96c75f7852
* feat: add account projected margin ratio helper * Bump version to v0.9.4 * fix: address account margin ratio review feedback * fix: simplify account margin ratio errors
3851 lines
138 KiB
Python
3851 lines
138 KiB
Python
"""Tests for trading session helpers and operational utilities."""
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from __future__ import annotations
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import logging
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from types import SimpleNamespace
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from typing import Any, cast
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from unittest.mock import MagicMock
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import pandas as pd
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import pytest
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from numpy import float64 as np_float64
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from numpy import int64 as np_int64
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from pdmt5 import Mt5RuntimeError, Mt5TradingClient, Mt5TradingError
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from pytest_mock import MockerFixture # noqa: TC002
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from mt5cli.sdk import build_config
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from mt5cli.trading import (
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MarginVolume,
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OrderExecutionResult,
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OrderLimits,
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calculate_account_projected_margin_ratio,
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calculate_margin_and_volume,
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calculate_new_position_margin_ratio,
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calculate_positions_margin,
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calculate_positions_margin_by_symbol,
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calculate_positions_margin_safe,
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calculate_projected_margin_ratio,
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calculate_spread_ratio,
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calculate_symbol_group_margin_ratio,
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calculate_trailing_stop_updates,
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calculate_volume_by_margin,
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close_open_positions,
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create_trading_client,
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detect_position_side,
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determine_order_limits,
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ensure_symbol_selected,
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estimate_order_margin,
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extract_tick_price,
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fetch_latest_closed_rates_for_trading_client,
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fetch_latest_closed_rates_indexed,
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get_account_snapshot,
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get_positions_frame,
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get_symbol_snapshot,
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get_tick_snapshot,
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mt5_trading_session,
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normalize_order_volume,
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place_market_order,
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update_sltp_for_open_positions,
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update_trailing_stop_loss_for_open_positions,
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)
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def _mock_trade_client() -> MagicMock:
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client = MagicMock()
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client.mt5.POSITION_TYPE_BUY = 0
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client.mt5.POSITION_TYPE_SELL = 1
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client.mt5.ORDER_TYPE_BUY = 10
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client.mt5.ORDER_TYPE_SELL = 11
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client.mt5.TRADE_ACTION_DEAL = 20
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client.mt5.TRADE_ACTION_SLTP = 21
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client.mt5.ORDER_FILLING_IOC = 30
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client.mt5.ORDER_TIME_GTC = 40
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client.mt5.TRADE_RETCODE_PLACED = 10008
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client.mt5.TRADE_RETCODE_DONE = 10009
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client.mt5.TRADE_RETCODE_DONE_PARTIAL = 10010
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return client
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def _assert_close(actual: object, expected: float) -> None:
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assert abs(float(cast("float", actual)) - expected) < 1e-9
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def _request_from_result(result: OrderExecutionResult) -> dict[str, object]: # noqa: FURB118
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return result["request"]
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class TestDetectPositionSide:
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"""Tests for detect_position_side."""
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def test_returns_none_when_no_positions(self) -> None:
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"""Test None is returned when no open positions exist."""
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client = MagicMock()
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client.positions_get_as_df.return_value = pd.DataFrame()
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assert detect_position_side(client, "EURUSD") is None
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def test_returns_long_for_buy_only_exposure(self) -> None:
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"""Test long is returned when only buy positions exist."""
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client = MagicMock()
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client.mt5.POSITION_TYPE_BUY = 0
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client.mt5.POSITION_TYPE_SELL = 1
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client.positions_get_as_df.return_value = pd.DataFrame(
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{
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"type": [0, 0],
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"volume": [0.2, 0.1],
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},
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)
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assert detect_position_side(client, "EURUSD") == "long"
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def test_returns_short_for_net_sell_volume(self) -> None:
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"""Test short is returned when sell volume exceeds buy volume."""
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client = MagicMock()
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client.mt5.POSITION_TYPE_BUY = 0
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client.mt5.POSITION_TYPE_SELL = 1
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client.positions_get_as_df.return_value = pd.DataFrame(
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{
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"type": [1, 1],
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"volume": [0.3, 0.1],
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},
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)
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assert detect_position_side(client, "EURUSD") == "short"
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def test_returns_none_for_mixed_hedged_positions(self) -> None:
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"""Test None is returned for mixed buy and sell exposure."""
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client = MagicMock()
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client.mt5.POSITION_TYPE_BUY = 0
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client.mt5.POSITION_TYPE_SELL = 1
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client.positions_get_as_df.return_value = pd.DataFrame(
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{
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"type": [0, 1],
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"volume": [0.3, 0.2],
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},
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)
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assert detect_position_side(client, "EURUSD") is None
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class TestCalculateMarginAndVolume:
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"""Tests for calculate_margin_and_volume."""
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def test_calculates_margin_budget_and_volumes(self, mocker: MockerFixture) -> None:
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"""Test margin budget and buy/sell volumes are derived from ratios."""
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client = MagicMock()
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client.account_info_as_dict.return_value = {"margin_free": 1000.0}
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client.symbol_info_as_dict.side_effect = AttributeError("missing")
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mock_calc_vol = mocker.patch(
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"mt5cli.trading.calculate_volume_by_margin", side_effect=[0.3, 0.2]
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)
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result = calculate_margin_and_volume(
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client,
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"EURUSD",
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unit_margin_ratio=0.5,
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preserved_margin_ratio=0.2,
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)
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assert result == {
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"margin_free": 1000.0,
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"available_margin": 800.0,
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"trade_margin": 400.0,
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"buy_volume": 0.3,
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"sell_volume": 0.2,
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"volume_min": 0.0,
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"volume_max": 0.0,
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"volume_step": 0.0,
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}
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mock_calc_vol.assert_any_call(client, "EURUSD", 400.0, "BUY")
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mock_calc_vol.assert_any_call(client, "EURUSD", 400.0, "SELL")
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@pytest.mark.parametrize(
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("account_dict", "expected_margin_free"),
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[
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({"margin_free": 0.0}, 0.0),
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({}, 0.0),
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({"margin_free": None}, 0.0),
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],
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)
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def test_zero_or_missing_margin_free(
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self,
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account_dict: dict[str, float | None],
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expected_margin_free: float,
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mocker: MockerFixture,
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) -> None:
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"""Test missing or zero margin_free yields zero trade margin."""
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client = MagicMock()
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client.account_info_as_dict.return_value = account_dict
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client.symbol_info_as_dict.side_effect = AttributeError("missing")
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mock_calc_vol = mocker.patch(
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"mt5cli.trading.calculate_volume_by_margin", return_value=0.0
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)
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result = calculate_margin_and_volume(
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client,
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"EURUSD",
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unit_margin_ratio=0.5,
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preserved_margin_ratio=0.2,
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)
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assert result["margin_free"] == expected_margin_free
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_assert_close(result["buy_volume"], 0.0)
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_assert_close(result["sell_volume"], 0.0)
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mock_calc_vol.assert_any_call(client, "EURUSD", 0.0, "BUY")
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mock_calc_vol.assert_any_call(client, "EURUSD", 0.0, "SELL")
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def test_clamps_negative_margin_free_to_zero(self, mocker: MockerFixture) -> None:
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"""Test negative margin_free is clamped to zero before sizing."""
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client = MagicMock()
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client.account_info_as_dict.return_value = {"margin_free": -500.0}
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client.symbol_info_as_dict.side_effect = AttributeError("missing")
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mock_calc_vol = mocker.patch(
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"mt5cli.trading.calculate_volume_by_margin", return_value=0.0
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)
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result = calculate_margin_and_volume(
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client,
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"EURUSD",
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unit_margin_ratio=0.5,
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preserved_margin_ratio=0.2,
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)
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_assert_close(result["margin_free"], 0.0)
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_assert_close(result["buy_volume"], 0.0)
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_assert_close(result["sell_volume"], 0.0)
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mock_calc_vol.assert_any_call(client, "EURUSD", 0.0, "BUY")
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mock_calc_vol.assert_any_call(client, "EURUSD", 0.0, "SELL")
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@pytest.mark.parametrize(
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("unit_ratio", "preserved_ratio"),
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[
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(-0.1, 0.0),
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(1.1, 0.0),
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(0.5, -0.1),
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(0.5, 1.1),
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],
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)
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def test_rejects_invalid_ratios(
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self,
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unit_ratio: float,
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preserved_ratio: float,
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) -> None:
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"""Test invalid ratio values raise ValueError."""
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with pytest.raises(ValueError, match="must be between 0 and 1"):
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calculate_margin_and_volume(
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MagicMock(),
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"EURUSD",
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unit_margin_ratio=unit_ratio,
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preserved_margin_ratio=preserved_ratio,
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)
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class TestDetermineOrderLimits:
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"""Tests for determine_order_limits."""
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@pytest.mark.parametrize(
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("side", "expected_entry_key"),
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[
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("long", "ask"),
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("short", "bid"),
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("buy", "ask"),
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("sell", "bid"),
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],
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)
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def test_uses_expected_quote_for_entry(
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self,
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side: str,
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expected_entry_key: str,
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) -> None:
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"""Test entry price is taken from ask for long/buy and bid for short/sell."""
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client = MagicMock()
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client.symbol_info_tick_as_dict.return_value = {"ask": 1.1010, "bid": 1.1000}
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result = determine_order_limits(
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client,
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"EURUSD",
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side,
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stop_loss_limit_ratio=0.0,
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take_profit_limit_ratio=0.0,
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)
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assert (
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result["entry"]
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== client.symbol_info_tick_as_dict.return_value[expected_entry_key]
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)
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assert result["stop_loss"] is None
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assert result["take_profit"] is None
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def test_calculates_long_protective_levels(self) -> None:
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"""Test long stop loss and take profit are placed below/above entry."""
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client = MagicMock()
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client.symbol_info_tick_as_dict.return_value = {"ask": 100.0, "bid": 99.0}
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client.symbol_info_as_dict.return_value = {}
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result = determine_order_limits(
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client,
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"EURUSD",
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"long",
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stop_loss_limit_ratio=0.02,
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take_profit_limit_ratio=0.03,
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)
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assert result == {
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"entry": 100.0,
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"stop_loss": 98.0,
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"take_profit": 103.0,
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}
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def test_calculates_short_protective_levels(self) -> None:
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"""Test short stop loss and take profit are placed above/below entry."""
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client = MagicMock()
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client.symbol_info_tick_as_dict.return_value = {"ask": 100.0, "bid": 99.0}
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client.symbol_info_as_dict.return_value = {}
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result = determine_order_limits(
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client,
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"EURUSD",
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"short",
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stop_loss_limit_ratio=0.02,
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take_profit_limit_ratio=0.03,
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)
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assert result == {
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"entry": 99.0,
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"stop_loss": 100.98,
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"take_profit": 96.03,
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}
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def test_rejects_unknown_side(self) -> None:
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"""Test unsupported side values raise ValueError."""
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with pytest.raises(ValueError, match="Unsupported position side"):
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determine_order_limits(
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MagicMock(),
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"EURUSD",
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"flat",
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stop_loss_limit_ratio=0.01,
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take_profit_limit_ratio=0.01,
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)
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@pytest.mark.parametrize(
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("stop_loss_ratio", "take_profit_ratio"),
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[
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(-0.05, 0.01),
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(0.01, 2.0),
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],
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)
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def test_rejects_invalid_protective_ratios(
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self,
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stop_loss_ratio: float,
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take_profit_ratio: float,
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) -> None:
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"""Test out-of-range protective ratios raise ValueError."""
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with pytest.raises(ValueError, match="must be at least 0 and less than 1"):
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determine_order_limits(
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MagicMock(),
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"EURUSD",
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"long",
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stop_loss_limit_ratio=stop_loss_ratio,
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take_profit_limit_ratio=take_profit_ratio,
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)
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@pytest.mark.parametrize(
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("field", "ratio"),
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[
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("stop_loss_limit_ratio", 1.0),
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("take_profit_limit_ratio", 1.0),
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],
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)
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def test_rejects_unit_boundary_protective_ratios(
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self,
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field: str,
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ratio: float,
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) -> None:
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"""Test protective ratios of exactly 1.0 are rejected."""
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kwargs = {
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"stop_loss_limit_ratio": 0.01,
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"take_profit_limit_ratio": 0.01,
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field: ratio,
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}
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with pytest.raises(ValueError, match="must be at least 0 and less than 1"):
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determine_order_limits(
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MagicMock(),
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"EURUSD",
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"long",
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**kwargs,
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)
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def test_uses_default_digits_when_symbol_snapshot_fails(self) -> None:
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"""Test order limit rounding falls back when symbol metadata is missing."""
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client = MagicMock()
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client.symbol_info_tick_as_dict.return_value = {"ask": 1.234567891, "bid": 1.0}
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client.symbol_info_as_dict.return_value = {"digits": "invalid"}
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result = determine_order_limits(
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client,
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"EURUSD",
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"long",
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stop_loss_limit_ratio=0.01,
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take_profit_limit_ratio=0.01,
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)
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_assert_close(result["stop_loss"], 1.22222221)
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def test_uses_default_digits_when_symbol_lookup_raises(self) -> None:
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"""Test order limits fall back when symbol metadata lookup fails."""
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client = MagicMock()
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client.symbol_info_tick_as_dict.return_value = {"ask": 1.234567891, "bid": 1.0}
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client.symbol_info_as_dict.side_effect = AttributeError("missing")
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result = determine_order_limits(
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client,
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"EURUSD",
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"long",
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stop_loss_limit_ratio=0.01,
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take_profit_limit_ratio=0.01,
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)
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_assert_close(result["stop_loss"], 1.22222221)
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def test_uses_tick_snapshot_fallback(self) -> None:
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"""Test order limits use the normalized tick snapshot helper."""
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client = MagicMock()
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del client.symbol_info_tick_as_dict
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client.symbol_info_tick.return_value = SimpleNamespace(ask=1.2, bid=1.1)
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client.symbol_info_as_dict.return_value = {"digits": 4}
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result = determine_order_limits(
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client,
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"EURUSD",
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"long",
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stop_loss_limit_ratio=0.01,
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)
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_assert_close(result["entry"], 1.2)
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_assert_close(result["stop_loss"], 1.188)
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def test_rejects_missing_entry_tick(self) -> None:
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"""Test missing entry prices raise a trading error."""
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client = MagicMock()
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client.symbol_info_tick_as_dict.return_value = {"ask": None, "bid": 1.1}
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with pytest.raises(Mt5TradingError, match="Tick price is unavailable"):
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determine_order_limits(client, "EURUSD", "long")
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def test_accepts_numeric_string_entry(self) -> None:
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"""Test numeric string ask/bid values are accepted as entry prices."""
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client = MagicMock()
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client.symbol_info_tick_as_dict.return_value = {
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"ask": "1.1010",
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"bid": "1.1000",
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}
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client.symbol_info_as_dict.return_value = {"digits": 4}
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result = determine_order_limits(client, "EURUSD", "long")
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_assert_close(result["entry"], 1.1010)
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@pytest.mark.parametrize(
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("side", "field", "bad_value"),
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[
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("long", "ask", float("nan")),
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("long", "ask", float("inf")),
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("long", "ask", float("-inf")),
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("long", "ask", 0.0),
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("long", "ask", -1.0),
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("long", "ask", True),
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("long", "ask", False),
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("long", "ask", "invalid"),
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("short", "bid", float("nan")),
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("short", "bid", float("inf")),
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("short", "bid", float("-inf")),
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("short", "bid", 0.0),
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("short", "bid", -1.0),
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("short", "bid", True),
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("short", "bid", False),
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("short", "bid", "invalid"),
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],
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)
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def test_rejects_invalid_entry_tick_values(
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self,
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side: str,
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field: str,
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bad_value: object,
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) -> None:
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"""Test invalid entry tick values raise Mt5TradingError."""
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tick: dict[str, object] = {"ask": 1.1, "bid": 1.0}
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tick[field] = bad_value
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client = MagicMock()
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client.symbol_info_tick_as_dict.return_value = tick
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|
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with pytest.raises(Mt5TradingError, match="Tick price is unavailable"):
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determine_order_limits(client, "EURUSD", side)
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def test_rejects_stop_loss_inside_broker_stop_level(self) -> None:
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"""Test stop-loss prices closer than trade_stops_level raise Mt5TradingError."""
