_events,
+        )
 
 
 def collect_history(
@@ -776,7 +805,7 @@ def collect_history(
     with _connected_client(mt5_config) as client, sqlite3.connect(output) as conn:
         conn.execute("PRAGMA journal_mode=WAL")
         conn.execute("PRAGMA synchronous=NORMAL")
-        written_tables, written_columns = _write_collected_datasets(
+        written_tables, written_columns = write_collected_datasets(
             conn,
             client,
             symbols,
@@ -787,10 +816,10 @@ def collect_history(
             end,
             if_exists,
         )
-        _create_collect_history_indexes(conn, written_columns)
+        create_history_indexes(conn, written_columns)
         if with_views and Dataset.history_deals in written_tables:
-            _create_cash_events_view(conn, written_columns[Dataset.history_deals])
-            _create_positions_reconstructed_view(
+            create_cash_events_view(conn, written_columns[Dataset.history_deals])
+            create_positions_reconstructed_view(
                 conn,
                 written_columns[Dataset.history_deals],
             )
@@ -1021,3 +1050,37 @@ def market_book(
 ) -> pd.DataFrame:
     """Return market depth for a symbol."""
     return _make_client(config=config).market_book(symbol)
+
+
+def recent_ticks(
+    symbol: str,
+    seconds: float,
+    *,
+    date_to: datetime | str | None = None,
+    count: int = 10000,
+    flags: int | str = "ALL",
+    config: Mt5Config | None = None,
+) -> pd.DataFrame:
+    """Return ticks from a recent time window ending at ``date_to`` or now.
+
+    See ``Mt5CliClient.recent_ticks`` for parameter and return details.
+    """
+    return _make_client(config=config).recent_ticks(
+        symbol,
+        seconds,
+        date_to=date_to,
+        count=count,
+        flags=flags,
+    )
+
+
+def minimum_margins(
+    symbol: str,
+    *,
+    config: Mt5Config | None = None,
+) -> pd.DataFrame:
+    """Return minimum-volume buy and sell margin requirements.
+
+    See ``Mt5CliClient.minimum_margins`` for return details.
+    """
+    return _make_client(config=config).minimum_margins(symbol)

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 = "0.4.0"
+version = "0.4.3"
 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"}]
@@ -124,6 +124,7 @@ ignore = [
 ]
 
 [tool.ruff.lint.per-file-ignores]
+"mt5cli/history.py" = ["TC003"]
 "tests/**/*.py" = [
   "DOC201",   # Missing return documentation
   "DOC501",   # Raised exception missing from docstring

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
 
@@ -316,6 +316,65 @@ 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,
@@ -1089,7 +1148,7 @@ class TestCollectHistory:
         assert all(row[0] not in {0, 1} for row in cash)
         # Position 100 (BUY 1@1.10 + BUY 3@1.20 then SELL 4@1.50) is closed.
         # Position 200 (BUY 2@2.00 then SELL 2@2.20) is closed.
-        # Position 300 (open-only) and 400 (reversal-only) are excluded.
+        # Position 400 (reversal-only with non-trade deal type) stays excluded.
         assert set(positions) == {100, 200, 500, 600}
         pos_100 = positions[100]
         tol = 1e-9
@@ -1106,10 +1165,10 @@ class TestCollectHistory:
         assert abs(pos_500[5] - 1.05) < tol
         pos_600 = positions[600]
         assert abs(pos_600[1] - 3.0) < tol
-        assert abs(pos_600[2] - 3.0) < tol
+        assert abs(pos_600[2] - 4.0) < tol  # reversal + close volumes
         assert abs(pos_600[3] - 1.0) < tol
         assert abs(pos_600[4] - 1.10) < tol
-        assert abs(pos_600[5] - 1.40) < tol
+        assert abs(pos_600[5] - 3.5475) < tol
         assert pos_600[6] == 1
 
     def test_collect_history_filters_history_symbols_exactly(

tests/test_sdk.py

@@ -4,7 +4,7 @@ from __future__ import annotations
 
 import logging
 import sqlite3
-from datetime import UTC, datetime
+from datetime import UTC, datetime, timedelta
 from typing import TYPE_CHECKING
 from unittest.mock import MagicMock
 
