VER: Release 0.26.0

See release notes.

CHANGELOG.md

@@ -1,5 +1,13 @@
 # Changelog
 
+## 0.26.0 - 2024-01-16
+
+This release adds support for transcoding DBN data into Apache parquet.
+
+#### Enhancements
+- Added `DBNStore.to_parquet` for transcoding DBN data into Apache parquet using `pyarrow`
+- Upgraded `databento-dbn` to 0.15.0
+
 ## 0.25.0 - 2024-01-09
 
 #### Breaking changes

README.md

@@ -32,9 +32,10 @@ The library is fully compatible with the latest distribution of Anaconda 3.8 and
 The minimum dependencies as found in the `pyproject.toml` are also listed below:
 - python = "^3.8"
 - aiohttp = "^3.8.3"
-- databento-dbn = "0.14.2"
+- databento-dbn = "0.15.0"
 - numpy= ">=1.23.5"
 - pandas = ">=1.5.3"
+- pyarrow = ">=13.0.0"
 - requests = ">=2.24.0"
 - zstandard = ">=0.21.0"
 

databento/common/dbnstore.py

@@ -15,6 +15,7 @@
     Any,
     BinaryIO,
     Callable,
+    Final,
     Literal,
     Protocol,
     overload,
@@ -23,6 +24,8 @@
 import databento_dbn
 import numpy as np
 import pandas as pd
+import pyarrow as pa
+import pyarrow.parquet as pq
 import zstandard
 from databento_dbn import FIXED_PRICE_SCALE
 from databento_dbn import Compression
@@ -51,6 +54,8 @@
 
 logger = logging.getLogger(__name__)
 
+PARQUET_CHUNK_SIZE: Final = 2**16
+
 if TYPE_CHECKING:
     from databento.historical.client import Historical
 
@@ -791,18 +796,14 @@ def to_csv(
         compression : Compression or str, default `Compression.NONE`
             The output compression for writing.
         schema : Schema or str, optional
-            The schema for the csv.
+            The DBN schema for the csv.
             This is only required when reading a DBN stream with mixed record types.
 
         Raises
         ------
         ValueError
             If the schema for the array cannot be determined.
 
-        Notes
-        -----
-        Requires all the data to be brought up into memory to then be written.
-
         """
         compression = validate_enum(compression, Compression, "compression")
         schema = validate_maybe_enum(schema, Schema, "schema")
@@ -870,7 +871,7 @@ def to_df(
             a 'symbol' column, mapping the instrument ID to its requested symbol for
             every record.
         schema : Schema or str, optional
-            The schema for the dataframe.
+            The DBN schema for the dataframe.
             This is only required when reading a DBN stream with mixed record types.
         count : int, optional
             If set, instead of returning a single `DataFrame` a `DataFrameIterator`
@@ -887,7 +888,7 @@ def to_df(
         Raises
         ------
         ValueError
-            If the schema for the array cannot be determined.
+            If the DBN schema is unspecified and cannot be determined.
 
         """
         schema = validate_maybe_enum(schema, Schema, "schema")
@@ -919,6 +920,81 @@ def to_df(
 
         return df_iter
 
+    def to_parquet(
+        self,
+        path: Path | str,
+        price_type: Literal["fixed", "float"] = "float",
+        pretty_ts: bool = True,
+        map_symbols: bool = True,
+        schema: Schema | str | None = None,
+        **kwargs: Any,
+    ) -> None:
+        """
+        Write the data to a parquet file at the given path.
+
+        Parameters
+        ----------
+        price_type : str, default "float"
+            The price type to use for price fields.
+            If "fixed", prices will have a type of `int` in fixed decimal format; each unit representing 1e-9 or 0.000000001.
+            If "float", prices will have a type of `float`.
+            The "decimal" price type is not supported at this time.
+        pretty_ts : bool, default True
+            If all timestamp columns should be converted from UNIX nanosecond
+            `int` to tz-aware UTC `pyarrow.TimestampType`.
+        map_symbols : bool, default True
+            If symbology mappings from the metadata should be used to create
+            a 'symbol' column, mapping the instrument ID to its requested symbol for
+            every record.
+        schema : Schema or str, optional
+            The DBN schema for the parquet file.
+            This is only required when reading a DBN stream with mixed record types.
+
+        Raises
+        ------
+        ValueError
+            If an incorrect price type is specified.
+            If the DBN schema is unspecified and cannot be determined.
+
+        """
+        if price_type == "decimal":
+            raise ValueError("the 'decimal' price type is not currently supported")
+
+        schema = validate_maybe_enum(schema, Schema, "schema")
+        if schema is None:
+            if self.schema is None:
+                raise ValueError("a schema must be specified for mixed DBN data")
+            schema = self.schema
+
+        dataframe_iter = self.to_df(
+            price_type=price_type,
+            pretty_ts=pretty_ts,
+            map_symbols=map_symbols,
+            schema=schema,
+            count=PARQUET_CHUNK_SIZE,
+        )
+
+        writer = None
+        try:
+            for frame in dataframe_iter:
+                if writer is None:
+                    # Initialize the writer using the first DataFrame
+                    parquet_schema = pa.Schema.from_pandas(frame)
+                    writer = pq.ParquetWriter(
+                        where=path,
+                        schema=parquet_schema,
+                        **kwargs,
+                    )
+                writer.write_table(
+                    pa.Table.from_pandas(
+                        frame,
+                        schema=parquet_schema,
+                    ),
+                )
+        finally:
+            if writer is not None:
+                writer.close()
+
     def to_file(self, path: Path | str) -> None:
         """
         Write the data to a DBN file at the given path.
@@ -972,18 +1048,14 @@ def to_json(
         compression : Compression or str, default `Compression.NONE`
             The output compression for writing.
         schema : Schema or str, optional
-            The schema for the json.
+            The DBN schema for the json.
             This is only required when reading a DBN stream with mixed record types.
 