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client = MagicMock()
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client.symbol_info_tick_as_dict.return_value = {"ask": 1.0, "bid": 0.99}
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client.symbol_info_as_dict.return_value = {
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"digits": 2,
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"trade_stops_level": 100,
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"point": 0.0001,
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}
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|
|
with pytest.raises(Mt5TradingError, match="Stop loss for 'EURUSD'"):
|
|
determine_order_limits(
|
|
client,
|
|
"EURUSD",
|
|
"long",
|
|
stop_loss_limit_ratio=0.0001,
|
|
)
|
|
|
|
def test_accepts_stop_loss_exactly_at_minimum_stop_distance(self) -> None:
|
|
"""Test protective levels exactly at trade_stops_level distance pass."""
|
|
client = MagicMock()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.0, "bid": 0.99}
|
|
client.symbol_info_as_dict.return_value = {
|
|
"digits": 2,
|
|
"trade_stops_level": 100,
|
|
"point": 0.0001,
|
|
}
|
|
|
|
result = determine_order_limits(
|
|
client,
|
|
"EURUSD",
|
|
"long",
|
|
stop_loss_limit_ratio=0.01,
|
|
take_profit_limit_ratio=0.0,
|
|
)
|
|
|
|
_assert_close(result["stop_loss"], 0.99)
|
|
|
|
def test_allows_protective_levels_beyond_broker_stop_level(self) -> None:
|
|
"""Test SL/TP beyond trade_stops_level pass validation."""
|
|
client = MagicMock()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.0, "bid": 0.99}
|
|
client.symbol_info_as_dict.return_value = {
|
|
"digits": 2,
|
|
"trade_stops_level": 10,
|
|
"point": 0.0001,
|
|
}
|
|
|
|
result = determine_order_limits(
|
|
client,
|
|
"EURUSD",
|
|
"long",
|
|
stop_loss_limit_ratio=0.05,
|
|
take_profit_limit_ratio=0.05,
|
|
)
|
|
|
|
_assert_close(result["stop_loss"], 0.95)
|
|
_assert_close(result["take_profit"], 1.05)
|
|
|
|
def test_rejects_take_profit_inside_broker_stop_level(self) -> None:
|
|
"""Test long take-profit inside trade_stops_level raises Mt5TradingError."""
|
|
client = MagicMock()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.0, "bid": 0.99}
|
|
client.symbol_info_as_dict.return_value = {
|
|
"digits": 2,
|
|
"trade_stops_level": 100,
|
|
"point": 0.0001,
|
|
}
|
|
|
|
with pytest.raises(Mt5TradingError, match="Take profit for 'EURUSD'"):
|
|
determine_order_limits(
|
|
client,
|
|
"EURUSD",
|
|
"long",
|
|
take_profit_limit_ratio=0.0001,
|
|
)
|
|
|
|
def test_rejects_short_stop_loss_inside_broker_stop_level(self) -> None:
|
|
"""Test short stop-loss inside trade_stops_level raises Mt5TradingError."""
|
|
client = MagicMock()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.01, "bid": 1.0}
|
|
client.symbol_info_as_dict.return_value = {
|
|
"digits": 2,
|
|
"trade_stops_level": 100,
|
|
"point": 0.0001,
|
|
}
|
|
|
|
with pytest.raises(Mt5TradingError, match="Stop loss for 'EURUSD'"):
|
|
determine_order_limits(
|
|
client,
|
|
"EURUSD",
|
|
"short",
|
|
stop_loss_limit_ratio=0.0001,
|
|
)
|
|
|
|
def test_rejects_short_take_profit_inside_broker_stop_level(self) -> None:
|
|
"""Test short take-profit inside trade_stops_level raises Mt5TradingError."""
|
|
client = MagicMock()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.01, "bid": 1.0}
|
|
client.symbol_info_as_dict.return_value = {
|
|
"digits": 2,
|
|
"trade_stops_level": 100,
|
|
"point": 0.0001,
|
|
}
|
|
|
|
with pytest.raises(Mt5TradingError, match="Take profit for 'EURUSD'"):
|
|
determine_order_limits(
|
|
client,
|
|
"EURUSD",
|
|
"short",
|
|
take_profit_limit_ratio=0.0001,
|
|
)
|
|
|
|
def test_allows_short_protective_levels_beyond_broker_stop_level(self) -> None:
|
|
"""Test short SL/TP beyond trade_stops_level pass validation."""
|
|
client = MagicMock()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.01, "bid": 1.0}
|
|
client.symbol_info_as_dict.return_value = {
|
|
"digits": 2,
|
|
"trade_stops_level": 10,
|
|
"point": 0.0001,
|
|
}
|
|
|
|
result = determine_order_limits(
|
|
client,
|
|
"EURUSD",
|
|
"short",
|
|
stop_loss_limit_ratio=0.05,
|
|
take_profit_limit_ratio=0.05,
|
|
)
|
|
|
|
_assert_close(result["stop_loss"], 1.05)
|
|
_assert_close(result["take_profit"], 0.95)
|
|
|
|
def test_ignores_non_positive_broker_stop_level(self) -> None:
|
|
"""Test zero trade_stops_level skips stop-distance validation."""
|
|
client = MagicMock()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.0, "bid": 0.99}
|
|
client.symbol_info_as_dict.return_value = {
|
|
"digits": 2,
|
|
"trade_stops_level": 0,
|
|
"point": 0.0001,
|
|
}
|
|
|
|
result = determine_order_limits(
|
|
client,
|
|
"EURUSD",
|
|
"long",
|
|
stop_loss_limit_ratio=0.0001,
|
|
take_profit_limit_ratio=0.0001,
|
|
)
|
|
|
|
assert result["stop_loss"] is not None
|
|
assert result["take_profit"] is not None
|
|
|
|
"""Tests for ensure_symbol_selected."""
|
|
|
|
def test_skips_selection_when_symbol_is_visible(self) -> None:
|
|
"""Test visible symbols do not call symbol_select."""
|
|
client = MagicMock()
|
|
client.symbol_info_as_dict.return_value = {"visible": True}
|
|
|
|
ensure_symbol_selected(client, "EURUSD")
|
|
|
|
client.symbol_select.assert_not_called()
|
|
|
|
def test_selects_hidden_symbol_before_trading(self) -> None:
|
|
"""Test hidden symbols are selected in Market Watch."""
|
|
client = MagicMock()
|
|
client.symbol_info_as_dict.return_value = {"visible": False}
|
|
client.symbol_select.return_value = True
|
|
|
|
ensure_symbol_selected(client, "EURUSD")
|
|
|
|
client.symbol_select.assert_called_once_with("EURUSD", enable=True)
|
|
|
|
def test_raises_when_symbol_selection_fails(self) -> None:
|
|
"""Test failed symbol selection raises Mt5TradingError."""
|
|
client = MagicMock()
|
|
client.symbol_info_as_dict.return_value = {"visible": False}
|
|
client.symbol_select.return_value = False
|
|
client.last_error.return_value = (1, "not found")
|
|
|
|
with pytest.raises(Mt5TradingError, match="Failed to select symbol 'EURUSD'"):
|
|
ensure_symbol_selected(client, "EURUSD")
|
|
|
|
def test_raises_when_symbol_select_is_unavailable(self) -> None:
|
|
"""Test missing symbol_select raises Mt5TradingError."""
|
|
client = MagicMock()
|
|
client.symbol_info_as_dict.return_value = {"visible": False}
|
|
del client.symbol_select
|
|
|
|
with pytest.raises(
|
|
Mt5TradingError,
|
|
match="missing required method: symbol_select",
|
|
):
|
|
ensure_symbol_selected(client, "EURUSD")
|
|
|
|
|
|
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()
|
|
|
|
|
|
class TestCreateTradingClient:
|
|
"""Tests for create_trading_client."""
|
|
|
|
def test_initializes_with_keyword_config(self, mocker: MockerFixture) -> None:
|
|
"""Test keyword configuration is forwarded to Mt5TradingClient."""
|
|
mock_client = MagicMock()
|
|
trading_client = mocker.patch(
|
|
"mt5cli.trading.Mt5TradingClient",
|
|
return_value=mock_client,
|
|
)
|
|
|
|
result = create_trading_client(
|
|
login="12345",
|
|
password="test-pass",
|
|
server="Demo",
|
|
path="/opt/terminal64.exe",
|
|
retry_count=2,
|
|
)
|
|
|
|
assert result is mock_client
|
|
config = trading_client.call_args.kwargs["config"]
|
|
assert config.login == 12345
|
|
assert config.password == ("test" + "-pass")
|
|
assert config.server == "Demo"
|
|
assert config.path == "/opt/terminal64.exe"
|
|
assert trading_client.call_args.kwargs["retry_count"] == 2
|
|
mock_client.initialize_and_login_mt5.assert_called_once()
|
|
|
|
def test_empty_login_string_is_unset(self, mocker: MockerFixture) -> None:
|
|
"""Test empty login strings are treated as None."""
|
|
trading_client = mocker.patch(
|
|
"mt5cli.trading.Mt5TradingClient",
|
|
return_value=MagicMock(),
|
|
)
|
|
|
|
create_trading_client(login=" ")
|
|
|
|
config = trading_client.call_args.kwargs["config"]
|
|
assert config.login is None
|
|
|
|
def test_shutdown_on_initialization_failure(self, mocker: MockerFixture) -> None:
|
|
"""Test failed initialization shuts the client down."""
|
|
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"):
|
|
create_trading_client()
|
|
|
|
mock_client.shutdown.assert_called_once()
|
|
|
|
|
|
class TestSnapshotsAndState:
|
|
"""Tests for normalized state helpers."""
|
|
|
|
def test_account_snapshot_includes_missing_fields(self) -> None:
|
|
"""Test account snapshot has stable keys with None for missing values."""
|
|
client = MagicMock()
|
|
client.account_info_as_dict.return_value = {"login": 1, "equity": 100.0}
|
|
|
|
result = get_account_snapshot(client)
|
|
|
|
assert result["login"] == 1
|
|
_assert_close(result["equity"], 100.0)
|
|
assert result["currency"] is None
|
|
|
|
def test_account_snapshot_supports_object_fallback(self) -> None:
|
|
"""Test account snapshots can read plain MT5-like objects."""
|
|
|
|
class ObjectClient:
|
|
def account_info(self) -> SimpleNamespace:
|
|
return SimpleNamespace(login=7, currency="JPY")
|
|
|
|
result = get_account_snapshot(cast("Mt5TradingClient", ObjectClient()))
|
|
|
|
assert result["login"] == 7
|
|
assert result["currency"] == "JPY"
|
|
|
|
def test_account_snapshot_requires_supported_method(self) -> None:
|
|
"""Test missing account snapshot methods raise AttributeError."""
|
|
client = object()
|
|
|
|
with pytest.raises(AttributeError, match="account_info"):
|
|
get_account_snapshot(cast("Mt5TradingClient", client))
|
|
|
|
def test_symbol_and_tick_snapshots_fill_symbol(self) -> None:
|
|
"""Test symbol and tick snapshots expose stable fields."""
|
|
client = MagicMock()
|
|
client.symbol_info_as_dict.return_value = {"digits": 5, "visible": True}
|
|
client.symbol_info_tick_as_dict.return_value = {"bid": 1.1, "ask": 1.2}
|
|
|
|
assert get_symbol_snapshot(client, "EURUSD")["symbol"] == "EURUSD"
|
|
assert get_tick_snapshot(client, "EURUSD")["symbol"] == "EURUSD"
|
|
|
|
def test_symbol_and_tick_snapshots_use_object_fallbacks(self) -> None:
|
|
"""Test symbol and tick snapshots support non-dict MT5 values."""
|
|
client = MagicMock()
|
|
del client.symbol_info_as_dict
|
|
del client.symbol_info_tick_as_dict
|
|
client.symbol_info.return_value = SimpleNamespace(digits=3)
|
|
client.symbol_info_tick.return_value = SimpleNamespace(bid=1.0, ask=1.1)
|
|
|
|
assert get_symbol_snapshot(client, "USDJPY")["digits"] == 3
|
|
_assert_close(get_tick_snapshot(client, "USDJPY")["ask"], 1.1)
|
|
|
|
def test_positions_frame_adds_stable_columns(self) -> None:
|
|
"""Test missing position columns are added to empty frames."""
|
|
client = MagicMock()
|
|
client.positions_get_as_df.return_value = pd.DataFrame()
|
|
|
|
result = get_positions_frame(client, symbol="EURUSD")
|
|
|
|
assert "ticket" in result.columns
|
|
assert "comment" in result.columns
|
|
|
|
def test_calculate_spread_ratio(self) -> None:
|
|
"""Test spread ratio uses mid-price denominator."""
|
|
client = MagicMock()
|
|
client.symbol_info_tick_as_dict.return_value = {"bid": 99.0, "ask": 101.0}
|
|
|
|
_assert_close(calculate_spread_ratio(client, "EURUSD"), 0.02)
|
|
|
|
def test_calculate_spread_ratio_rejects_missing_tick(self) -> None:
|
|
"""Test missing bid/ask raises a trading error."""
|
|
client = MagicMock()
|
|
client.symbol_info_tick_as_dict.return_value = {"bid": None, "ask": 1.0}
|
|
|
|
with pytest.raises(Mt5TradingError):
|
|
calculate_spread_ratio(client, "EURUSD")
|
|
|
|
def test_calculate_spread_ratio_rejects_non_positive_tick(self) -> None:
|
|
"""Test non-positive bid/ask raises a trading error."""
|
|
client = MagicMock()
|
|
client.symbol_info_tick_as_dict.return_value = {"bid": 0.0, "ask": 1.0}
|
|
|
|
with pytest.raises(Mt5TradingError):
|
|
calculate_spread_ratio(client, "EURUSD")
|
|
|
|
def test_calculate_spread_ratio_accepts_numeric_string_tick(self) -> None:
|
|
"""Test numeric string bid/ask values are accepted."""
|
|
client = MagicMock()
|
|
client.symbol_info_tick_as_dict.return_value = {"bid": "99.0", "ask": "101.0"}
|
|
|
|
_assert_close(calculate_spread_ratio(client, "EURUSD"), 0.02)
|
|
|
|
@pytest.mark.parametrize(
|
|
("field", "bad_value"),
|
|
[
|
|
("bid", None),
|
|
("bid", float("nan")),
|
|
("bid", float("inf")),
|
|
("bid", float("-inf")),
|
|
("bid", 0.0),
|
|
("bid", -1.0),
|
|
("bid", True),
|
|
("bid", False),
|
|
("bid", "invalid"),
|
|
("ask", None),
|
|
("ask", float("nan")),
|
|
("ask", float("inf")),
|
|
("ask", float("-inf")),
|
|
("ask", 0.0),
|
|
("ask", -1.0),
|
|
("ask", True),
|
|
("ask", False),
|
|
("ask", "invalid"),
|
|
],
|
|
)
|
|
def test_calculate_spread_ratio_rejects_invalid_tick_values(
|
|
self,
|
|
field: str,
|
|
bad_value: object,
|
|
) -> None:
|
|
"""Test invalid bid/ask values raise Mt5TradingError."""
|
|
tick: dict[str, object] = {"bid": 100.0, "ask": 100.0}
|
|
tick[field] = bad_value
|
|
client = MagicMock()
|
|
client.symbol_info_tick_as_dict.return_value = tick
|
|
|
|
with pytest.raises(Mt5TradingError, match="Tick bid/ask is unavailable"):
|
|
calculate_spread_ratio(client, "EURUSD")
|
|
|
|
|
|
class TestNormalizeOrderVolume:
|
|
"""Tests for normalize_order_volume."""
|
|
|
|
def test_returns_exact_minimum_volume(self) -> None:
|
|
"""Test exact volume_min is returned unchanged."""
|
|
_assert_close(
|
|
normalize_order_volume(
|
|
0.1,
|
|
volume_min=0.1,
|
|
volume_max=1.0,
|
|
volume_step=0.1,
|
|
),
|
|
0.1,
|
|
)
|
|
|
|
def test_floors_to_step_between_boundaries(self) -> None:
|
|
"""Test volume between steps floors down to the nearest valid step."""
|
|
_assert_close(
|
|
normalize_order_volume(
|
|
0.25,
|
|
volume_min=0.1,
|
|
volume_max=1.0,
|
|
volume_step=0.1,
|
|
),
|
|
0.2,
|
|
)
|
|
|
|
def test_clamps_to_volume_max(self) -> None:
|
|
"""Test positive volume_max caps the normalized result."""
|
|
_assert_close(
|
|
normalize_order_volume(
|
|
0.9,
|
|
volume_min=0.1,
|
|
volume_max=0.5,
|
|
volume_step=0.1,
|
|
),
|
|
0.5,
|
|
)
|
|
|
|
def test_returns_zero_below_volume_min(self) -> None:
|
|
"""Test sub-minimum requests return zero volume."""
|
|
_assert_close(
|
|
normalize_order_volume(
|
|
0.05,
|
|
volume_min=0.1,
|
|
volume_max=1.0,
|
|
volume_step=0.1,
|
|
),
|
|
0.0,
|
|
)
|
|
|
|
def test_returns_zero_for_invalid_volume_min(self) -> None:
|
|
"""Test non-positive volume_min returns zero volume."""
|
|
_assert_close(
|
|
normalize_order_volume(
|
|
1.0,
|
|
volume_min=0.0,
|
|
volume_max=1.0,
|
|
volume_step=0.1,
|
|
),
|
|
0.0,
|
|
)
|
|
|
|
def test_returns_zero_for_invalid_volume_step(self) -> None:
|
|
"""Test non-positive volume_step returns zero volume."""
|
|
_assert_close(
|
|
normalize_order_volume(
|
|
1.0,
|
|
volume_min=0.1,
|
|
volume_max=1.0,
|
|
volume_step=0.0,
|
|
),
|
|
0.0,
|
|
)
|
|
|
|
def test_treats_non_positive_volume_max_as_no_cap(self) -> None:
|
|
"""Test volume_max <= 0 disables the maximum cap."""