@@ -16,6 +16,7 @@ if TYPE_CHECKING:
     from pathlib import Path
 
 from mt5cli import sdk
+from mt5cli.history import DEFAULT_HISTORY_TIMEFRAMES
 from mt5cli.sdk import (
     Mt5CliClient,
     account_info,
@@ -30,12 +31,16 @@ from mt5cli.sdk import (
     history_orders,
     last_error,
     market_book,
+    minimum_margins,
     orders,
     positions,
+    recent_ticks,
     symbol_info,
     symbol_info_tick,
     symbols,
     terminal_info,
+    update_history,
+    update_history_with_config,
     version,
 )
 from mt5cli.utils import Dataset
@@ -464,3 +469,514 @@ class TestCollectHistory:
             }
         assert "cash_events" not in views
         assert "positions_reconstructed" not in views
+
+
+class TestUpdateHistory:
+    """Tests for update_history SDK functions."""
+
+    @pytest.fixture
+    def connected_client(self) -> MagicMock:
+        """Create a connected mock client without MT5 lifecycle patching."""
+        return MagicMock()
+
+    def test_update_history_appends_incrementally(
+        self,
+        connected_client: MagicMock,
+        mocker: MockerFixture,
+        tmp_path: Path,
+    ) -> None:
+        """Test sequential SQLite history updates use existing max timestamps."""
+        date_to = datetime(2024, 1, 2, tzinfo=UTC)
+        first_expected_start = datetime(2024, 1, 1, tzinfo=UTC)
+        second_expected_start = datetime(2024, 1, 1, 12, tzinfo=UTC)
+        rate_starts: list[datetime] = []
+        deal_starts: list[datetime] = []
+
+        def make_rates(**kwargs: object) -> pd.DataFrame:
+            assert kwargs["symbol"] == "EURUSD"
+            assert kwargs["timeframe"] == 1
+            assert kwargs["date_to"] == date_to
+            rate_starts.append(kwargs["date_from"])  # type: ignore[arg-type]
+            return pd.DataFrame({
+                "time": ["2024-01-01T12:00:00+00:00"],
+                "open": [1.0 + len(rate_starts) / 10],
+            })
+
+        def make_deals(**kwargs: object) -> pd.DataFrame:
+            assert kwargs["date_to"] == date_to
+            deal_starts.append(kwargs["date_from"])  # type: ignore[arg-type]
+            return pd.DataFrame({
+                "ticket": [10],
+                "position_id": [100],
+                "symbol": ["EURUSD"],
+                "time": ["2024-01-01T12:00:00+00:00"],
+                "type": [0],
+                "entry": [0],
+                "volume": [1.0],
+                "price": [1.1],
+                "profit": [0.0],
+            })
+
+        connected_client.copy_rates_range_as_df.side_effect = make_rates
+        connected_client.history_deals_get_as_df.side_effect = make_deals
+        mocker.patch("mt5cli.sdk.Mt5DataClient")
+        output = tmp_path / "incremental-history.db"
+
+        for _ in range(2):
+            update_history(
+                client=connected_client,
+                output=output,
+                symbols=["EURUSD"],
+                datasets={Dataset.rates, Dataset.history_deals},
+                timeframes=["M1"],
+                lookback_hours=24,
+                date_to=date_to,
+                with_views=True,
+            )
+
+        assert rate_starts == [first_expected_start, second_expected_start]
+        assert deal_starts == [first_expected_start, first_expected_start]
+        connected_client.initialize_and_login_mt5.assert_not_called()
+        connected_client.shutdown.assert_not_called()
+        with sqlite3.connect(output) as conn:
+            assert conn.execute("SELECT COUNT(*) FROM rates").fetchone() == (1,)
+            assert conn.execute("SELECT open FROM rates").fetchone() == (1.2,)
+            assert conn.execute(
+                "SELECT COUNT(*) FROM history_deals",
+            ).fetchone() == (1,)
+            assert conn.execute(
+                "SELECT name FROM sqlite_master WHERE name = 'cash_events'",
+            ).fetchone() == ("cash_events",)
+
+    def test_update_history_rejects_invalid_inputs(
+        self,
+        connected_client: MagicMock,
+        tmp_path: Path,
+    ) -> None:
