Pratik Bhadane
272 lines
7.6 KiB
Python
272 lines
7.6 KiB
Python
"""
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ferro_ta.adapters — Market data adapters (pluggable).
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Defines an abstract ``DataAdapter`` interface and a concrete
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``CsvAdapter`` that loads OHLCV data from a CSV file. Users can
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subclass ``DataAdapter`` to add their own data sources (e.g. Alpaca,
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Yahoo Finance, a database, etc.) while keeping the rest of the pipeline
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unchanged.
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Classes
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-------
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DataAdapter
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Abstract base class. Subclasses must implement :meth:`fetch`.
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CsvAdapter
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Load OHLCV data from a CSV file. Requires pandas.
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InMemoryAdapter
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Wrap an already-loaded pandas DataFrame or dict of arrays.
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Functions
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---------
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register_adapter(name, adapter_class)
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Register an adapter class under a name for lookup by string.
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get_adapter(name)
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Return an adapter class previously registered under *name*.
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Examples
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--------
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>>> from ferro_ta.data.adapters import InMemoryAdapter
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>>> import numpy as np
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>>> n = 50
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>>> rng = np.random.default_rng(0)
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>>> close = np.cumprod(1 + rng.normal(0, 0.01, n)) * 100
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>>> adapter = InMemoryAdapter({
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... "open": close, "high": close * 1.001,
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... "low": close * 0.999, "close": close,
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... "volume": np.ones(n) * 1000,
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... })
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>>> ohlcv = adapter.fetch()
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>>> "close" in ohlcv
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True
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"""
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from __future__ import annotations
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import abc
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from typing import Any, Optional
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__all__ = [
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"DataAdapter",
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"CsvAdapter",
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"InMemoryAdapter",
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"register_adapter",
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"get_adapter",
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]
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# ---------------------------------------------------------------------------
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# Registry
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# ---------------------------------------------------------------------------
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_ADAPTER_REGISTRY: dict[str, type[DataAdapter]] = {}
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def register_adapter(name: str, adapter_class: type[DataAdapter]) -> None:
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"""Register *adapter_class* under *name*.
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Parameters
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----------
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name : str
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adapter_class : type — must subclass :class:`DataAdapter`
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Examples
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--------
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>>> from ferro_ta.data.adapters import register_adapter, DataAdapter
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>>> class MyAdapter(DataAdapter):
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... def fetch(self, **kwargs): return {}
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>>> register_adapter("my_source", MyAdapter)
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"""
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if not issubclass(adapter_class, DataAdapter):
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raise TypeError(f"{adapter_class!r} must subclass DataAdapter")
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_ADAPTER_REGISTRY[name] = adapter_class
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def get_adapter(name: str) -> type[DataAdapter]:
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"""Return the adapter class registered under *name*.
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Parameters
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----------
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name : str
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Raises
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------
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KeyError
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If *name* is not registered.
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"""
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if name not in _ADAPTER_REGISTRY:
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available = sorted(_ADAPTER_REGISTRY.keys())
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raise KeyError(f"No adapter registered under {name!r}. Available: {available}")
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return _ADAPTER_REGISTRY[name]
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# ---------------------------------------------------------------------------
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# Abstract base
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# ---------------------------------------------------------------------------
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class DataAdapter(abc.ABC):
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"""Abstract base class for market data adapters.
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Subclasses must implement :meth:`fetch`, which returns OHLCV data as
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a ``pandas.DataFrame`` (preferred) or a ``dict`` of numpy arrays.
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The contract for the returned data:
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- Keys/columns: ``open``, ``high``, ``low``, ``close``, ``volume``
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(additional columns are allowed but not required).
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- Values: numeric (float64-compatible).
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- Index (for DataFrames): ideally a ``DatetimeIndex``; not required.
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"""
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@abc.abstractmethod
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def fetch(self, **kwargs: Any) -> Any:
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"""Return OHLCV data.
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Returns
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-------
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pandas.DataFrame or dict
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OHLCV data with keys/columns ``open``, ``high``, ``low``,
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``close``, ``volume``.
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"""
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def __repr__(self) -> str:
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return f"{type(self).__name__}()"
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# ---------------------------------------------------------------------------
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# CsvAdapter
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# ---------------------------------------------------------------------------
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class CsvAdapter(DataAdapter):
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"""Load OHLCV data from a CSV file.
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The CSV must have a header row. Column names are configurable.
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Parameters
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----------
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path : str
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Path to the CSV file.
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open_col, high_col, low_col, close_col, volume_col : str
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CSV column names for each OHLCV field.
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index_col : str or None
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Column to use as the DataFrame index (e.g. ``'timestamp'``).
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parse_dates : bool
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If ``True`` (default), attempt to parse the index as dates.
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Requires
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--------
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pandas
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Examples
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--------
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>>> from ferro_ta.data.adapters import CsvAdapter
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>>> # adapter = CsvAdapter("data.csv", index_col="date")
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>>> # ohlcv = adapter.fetch()
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"""
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def __init__(
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self,
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path: str,
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*,
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open_col: str = "open",
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high_col: str = "high",
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low_col: str = "low",
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close_col: str = "close",
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volume_col: str = "volume",
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index_col: Optional[str] = None,
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parse_dates: bool = True,
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) -> None:
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self.path = path
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self.open_col = open_col
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self.high_col = high_col
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self.low_col = low_col
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self.close_col = close_col
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self.volume_col = volume_col
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self.index_col = index_col
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self.parse_dates = parse_dates
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def fetch(self, **kwargs: Any) -> Any:
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"""Load the CSV and return a pandas DataFrame.
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Raises
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------
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ImportError
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If pandas is not installed.
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"""
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try:
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import pandas as pd
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except ImportError as exc:
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raise ImportError(
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"pandas is required for CsvAdapter. Install with: pip install pandas"
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) from exc
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df = pd.read_csv(
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self.path,
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index_col=self.index_col,
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parse_dates=self.parse_dates if self.index_col is not None else False,
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)
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# Rename columns if they differ from the standard names
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rename = {}
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for src, dst in [
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(self.open_col, "open"),
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(self.high_col, "high"),
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(self.low_col, "low"),
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(self.close_col, "close"),
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(self.volume_col, "volume"),
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]:
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if src != dst and src in df.columns:
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rename[src] = dst
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if rename:
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df = df.rename(columns=rename)
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return df
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def __repr__(self) -> str:
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return f"CsvAdapter(path={self.path!r})"
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# ---------------------------------------------------------------------------
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# InMemoryAdapter
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# ---------------------------------------------------------------------------
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class InMemoryAdapter(DataAdapter):
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"""Wrap already-loaded OHLCV data (dict or DataFrame).
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Parameters
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----------
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data : dict or pandas.DataFrame
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OHLCV data.
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Examples
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--------
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>>> import numpy as np
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>>> from ferro_ta.data.adapters import InMemoryAdapter
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>>> n = 10
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>>> close = np.ones(n) * 100.0
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>>> adapter = InMemoryAdapter({"open": close, "high": close,
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... "low": close, "close": close,
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... "volume": close})
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>>> ohlcv = adapter.fetch()
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>>> "close" in ohlcv
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True
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"""
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def __init__(self, data: Any) -> None:
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self._data = data
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def fetch(self, **kwargs: Any) -> Any:
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"""Return the wrapped data as-is."""
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return self._data
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def __repr__(self) -> str:
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return "InMemoryAdapter(...)"
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# ---------------------------------------------------------------------------
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# Register built-in adapters
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# ---------------------------------------------------------------------------
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register_adapter("csv", CsvAdapter)
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register_adapter("memory", InMemoryAdapter)
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