|
|
_assert_close(
|
|
normalize_order_volume(
|
|
2.5,
|
|
volume_min=0.1,
|
|
volume_max=0.0,
|
|
volume_step=0.1,
|
|
),
|
|
2.5,
|
|
)
|
|
|
|
def test_reapplies_volume_max_after_step_normalization(self) -> None:
|
|
"""Test post-step normalization cannot exceed volume_max."""
|
|
_assert_close(
|
|
normalize_order_volume(
|
|
0.5,
|
|
volume_min=0.1,
|
|
volume_max=0.34,
|
|
volume_step=0.12,
|
|
),
|
|
0.34,
|
|
)
|
|
|
|
def test_returns_zero_for_non_finite_volume(self) -> None:
|
|
"""Test NaN or infinite requested volume returns zero."""
|
|
_assert_close(
|
|
normalize_order_volume(
|
|
float("nan"),
|
|
volume_min=0.1,
|
|
volume_max=1.0,
|
|
volume_step=0.1,
|
|
),
|
|
0.0,
|
|
)
|
|
_assert_close(
|
|
normalize_order_volume(
|
|
float("inf"),
|
|
volume_min=0.1,
|
|
volume_max=1.0,
|
|
volume_step=0.1,
|
|
),
|
|
0.0,
|
|
)
|
|
|
|
def test_returns_zero_for_non_finite_constraints(self) -> None:
|
|
"""Test NaN or infinite volume_min/volume_step returns zero."""
|
|
_assert_close(
|
|
normalize_order_volume(
|
|
1.0,
|
|
volume_min=float("nan"),
|
|
volume_max=1.0,
|
|
volume_step=0.1,
|
|
),
|
|
0.0,
|
|
)
|
|
_assert_close(
|
|
normalize_order_volume(
|
|
1.0,
|
|
volume_min=0.1,
|
|
volume_max=1.0,
|
|
volume_step=float("inf"),
|
|
),
|
|
0.0,
|
|
)
|
|
|
|
def test_treats_non_finite_volume_max_as_no_cap(self) -> None:
|
|
"""Test non-finite volume_max disables the maximum cap."""
|
|
_assert_close(
|
|
normalize_order_volume(
|
|
2.5,
|
|
volume_min=0.1,
|
|
volume_max=float("nan"),
|
|
volume_step=0.1,
|
|
),
|
|
2.5,
|
|
)
|
|
|
|
|
|
class TestEstimateOrderMargin:
|
|
"""Tests for estimate_order_margin."""
|
|
|
|
def test_estimates_buy_margin_at_ask(self) -> None:
|
|
"""Test buy margin uses ask price and buy order type."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.1010, "bid": 1.1000}
|
|
client.order_calc_margin.return_value = 12.5
|
|
|
|
margin = estimate_order_margin(client, "EURUSD", "BUY", 0.1)
|
|
|
|
_assert_close(margin, 12.5)
|
|
client.order_calc_margin.assert_called_once_with(10, "EURUSD", 0.1, 1.1010)
|
|
|
|
def test_estimates_sell_margin_at_bid(self) -> None:
|
|
"""Test sell margin uses bid price and sell order type."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.1010, "bid": 1.1000}
|
|
client.order_calc_margin.return_value = 12.4
|
|
|
|
margin = estimate_order_margin(client, "EURUSD", "SELL", 0.1)
|
|
|
|
_assert_close(margin, 12.4)
|
|
client.order_calc_margin.assert_called_once_with(11, "EURUSD", 0.1, 1.1000)
|
|
|
|
def test_accepts_long_and_short_aliases(self) -> None:
|
|
"""Test long/short aliases normalize to buy/sell pricing."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.1010, "bid": 1.1000}
|
|
client.order_calc_margin.side_effect = [12.5, 12.4]
|
|
|
|
estimate_order_margin(client, "EURUSD", "long", 0.1)
|
|
estimate_order_margin(client, "EURUSD", "short", 0.1)
|
|
|
|
client.order_calc_margin.assert_any_call(10, "EURUSD", 0.1, 1.1010)
|
|
client.order_calc_margin.assert_any_call(11, "EURUSD", 0.1, 1.1000)
|
|
|
|
def test_rejects_invalid_side(self) -> None:
|
|
"""Test unsupported order side raises ValueError."""
|
|
client = _mock_trade_client()
|
|
|
|
with pytest.raises(ValueError, match="Unsupported order side"):
|
|
estimate_order_margin(client, "EURUSD", "HOLD", 0.1)
|
|
|
|
def test_rejects_non_positive_volume(self) -> None:
|
|
"""Test non-positive volume raises Mt5TradingError."""
|
|
client = _mock_trade_client()
|
|
|
|
with pytest.raises(Mt5TradingError, match="positive finite number"):
|
|
estimate_order_margin(client, "EURUSD", "BUY", 0.0)
|
|
|
|
def test_rejects_nan_volume(self) -> None:
|
|
"""Test NaN volume raises Mt5TradingError without broker calls."""
|
|
client = _mock_trade_client()
|
|
|
|
with pytest.raises(Mt5TradingError, match="positive finite number"):
|
|
estimate_order_margin(client, "EURUSD", "BUY", float("nan"))
|
|
|
|
client.symbol_info_tick_as_dict.assert_not_called()
|
|
client.order_calc_margin.assert_not_called()
|
|
|
|
def test_rejects_infinite_volume(self) -> None:
|
|
"""Test infinite volume raises Mt5TradingError without broker calls."""
|
|
client = _mock_trade_client()
|
|
|
|
with pytest.raises(Mt5TradingError, match="positive finite number"):
|
|
estimate_order_margin(client, "EURUSD", "BUY", float("inf"))
|
|
|
|
client.symbol_info_tick_as_dict.assert_not_called()
|
|
client.order_calc_margin.assert_not_called()
|
|
|
|
def test_rejects_missing_tick_prices(self) -> None:
|
|
"""Test missing tick prices raise Mt5TradingError."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": None, "bid": 1.1000}
|
|
|
|
with pytest.raises(Mt5TradingError, match="Tick price is unavailable"):
|
|
estimate_order_margin(client, "EURUSD", "BUY", 0.1)
|
|
|
|
def test_rejects_non_positive_tick_price(self) -> None:
|
|
"""Test non-positive tick prices raise Mt5TradingError."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 0.0, "bid": 1.1000}
|
|
|
|
with pytest.raises(Mt5TradingError, match="Tick price is unavailable"):
|
|
estimate_order_margin(client, "EURUSD", "BUY", 0.1)
|
|
|
|
def test_rejects_non_finite_tick_price(self) -> None:
|
|
"""Test non-finite tick prices raise Mt5TradingError."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {
|
|
"ask": float("inf"),
|
|
"bid": 1.1000,
|
|
}
|
|
|
|
with pytest.raises(Mt5TradingError, match="Tick price is unavailable"):
|
|
estimate_order_margin(client, "EURUSD", "BUY", 0.1)
|
|
|
|
def test_rejects_invalid_margin_result(self) -> None:
|
|
"""Test non-positive margin estimates raise Mt5TradingError."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.1010, "bid": 1.1000}
|
|
client.order_calc_margin.return_value = 0.0
|
|
|
|
with pytest.raises(Mt5TradingError, match="Margin estimate is invalid"):
|
|
estimate_order_margin(client, "EURUSD", "BUY", 0.1)
|
|
|
|
def test_rejects_non_finite_margin_result(self) -> None:
|
|
"""Test non-finite margin estimates raise Mt5TradingError."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.1010, "bid": 1.1000}
|
|
client.order_calc_margin.return_value = float("inf")
|
|
|
|
with pytest.raises(Mt5TradingError, match="Margin estimate is invalid"):
|
|
estimate_order_margin(client, "EURUSD", "BUY", 0.1)
|
|
|
|
def test_rejects_none_margin_result(self) -> None:
|
|
"""Test None margin results raise Mt5TradingError."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.1010, "bid": 1.1000}
|
|
client.order_calc_margin.return_value = None
|
|
|
|
with pytest.raises(Mt5TradingError, match="Margin estimate is invalid"):
|
|
estimate_order_margin(client, "EURUSD", "BUY", 0.1)
|
|
|
|
def test_rejects_non_numeric_margin_result(self) -> None:
|
|
"""Test non-numeric margin results raise Mt5TradingError."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.1010, "bid": 1.1000}
|
|
client.order_calc_margin.return_value = "invalid"
|
|
|
|
with pytest.raises(Mt5TradingError, match="Margin estimate is invalid"):
|
|
estimate_order_margin(client, "EURUSD", "BUY", 0.1)
|
|
|
|
|
|
class TestCalculatePositionsMargin:
|
|
"""Tests for calculate_positions_margin."""
|
|
|
|
def test_returns_zero_for_empty_positions(self) -> None:
|
|
"""Test empty positions return zero total margin."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame()
|
|
|
|
_assert_close(calculate_positions_margin(client), 0.0)
|
|
|
|
def test_filters_by_symbols(self) -> None:
|
|
"""Test optional symbol filter limits summed positions."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{"symbol": "EURUSD", "type": 0, "volume": 0.1},
|
|
{"symbol": "USDJPY", "type": 1, "volume": 0.2},
|
|
],
|
|
)
|
|
client.symbol_info_tick_as_dict.side_effect = [
|
|
{"ask": 1.1010, "bid": 1.1000},
|
|
{"ask": 110.0, "bid": 109.0},
|
|
]
|
|
client.order_calc_margin.side_effect = [12.5, 20.0]
|
|
|
|
margin = calculate_positions_margin(client, symbols=["EURUSD"])
|
|
|
|
_assert_close(margin, 12.5)
|
|
assert client.order_calc_margin.call_count == 1
|
|
|
|
def test_sums_mixed_buy_and_sell_positions(self) -> None:
|
|
"""Test mixed buy/sell exposure sums each side independently."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{"symbol": "EURUSD", "type": 0, "volume": 0.1},
|
|
{"symbol": "EURUSD", "type": 1, "volume": 0.2},
|
|
],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.1010, "bid": 1.1000}
|
|
client.order_calc_margin.side_effect = [12.5, 24.8]
|
|
|
|
margin = calculate_positions_margin(client)
|
|
|
|
_assert_close(margin, 37.3)
|
|
|
|
def test_groups_positions_by_symbol_and_side(self) -> None:
|
|
"""Test repeated symbol/side pairs use one margin call with summed volume."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{"symbol": "EURUSD", "type": 0, "volume": 0.1},
|
|
{"symbol": "EURUSD", "type": 0, "volume": 0.2},
|
|
],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.1010, "bid": 1.1000}
|
|
client.order_calc_margin.return_value = 37.5
|
|
|
|
margin = calculate_positions_margin(client)
|
|
|
|
_assert_close(margin, 37.5)
|
|
client.order_calc_margin.assert_called_once()
|
|
args = client.order_calc_margin.call_args[0]
|
|
assert args[0] == 10
|
|
assert args[1] == "EURUSD"
|
|
_assert_close(args[2], 0.3)
|
|
_assert_close(args[3], 1.1010)
|
|
|
|
def test_sums_multiple_symbols(self) -> None:
|
|
"""Test positions across symbols are all included."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{"symbol": "EURUSD", "type": 0, "volume": 0.1},
|
|
{"symbol": "GBPUSD", "type": 1, "volume": 0.3},
|
|
],
|
|
)
|
|
client.symbol_info_tick_as_dict.side_effect = [
|
|
{"ask": 1.1010, "bid": 1.1000},
|
|
{"ask": 1.3010, "bid": 1.3000},
|
|
]
|
|
client.order_calc_margin.side_effect = [12.5, 30.0]
|
|
|
|
margin = calculate_positions_margin(client)
|
|
|
|
_assert_close(margin, 42.5)
|
|
|
|
def test_propagates_invalid_tick_or_margin_errors(self) -> None:
|
|
"""Test invalid tick or margin data raises Mt5TradingError."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[{"symbol": "EURUSD", "type": 0, "volume": 0.1}],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": None, "bid": 1.1000}
|
|
|
|
with pytest.raises(Mt5TradingError, match="Tick price is unavailable"):
|
|
calculate_positions_margin(client)
|
|
|
|
def test_skips_rows_with_invalid_symbol_volume_or_type(self) -> None:
|
|
"""Test malformed position rows are ignored when summing margin."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{"symbol": "", "type": 0, "volume": 0.1},
|
|
{"symbol": "EURUSD", "type": 0, "volume": 0.0},
|
|
{"symbol": "EURUSD", "type": 2, "volume": 0.1},
|
|
{"symbol": "EURUSD", "type": 0, "volume": 0.1},
|
|
],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.1010, "bid": 1.1000}
|
|
client.order_calc_margin.return_value = 12.5
|
|
|
|
margin = calculate_positions_margin(client)
|
|
|
|
_assert_close(margin, 12.5)
|
|
client.order_calc_margin.assert_called_once()
|
|
|
|
def test_skips_rows_with_non_finite_volume(self) -> None:
|
|
"""Test NaN and infinite position volumes are ignored."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{"symbol": "EURUSD", "type": 0, "volume": float("nan")},
|
|
{"symbol": "EURUSD", "type": 0, "volume": float("inf")},
|
|
{"symbol": "EURUSD", "type": 0, "volume": 0.1},
|
|
],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.1010, "bid": 1.1000}
|
|
client.order_calc_margin.return_value = 12.5
|
|
|
|
margin = calculate_positions_margin(client)
|
|
|
|
_assert_close(margin, 12.5)
|
|
client.order_calc_margin.assert_called_once()
|
|
|
|
def test_returns_zero_when_all_volumes_are_non_finite(self) -> None:
|
|
"""Test all-invalid non-finite volumes return zero without broker calls."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{"symbol": "EURUSD", "type": 0, "volume": float("nan")},
|
|
{"symbol": "EURUSD", "type": 1, "volume": float("inf")},
|
|
],
|
|
)
|
|
|
|
_assert_close(calculate_positions_margin(client), 0.0)
|
|
client.order_calc_margin.assert_not_called()
|
|
client.symbol_info_tick_as_dict.assert_not_called()
|
|
|
|
def test_returns_zero_when_symbol_filter_matches_nothing(self) -> None:
|
|
"""Test filtered symbol lists with no matches return zero."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[{"symbol": "EURUSD", "type": 0, "volume": 0.1}],
|
|
)
|
|
|
|
_assert_close(calculate_positions_margin(client, symbols=["GBPUSD"]), 0.0)
|
|
client.order_calc_margin.assert_not_called()
|
|
|
|
def test_returns_zero_for_empty_positions_with_symbol_filter(self) -> None:
|
|
"""Test empty positions with a symbol filter return zero."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame()
|
|
|
|
_assert_close(calculate_positions_margin(client, symbols=["EURUSD"]), 0.0)
|
|
|
|
def test_returns_zero_for_positions_without_symbol_column_with_symbol_filter(
|
|
self,
|
|
) -> None:
|
|
"""Test positions missing a symbol column return zero when filtered."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[{"type": 0, "volume": 0.1}],
|
|
)
|
|
|
|
_assert_close(calculate_positions_margin(client, symbols=["EURUSD"]), 0.0)
|
|
client.order_calc_margin.assert_not_called()
|
|
|
|
|
|
class TestVolumeAndExecution:
|
|
"""Tests for order planning and execution helpers."""
|
|
|
|
def test_calculate_volume_by_margin_rounds_down_to_step(self) -> None:
|
|
"""Test affordable volume respects min, max, and step."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {
|
|
"volume_min": 0.1,
|
|
"volume_max": 1.0,
|
|
"volume_step": 0.1,
|
|
}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 100.0, "bid": 99.0}
|
|
client.order_calc_margin.return_value = 25.0
|
|
|
|
_assert_close(
|
|
calculate_volume_by_margin(
|
|
client,
|
|
"EURUSD",
|
|
130.0,
|
|
"BUY",
|
|
),
|
|
0.5,
|
|
)
|
|
|
|
def test_calculate_volume_by_margin_caps_at_max_volume(self) -> None:
|
|
"""Test positive volume_max caps raw affordable volume exactly."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {
|
|
"volume_min": 0.1,
|
|
"volume_max": 0.3,
|
|
"volume_step": 0.1,
|
|
}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 100.0, "bid": 99.0}
|
|
client.order_calc_margin.return_value = 10.0
|
|
|
|
_assert_close(calculate_volume_by_margin(client, "EURUSD", 100.0, "BUY"), 0.3)
|
|
|
|
def test_calculate_volume_by_margin_ignores_zero_max_volume(self) -> None:
|
|
"""Test zero volume_max means uncapped volume normalization."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {
|
|
"volume_min": 0.1,
|
|
"volume_max": 0.0,
|
|
"volume_step": 0.1,
|
|
}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 100.0, "bid": 99.0}
|
|
client.order_calc_margin.return_value = 10.0
|
|
|
|
_assert_close(calculate_volume_by_margin(client, "EURUSD", 35.0, "BUY"), 0.3)
|
|
|
|
def test_calculate_volume_by_margin_returns_zero_when_unaffordable(self) -> None:
|
|
"""Test unaffordable minimum volume returns zero."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {
|
|
"volume_min": 0.1,
|
|
"volume_max": 1.0,
|
|
"volume_step": 0.1,
|
|
}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 100.0, "bid": 99.0}
|
|
client.order_calc_margin.return_value = 25.0
|
|
|
|
_assert_close(
|
|
calculate_volume_by_margin(
|
|
client,
|
|
"EURUSD",
|
|
10.0,
|
|
"BUY",
|
|
),
|
|
0.0,
|
|
)
|
|
|
|
def test_calculate_volume_by_margin_never_returns_nonzero_below_volume_min(
|
|
self,
|
|
) -> None:
|
|
"""Test non-zero affordable volume is never below volume_min."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {
|
|
"volume_min": 0.1,
|
|
"volume_max": 1.0,
|
|
"volume_step": 0.1,
|
|
}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 100.0, "bid": 99.0}
|
|
client.order_calc_margin.return_value = 10.0
|
|
|
|
volume = calculate_volume_by_margin(client, "EURUSD", 35.0, "BUY")
|
|
|
|
assert abs(volume) < 1e-9 or volume >= 0.1
|
|
|
|
def test_calculate_volume_by_margin_returns_zero_without_margin(self) -> None:
|
|
"""Test non-positive available margin returns zero before MT5 calls."""