+        """Test validation errors for incremental history updates."""
+        output = tmp_path / "invalid-update.db"
+        with pytest.raises(ValueError, match="At least one symbol"):
+            update_history(
+                client=connected_client,
+                output=output,
+                symbols=[],
+            )
+        with pytest.raises(ValueError, match="lookback_hours must be positive"):
+            update_history(
+                client=connected_client,
+                output=output,
+                symbols=["EURUSD"],
+                lookback_hours=0,
+            )
+        with pytest.raises(ValueError, match="Invalid timeframe"):
+            update_history(
+                client=connected_client,
+                output=output,
+                symbols=["EURUSD"],
+                datasets={Dataset.rates},
+                timeframes=["BAD"],
+            )
+        with pytest.raises(ValueError, match="Invalid tick flags"):
+            update_history(
+                client=connected_client,
+                output=output,
+                symbols=["EURUSD"],
+                datasets={Dataset.ticks},
+                flags="BAD",
+            )
+
+    def test_update_history_noops_for_empty_datasets(
+        self,
+        connected_client: MagicMock,
+        mocker: MockerFixture,
+        tmp_path: Path,
+    ) -> None:
+        """Test empty dataset selection skips MT5 and SQLite writes."""
+        writer = mocker.patch("mt5cli.sdk.write_incremental_datasets")
+        connect = mocker.patch("mt5cli.sdk.sqlite3.connect")
+        update_history(
+            client=connected_client,
+            output=tmp_path / "empty-datasets.db",
+            symbols=["EURUSD"],
+            datasets=set(),
+        )
+        writer.assert_not_called()
+        connect.assert_not_called()
+
+    def test_update_history_uses_all_default_timeframes(
+        self,
+        connected_client: MagicMock,
+        mocker: MockerFixture,
+        tmp_path: Path,
+    ) -> None:
+        """Test that timeframes=None writes rates for all default MT5 timeframes."""
+        timeframes_written: list[int] = []
+
+        def capture(
+            *args: object,
+            **_kwargs: object,
+        ) -> tuple[set[Dataset], dict[Dataset, set[str]]]:
+            timeframes_written.extend(args[4])  # type: ignore[arg-type]
+            return set(), {}
+
+        mocker.patch("mt5cli.sdk.write_incremental_datasets", side_effect=capture)
+        update_history(
+            client=connected_client,
+            output=tmp_path / "default-timeframes.db",
+            symbols=["EURUSD"],
+            datasets={Dataset.rates},
+            timeframes=None,
+            lookback_hours=1,
+            date_to=datetime(2024, 1, 1, tzinfo=UTC),
+        )
+        assert len(timeframes_written) == len(DEFAULT_HISTORY_TIMEFRAMES)
+
+    def test_update_history_uses_specified_timeframes(
+        self,
+        connected_client: MagicMock,
+        mocker: MockerFixture,
+        tmp_path: Path,
+    ) -> None:
+        """Test explicit timeframes limit rate updates."""
+        timeframes_written: list[int] = []
+
+        def capture(
+            *args: object,
+            **_kwargs: object,
+        ) -> tuple[set[Dataset], dict[Dataset, set[str]]]:
+            timeframes_written.extend(args[4])  # type: ignore[arg-type]
+            return set(), {}
+
+        mocker.patch("mt5cli.sdk.write_incremental_datasets", side_effect=capture)
+        update_history(
+            client=connected_client,
+            output=tmp_path / "specific-timeframes.db",
+            symbols=["EURUSD"],
+            datasets={Dataset.rates},
+            timeframes=["M1", "H1"],
+            lookback_hours=1,
+            date_to=datetime(2024, 1, 1, tzinfo=UTC),
+        )
+        assert timeframes_written == [1, 16385]
+
+    def test_update_history_updates_ticks_and_orders(
+        self,
+        connected_client: MagicMock,
+        tmp_path: Path,
+    ) -> None:
