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https://github.com/OpenBB-finance/OpenBB.git
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f6867c2b18
* refactor charting for v5 patterns and decouple entirely * coveragerc * lint and tests * fix tests * configure dev group with openbb-technical * ty * fix cli test * remove 3.15 from test matrix - dependencies are unstable --------- Co-authored-by: deeleeramone <>
137 lines
4.3 KiB
Python
137 lines
4.3 KiB
Python
"""Shared deterministic real-data fixtures for the charting test suite."""
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from __future__ import annotations
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import sys
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import types
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import numpy as np
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import pandas as pd
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import pytest
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from openbb_core.provider.abstract.data import Data
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SYMBOLS = ("AAA", "BBB", "CCC", "DDD")
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def _install_fake_pywry() -> None:
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"""Install a minimal fake ``pywry`` so the GUI backend runs headlessly.
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``pywry`` is an optional GUI dependency with no wheels for every supported
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Python (e.g. 3.14), so CI cannot install it. It is the one true external
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boundary — the window/websocket layer — so a faithful in-memory stand-in is
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the correct test double. Installing it unconditionally keeps backend tests
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deterministic across every environment.
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"""
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pywry = types.ModuleType("pywry")
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pywry._OPENBB_FAKE = True # type: ignore[attr-defined]
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class _Component:
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def __init__(self, **kwargs):
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self.__dict__.update(kwargs)
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class Toolbar(_Component):
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def __init__(self, **kwargs):
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super().__init__(**kwargs)
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self.items = kwargs.get("items", [])
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class _App:
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def __init__(self, **kwargs):
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self.__dict__.update(kwargs)
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self.theme = kwargs.get("theme")
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def show_plotly(self, **kwargs):
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return None
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def show_dataframe(self, **kwargs):
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return None
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def show(self, **kwargs):
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return None
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def emit(self, *args, **kwargs):
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return None
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def close(self, *args, **kwargs):
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return None
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class ThemeMode:
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DARK = "dark"
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LIGHT = "light"
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pywry.PyWry = _App # type: ignore[attr-defined]
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pywry.ThemeMode = ThemeMode # type: ignore[attr-defined]
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pywry.Toolbar = Toolbar # type: ignore[attr-defined]
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pywry.Button = _Component # type: ignore[attr-defined]
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pywry.Div = _Component # type: ignore[attr-defined]
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pywry.TextArea = _Component # type: ignore[attr-defined]
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pywry.PlotlyConfig = _Component # type: ignore[attr-defined]
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grid = types.ModuleType("pywry.grid")
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class _GridData:
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def __init__(self, frame):
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self.columns = list(frame.columns)
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self.index_columns = []
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self.column_types = {col: "text" for col in frame.columns}
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self.row_data = frame.to_dict(orient="records")
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grid.normalize_data = _GridData # type: ignore[attr-defined]
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grid.build_column_defs = lambda columns, index_columns, column_types: [ # type: ignore[attr-defined]
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{"field": col} for col in columns
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]
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pywry.grid = grid # type: ignore[attr-defined]
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sys.modules["pywry"] = pywry
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sys.modules["pywry.grid"] = grid
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_install_fake_pywry()
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def _make_ohlcv(
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seed: int, periods: int = 200, start: str = "2023-01-01"
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) -> pd.DataFrame:
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"""Build a deterministic, valid OHLCV frame with a ``date`` index."""
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rng = np.random.default_rng(seed)
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idx = pd.date_range(start, periods=periods, freq="D")
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close = 100 + np.cumsum(rng.normal(0, 1, periods))
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open_ = close + rng.normal(0, 0.5, periods)
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high = np.maximum(open_, close) + np.abs(rng.normal(0, 0.5, periods))
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low = np.minimum(open_, close) - np.abs(rng.normal(0, 0.5, periods))
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volume = rng.integers(1_000_000, 5_000_000, periods)
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frame = pd.DataFrame(
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{"open": open_, "high": high, "low": low, "close": close, "volume": volume},
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index=idx,
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)
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frame.index.name = "date"
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return frame
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@pytest.fixture
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def ohlcv_df() -> pd.DataFrame:
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"""A single-symbol OHLCV DataFrame indexed by date (200 rows)."""
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return _make_ohlcv(seed=42)
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@pytest.fixture
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def ohlcv_records(ohlcv_df) -> list[dict]:
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"""The OHLCV frame as a list of ``date``-stamped record dicts."""
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out = ohlcv_df.reset_index()
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out["date"] = out["date"].dt.strftime("%Y-%m-%d")
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return out.to_dict(orient="records")
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@pytest.fixture
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def ohlcv_data(ohlcv_records) -> list[Data]:
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"""The OHLCV records as real ``Data`` models."""
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return [Data.model_validate(row) for row in ohlcv_records]
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@pytest.fixture
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def multi_close_df() -> pd.DataFrame:
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"""A multi-symbol close-price frame (wide), indexed by date."""
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frames = {sym: _make_ohlcv(seed=i)["close"] for i, sym in enumerate(SYMBOLS)}
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wide = pd.DataFrame(frames)
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wide.index.name = "date"
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return wide
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