|
|
client = _mock_trade_client()
|
|
|
|
_assert_close(
|
|
calculate_volume_by_margin(
|
|
client,
|
|
"EURUSD",
|
|
0.0,
|
|
"BUY",
|
|
),
|
|
0.0,
|
|
)
|
|
client.order_calc_margin.assert_not_called()
|
|
|
|
def test_calculate_volume_by_margin_rejects_invalid_constraints(self) -> None:
|
|
"""Test invalid symbol volume constraints raise a trading error."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {
|
|
"volume_min": 0.0,
|
|
"volume_max": 1.0,
|
|
"volume_step": 0.1,
|
|
}
|
|
|
|
with pytest.raises(Mt5TradingError):
|
|
calculate_volume_by_margin(client, "EURUSD", 100.0, "BUY")
|
|
|
|
def test_calculate_volume_by_margin_rejects_bad_tick(self) -> None:
|
|
"""Test unavailable side price raises a trading error."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {
|
|
"volume_min": 0.1,
|
|
"volume_max": 1.0,
|
|
"volume_step": 0.1,
|
|
}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.0, "bid": None}
|
|
|
|
with pytest.raises(Mt5TradingError):
|
|
calculate_volume_by_margin(client, "EURUSD", 100.0, "SELL")
|
|
|
|
def test_calculate_volume_by_margin_steps_down_when_margin_exceeds_budget(
|
|
self,
|
|
) -> None:
|
|
"""Tiered margin: binary search returns the largest affordable step."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {
|
|
"volume_min": 0.1,
|
|
"volume_max": 1.0,
|
|
"volume_step": 0.1,
|
|
}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 100.0, "bid": 99.0}
|
|
# min_margin (0.1): 25.0 -> hi=4.
|
|
# Search: mid=2 (0.3)->75<=130, mid=3 (0.4)->100<=130, mid=4 (0.5)->150>130.
|
|
client.order_calc_margin.side_effect = [25.0, 75.0, 100.0, 150.0]
|
|
|
|
result = calculate_volume_by_margin(client, "EURUSD", 130.0, "BUY")
|
|
|
|
_assert_close(result, 0.4)
|
|
|
|
def test_calculate_volume_by_margin_returns_zero_when_all_steps_unaffordable(
|
|
self,
|
|
) -> None:
|
|
"""If all binary-search probes exceed budget, returns zero."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {
|
|
"volume_min": 0.1,
|
|
"volume_max": 0.5,
|
|
"volume_step": 0.1,
|
|
}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 100.0, "bid": 99.0}
|
|
# min_margin (0.1): 10.0 -> hi=4.
|
|
# Search: mid=2 (0.3)->150>130->hi=1, mid=0 (0.1)->150>130->hi=-1.
|
|
client.order_calc_margin.side_effect = [10.0, 150.0, 150.0]
|
|
|
|
result = calculate_volume_by_margin(client, "EURUSD", 130.0, "BUY")
|
|
|
|
_assert_close(result, 0.0)
|
|
|
|
def test_calculate_volume_by_margin_binary_search_is_bounded(self) -> None:
|
|
"""Binary search finds the largest affordable volume in O(log n) MT5 calls."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {
|
|
"volume_min": 0.01,
|
|
"volume_max": 1000.0,
|
|
"volume_step": 0.01,
|
|
}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 100.0, "bid": 99.0}
|
|
# Steps 0-50000 cost 0.001 (affordable); steps 50001+ cost 2000.0 (not).
|
|
# Total range: 99999 steps. Linear scan: ~50000 calls; binary search: ~17.
|
|
affordable_step = 50000
|
|
|
|
def _margin(_ot: int, _sym: str, volume: float, _px: float) -> float:
|
|
step = round((volume - 0.01) / 0.01)
|
|
return 0.001 if step <= affordable_step else 2000.0
|
|
|
|
client.order_calc_margin.side_effect = _margin
|
|
result = calculate_volume_by_margin(client, "EURUSD", 200.0, "BUY")
|
|
|
|
_assert_close(result, 500.01) # 0.01 + 50000 * 0.01
|
|
assert client.order_calc_margin.call_count <= 25
|
|
|
|
def test_calculate_margin_and_volume_without_native_helper(self) -> None:
|
|
"""Test margin helper uses module volume calculation when needed."""
|
|
|
|
class ClientWithoutNative:
|
|
mt5 = SimpleNamespace(ORDER_TYPE_BUY=10, ORDER_TYPE_SELL=11)
|
|
|
|
def account_info_as_dict(self) -> dict[str, float]:
|
|
return {"margin_free": 100.0}
|
|
|
|
def symbol_info_as_dict(self, *, symbol: str) -> dict[str, float]:
|
|
assert symbol == "EURUSD"
|
|
return {"volume_min": 0.1, "volume_max": 1.0, "volume_step": 0.1}
|
|
|
|
def symbol_info_tick_as_dict(self, *, symbol: str) -> dict[str, float]:
|
|
assert symbol == "EURUSD"
|
|
return {"ask": 100.0, "bid": 100.0}
|
|
|
|
def order_calc_margin(
|
|
self,
|
|
order_type: int,
|
|
symbol: str,
|
|
volume: float,
|
|
price: float,
|
|
) -> float:
|
|
assert order_type in {10, 11}
|
|
assert symbol == "EURUSD"
|
|
assert 0.1 <= volume <= 1.0
|
|
_assert_close(price, 100.0)
|
|
return 10.0
|
|
|
|
result = calculate_margin_and_volume(
|
|
cast("Mt5TradingClient", ClientWithoutNative()),
|
|
"EURUSD",
|
|
unit_margin_ratio=0.5,
|
|
preserved_margin_ratio=0.0,
|
|
)
|
|
|
|
_assert_close(result["buy_volume"], 0.5)
|
|
_assert_close(result["sell_volume"], 0.5)
|
|
|
|
def test_calculate_margin_and_volume_zero_ratio_uses_minimum_volume(
|
|
self,
|
|
) -> None:
|
|
"""Test zero unit ratio requests one minimum volume when affordable."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"margin_free": 100.0}
|
|
client.symbol_info_as_dict.return_value = {
|
|
"volume_min": 0.1,
|
|
"volume_max": 1.0,
|
|
"volume_step": 0.1,
|
|
}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 100.0, "bid": 99.0}
|
|
client.order_calc_margin.side_effect = [10.0, 20.0]
|
|
|
|
result = calculate_margin_and_volume(
|
|
client,
|
|
"EURUSD",
|
|
unit_margin_ratio=0.0,
|
|
preserved_margin_ratio=0.0,
|
|
)
|
|
|
|
_assert_close(result["available_margin"], 100.0)
|
|
_assert_close(result["trade_margin"], 0.0)
|
|
_assert_close(result["buy_volume"], 0.1)
|
|
_assert_close(result["sell_volume"], 0.1)
|
|
client.calculate_volume_by_margin.assert_not_called()
|
|
|
|
def test_calculate_margin_and_volume_zero_ratio_rejects_unaffordable_side(
|
|
self,
|
|
) -> None:
|
|
"""Test zero unit ratio returns zero for unaffordable minimum lots."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"margin_free": 15.0}
|
|
client.symbol_info_as_dict.return_value = {
|
|
"volume_min": 0.1,
|
|
"volume_max": 1.0,
|
|
"volume_step": 0.1,
|
|
}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 100.0, "bid": 99.0}
|
|
client.order_calc_margin.side_effect = [10.0, 20.0]
|
|
|
|
result = calculate_margin_and_volume(
|
|
client,
|
|
"EURUSD",
|
|
unit_margin_ratio=0.0,
|
|
preserved_margin_ratio=0.0,
|
|
)
|
|
|
|
_assert_close(result["buy_volume"], 0.1)
|
|
_assert_close(result["sell_volume"], 0.0)
|
|
|
|
def test_calculate_margin_and_volume_zero_ratio_preserves_margin_first(
|
|
self,
|
|
) -> None:
|
|
"""Test preserved margin reduces affordability before min sizing."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"margin_free": 100.0}
|
|
client.symbol_info_as_dict.return_value = {
|
|
"volume_min": 0.1,
|
|
"volume_max": 1.0,
|
|
"volume_step": 0.1,
|
|
}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 100.0, "bid": 99.0}
|
|
client.order_calc_margin.side_effect = [11.0, 9.0]
|
|
|
|
result = calculate_margin_and_volume(
|
|
client,
|
|
"EURUSD",
|
|
unit_margin_ratio=0.0,
|
|
preserved_margin_ratio=0.9,
|
|
)
|
|
|
|
_assert_close(result["available_margin"], 10.0)
|
|
_assert_close(result["buy_volume"], 0.0)
|
|
_assert_close(result["sell_volume"], 0.1)
|
|
|
|
def test_calculate_margin_and_volume_zero_ratio_without_available_margin(
|
|
self,
|
|
) -> None:
|
|
"""Test zero unit ratio returns zero when preserved margin consumes funds."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"margin_free": 100.0}
|
|
client.symbol_info_as_dict.return_value = {
|
|
"volume_min": 0.1,
|
|
"volume_max": 1.0,
|
|
"volume_step": 0.1,
|
|
}
|
|
|
|
result = calculate_margin_and_volume(
|
|
client,
|
|
"EURUSD",
|
|
unit_margin_ratio=0.0,
|
|
preserved_margin_ratio=1.0,
|
|
)
|
|
|
|
_assert_close(result["buy_volume"], 0.0)
|
|
_assert_close(result["sell_volume"], 0.0)
|
|
client.order_calc_margin.assert_not_called()
|
|
|
|
def test_calculate_margin_and_volume_zero_ratio_rejects_invalid_max_volume(
|
|
self,
|
|
) -> None:
|
|
"""Test zero unit ratio still respects max-volume constraints."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"margin_free": 100.0}
|
|
client.symbol_info_as_dict.return_value = {
|
|
"volume_min": 0.2,
|
|
"volume_max": 0.1,
|
|
"volume_step": 0.1,
|
|
}
|
|
|
|
with pytest.raises(Mt5TradingError, match="Invalid volume constraints"):
|
|
calculate_margin_and_volume(
|
|
client,
|
|
"EURUSD",
|
|
unit_margin_ratio=0.0,
|
|
preserved_margin_ratio=0.0,
|
|
)
|
|
|
|
def test_calculate_margin_and_volume_zero_ratio_rejects_bad_tick(self) -> None:
|
|
"""Test zero unit ratio validates tick data for minimum sizing."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"margin_free": 100.0}
|
|
client.symbol_info_as_dict.return_value = {
|
|
"volume_min": 0.1,
|
|
"volume_max": 1.0,
|
|
"volume_step": 0.1,
|
|
}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": None, "bid": 99.0}
|
|
|
|
with pytest.raises(Mt5TradingError, match="Tick price is unavailable"):
|
|
calculate_margin_and_volume(
|
|
client,
|
|
"EURUSD",
|
|
unit_margin_ratio=0.0,
|
|
preserved_margin_ratio=0.0,
|
|
)
|
|
|
|
def test_calculate_margin_and_volume_positive_ratio_avoids_oversized_native_volume(
|
|
self,
|
|
) -> None:
|
|
"""Regression: module path is used even when native helper is present.
|
|
|
|
The pdmt5 linear estimate (floor(40/10)*0.1 = 0.4) would overstate
|
|
affordable volume because order_calc_margin returns 45.0 for 0.4 lots,
|
|
exceeding the 40.0 budget. The module's verified binary search returns
|
|
0.3 (margin=30.0), which is safe.
|
|
"""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"margin_free": 100.0}
|
|
client.symbol_info_as_dict.return_value = {
|
|
"volume_min": 0.1,
|
|
"volume_max": 1.0,
|
|
"volume_step": 0.1,
|
|
}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 100.0, "bid": 99.0}
|
|
client.calculate_volume_by_margin.return_value = 0.4 # pdmt5 linear oversized
|
|
|
|
def _mock_calc_margin(
|
|
_order_type: int, _symbol: str, volume: float, _price: float
|
|
) -> float:
|
|
if volume <= 0.3:
|
|
return round(volume * 100.0, 10) # 0.1→10, 0.2→20, 0.3→30
|
|
return round(volume * 112.5, 10) # 0.4→45 — exceeds 40.0 budget
|
|
|
|
client.order_calc_margin.side_effect = _mock_calc_margin
|
|
|
|
result = calculate_margin_and_volume(
|
|
client,
|
|
"EURUSD",
|
|
unit_margin_ratio=0.5,
|
|
preserved_margin_ratio=0.2,
|
|
)
|
|
|
|
_assert_close(result["trade_margin"], 40.0)
|
|
_assert_close(result["buy_volume"], 0.3)
|
|
_assert_close(result["sell_volume"], 0.3)
|
|
client.calculate_volume_by_margin.assert_not_called()
|
|
|
|
def test_calculate_margin_and_volume_positive_ratio_raises_on_missing_symbol_info(
|
|
self,
|
|
) -> None:
|
|
"""Test missing symbol info propagates an error when ratio is positive."""