+        """Test incremental update writes selected ticks and orders datasets."""
+        date_to = datetime(2024, 1, 2, tzinfo=UTC)
+        expected_start = datetime(2024, 1, 1, tzinfo=UTC)
+
+        def make_ticks(**kwargs: object) -> pd.DataFrame:
+            assert kwargs["symbol"] == "EURUSD"
+            assert kwargs["date_from"] == expected_start
+            assert kwargs["date_to"] == date_to
+            assert kwargs["flags"] == 1
+            return pd.DataFrame({
+                "time": ["2024-01-01T12:00:00+00:00"],
+                "time_msc": [1_704_110_400_000],
+                "bid": [1.1],
+            })
+
+        def make_orders(**kwargs: object) -> pd.DataFrame:
+            assert kwargs["symbol"] == "EURUSD"
+            assert kwargs["date_from"] == expected_start
+            assert kwargs["date_to"] == date_to
+            return pd.DataFrame({
+                "ticket": [1],
+                "symbol": ["EURUSD"],
+                "time": ["2024-01-01T12:00:00+00:00"],
+                "type": [0],
+            })
+
+        connected_client.copy_ticks_range_as_df.side_effect = make_ticks
+        connected_client.history_orders_get_as_df.side_effect = make_orders
+        output = tmp_path / "ticks-orders.db"
+        update_history(
+            client=connected_client,
+            output=output,
+            symbols=["EURUSD"],
+            datasets={Dataset.ticks, Dataset.history_orders},
+            lookback_hours=24,
+            date_to=date_to,
+        )
+        with sqlite3.connect(output) as conn:
+            assert conn.execute("SELECT COUNT(*) FROM ticks").fetchone() == (1,)
+            assert conn.execute(
+                "SELECT COUNT(*) FROM history_orders",
+            ).fetchone() == (1,)
+
+    def test_update_history_with_config_opens_and_closes_connection(
+        self,
+        mocker: MockerFixture,
+        tmp_path: Path,
+    ) -> None:
+        """Test update_history_with_config manages MT5 connection lifecycle."""
+        mock_client = MagicMock()
+        mocker.patch("mt5cli.sdk.Mt5DataClient", return_value=mock_client)
+        updater = mocker.patch("mt5cli.sdk.update_history")
+        update_history_with_config(
+            output=tmp_path / "config-wrapper.db",
+            symbols=["EURUSD"],
+            datasets={Dataset.history_deals},
+            timeframes=["M1"],
+            flags="ALL",
+            lookback_hours=1,
+            date_to=datetime(2024, 1, 1, tzinfo=UTC),
+            deduplicate=False,
+            create_rate_views=False,
+            with_views=True,
+            include_account_events=False,
+        )
+        mock_client.initialize_and_login_mt5.assert_called_once()
+        mock_client.shutdown.assert_called_once()
+        updater.assert_called_once()
+        assert updater.call_args.kwargs == {
+            "client": mock_client,
+            "output": tmp_path / "config-wrapper.db",
+            "symbols": ["EURUSD"],
+            "datasets": {Dataset.history_deals},
+            "timeframes": ["M1"],
+            "flags": "ALL",
+            "lookback_hours": 1,
+            "date_to": datetime(2024, 1, 1, tzinfo=UTC),
+            "deduplicate": False,
+            "create_rate_views": False,
+            "with_views": True,
+            "include_account_events": False,
+        }
+
+    def test_update_history_with_config_validates_before_connecting(
+        self,
+        mocker: MockerFixture,
+        tmp_path: Path,
+    ) -> None:
+        """Test invalid inputs fail before MT5 is initialized."""
+        mock_client = MagicMock()
+        mocker.patch("mt5cli.sdk.Mt5DataClient", return_value=mock_client)
+        with pytest.raises(ValueError, match="lookback_hours must be positive"):
+            update_history_with_config(
+                output=tmp_path / "invalid-config.db",
+                symbols=["EURUSD"],
+                lookback_hours=0,
+            )
+        mock_client.initialize_and_login_mt5.assert_not_called()
+        mock_client.shutdown.assert_not_called()
+
+    def test_update_history_with_config_noops_for_empty_datasets(