         Raises
         ------
         ValueError
             If the schema for the array cannot be determined.
 
-        Notes
-        -----
-        Requires all the data to be brought up into memory to then be written.
-
         """
         compression = validate_enum(compression, Compression, "compression")
         schema = validate_maybe_enum(schema, Schema, "schema")
@@ -1030,7 +1102,7 @@ def to_ndarray(
         Parameters
         ----------
         schema : Schema or str, optional
-            The schema for the array.
+            The DBN schema for the array.
             This is only required when reading a DBN stream with mixed record types.
         count : int, optional
             If set, instead of returning a single `np.ndarray` a `NDArrayIterator`
@@ -1047,7 +1119,7 @@ def to_ndarray(
         Raises
         ------
         ValueError
-            If the schema for the array cannot be determined.
+            If the DBN schema is unspecified and cannot be determined.
 
         """
         schema = validate_maybe_enum(schema, Schema, "schema")
@@ -1120,7 +1192,7 @@ def _transcode(
             pretty_ts=pretty_ts,
             has_metadata=True,
             map_symbols=map_symbols,
-            symbol_interval_map=symbol_map,  # type: ignore [arg-type]
+            symbol_interval_map=symbol_map,
             schema=schema,
         )
 
@@ -1329,8 +1401,7 @@ def _format_px(
         if price_type == "decimal":
             for field in px_fields:
                 df[field] = (
-                    df[field].replace(INT64_NULL, np.nan).apply(decimal.Decimal)
-                    / FIXED_PRICE_SCALE
+                    df[field].replace(INT64_NULL, np.nan).apply(decimal.Decimal) / FIXED_PRICE_SCALE
                 )
         elif price_type == "float":
             for field in px_fields:

databento/common/parsing.py

@@ -4,7 +4,8 @@
 from datetime import date
 from functools import partial
 from functools import singledispatch
-from numbers import Number
+from numbers import Integral
+from typing import Any
 
 import pandas as pd
 from databento_dbn import SType
@@ -59,7 +60,7 @@ def optional_values_list_to_string(
 
 @singledispatch
 def optional_symbols_list_to_list(
-    symbols: Iterable[str] | Iterable[Number] | str | Number | None,
+    symbols: Iterable[str | int | Integral] | str | int | Integral | None,
     stype_in: SType,
 ) -> list[str]:
     """
@@ -68,7 +69,7 @@ def optional_symbols_list_to_list(
 
     Parameters
     ----------
-    symbols : iterable of str, iterable of Number, str, or Number optional
+    symbols : Iterable of str or int or Number, or str or int or Number, optional
         The symbols to concatenate.
     stype_in : SType
         The input symbology type for the request.
@@ -84,7 +85,7 @@ def optional_symbols_list_to_list(
     """
     raise TypeError(
         f"`{symbols}` is not a valid type for symbol input; "
-        "allowed types are Iterable[str], Iterable[int], str, int, and None.",
+        "allowed types are Iterable[str | int], str, int, and None.",
     )
 
 
@@ -102,10 +103,10 @@ def _(_: None, __: SType) -> list[str]:
     return [ALL_SYMBOLS]
 
 
-@optional_symbols_list_to_list.register(cls=Number)
-def _(symbols: Number, stype_in: SType) -> list[str]:
+@optional_symbols_list_to_list.register(cls=Integral)
+def _(symbols: Integral, stype_in: SType) -> list[str]:
     """
-    Dispatch method for optional_symbols_list_to_list. Handles numerical types,
+    Dispatch method for optional_symbols_list_to_list. Handles integral types,
     alerting when an integer is given for STypes that expect strings.
 