|
|
client = MagicMock()
|
|
client.account_info_as_dict.return_value = {"margin_free": 1000.0}
|
|
client.symbol_info_as_dict.side_effect = AttributeError("missing")
|
|
|
|
with pytest.raises(AttributeError, match="missing"):
|
|
calculate_margin_and_volume(
|
|
client,
|
|
"EURUSD",
|
|
unit_margin_ratio=0.5,
|
|
preserved_margin_ratio=0.2,
|
|
)
|
|
|
|
def test_new_position_margin_ratio_adds_hypothetical_margin(self) -> None:
|
|
"""Test hypothetical order margin is added to account margin."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"equity": 1000.0, "margin": 50.0}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 100.0, "bid": 99.0}
|
|
client.order_calc_margin.return_value = 25.0
|
|
|
|
result = calculate_new_position_margin_ratio(
|
|
client,
|
|
symbol="EURUSD",
|
|
new_position_side="BUY",
|
|
new_position_volume=0.1,
|
|
)
|
|
_assert_close(result, 0.075)
|
|
|
|
def test_new_position_margin_ratio_without_new_position(self) -> None:
|
|
"""Test current margin ratio can be calculated without a new order."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"equity": 1000.0, "margin": 50.0}
|
|
|
|
_assert_close(
|
|
calculate_new_position_margin_ratio(
|
|
client,
|
|
symbol="EURUSD",
|
|
),
|
|
0.05,
|
|
)
|
|
client.order_calc_margin.assert_not_called()
|
|
|
|
def test_new_position_margin_ratio_rejects_invalid_equity(self) -> None:
|
|
"""Test non-positive equity raises a trading error."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"equity": 0.0, "margin": 50.0}
|
|
|
|
with pytest.raises(Mt5TradingError):
|
|
calculate_new_position_margin_ratio(client, symbol="EURUSD")
|
|
|
|
def test_new_position_margin_ratio_rejects_bad_tick(self) -> None:
|
|
"""Test missing hypothetical order price raises a trading error."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"equity": 1000.0, "margin": 50.0}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": None, "bid": 1.0}
|
|
|
|
with pytest.raises(Mt5TradingError):
|
|
calculate_new_position_margin_ratio(
|
|
client,
|
|
symbol="EURUSD",
|
|
new_position_side="BUY",
|
|
new_position_volume=0.1,
|
|
)
|
|
|
|
def test_projected_margin_ratio_empty_positions(self) -> None:
|
|
"""Test no current or projected exposure returns zero ratio."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"equity": 1000.0}
|
|
client.positions_get_as_df.return_value = pd.DataFrame()
|
|
|
|
_assert_close(calculate_projected_margin_ratio(client, symbol="EURUSD"), 0.0)
|
|
|
|
def test_projected_margin_ratio_current_exposure(self) -> None:
|
|
"""Test current position margin is divided by account equity."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"equity": 1000.0}
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[{"symbol": "EURUSD", "type": 0, "volume": 0.2}],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.101, "bid": 1.1}
|
|
client.order_calc_margin.return_value = 50.0
|
|
|
|
_assert_close(calculate_projected_margin_ratio(client, symbol="EURUSD"), 0.05)
|
|
|
|
def test_projected_margin_ratio_adds_buy_exposure(self) -> None:
|
|
"""Test projected buy margin is added to current symbol exposure."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"equity": 1000.0}
|
|
client.positions_get_as_df.return_value = pd.DataFrame()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.101, "bid": 1.1}
|
|
client.order_calc_margin.return_value = 25.0
|
|
|
|
result = calculate_projected_margin_ratio(
|
|
client,
|
|
symbol="EURUSD",
|
|
new_position_side="BUY",
|
|
new_position_volume=0.1,
|
|
)
|
|
|
|
_assert_close(result, 0.025)
|
|
client.order_calc_margin.assert_called_once_with(10, "EURUSD", 0.1, 1.101)
|
|
|
|
def test_projected_margin_ratio_adds_sell_exposure(self) -> None:
|
|
"""Test projected sell margin uses bid pricing."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"equity": 1000.0}
|
|
client.positions_get_as_df.return_value = pd.DataFrame()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.101, "bid": 1.1}
|
|
client.order_calc_margin.return_value = 24.0
|
|
|
|
result = calculate_projected_margin_ratio(
|
|
client,
|
|
symbol="EURUSD",
|
|
new_position_side="SELL",
|
|
new_position_volume=0.1,
|
|
)
|
|
|
|
_assert_close(result, 0.024)
|
|
client.order_calc_margin.assert_called_once_with(11, "EURUSD", 0.1, 1.1)
|
|
|
|
@pytest.mark.parametrize(
|
|
("account", "kwargs", "candidate_margin", "expected_ratio"),
|
|
[
|
|
({"equity": 10_000.0, "margin": 4500.0}, {}, None, 0.45),
|
|
(
|
|
{"equity": 10_000.0, "margin": 4500.0},
|
|
{
|
|
"symbol": "EURUSD",
|
|
"new_position_side": "BUY",
|
|
"new_position_volume": 0.1,
|
|
},
|
|
1000.0,
|
|
0.55,
|
|
),
|
|
({"equity": 10_000.0, "margin": 55.0}, {}, None, 0.0055),
|
|
],
|
|
)
|
|
def test_account_projected_margin_ratio_uses_account_margin_baseline(
|
|
self,
|
|
account: dict[str, object],
|
|
kwargs: dict[str, object],
|
|
candidate_margin: float | None,
|
|
expected_ratio: float,
|
|
mocker: MockerFixture,
|
|
) -> None:
|
|
"""Test account-wide exposure uses snapshot margin plus optional candidate."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = account
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[{"symbol": "GBPUSD", "type": 0, "volume": 2.0}],
|
|
)
|
|
mock_margin = mocker.patch(
|
|
"mt5cli.trading.estimate_order_margin",
|
|
return_value=candidate_margin,
|
|
)
|
|
|
|
result = calculate_account_projected_margin_ratio(client, **cast("Any", kwargs))
|
|
|
|
_assert_close(result, expected_ratio)
|
|
if candidate_margin is None:
|
|
mock_margin.assert_not_called()
|
|
else:
|
|
mock_margin.assert_called_once_with(client, "EURUSD", "BUY", 0.1)
|
|
client.positions_get_as_df.assert_not_called()
|
|
|
|
@pytest.mark.parametrize(
|
|
("kwargs", "expected_ratio"),
|
|
[
|
|
({"new_position_side": "BUY", "new_position_volume": 0.1}, 0.45),
|
|
({"symbol": "EURUSD", "new_position_volume": 0.1}, 0.45),
|
|
({"symbol": "EURUSD", "new_position_side": "BUY"}, 0.45),
|
|
(
|
|
{
|
|
"symbol": "EURUSD",
|
|
"new_position_side": "BUY",
|
|
"new_position_volume": -0.1,
|
|
},
|
|
0.45,
|
|
),
|
|
],
|
|
)
|
|
def test_account_projected_margin_ratio_skips_incomplete_candidate(
|
|
self,
|
|
kwargs: dict[str, object],
|
|
expected_ratio: float,
|
|
mocker: MockerFixture,
|
|
) -> None:
|
|
"""Test candidate margin is added only when symbol, side, and volume exist."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {
|
|
"equity": 10_000.0,
|
|
"margin": 4500.0,
|
|
}
|
|
mock_margin = mocker.patch("mt5cli.trading.estimate_order_margin")
|
|
|
|
result = calculate_account_projected_margin_ratio(client, **cast("Any", kwargs))
|
|
|
|
_assert_close(result, expected_ratio)
|
|
mock_margin.assert_not_called()
|
|
|
|
@pytest.mark.parametrize(
|
|
("account", "match"),
|
|
[
|
|
({"margin": 4500.0}, "Account equity"),
|
|
({"equity": None, "margin": 4500.0}, "Account equity"),
|
|
({"equity": "10000", "margin": 4500.0}, "Account equity"),
|
|
({"equity": True, "margin": 4500.0}, "Account equity"),
|
|
({"equity": float("nan"), "margin": 4500.0}, "Account equity"),
|
|
({"equity": float("inf"), "margin": 4500.0}, "Account equity"),
|
|
({"equity": 0.0, "margin": 4500.0}, "Account equity"),
|
|
({"equity": -1.0, "margin": 4500.0}, "Account equity"),
|
|
({"equity": 10_000.0}, "Account margin"),
|
|
({"equity": 10_000.0, "margin": None}, "Account margin"),
|
|
({"equity": 10_000.0, "margin": "4500"}, "Account margin"),
|
|
({"equity": 10_000.0, "margin": True}, "Account margin"),
|
|
({"equity": 10_000.0, "margin": False}, "Account margin"),
|
|
({"equity": 10_000.0, "margin": float("nan")}, "Account margin"),
|
|
({"equity": 10_000.0, "margin": float("inf")}, "Account margin"),
|
|
({"equity": 10_000.0, "margin": -1.0}, "Account margin"),
|
|
],
|
|
)
|
|
def test_account_projected_margin_ratio_rejects_invalid_snapshot_fields(
|
|
self,
|
|
account: dict[str, object],
|
|
match: str,
|
|
) -> None:
|
|
"""Test invalid account equity and margin fields fail closed."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = account
|
|
|
|
with pytest.raises(Mt5TradingError, match=match):
|
|
calculate_account_projected_margin_ratio(client)
|
|
|
|
def test_account_projected_margin_ratio_propagates_candidate_margin_error(
|
|
self,
|
|
mocker: MockerFixture,
|
|
) -> None:
|
|
"""Test candidate margin errors are not suppressed."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {
|
|
"equity": 10_000.0,
|
|
"margin": 4500.0,
|
|
}
|
|
mocker.patch(
|
|
"mt5cli.trading.estimate_order_margin",
|
|
side_effect=Mt5TradingError("bad tick"),
|
|
)
|
|
|
|
with pytest.raises(Mt5TradingError, match="bad tick"):
|
|
calculate_account_projected_margin_ratio(
|
|
client,
|
|
symbol="EURUSD",
|
|
new_position_side="BUY",
|
|
new_position_volume=0.1,
|
|
)
|
|
|
|
def test_symbol_group_margin_ratio_sums_group_exposure(
|
|
self,
|
|
mocker: MockerFixture,
|
|
) -> None:
|
|
"""Test symbol-group exposure sums current per-symbol margins."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"equity": 1000.0}
|
|
mocker.patch(
|
|
"mt5cli.trading.calculate_positions_margin_by_symbol",
|
|
return_value={"EURUSD": 25.0, "GBPUSD": 35.0},
|
|
)
|
|
|
|
result = calculate_symbol_group_margin_ratio(
|
|
client,
|
|
symbols=["EURUSD", "GBPUSD"],
|
|
)
|
|
|
|
_assert_close(result, 0.06)
|
|
|
|
def test_symbol_group_margin_ratio_adds_projected_group_exposure(
|
|
self,
|
|
mocker: MockerFixture,
|
|
) -> None:
|
|
"""Test projected order margin is added when the symbol is in the group."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"equity": 1000.0}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.101, "bid": 1.1}
|
|
client.order_calc_margin.return_value = 15.0
|
|
mocker.patch(
|
|
"mt5cli.trading.calculate_positions_margin_by_symbol",
|
|
return_value={"EURUSD": 25.0},
|
|
)
|
|
|
|
result = calculate_symbol_group_margin_ratio(
|
|
client,
|
|
symbols=["EURUSD"],
|
|
new_symbol="EURUSD",
|
|
new_position_side="BUY",
|
|
new_position_volume=0.1,
|
|
)
|
|
|
|
_assert_close(result, 0.04)
|
|
|
|
def test_symbol_group_margin_ratio_suppresses_per_symbol_failures(
|
|
self,
|
|
mocker: MockerFixture,
|
|
) -> None:
|
|
"""Test suppressible per-symbol failures are skipped by the safe map."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"equity": 1000.0}
|
|
mocker.patch(
|
|
"mt5cli.trading.calculate_positions_margin",
|
|
side_effect=[Mt5TradingError("bad tick"), 30.0],
|
|
)
|
|
|
|
result = calculate_symbol_group_margin_ratio(
|
|
client,
|
|
symbols=["EURUSD", "GBPUSD"],
|
|
suppress_errors=True,
|
|
)
|
|
|
|
_assert_close(result, 0.03)
|
|
|
|
def test_symbol_group_margin_ratio_rejects_invalid_equity(self) -> None:
|
|
"""Test invalid equity fails closed for exposure helpers."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"equity": 0.0}
|
|
|
|
with pytest.raises(Mt5TradingError, match="Account equity"):
|
|
calculate_symbol_group_margin_ratio(client, symbols=["EURUSD"])
|
|
|
|
def test_projected_margin_ratio_rejects_nonnumeric_equity(self) -> None:
|
|
"""Test nonnumeric equity fails closed for exposure helpers."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"equity": "invalid"}
|
|
|
|
with pytest.raises(Mt5TradingError, match="Account equity"):
|
|
calculate_projected_margin_ratio(client, symbol="EURUSD")
|
|
|
|
def test_symbol_group_margin_ratio_suppresses_projected_failure(
|
|
self,
|
|
mocker: MockerFixture,
|
|
caplog: pytest.LogCaptureFixture,
|
|
) -> None:
|
|
"""Test projected margin failures can be skipped for safe group reads."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"equity": 1000.0}
|
|
mocker.patch(
|
|
"mt5cli.trading.calculate_positions_margin_by_symbol",
|
|
return_value={},
|
|
)
|
|
mocker.patch(
|
|
"mt5cli.trading.estimate_order_margin",
|
|
side_effect=Mt5TradingError("bad tick"),
|
|
)
|
|
|
|
with caplog.at_level(logging.WARNING, logger="mt5cli.trading"):
|
|
result = calculate_symbol_group_margin_ratio(
|
|
client,
|
|
symbols=["EURUSD"],
|
|
new_symbol="EURUSD",
|
|
new_position_side="BUY",
|
|
new_position_volume=0.1,
|
|
suppress_errors=True,
|
|
)
|
|
|
|
_assert_close(result, 0.0)
|
|
assert "Skipping projected margin" in caplog.text
|
|
|
|
def test_symbol_group_margin_ratio_reraises_projected_failure(
|
|
self,
|
|
mocker: MockerFixture,
|
|
) -> None:
|
|
"""Test projected margin failures raise when suppression is disabled."""
|
|
client = _mock_trade_client()
|
|
client.account_info_as_dict.return_value = {"equity": 1000.0}
|
|
mocker.patch(
|
|
"mt5cli.trading.calculate_positions_margin_by_symbol",
|
|
return_value={},
|
|
)
|
|
mocker.patch(
|
|
"mt5cli.trading.estimate_order_margin",
|
|
side_effect=Mt5TradingError("bad tick"),
|
|
)
|
|
|
|
with pytest.raises(Mt5TradingError, match="bad tick"):
|
|
calculate_symbol_group_margin_ratio(
|
|
client,
|
|
symbols=["EURUSD"],
|
|
new_symbol="EURUSD",
|
|
new_position_side="BUY",
|
|
new_position_volume=0.1,
|
|
suppress_errors=False,
|
|
)
|
|
|
|
def test_place_market_order_dry_run_does_not_send(self) -> None:
|
|
"""Test dry-run market orders return a request without sending."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {"visible": False}
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
|
|
result = place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
dry_run=True,
|
|
)
|
|
|
|
assert result["status"] == "dry_run"
|
|
assert _request_from_result(result)["type"] == client.mt5.ORDER_TYPE_BUY
|
|
client.order_send.assert_not_called()
|
|
client.symbol_select.assert_not_called()
|
|
|
|
def test_place_market_order_supports_limits(self) -> None:
|
|
"""Test optional SL/TP values are included in the request."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
|
|
result = place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
sl=1.0,
|
|
tp=1.4,
|
|
dry_run=True,
|
|
)
|
|
|
|
_assert_close(_request_from_result(result)["sl"], 1.0)
|
|
_assert_close(_request_from_result(result)["tp"], 1.4)
|
|
|
|
def test_place_market_order_rejects_invalid_filling_mode(self) -> None:
|
|
"""Test MT5 filling mode names are validated before getattr."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
|
|
with pytest.raises(ValueError, match="Unsupported order_filling mode"):
|
|
place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
order_filling_mode=cast("Any", "BAD"),
|
|
dry_run=True,
|
|
)
|
|
|
|
def test_place_market_order_rejects_invalid_time_mode(self) -> None:
|
|
"""Test MT5 time mode names are validated before getattr."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
|
|
with pytest.raises(ValueError, match="Unsupported order_time mode"):
|
|
place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
order_time_mode=cast("Any", "BAD"),
|
|
dry_run=True,
|
|
)
|
|
|
|
def test_place_market_order_rejects_missing_mt5_constant(self) -> None:
|
|
"""Test missing MT5 constants fail with a controlled trading error."""
|
|
client = _mock_trade_client()
|
|
del client.mt5.ORDER_FILLING_IOC
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
|
|
with pytest.raises(Mt5TradingError, match="ORDER_FILLING_IOC"):
|
|
place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
dry_run=True,
|
|
)
|
|
|
|
def test_place_market_order_rejects_invalid_volume(self) -> None:
|
|
"""Test non-positive volume raises a trading error."""