+        self,
+        mocker: MockerFixture,
+        tmp_path: Path,
+    ) -> None:
+        """Test empty dataset selection skips MT5 initialization."""
+        mock_client = MagicMock()
+        mocker.patch("mt5cli.sdk.Mt5DataClient", return_value=mock_client)
+        updater = mocker.patch("mt5cli.sdk.update_history")
+        update_history_with_config(
+            output=tmp_path / "empty-config.db",
+            symbols=["EURUSD"],
+            datasets=set(),
+        )
+        mock_client.initialize_and_login_mt5.assert_not_called()
+        mock_client.shutdown.assert_not_called()
+        updater.assert_not_called()
+
+    def test_update_history_defaults_date_to_now(
+        self,
+        connected_client: MagicMock,
+        mocker: MockerFixture,
+        tmp_path: Path,
+    ) -> None:
+        """Test update_history uses current UTC time when date_to is omitted."""
+        captured: dict[str, datetime] = {}
+
+        def capture(
+            *args: object,
+            **_kwargs: object,
+        ) -> tuple[set[Dataset], dict[Dataset, set[str]]]:
+            captured["end"] = args[7]  # type: ignore[assignment]
+            return set(), {}
+
+        mocker.patch("mt5cli.sdk.write_incremental_datasets", side_effect=capture)
+        before = datetime.now(UTC)
+        update_history(
+            client=connected_client,
+            output=tmp_path / "now-default.db",
+            symbols=["EURUSD"],
+            datasets={Dataset.rates},
+            timeframes=["M1"],
+            lookback_hours=12,
+        )
+        after = datetime.now(UTC)
+        assert before <= captured["end"] <= after
+
+
+class TestRecentTicks:
+    """Tests for recent_ticks helper."""
+
+    def test_recent_ticks_uses_explicit_date_to_window(
+        self,
+        mocker: MockerFixture,
+    ) -> None:
+        """Test recent_ticks fetches the requested trailing window."""
+        client = MagicMock()
+        end = datetime(2024, 1, 2, 12, 0, 0, tzinfo=UTC)
+        client.copy_ticks_from_as_df.return_value = pd.DataFrame({
+            "time": [end],
+            "bid": [1.0],
+        })
+        mocker.patch("mt5cli.sdk.Mt5DataClient", return_value=client)
+        result = recent_ticks(
+            "EURUSD",
+            60,
+            date_to=end,
+            count=100,
+            flags="INFO",
+            config=build_config(login=123),
+        )
+        assert isinstance(result, pd.DataFrame)
+        client.copy_ticks_from_as_df.assert_called_once_with(
+            symbol="EURUSD",
+            date_from=end - timedelta(seconds=60),
+            count=100,
+            flags=2,
+        )
+        client.copy_ticks_range_as_df.assert_not_called()
+
+    def test_recent_ticks_uses_latest_tick_when_date_to_omitted(
+        self,
+        mocker: MockerFixture,
+    ) -> None:
+        """Test recent_ticks anchors the window on the latest tick time."""
+        client = MagicMock()
+        tick = MagicMock()
+        tick.time = datetime(2024, 1, 2, 12, 0, 0, tzinfo=UTC)
+        client.symbol_info_tick.return_value = tick
+        client.copy_ticks_from_as_df.return_value = pd.DataFrame({
+            "time": [1, 2],
+            "bid": [1.0, 1.1],
+        })
+        client.copy_ticks_range_as_df.return_value = pd.DataFrame({
+            "time": [1, 2, 3],
+            "bid": [1.0, 1.1, 1.2],
+        })
+        mocker.patch("mt5cli.sdk.Mt5DataClient", return_value=client)
+        result = Mt5CliClient().recent_ticks("EURUSD", 30, count=2, flags="ALL")
+        assert len(result) == 2
+        client.symbol_info_tick.assert_called_once_with("EURUSD")
+        client.copy_ticks_from_as_df.assert_called_once()
+        _, kwargs = client.copy_ticks_range_as_df.call_args
+        assert kwargs["symbol"] == "EURUSD"
+        assert kwargs["date_to"] == tick.time
+        assert kwargs["date_from"] == tick.time - timedelta(seconds=30)
+        assert kwargs["flags"] == 1
+
+    def test_recent_ticks_rejects_unsupported_tick_time(
+        self,