     See Also
@@ -147,7 +148,7 @@ def _(symbols: str, stype_in: SType) -> list[str]:
 
 
 @optional_symbols_list_to_list.register(cls=Iterable)
-def _(symbols: Iterable[str] | Iterable[int], stype_in: SType) -> list[str]:
+def _(symbols: Iterable[Any], stype_in: SType) -> list[str]:
     """
     Dispatch method for optional_symbols_list_to_list. Handles Iterables by
     dispatching the individual members.

databento/historical/api/batch.py

@@ -2,6 +2,7 @@
 
 import logging
 import os
+from collections.abc import Iterable
 from datetime import date
 from os import PathLike
 from pathlib import Path
@@ -48,7 +49,7 @@ def __init__(self, key: str, gateway: str) -> None:
     def submit_job(
         self,
         dataset: Dataset | str,
-        symbols: list[str] | str,
+        symbols: Iterable[str | int] | str | int,
         schema: Schema | str,
         start: pd.Timestamp | date | str | int,
         end: pd.Timestamp | date | str | int | None = None,
@@ -75,7 +76,7 @@ def submit_job(
         ----------
         dataset : Dataset or str
             The dataset code (string identifier) for the request.
-        symbols : list[str | int] or str
+        symbols : Iterable[str | int] or str or int
             The instrument symbols to filter for. Takes up to 2,000 symbols per request.
             If more than 1 symbol is specified, the data is merged and sorted by time.
             If 'ALL_SYMBOLS' or `None` then will be for **all** symbols.

databento/historical/api/metadata.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+from collections.abc import Iterable
 from datetime import date
 from typing import Any
 
@@ -261,7 +262,7 @@ def get_record_count(
         dataset: Dataset | str,
         start: pd.Timestamp | date | str | int,
         end: pd.Timestamp | date | str | int | None = None,
-        symbols: list[str] | str | None = None,
+        symbols: Iterable[str | int] | str | int | None = None,
         schema: Schema | str = "trades",
         stype_in: SType | str = "raw_symbol",
         limit: int | None = None,
@@ -285,7 +286,7 @@ def get_record_count(
             If an integer is passed, then this represents nanoseconds since the UNIX epoch.
             Values are forward filled based on the resolution provided.
             Defaults to the same value as `start`.
-        symbols : list[str | int] or str, optional
+        symbols : Iterable[str | int] or str or int, optional
             The instrument symbols to filter for. Takes up to 2,000 symbols per request.
             If 'ALL_SYMBOLS' or `None` then will be for **all** symbols.
         schema : Schema or str {'mbo', 'mbp-1', 'mbp-10', 'trades', 'tbbo', 'ohlcv-1s', 'ohlcv-1m', 'ohlcv-1h', 'ohlcv-1d', 'definition', 'statistics', 'status'}, default 'trades'  # noqa
@@ -329,7 +330,7 @@ def get_billable_size(
         dataset: Dataset | str,
         start: pd.Timestamp | date | str | int,
         end: pd.Timestamp | date | str | int | None = None,
-        symbols: list[str] | str | None = None,
+        symbols: Iterable[str | int] | str | int | None = None,
         schema: Schema | str = "trades",
         stype_in: SType | str = "raw_symbol",
         limit: int | None = None,
@@ -354,7 +355,7 @@ def get_billable_size(
             If an integer is passed, then this represents nanoseconds since the UNIX epoch.
             Values are forward filled based on the resolution provided.
             Defaults to the same value as `start`.
-        symbols : list[str | int] or str, optional
+        symbols : Iterable[str | int] or str or int, optional
             The instrument symbols to filter for. Takes up to 2,000 symbols per request.
             If 'ALL_SYMBOLS' or `None` then will be for **all** symbols.
         schema : Schema or str {'mbo', 'mbp-1', 'mbp-10', 'trades', 'tbbo', 'ohlcv-1s', 'ohlcv-1m', 'ohlcv-1h', 'ohlcv-1d', 'definition', 'statistics', 'status'}, default 'trades'  # noqa
@@ -399,7 +400,7 @@ def get_cost(
         start: pd.Timestamp | date | str | int,
         end: pd.Timestamp | date | str | int | None = None,
         mode: FeedMode | str = "historical-streaming",
-        symbols: list[str] | str | None = None,
+        symbols: Iterable[str | int] | str | int | None = None,
         schema: Schema | str = "trades",
         stype_in: SType | str = "raw_symbol",
         limit: int | None = None,
@@ -426,7 +427,7 @@ def get_cost(
             Defaults to the same value as `start`.
         mode : FeedMode or str {'live', 'historical-streaming', 'historical'}, default 'historical-streaming'
             The data feed mode for the request.
-        symbols : list[str | int] or str, optional
+        symbols : Iterable[str | int] or str or int, optional
             The instrument symbols to filter for. Takes up to 2,000 symbols per request.
             If 'ALL_SYMBOLS' or `None` then will be for **all** symbols.
         schema : Schema or str {'mbo', 'mbp-1', 'mbp-10', 'trades', 'tbbo', 'ohlcv-1s', 'ohlcv-1m', 'ohlcv-1h', 'ohlcv-1d', 'definition', 'statistics', 'status'}, default 'trades'  # noqa