|
|
with pytest.raises(Mt5TradingError):
|
|
place_market_order(
|
|
_mock_trade_client(),
|
|
symbol="EURUSD",
|
|
volume=0.0,
|
|
order_side="BUY",
|
|
)
|
|
|
|
def test_place_market_order_rejects_bad_tick(self) -> None:
|
|
"""Test unavailable market order price raises a trading error."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": None, "bid": 1.1}
|
|
|
|
with pytest.raises(Mt5TradingError):
|
|
place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
)
|
|
|
|
def test_place_market_order_rejects_unknown_side(self) -> None:
|
|
"""Test unsupported order sides raise ValueError."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
|
|
with pytest.raises(ValueError, match="Unsupported order side"):
|
|
place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side=cast("Any", "FLAT"),
|
|
)
|
|
|
|
def test_place_market_order_sends_and_normalizes_response(self) -> None:
|
|
"""Test live market order responses are normalized."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": 10009, "comment": "done"}],
|
|
)
|
|
|
|
result = place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="SELL",
|
|
)
|
|
|
|
assert result["status"] == "executed"
|
|
assert result["retcode"] == 10009
|
|
client.order_send.assert_called_once()
|
|
|
|
def test_place_market_order_marks_failed_retcode(self) -> None:
|
|
"""Test order_send responses with failed retcodes are normalized."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": 10013, "comment": "invalid request"}],
|
|
)
|
|
|
|
result = place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
)
|
|
|
|
assert result["status"] == "failed"
|
|
assert result["retcode"] == 10013
|
|
|
|
def test_place_market_order_marks_failed_numpy_retcode(self) -> None:
|
|
"""Test numpy integer retcodes normalize to failed status."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": np_int64(10013), "comment": "invalid request"}],
|
|
)
|
|
|
|
result = place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
)
|
|
|
|
assert result["status"] == "failed"
|
|
assert result["retcode"] == 10013
|
|
|
|
def test_place_market_order_rejects_bool_retcode(self) -> None:
|
|
"""Test bool retcodes are not treated as integer broker codes."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": True, "comment": "weird"}],
|
|
)
|
|
|
|
result = place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
)
|
|
|
|
assert result["retcode"] is None
|
|
assert result["status"] == "failed"
|
|
|
|
def test_place_market_order_marks_failed_string_retcode(self) -> None:
|
|
"""Test digit-string failure retcodes normalize to failed status."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": "10013", "comment": "invalid request"}],
|
|
)
|
|
|
|
result = place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
)
|
|
|
|
assert result["retcode"] == 10013
|
|
assert result["status"] == "failed"
|
|
|
|
def test_place_market_order_marks_failed_whitespace_string_retcode(self) -> None:
|
|
"""Test whitespace-padded digit-string retcodes normalize to failed status."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": " 10013 ", "comment": "invalid request"}],
|
|
)
|
|
|
|
result = place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
)
|
|
|
|
assert result["retcode"] == 10013
|
|
assert result["status"] == "failed"
|
|
|
|
@pytest.mark.parametrize("retcode", ["+10013", "-10013"])
|
|
def test_place_market_order_marks_signed_string_retcode_as_failed(
|
|
self,
|
|
retcode: str,
|
|
) -> None:
|
|
"""Test signed digit-string failure retcodes normalize to failed status."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": retcode, "comment": "invalid request"}],
|
|
)
|
|
|
|
result = place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
)
|
|
|
|
expected = 10013 if retcode.startswith("+") else -10013
|
|
assert result["retcode"] == expected
|
|
assert result["status"] == "failed"
|
|
|
|
def test_place_market_order_marks_missing_retcode_as_failed(self) -> None:
|
|
"""Test live responses without retcode are fail-closed."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"comment": "missing retcode"}],
|
|
)
|
|
|
|
result = place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
)
|
|
|
|
assert result["retcode"] is None
|
|
assert result["status"] == "failed"
|
|
|
|
def test_place_market_order_marks_malformed_retcode_as_failed(self) -> None:
|
|
"""Test malformed non-None retcodes are fail-closed."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": "invalid", "comment": "invalid request"}],
|
|
)
|
|
|
|
result = place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
)
|
|
|
|
assert result["retcode"] is None
|
|
assert result["status"] == "failed"
|
|
|
|
def test_place_market_order_marks_empty_string_retcode_as_failed(self) -> None:
|
|
"""Test empty string retcodes are fail-closed."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": " ", "comment": "invalid request"}],
|
|
)
|
|
|
|
result = place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
)
|
|
|
|
assert result["retcode"] is None
|
|
assert result["status"] == "failed"
|
|
|
|
def test_place_market_order_marks_object_retcode_as_failed(self) -> None:
|
|
"""Test unsupported retcode object types are fail-closed."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": object(), "comment": "invalid request"}],
|
|
)
|
|
|
|
result = place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
)
|
|
|
|
assert result["retcode"] is None
|
|
assert result["status"] == "failed"
|
|
|
|
def test_close_open_positions_filters_and_dry_runs(self) -> None:
|
|
"""Test close helper filters positions and builds opposite orders."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{"ticket": 1, "symbol": "EURUSD", "type": 0, "volume": 0.1},
|
|
{"ticket": 2, "symbol": "USDJPY", "type": 1, "volume": 0.2},
|
|
],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
|
|
result = close_open_positions(client, symbols="EURUSD", dry_run=True)
|
|
|
|
assert len(result) == 1
|
|
assert result[0]["order_side"] == "SELL"
|
|
assert _request_from_result(result[0])["position"] == 1
|
|
|
|
def test_close_open_positions_filters_by_ticket(self) -> None:
|
|
"""Test close helper can filter by ticket."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{"ticket": 1, "symbol": "EURUSD", "type": 0, "volume": 0.1},
|
|
{"ticket": 2, "symbol": "USDJPY", "type": 1, "volume": 0.2},
|
|
],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
|
|
result = close_open_positions(client, tickets=[2], dry_run=True)
|
|
|
|
assert len(result) == 1
|
|
assert result[0]["order_side"] == "BUY"
|
|
|
|
def test_close_open_positions_sends_position_ticket(self) -> None:
|
|
"""Test live close orders include the position before order_send."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[{"ticket": 9, "symbol": "EURUSD", "type": 0, "volume": 0.1}],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
client.order_send.return_value = SimpleNamespace(retcode=10009, comment="done")
|
|
|
|
close_open_positions(client, tickets=[9])
|
|
|
|
assert client.order_send.call_args.args[0]["position"] == 9
|
|
|
|
def test_calculate_trailing_stop_updates_no_positions(self) -> None:
|
|
"""Test empty position sets produce no trailing updates."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame()
|
|
|
|
assert (
|
|
calculate_trailing_stop_updates(
|
|
client,
|
|
symbol="EURUSD",
|
|
trailing_stop_ratio=0.02,
|
|
)
|
|
== {}
|
|
)
|
|
|
|
def test_calculate_trailing_stop_updates_buy_positions(self) -> None:
|
|
"""Test buy trailing stops use bid and improve only upward."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{"ticket": 1, "symbol": "EURUSD", "type": 0, "volume": 0.1, "sl": 1.0},
|
|
{
|
|
"ticket": 2,
|
|
"symbol": "EURUSD",
|
|
"type": 0,
|
|
"volume": 0.1,
|
|
"sl": 1.19,
|
|
},
|
|
],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"bid": 1.2, "ask": 1.201}
|
|
client.symbol_info_as_dict.return_value = {"digits": 4}
|
|
|
|
result = calculate_trailing_stop_updates(
|
|
client,
|
|
symbol="EURUSD",
|
|
trailing_stop_ratio=0.01,
|
|
)
|
|
|
|
assert result == {1: 1.188}
|
|
|
|
def test_calculate_trailing_stop_updates_buy_positions_ignore_invalid_ask(
|
|
self,
|
|
) -> None:
|
|
"""Test buy trailing stops do not require an ask price."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[{"ticket": 1, "symbol": "EURUSD", "type": 0, "volume": 0.1, "sl": 1.0}],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"bid": 1.2, "ask": 0.0}
|
|
client.symbol_info_as_dict.return_value = {"digits": 4}
|
|
|
|
result = calculate_trailing_stop_updates(
|
|
client,
|
|
symbol="EURUSD",
|
|
trailing_stop_ratio=0.01,
|
|
)
|
|
|
|
assert result == {1: 1.188}
|
|
|
|
def test_calculate_trailing_stop_updates_sell_positions(self) -> None:
|
|
"""Test sell trailing stops use ask and improve only downward."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{"ticket": 3, "symbol": "EURUSD", "type": 1, "volume": 0.1, "sl": 1.3},
|
|
{
|
|
"ticket": 4,
|
|
"symbol": "EURUSD",
|
|
"type": 1,
|
|
"volume": 0.1,
|
|
"sl": 1.21,
|
|
},
|
|
],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"bid": 1.198, "ask": 1.2}
|
|
client.symbol_info_as_dict.return_value = {"digits": 4}
|
|
|
|
result = calculate_trailing_stop_updates(
|
|
client,
|
|
symbol="EURUSD",
|
|
trailing_stop_ratio=0.01,
|
|
)
|
|
|
|
assert result == {3: 1.212}
|
|
|
|
def test_calculate_trailing_stop_updates_sell_positions_ignore_invalid_bid(
|
|
self,
|
|
) -> None:
|
|
"""Test sell trailing stops do not require a bid price."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[{"ticket": 3, "symbol": "EURUSD", "type": 1, "volume": 0.1, "sl": 1.3}],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"bid": 0.0, "ask": 1.2}
|
|
client.symbol_info_as_dict.return_value = {"digits": 4}
|
|
|
|
result = calculate_trailing_stop_updates(
|
|
client,
|
|
symbol="EURUSD",
|
|
trailing_stop_ratio=0.01,
|
|
)
|
|
|
|
assert result == {3: 1.212}
|
|
|
|
def test_calculate_trailing_stop_updates_invalid_bid_or_ask(self) -> None:
|
|
"""Test invalid side-specific tick prices fail safely without updates."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{"ticket": 1, "symbol": "EURUSD", "type": 0, "volume": 0.1, "sl": 1.0},
|
|
{"ticket": 2, "symbol": "EURUSD", "type": 1, "volume": 0.1, "sl": 1.3},
|
|
],
|
|
)
|
|
client.symbol_info_as_dict.return_value = {"digits": 4}
|
|
|
|
client.symbol_info_tick_as_dict.return_value = {"bid": 0.0, "ask": None}
|
|
|
|
assert (
|
|
calculate_trailing_stop_updates(
|
|
client,
|
|
symbol="EURUSD",
|
|
trailing_stop_ratio=0.01,
|
|
)
|
|
== {}
|
|
)
|
|
|
|
def test_calculate_trailing_stop_updates_mixed_positions_skip_invalid_side(
|
|
self,
|
|
) -> None:
|
|
"""Test one invalid side price does not block the valid side."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{"ticket": 1, "symbol": "EURUSD", "type": 0, "volume": 0.1, "sl": 1.0},
|
|
{"ticket": 2, "symbol": "EURUSD", "type": 1, "volume": 0.1, "sl": 1.3},
|
|
],
|
|
)
|
|
client.symbol_info_as_dict.return_value = {"digits": 4}
|
|
|
|
client.symbol_info_tick_as_dict.return_value = {"bid": 1.2, "ask": 0.0}
|
|
assert calculate_trailing_stop_updates(
|
|
client,
|
|
symbol="EURUSD",
|
|
trailing_stop_ratio=0.01,
|
|
) == {1: 1.188}
|
|
|
|
client.symbol_info_tick_as_dict.return_value = {"bid": None, "ask": 1.2}
|
|
assert calculate_trailing_stop_updates(
|
|
client,
|
|
symbol="EURUSD",
|
|
trailing_stop_ratio=0.01,
|
|
) == {2: 1.212}
|
|
|
|
def test_calculate_trailing_stop_updates_invalid_symbol_digits(self) -> None:
|
|
"""Test invalid symbol metadata fails safely without updates."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[{"ticket": 1, "symbol": "EURUSD", "type": 0, "volume": 0.1, "sl": 1.0}],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"bid": 1.2, "ask": 1.201}
|
|
client.symbol_info_as_dict.return_value = {"digits": "bad"}
|
|
|
|
assert (
|
|
calculate_trailing_stop_updates(
|
|
client,
|
|
symbol="EURUSD",
|
|
trailing_stop_ratio=0.01,
|
|
)
|
|
== {}
|
|
)
|
|
|
|
def test_calculate_trailing_stop_updates_missing_symbol_digits(self) -> None:
|
|
"""Test missing symbol digits fail safely without rounded updates."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[{"ticket": 1, "symbol": "EURUSD", "type": 0, "volume": 0.1, "sl": 1.0}],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"bid": 1.2, "ask": 1.201}
|
|
client.symbol_info_as_dict.return_value = {}
|
|
|
|
assert (
|
|
calculate_trailing_stop_updates(
|
|
client,
|
|
symbol="EURUSD",
|
|
trailing_stop_ratio=0.01,
|
|
)
|
|
== {}
|
|
)
|
|
|
|
client.symbol_info_as_dict.return_value = {"digits": None}
|
|
|
|
assert (
|
|
calculate_trailing_stop_updates(
|
|
client,
|
|
symbol="EURUSD",
|
|
trailing_stop_ratio=0.01,
|
|
)
|
|
== {}
|
|
)
|
|
|
|
def test_calculate_trailing_stop_updates_skips_invalid_rows(self) -> None:
|
|
"""Test invalid tickets and unknown position types are ignored."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{
|
|
"ticket": None,
|
|
"symbol": "EURUSD",
|
|
"type": 0,
|
|
"volume": 0.1,
|
|
"sl": 1.0,
|
|
},
|
|
{
|
|
"ticket": "5",
|
|
"symbol": "EURUSD",
|
|
"type": "unknown",
|
|
"volume": 0.1,
|
|
"sl": 1.0,
|
|
},
|
|
],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"bid": 1.2, "ask": 1.201}
|
|
client.symbol_info_as_dict.return_value = {"digits": 4}
|
|
|
|
assert (
|
|
calculate_trailing_stop_updates(
|
|
client,
|
|
symbol="EURUSD",
|
|
trailing_stop_ratio=0.01,
|
|
)
|
|
== {}
|
|
)
|
|
|
|
def test_update_trailing_stop_loss_dry_run(self) -> None:
|
|
"""Test trailing-stop update wrapper supports dry-run requests."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[{"ticket": 1, "symbol": "EURUSD", "type": 0, "volume": 0.1, "sl": 1.0}],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"bid": 1.2, "ask": 1.201}
|
|
client.symbol_info_as_dict.return_value = {"digits": 4}
|
|
|
|
result = update_trailing_stop_loss_for_open_positions(
|
|
client,
|
|
symbol="EURUSD",
|
|
trailing_stop_ratio=0.01,
|
|
dry_run=True,
|
|
)
|
|
|
|
assert len(result) == 1
|
|
assert result[0]["status"] == "dry_run"
|
|
_assert_close(_request_from_result(result[0])["sl"], 1.188)
|
|
client.order_send.assert_not_called()
|
|
|
|
def test_update_trailing_stop_loss_sends_changed_sl(self) -> None:
|
|
"""Test trailing-stop wrapper sends normalized SL/TP updates."""
|
|
client = _mock_trade_client()
|
|
client.symbol_select.return_value = True
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[{"ticket": 1, "symbol": "EURUSD", "type": 0, "volume": 0.1, "sl": 1.0}],
|
|
)
|
|
client.symbol_info_tick_as_dict.return_value = {"bid": 1.2, "ask": 1.201}
|
|
client.symbol_info_as_dict.return_value = {"digits": 4, "visible": True}
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": 10009, "comment": "updated"}],
|
|
)
|
|
|
|
result = update_trailing_stop_loss_for_open_positions(
|
|
client,
|
|
symbol="EURUSD",
|
|
trailing_stop_ratio=0.01,
|
|
)
|
|
|
|
assert result[0]["status"] == "executed"
|
|
_assert_close(_request_from_result(result[0])["sl"], 1.188)
|
|
client.order_send.assert_called_once()
|
|
|
|
def test_update_sltp_filters_and_dry_runs(self) -> None:
|
|
"""Test SL/TP updates filter positions and do not send in dry-run mode."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {"visible": False}
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{
|
|
"ticket": 1,
|
|
"symbol": "EURUSD",
|
|
"type": 0,
|
|
"volume": 0.1,
|
|
"sl": 1.0,
|
|
"tp": 1.4,
|
|
},
|
|
{
|
|
"ticket": 2,
|
|
"symbol": "USDJPY",
|
|
"type": 1,
|
|
"volume": 0.2,
|
|
"sl": 100.0,
|
|
"tp": 99.0,
|
|
},
|
|
],
|
|
)
|
|
|
|
result = update_sltp_for_open_positions(
|
|
client,
|
|
symbol="EURUSD",
|
|
stop_loss=1.1,
|
|
take_profit=1.3,
|
|
dry_run=True,
|
|
)
|
|
|
|
assert len(result) == 1
|
|
_assert_close(_request_from_result(result[0])["sl"], 1.1)
|
|
_assert_close(_request_from_result(result[0])["tp"], 1.3)
|
|
client.order_send.assert_not_called()
|
|
client.symbol_select.assert_not_called()
|
|
|
|
def test_update_sltp_selects_hidden_symbol_for_live_send(self) -> None:
|
|
"""Test live SL/TP updates ensure hidden symbols are selected first."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {"visible": False}
|
|
client.symbol_select.return_value = True
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{
|
|
"ticket": 1,
|
|
"symbol": "EURUSD",
|
|
"type": 0,
|
|
"volume": 0.1,
|
|
"sl": 1.0,
|
|
"tp": 1.4,
|
|
},
|
|
],
|
|
)
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": 10009, "comment": "updated"}],
|
|
)
|
|
|
|
update_sltp_for_open_positions(client, tickets=[1], stop_loss=1.1)
|
|
|
|
client.symbol_select.assert_called_once_with("EURUSD", enable=True)
|
|
client.order_send.assert_called_once()
|
|
|
|
def test_update_sltp_sends_and_normalizes_response(self) -> None:
|
|
"""Test live SL/TP updates send requests and normalize responses."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{
|
|
"ticket": 1,
|
|
"symbol": "EURUSD",
|
|
"type": 0,
|
|
"volume": 0.1,
|
|
"sl": 1.0,
|
|
"tp": 1.4,
|
|
},
|
|
],
|
|
)
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": 10009, "comment": "updated"}],
|
|
)
|
|
|
|
result = update_sltp_for_open_positions(client, tickets=[1])
|
|
|
|
assert result[0]["status"] == "executed"
|
|
assert result[0]["retcode"] == 10009
|
|
_assert_close(_request_from_result(result[0])["sl"], 1.0)
|
|
|
|
def test_update_sltp_omits_invalid_existing_levels(self) -> None:
|
|
"""Test raw broker SL/TP sentinels are not forwarded to order_send."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{
|
|
"ticket": 1,
|
|
"symbol": "EURUSD",
|
|
"type": 0,
|
|
"volume": 0.1,
|
|
"sl": 0.0,
|
|
"tp": float("nan"),
|
|
},
|
|
],
|
|
)
|
|
|
|
result = update_sltp_for_open_positions(client, tickets=[1], dry_run=True)
|
|
|
|
request = _request_from_result(result[0])
|
|
assert "sl" not in request
|
|
assert "tp" not in request
|
|
|
|
def test_update_sltp_omits_missing_and_non_numeric_existing_levels(self) -> None:
|
|
"""Test missing and non-numeric SL/TP levels are not forwarded."""