+        mocker: MockerFixture,
+    ) -> None:
+        """Test recent_ticks raises when the latest tick time is unsupported."""
+        client = MagicMock()
+        tick = MagicMock()
+        tick.time = object()
+        client.symbol_info_tick.return_value = tick
+        mocker.patch("mt5cli.sdk.Mt5DataClient", return_value=client)
+        with pytest.raises(TypeError, match="Unsupported tick time value"):
+            Mt5CliClient().recent_ticks("EURUSD", 30)
+
+    @pytest.mark.parametrize(
+        "tick_time",
+        [
+            "2024-01-02T12:00:00+00:00",
+            1704196800,
+        ],
+    )
+    def test_recent_ticks_coerces_string_and_unix_tick_times(
+        self,
+        mocker: MockerFixture,
+        tick_time: str | int,
+    ) -> None:
+        """Test recent_ticks accepts string and unix tick timestamps."""
+        client = MagicMock()
+        tick = MagicMock()
+        tick.time = tick_time
+        client.symbol_info_tick.return_value = tick
+        expected_end = (
+            datetime(2024, 1, 2, 12, 0, 0, tzinfo=UTC)
+            if isinstance(tick_time, str)
+            else datetime.fromtimestamp(tick_time, tz=UTC)
+        )
+        client.copy_ticks_from_as_df.return_value = pd.DataFrame({
+            "time": [expected_end],
+        })
+        mocker.patch("mt5cli.sdk.Mt5DataClient", return_value=client)
+        Mt5CliClient().recent_ticks("EURUSD", 30)
+        _, kwargs = client.copy_ticks_from_as_df.call_args
+        assert kwargs["date_from"] == expected_end - timedelta(seconds=30)
+
+    def test_recent_ticks_returns_full_frame_when_count_not_positive(
+        self,
+        mocker: MockerFixture,
+    ) -> None:
+        """Test non-positive count returns the full range without trimming."""
+        client = MagicMock()
+        end = datetime(2024, 1, 2, 12, 0, 0, tzinfo=UTC)
+        client.copy_ticks_range_as_df.return_value = pd.DataFrame({
+            "time": [1, 2, 3],
+            "bid": [1.0, 1.1, 1.2],
+        })
+        mocker.patch("mt5cli.sdk.Mt5DataClient", return_value=client)
+        result = recent_ticks(
+            "EURUSD",
+            60,
+            date_to=end,
+            count=0,
+            config=build_config(login=123),
+        )
+        assert len(result) == 3
+        client.copy_ticks_from_as_df.assert_not_called()
+        client.copy_ticks_range_as_df.assert_called_once_with(
+            symbol="EURUSD",
+            date_from=end - timedelta(seconds=60),
+            date_to=end,
+            flags=1,
+        )
+
+
+class TestMinimumMargins:
+    """Tests for minimum_margins helper."""
+
+    def test_minimum_margins_shape(
+        self,
+        mocker: MockerFixture,
+    ) -> None:
+        """Test minimum_margins returns the expected summary columns."""
+        client = MagicMock()
+        sym = MagicMock(volume_min=0.01)
+        account = MagicMock(currency="USD")
+        tick = MagicMock(ask=1.1010, bid=1.1000)
+        client.symbol_info.return_value = sym
+        client.account_info.return_value = account
+        client.symbol_info_tick.return_value = tick
+        client.order_calc_margin.side_effect = [12.5, 12.4]
+        client.mt5.ORDER_TYPE_BUY = 0
+        client.mt5.ORDER_TYPE_SELL = 1
+        mocker.patch("mt5cli.sdk.Mt5DataClient", return_value=client)
+
+        result = minimum_margins("EURUSD", config=build_config(login=123))
+
+        pd.testing.assert_frame_equal(
+            result,
+            pd.DataFrame([
+                {
+                    "symbol": "EURUSD",
+                    "account_currency": "USD",
+                    "volume_min": 0.01,
+                    "buy_margin": 12.5,
+                    "sell_margin": 12.4,
+                }
+            ]),
+        )
+        client.order_calc_margin.assert_any_call(0, "EURUSD", 0.01, 1.1010)
+        client.order_calc_margin.assert_any_call(1, "EURUSD", 0.01, 1.1000)

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 = "0.4.0"
+version = "0.4.3"
 source = { editable = "." }
 dependencies = [
     { name = "click" },