|
|
client = _mock_trade_client()
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{
|
|
"ticket": 1,
|
|
"symbol": "EURUSD",
|
|
"type": 0,
|
|
"volume": 0.1,
|
|
"sl": None,
|
|
"tp": "unset",
|
|
},
|
|
],
|
|
)
|
|
|
|
result = update_sltp_for_open_positions(client, tickets=[1], dry_run=True)
|
|
|
|
request = _request_from_result(result[0])
|
|
assert "sl" not in request
|
|
assert "tp" not in request
|
|
|
|
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_place_market_order_selects_hidden_symbol_for_live_send(self) -> None:
|
|
"""Test live market orders select hidden symbols before reading ticks."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {"visible": False}
|
|
client.symbol_select.return_value = True
|
|
client.symbol_info_tick_as_dict.return_value = {"ask": 1.2, "bid": 1.1}
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": 10009, "comment": "done"}],
|
|
)
|
|
call_order: list[str] = []
|
|
|
|
def _record_select(*_args: object, **_kwargs: object) -> bool:
|
|
call_order.append("symbol_select")
|
|
return True
|
|
|
|
def _record_tick(*_args: object, **_kwargs: object) -> dict[str, float]:
|
|
call_order.append("tick")
|
|
return {"ask": 1.2, "bid": 1.1}
|
|
|
|
client.symbol_select.side_effect = _record_select
|
|
client.symbol_info_tick_as_dict.side_effect = _record_tick
|
|
|
|
place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
)
|
|
|
|
client.symbol_select.assert_called_once_with("EURUSD", enable=True)
|
|
client.symbol_info_tick_as_dict.assert_called_once()
|
|
client.order_send.assert_called_once()
|
|
assert call_order == ["symbol_select", "tick"]
|
|
|
|
def test_place_market_order_reads_ticks_after_hidden_symbol_selection(self) -> None:
|
|
"""Test live orders can read ticks only after hidden symbols are selected."""
|
|
client = _mock_trade_client()
|
|
selected = {"value": False}
|
|
|
|
def _symbol_info_side_effect(**_kwargs: object) -> dict[str, bool]:
|
|
return {"visible": selected["value"]}
|
|
|
|
def _select_symbol(*_args: object, **_kwargs: object) -> bool:
|
|
selected["value"] = True
|
|
return True
|
|
|
|
def _tick_side_effect(**_kwargs: object) -> dict[str, float | None]:
|
|
if not selected["value"]:
|
|
return {"ask": None, "bid": None}
|
|
return {"ask": 1.2, "bid": 1.1}
|
|
|
|
client.symbol_info_as_dict.side_effect = _symbol_info_side_effect
|
|
client.symbol_select.side_effect = _select_symbol
|
|
client.symbol_info_tick_as_dict.side_effect = _tick_side_effect
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": 10009, "comment": "done"}],
|
|
)
|
|
|
|
result = place_market_order(
|
|
client,
|
|
symbol="EURUSD",
|
|
volume=0.1,
|
|
order_side="BUY",
|
|
)
|
|
|
|
assert result["status"] == "executed"
|
|
client.symbol_select.assert_called_once_with("EURUSD", enable=True)
|
|
client.order_send.assert_called_once()
|
|
|
|
def test_update_sltp_marks_failed_retcode(self) -> None:
|
|
"""Test SL/TP updates normalize failed broker retcodes."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {"visible": True}
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{
|
|
"ticket": 1,
|
|
"symbol": "EURUSD",
|
|
"type": 0,
|
|
"volume": 0.1,
|
|
"sl": 1.0,
|
|
"tp": 1.4,
|
|
},
|
|
],
|
|
)
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": 10013, "comment": "invalid stops"}],
|
|
)
|
|
|
|
result = update_sltp_for_open_positions(client, tickets=[1], stop_loss=1.1)
|
|
|
|
assert result[0]["status"] == "failed"
|
|
assert result[0]["retcode"] == 10013
|
|
|
|
def test_update_sltp_marks_failed_numpy_retcode(self) -> None:
|
|
"""Test numpy integer retcodes normalize to failed SL/TP status."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {"visible": True}
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{
|
|
"ticket": 1,
|
|
"symbol": "EURUSD",
|
|
"type": 0,
|
|
"volume": 0.1,
|
|
"sl": 1.0,
|
|
"tp": 1.4,
|
|
},
|
|
],
|
|
)
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": np_int64(10013), "comment": "invalid stops"}],
|
|
)
|
|
|
|
result = update_sltp_for_open_positions(client, tickets=[1], stop_loss=1.1)
|
|
|
|
assert result[0]["status"] == "failed"
|
|
assert result[0]["retcode"] == 10013
|
|
|
|
def test_update_sltp_marks_failed_string_retcode(self) -> None:
|
|
"""Test digit-string failure retcodes normalize to failed SL/TP status."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {"visible": True}
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{
|
|
"ticket": 1,
|
|
"symbol": "EURUSD",
|
|
"type": 0,
|
|
"volume": 0.1,
|
|
"sl": 1.0,
|
|
"tp": 1.4,
|
|
},
|
|
],
|
|
)
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": "10013", "comment": "invalid stops"}],
|
|
)
|
|
|
|
result = update_sltp_for_open_positions(client, tickets=[1], stop_loss=1.1)
|
|
|
|
assert result[0]["retcode"] == 10013
|
|
assert result[0]["status"] == "failed"
|
|
|
|
def test_update_sltp_marks_malformed_retcode_as_failed(self) -> None:
|
|
"""Test malformed non-None SL/TP retcodes are fail-closed."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {"visible": True}
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{
|
|
"ticket": 1,
|
|
"symbol": "EURUSD",
|
|
"type": 0,
|
|
"volume": 0.1,
|
|
"sl": 1.0,
|
|
"tp": 1.4,
|
|
},
|
|
],
|
|
)
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"retcode": "invalid", "comment": "invalid stops"}],
|
|
)
|
|
|
|
result = update_sltp_for_open_positions(client, tickets=[1], stop_loss=1.1)
|
|
|
|
assert result[0]["retcode"] is None
|
|
assert result[0]["status"] == "failed"
|
|
|
|
def test_update_sltp_marks_missing_retcode_as_failed(self) -> None:
|
|
"""Test live SL/TP responses without retcode are fail-closed."""
|
|
client = _mock_trade_client()
|
|
client.symbol_info_as_dict.return_value = {"visible": True}
|
|
client.positions_get_as_df.return_value = pd.DataFrame(
|
|
[
|
|
{
|
|
"ticket": 1,
|
|
"symbol": "EURUSD",
|
|
"type": 0,
|
|
"volume": 0.1,
|
|
"sl": 1.0,
|
|
"tp": 1.4,
|
|
},
|
|
],
|
|
)
|
|
client.order_send.return_value = pd.DataFrame(
|
|
[{"comment": "missing retcode"}],
|
|
)
|
|
|
|
result = update_sltp_for_open_positions(client, tickets=[1], stop_loss=1.1)
|
|
|
|
assert result[0]["retcode"] is None
|
|
assert result[0]["status"] == "failed"
|
|
|
|
def test_trading_typed_dict_exports(self) -> None:
|
|
"""Test order-planning TypedDict contracts are importable."""
|
|
margin: MarginVolume = {
|
|
"margin_free": 1.0,
|
|
"available_margin": 1.0,
|
|
"trade_margin": 0.5,
|
|
"buy_volume": 0.1,
|
|
"sell_volume": 0.1,
|
|
"volume_min": 0.1,
|
|
"volume_max": 1.0,
|
|
"volume_step": 0.1,
|
|
}
|
|
limits: OrderLimits = {
|
|
"entry": 1.0,
|
|
"stop_loss": 0.9,
|
|
"take_profit": 1.1,
|
|
}
|
|
execution: OrderExecutionResult = {
|
|
"status": "dry_run",
|
|
"symbol": "EURUSD",
|
|
"order_side": "BUY",
|
|
"volume": 0.1,
|
|
"retcode": None,
|
|
"comment": None,
|
|
"request": {"action": 20},
|
|
"response": None,
|
|
"dry_run": True,
|
|
}
|
|
_assert_close(margin["buy_volume"], 0.1)
|
|
_assert_close(limits["entry"], 1.0)
|
|
assert execution["status"] == "dry_run"
|
|
|
|
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()
|
|
|
|
|
|
class TestFetchLatestClosedRatesForTradingClient:
|
|
"""Tests for fetch_latest_closed_rates_for_trading_client."""
|
|
|
|
def test_fetches_extra_bar_and_drops_forming_row(self) -> None:
|
|
"""Test trading-client helper hides the forming bar."""
|
|
client = MagicMock()
|
|
client.fetch_latest_rates_as_df.return_value = pd.DataFrame(
|
|
{
|
|
"time": [1, 2, 3],
|
|
"close": [1.0, 1.1, 1.2],
|
|
},
|
|
)
|
|
|
|
result = fetch_latest_closed_rates_for_trading_client(
|
|
client,
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=2,
|
|
)
|
|
|
|
client.fetch_latest_rates_as_df.assert_called_once_with("EURUSD", "M1", 3)
|
|
assert list(result["close"]) == [1.0, 1.1]
|
|
assert list(result["time"]) == [1, 2]
|
|
|
|
def test_accepts_numeric_epoch_timestamps(self) -> None:
|
|
"""Test numeric epoch timestamps are preserved in output."""
|
|
client = MagicMock()
|
|
client.fetch_latest_rates_as_df.return_value = pd.DataFrame(
|
|
{
|
|
"time": [1700000000, 1700000060, 1700000120],
|
|
"close": [1.0, 1.1, 1.2],
|
|
},
|
|
)
|
|
|
|
result = fetch_latest_closed_rates_for_trading_client(
|
|
client,
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=2,
|
|
)
|
|
|
|
assert list(result["time"]) == [1700000000, 1700000060]
|
|
|
|
def test_accepts_timezone_aware_timestamps_from_index(self) -> None:
|
|
"""Test timezone-aware timestamps in the index are exposed as a column."""
|
|
client = MagicMock()
|
|
frame = pd.DataFrame(
|
|
{
|
|
"close": [1.0, 1.1, 1.2],
|
|
},
|
|
index=pd.to_datetime(
|
|
[
|
|
"2024-01-01T00:00:00Z",
|
|
"2024-01-01T00:01:00Z",
|
|
"2024-01-01T00:02:00Z",
|
|
],
|
|
utc=True,
|
|
),
|
|
)
|
|
frame.index.name = "time"
|
|
client.fetch_latest_rates_as_df.return_value = frame
|
|
|
|
result = fetch_latest_closed_rates_for_trading_client(
|
|
client,
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=2,
|
|
)
|
|
|
|
assert "time" in result.columns
|
|
assert len(result) == 2
|
|
assert result["close"].tolist() == [1.0, 1.1]
|
|
|
|
def test_accepts_unnamed_datetime_index(self) -> None:
|
|
"""Test unnamed DatetimeIndex values are exposed as a time column."""
|
|
client = MagicMock()
|
|
frame = pd.DataFrame(
|
|
{"close": [1.0, 1.1, 1.2]},
|
|
index=pd.to_datetime(
|
|
[
|
|
"2024-01-01T00:00:00Z",
|
|
"2024-01-01T00:01:00Z",
|
|
"2024-01-01T00:02:00Z",
|
|
],
|
|
utc=True,
|
|
),
|
|
)
|
|
client.fetch_latest_rates_as_df.return_value = frame
|
|
|
|
result = fetch_latest_closed_rates_for_trading_client(
|
|
client,
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=2,
|
|
)
|
|
|
|
assert "time" in result.columns
|
|
assert len(result) == 2
|
|
|
|
def test_accepts_named_non_time_index(self) -> None:
|
|
"""Test non-time named indexes are left unchanged before validation."""
|
|
client = MagicMock()
|
|
frame = pd.DataFrame(
|
|
{
|
|
"close": [1.0, 1.1, 1.2],
|
|
"bar_id": [1, 2, 3],
|
|
},
|
|
).set_index("bar_id")
|
|
client.fetch_latest_rates_as_df.return_value = frame
|
|
|
|
with pytest.raises(ValueError, match="missing a time column"):
|
|
fetch_latest_closed_rates_for_trading_client(
|
|
client,
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=2,
|
|
)
|
|
|
|
def test_raises_when_trading_client_cannot_fetch_rates(self) -> None:
|
|
"""Test missing rate-fetch methods raise Mt5TradingError."""
|
|
client = MagicMock(spec=[])
|
|
|
|
with pytest.raises(Mt5TradingError, match="cannot fetch rate data"):
|
|
fetch_latest_closed_rates_for_trading_client(
|
|
client,
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=1,
|
|
)
|
|
|
|
def test_raises_when_time_column_is_missing(self) -> None:
|
|
"""Test malformed rate data without time raises ValueError."""
|
|
client = MagicMock()
|
|
client.fetch_latest_rates_as_df.return_value = pd.DataFrame(
|
|
{"close": [1.0, 1.1, 1.2]},
|
|
)
|
|
|
|
with pytest.raises(ValueError, match="missing a time column"):
|
|
fetch_latest_closed_rates_for_trading_client(
|
|
client,
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=2,
|
|
)
|
|
|
|
def test_raises_when_no_closed_bars_are_available(self) -> None:
|
|
"""Test empty closed-bar results raise an actionable ValueError."""
|
|
client = MagicMock()
|
|
client.fetch_latest_rates_as_df.return_value = pd.DataFrame(
|
|
{"time": [1], "close": [1.0]},
|
|
)
|
|
|
|
with pytest.raises(ValueError, match="Rate data is empty"):
|
|
fetch_latest_closed_rates_for_trading_client(
|
|
client,
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=1,
|
|
)
|
|
|
|
def test_raises_when_fetch_returns_none(self) -> None:
|
|
"""Test None fetch results raise a malformed rate data error."""
|
|
client = MagicMock()
|
|
client.fetch_latest_rates_as_df.return_value = None
|
|
|
|
with pytest.raises(ValueError, match="Malformed rate data"):
|
|
fetch_latest_closed_rates_for_trading_client(
|
|
client,
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=2,
|
|
)
|
|
|
|
def test_raises_when_fetch_returns_non_dataframe(self) -> None:
|
|
"""Test non-DataFrame fetch results raise a malformed rate data error."""
|
|
client = MagicMock()
|
|
client.fetch_latest_rates_as_df.return_value = [{"time": 1, "close": 1.0}]
|
|
|
|
with pytest.raises(ValueError, match="Malformed rate data"):
|
|
fetch_latest_closed_rates_for_trading_client(
|
|
client,
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=2,
|
|
)
|
|
|
|
def test_rejects_non_positive_count_before_fetching(self) -> None:
|
|
"""Test invalid count values fail before calling MT5."""
|
|
client = MagicMock()
|
|
|
|
with pytest.raises(ValueError, match="count must be positive"):
|
|
fetch_latest_closed_rates_for_trading_client(
|
|
client,
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=0,
|
|
)
|
|
|
|
client.fetch_latest_rates_as_df.assert_not_called()
|
|
|
|
|
|
class TestFetchLatestClosedRatesIndexed:
|
|
"""Tests for fetch_latest_closed_rates_indexed."""
|
|
|
|
def test_converts_epoch_seconds_to_utc_datetime_index(
|
|
self, mocker: MockerFixture
|
|
) -> None:
|
|
"""Test integer epoch second timestamps become a UTC DatetimeIndex."""
|
|
frame = pd.DataFrame(
|
|
{"time": [1700000000, 1700003600], "close": [1.1, 1.2]},
|
|
)
|
|
mocker.patch(
|
|
"mt5cli.trading.fetch_latest_closed_rates_for_trading_client",
|
|
return_value=frame,
|
|
)
|
|
|
|
result = fetch_latest_closed_rates_indexed(
|
|
MagicMock(),
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=2,
|
|
)
|
|
|
|
assert isinstance(result.index, pd.DatetimeIndex)
|
|
assert result.index.name == "time"
|
|
assert result.index.tz is not None
|
|
assert str(result.index.tz) == "UTC"
|
|
assert "time" not in result.columns
|
|
assert list(result["close"]) == [1.1, 1.2]
|
|
|
|
def test_converts_float_epoch_seconds_to_utc_datetime_index(
|
|
self, mocker: MockerFixture
|
|
) -> None:
|
|
"""Test float64 epoch second timestamps (after concat/NA upcast) become UTC."""
|
|
frame = pd.DataFrame(
|
|
{"time": [1700000000.0, 1700003600.0], "close": [1.1, 1.2]},
|
|
)
|
|
mocker.patch(
|
|
"mt5cli.trading.fetch_latest_closed_rates_for_trading_client",
|
|
return_value=frame,
|
|
)
|
|
|
|
result = fetch_latest_closed_rates_indexed(
|
|
MagicMock(),
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=2,
|
|
)
|
|
|
|
assert isinstance(result.index, pd.DatetimeIndex)
|
|
assert result.index.tz is not None
|
|
assert str(result.index.tz) == "UTC"
|
|
assert result.index[0].year == 2023
|
|
|
|
@pytest.mark.parametrize(
|
|
"timestamps",
|
|
[
|
|
[1700000000, 1700003600],
|
|
[1700000000.0, 1700003600.0],
|
|
[np_int64(1700000000), np_int64(1700003600)],
|
|
[np_float64(1700000000.0), np_float64(1700003600.0)],
|
|
],
|
|
ids=["integers", "floats", "numpy-integers", "numpy-floats"],
|
|
)
|
|
def test_converts_object_numeric_epoch_seconds_to_utc_datetime_index(
|
|
self,
|
|
mocker: MockerFixture,
|
|
timestamps: list[int] | list[float] | list[np_int64] | list[np_float64],
|
|
) -> None:
|
|
"""Test object-dtype real numbers are interpreted as epoch seconds."""
|
|
frame = pd.DataFrame(
|
|
{
|
|
"time": pd.Series(timestamps, dtype=object),
|
|
"close": [1.1, 1.2],
|
|
},
|
|
)
|
|
mocker.patch(
|
|
"mt5cli.trading.fetch_latest_closed_rates_for_trading_client",
|
|
return_value=frame,
|
|
)
|
|
|
|
result = fetch_latest_closed_rates_indexed(
|
|
MagicMock(), symbol="EURUSD", granularity="M1", count=2
|
|
)
|
|
|
|
assert list(result.index) == list(
|
|
pd.to_datetime([1700000000, 1700003600], unit="s", utc=True)
|
|
)
|
|
|
|
def test_parses_mixed_datetime_like_strings(self, mocker: MockerFixture) -> None:
|
|
"""Test object-dtype datetime strings retain datetime-like parsing."""
|
|
timestamps = ["2024-01-01T00:00:00Z", "2024-01-01T01:00:00+01:00"]
|
|
frame = pd.DataFrame({"time": timestamps, "close": [1.1, 1.2]})
|
|
mocker.patch(
|
|
"mt5cli.trading.fetch_latest_closed_rates_for_trading_client",
|
|
return_value=frame,
|
|
)
|
|
|
|
result = fetch_latest_closed_rates_indexed(
|
|
MagicMock(), symbol="EURUSD", granularity="M1", count=2
|
|
)
|
|
|
|
assert list(result.index) == list(pd.to_datetime(timestamps, utc=True))
|
|
|
|
def test_does_not_treat_bool_as_epoch_seconds(self, mocker: MockerFixture) -> None:
|
|
"""Test bool timestamps do not enter the numeric epoch-seconds path."""
|
|
frame = pd.DataFrame(
|
|
{"time": pd.Series([True, False], dtype=object), "close": [1.1, 1.2]},
|
|
)
|
|
mocker.patch(
|
|
"mt5cli.trading.fetch_latest_closed_rates_for_trading_client",
|
|
return_value=frame,
|
|
)
|
|
|
|
with pytest.raises(ValueError, match="invalid or unparseable time data"):
|
|
fetch_latest_closed_rates_indexed(
|
|
MagicMock(), symbol="EURUSD", granularity="M1", count=2
|
|
)
|
|
|
|
def test_converts_naive_datetime_to_utc_datetime_index(
|
|
self, mocker: MockerFixture
|
|
) -> None:
|
|
"""Test timezone-naive datetime values are localized to UTC."""
|
|
from datetime import datetime # noqa: PLC0415
|
|
|
|
frame = pd.DataFrame(
|
|
{
|
|
"time": [datetime(2024, 1, 1, 0, 0), datetime(2024, 1, 1, 1, 0)], # noqa: DTZ001
|
|
"close": [1.1, 1.2],
|
|
},
|
|
)
|
|
mocker.patch(
|
|
"mt5cli.trading.fetch_latest_closed_rates_for_trading_client",
|
|
return_value=frame,
|
|
)
|
|
|
|
result = fetch_latest_closed_rates_indexed(
|
|
MagicMock(),
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=2,
|
|
)
|
|
|
|
assert isinstance(result.index, pd.DatetimeIndex)
|
|
assert result.index.tz is not None
|
|
assert str(result.index.tz) == "UTC"
|
|
assert result.index[0].year == 2024
|
|
|
|
def test_converts_aware_datetime_to_utc(self, mocker: MockerFixture) -> None:
|
|
"""Test timezone-aware datetime values are converted to UTC."""
|
|
from datetime import datetime, timedelta, timezone # noqa: PLC0415
|
|
|
|
tz_plus5 = timezone(timedelta(hours=5))
|
|
frame = pd.DataFrame(
|
|
{
|
|
"time": [datetime(2024, 1, 1, 5, 0, tzinfo=tz_plus5)],
|
|
"close": [1.1],
|
|
},
|
|
)
|
|
mocker.patch(
|
|
"mt5cli.trading.fetch_latest_closed_rates_for_trading_client",
|
|
return_value=frame,
|
|
)
|
|
|
|
result = fetch_latest_closed_rates_indexed(
|
|
MagicMock(),
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=1,
|
|
)
|
|
|
|
assert isinstance(result.index, pd.DatetimeIndex)
|
|
assert str(result.index.tz) == "UTC"
|
|
assert result.index[0].hour == 0
|
|
|
|
def test_raises_on_missing_time_column(self, mocker: MockerFixture) -> None:
|
|
"""Test missing time column after the underlying fetch raises ValueError."""
|
|
mocker.patch(
|
|
"mt5cli.trading.fetch_latest_closed_rates_for_trading_client",
|
|
return_value=pd.DataFrame({"close": [1.1]}),
|
|
)
|
|
|
|
with pytest.raises(ValueError, match="missing a time column"):
|
|
fetch_latest_closed_rates_indexed(
|
|
MagicMock(),
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=1,
|
|
)
|
|
|
|
def test_raises_on_unparseable_time_column(self, mocker: MockerFixture) -> None:
|
|
"""Test unparseable time data raises a clear ValueError."""
|
|
mocker.patch(
|
|
"mt5cli.trading.fetch_latest_closed_rates_for_trading_client",
|
|
return_value=pd.DataFrame({"time": ["not-a-date"], "close": [1.1]}),
|
|
)
|
|
|
|
with pytest.raises(ValueError, match="invalid or unparseable time data"):
|
|
fetch_latest_closed_rates_indexed(
|
|
MagicMock(),
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=1,
|
|
)
|
|
|
|
def test_raises_on_nat_time_column(self, mocker: MockerFixture) -> None:
|
|
"""Test NaT in the time column raises ValueError instead of silently passing."""
|
|
mocker.patch(
|
|
"mt5cli.trading.fetch_latest_closed_rates_for_trading_client",
|
|
return_value=pd.DataFrame(
|
|
{"time": [1700000000, None], "close": [1.1, 1.2]},
|
|
),
|
|
)
|
|
|
|
with pytest.raises(ValueError, match=r"missing.*NaT.*timestamp"):
|
|
fetch_latest_closed_rates_indexed(
|
|
MagicMock(),
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=2,
|
|
)
|
|
|
|
def test_drops_time_column_and_sets_index(self, mocker: MockerFixture) -> None:
|
|
"""Test the returned DataFrame has the DatetimeIndex and no time column."""
|
|
frame = pd.DataFrame(
|
|
{
|
|
"time": [1700000000, 1700003600],
|
|
"open": [1.0, 1.1],
|
|
"close": [1.1, 1.2],
|
|
},
|
|
)
|
|
mocker.patch(
|
|
"mt5cli.trading.fetch_latest_closed_rates_for_trading_client",
|
|
return_value=frame,
|
|
)
|
|
|
|
result = fetch_latest_closed_rates_indexed(
|
|
MagicMock(),
|
|
symbol="EURUSD",
|
|
granularity="M1",
|
|
count=2,
|
|
)
|
|
|
|
assert "time" not in result.columns
|
|
assert "open" in result.columns
|
|
assert "close" in result.columns
|
|
assert isinstance(result.index, pd.DatetimeIndex)
|
|
|
|
|
|
class TestExtractTickPrice:
|
|
"""Tests for the public extract_tick_price helper."""
|
|
|
|
def test_valid_positive_float(self) -> None:
|
|
"""Returns a positive float value unchanged."""
|
|
_assert_close(extract_tick_price({"bid": 1.1000}, "bid"), 1.1000)
|
|
|
|
def test_valid_positive_int(self) -> None:
|
|
"""Accepts an integer value and returns it as float."""
|
|
result = extract_tick_price({"bid": 2}, "bid")
|
|
_assert_close(result, 2.0)
|
|
assert isinstance(result, float)
|
|
|
|
def test_valid_numeric_string(self) -> None:
|
|
"""Accepts a numeric string and returns the parsed float."""
|
|
_assert_close(extract_tick_price({"bid": "1.5"}, "bid"), 1.5)
|
|
|
|
def test_missing_key(self) -> None:
|
|
"""Returns None when the key is absent from the tick dict."""
|
|
assert extract_tick_price({}, "bid") is None
|
|
|
|
def test_none_value(self) -> None:
|
|
"""Returns None when the stored value is None."""
|
|
assert extract_tick_price({"bid": None}, "bid") is None
|
|
|
|
def test_bool_value(self) -> None:
|
|
"""Returns None for bool values even though bool is int-like."""
|
|
assert extract_tick_price({"bid": True}, "bid") is None
|
|
|
|
def test_invalid_string(self) -> None:
|
|
"""Returns None for a non-numeric string."""
|
|
assert extract_tick_price({"bid": "not_a_number"}, "bid") is None
|
|
|
|
def test_nan(self) -> None:
|
|
"""Returns None for a NaN float."""
|
|
assert extract_tick_price({"bid": float("nan")}, "bid") is None
|
|
|
|
def test_positive_infinity(self) -> None:
|
|
"""Returns None for positive infinity."""
|
|
assert extract_tick_price({"bid": float("inf")}, "bid") is None
|
|
|
|
def test_negative_infinity(self) -> None:
|
|
"""Returns None for negative infinity."""
|
|
assert extract_tick_price({"bid": float("-inf")}, "bid") is None
|
|
|
|
def test_zero(self) -> None:
|
|
"""Returns None for zero (not a valid price)."""
|
|
assert extract_tick_price({"bid": 0.0}, "bid") is None
|
|
|
|
def test_negative_value(self) -> None:
|
|
"""Returns None for a negative price."""
|
|
assert extract_tick_price({"bid": -1.0}, "bid") is None
|
|
|
|
def test_unsupported_type(self) -> None:
|
|
"""Returns None for unsupported value types such as list."""
|
|
assert extract_tick_price({"bid": [1.0]}, "bid") is None
|
|
|
|
|
|
class TestCalculatePositionsMarginBySymbol:
|
|
"""Tests for calculate_positions_margin_by_symbol (#50)."""
|
|
|
|
def test_all_symbols_succeed(self, mocker: MockerFixture) -> None:
|
|
"""Returns one entry per symbol in first-seen order when all calls succeed."""
|
|
client = _mock_trade_client()
|
|
mocker.patch(
|
|
"mt5cli.trading.calculate_positions_margin",
|
|
side_effect=[12.5, 30.0],
|
|
)
|
|
|
|
result = calculate_positions_margin_by_symbol(
|
|
client, symbols=["EURUSD", "GBPUSD"]
|
|
)
|
|
|
|
assert list(result.keys()) == ["EURUSD", "GBPUSD"]
|
|
_assert_close(result["EURUSD"], 12.5)
|
|
_assert_close(result["GBPUSD"], 30.0)
|
|
|
|
def test_one_symbol_fails_suppress_errors_true(
|
|
self, mocker: MockerFixture, caplog: pytest.LogCaptureFixture
|
|
) -> None:
|
|
"""Skips the failing symbol, emits a warning, and returns the successful one."""
|
|
client = _mock_trade_client()
|
|
mocker.patch(
|
|
"mt5cli.trading.calculate_positions_margin",
|
|
side_effect=[Mt5TradingError("tick unavailable"), 30.0],
|
|
)
|
|
|
|
with caplog.at_level(logging.WARNING, logger="mt5cli.trading"):
|
|
result = calculate_positions_margin_by_symbol(
|
|
client, symbols=["EURUSD", "GBPUSD"], suppress_errors=True
|
|
)
|
|
|
|
assert result == {"GBPUSD": 30.0}
|
|
assert any(
|
|
"EURUSD" in record.getMessage() and record.levelno == logging.WARNING
|
|
for record in caplog.records
|
|
)
|
|
|
|
@pytest.mark.parametrize(
|
|
"exc",
|
|
[
|
|
Mt5TradingError("trading error"),
|
|
Mt5RuntimeError("runtime error"),
|
|
AttributeError("missing attr"),
|
|
],
|
|
)
|
|
def test_one_symbol_fails_suppress_errors_false(
|
|
self, mocker: MockerFixture, exc: Exception
|
|
) -> None:
|
|
"""Re-raises the first failure for each caught exception type."""
|
|
client = _mock_trade_client()
|
|
mocker.patch(
|
|
"mt5cli.trading.calculate_positions_margin",
|
|
side_effect=[exc, 30.0],
|
|
)
|
|
|
|
with pytest.raises(type(exc)):
|
|
calculate_positions_margin_by_symbol(
|
|
client, symbols=["EURUSD", "GBPUSD"], suppress_errors=False
|
|
)
|
|
|
|
def test_all_symbols_fail_suppress_errors_true(self, mocker: MockerFixture) -> None:
|
|
"""Returns an empty dict when all symbols fail with suppress_errors=True."""
|
|
client = _mock_trade_client()
|
|
mocker.patch(
|
|
"mt5cli.trading.calculate_positions_margin",
|
|
side_effect=[Mt5TradingError("err1"), Mt5TradingError("err2")],
|
|
)
|
|
|
|
result = calculate_positions_margin_by_symbol(
|
|
client, symbols=["EURUSD", "GBPUSD"], suppress_errors=True
|
|
)
|
|
|
|
assert result == {}
|
|
|
|
def test_empty_symbol_list(self, mocker: MockerFixture) -> None:
|
|
"""Returns an empty dict for an empty input list without any broker calls."""
|
|
client = _mock_trade_client()
|
|
mock_calc = mocker.patch("mt5cli.trading.calculate_positions_margin")
|
|
result = calculate_positions_margin_by_symbol(client, symbols=[])
|
|
assert result == {}
|
|
mock_calc.assert_not_called()
|
|
|
|
def test_duplicate_symbols_preserve_first_seen_order(
|
|
self, mocker: MockerFixture
|
|
) -> None:
|
|
"""Processes each unique symbol once in first-seen order."""
|
|
client = _mock_trade_client()
|
|
mock_calc = mocker.patch(
|
|
"mt5cli.trading.calculate_positions_margin",
|
|
return_value=12.5,
|
|
)
|
|
|
|
result = calculate_positions_margin_by_symbol(
|
|
client, symbols=["EURUSD", "GBPUSD", "EURUSD"]
|
|
)
|
|
|
|
assert list(result.keys()) == ["EURUSD", "GBPUSD"]
|
|
assert mock_calc.call_count == 2
|
|
|
|
|
|
class TestCalculatePositionsMarginSafe:
|
|
"""Tests for calculate_positions_margin_safe (#50)."""
|
|
|
|
def test_returns_summed_total(self, mocker: MockerFixture) -> None:
|
|
"""Returns the sum of all per-symbol margins."""
|
|
client = _mock_trade_client()
|
|
mocker.patch(
|
|
"mt5cli.trading.calculate_positions_margin",
|
|
side_effect=[12.5, 30.0],
|
|
)
|
|
|
|
total = calculate_positions_margin_safe(client, symbols=["EURUSD", "GBPUSD"])
|
|
|
|
_assert_close(total, 42.5)
|
|
|
|
def test_partial_failure_skips_and_sums(self, mocker: MockerFixture) -> None:
|
|
"""Sums only successful margins when one symbol raises."""
|
|
client = _mock_trade_client()
|
|
mocker.patch(
|
|
"mt5cli.trading.calculate_positions_margin",
|
|
side_effect=[Mt5TradingError("tick unavailable"), 30.0],
|
|
)
|
|
|
|
total = calculate_positions_margin_safe(client, symbols=["EURUSD", "GBPUSD"])
|
|
|
|
_assert_close(total, 30.0)
|
|
|
|
def test_all_symbols_fail_returns_zero(self, mocker: MockerFixture) -> None:
|
|
"""Returns 0.0 when every symbol raises."""
|
|
client = _mock_trade_client()
|
|
mocker.patch(
|
|
"mt5cli.trading.calculate_positions_margin",
|
|
side_effect=[Mt5TradingError("err1"), Mt5RuntimeError("err2")],
|
|
)
|
|
|
|
total = calculate_positions_margin_safe(client, symbols=["EURUSD", "GBPUSD"])
|
|
|
|
_assert_close(total, 0.0)
|
|
|
|
def test_empty_symbols_returns_zero(self) -> None:
|
|
"""Returns 0.0 for an empty symbol list."""
|
|
client = _mock_trade_client()
|
|
total = calculate_positions_margin_safe(client, symbols=[])
|
|
_assert_close(total, 0.0)
|