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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,113 @@ | ||
| from __future__ import annotations | ||
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| from collections.abc import Iterable | ||
| from datetime import date | ||
|
|
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| import pandas as pd | ||
| from databento_dbn import Compression | ||
| from databento_dbn import SType | ||
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| from databento.common import API_VERSION | ||
| from databento.common.constants import ADJUSTMENT_FACTORS_DATE_COLUMNS | ||
| from databento.common.constants import ADJUSTMENT_FACTORS_DATETIME_COLUMNS | ||
| from databento.common.http import BentoHttpAPI | ||
| from databento.common.parsing import convert_date_columns | ||
| from databento.common.parsing import convert_datetime_columns | ||
| from databento.common.parsing import convert_ndjson_to_df | ||
| from databento.common.parsing import datetime_to_string | ||
| from databento.common.parsing import optional_datetime_to_string | ||
| from databento.common.parsing import optional_string_to_list | ||
| from databento.common.parsing import optional_symbols_list_to_list | ||
|
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|
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| class AdjustmentFactorsHttpAPI(BentoHttpAPI): | ||
| """ | ||
| Provides request methods for the adjustment factors HTTP API endpoints. | ||
| """ | ||
|
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| def __init__(self, key: str, gateway: str) -> None: | ||
| super().__init__(key=key, gateway=gateway) | ||
| self._base_url = gateway + f"/v{API_VERSION}/adjustment_factors" | ||
|
|
||
| def get_range( | ||
| self, | ||
| start: pd.Timestamp | date | str | int, | ||
| end: pd.Timestamp | date | str | int | None = None, | ||
| symbols: Iterable[str] | str | None = None, | ||
| stype_in: SType | str = "raw_symbol", | ||
| countries: Iterable[str] | str | None = None, | ||
| security_types: Iterable[str] | str | None = None, | ||
| ) -> pd.DataFrame: | ||
| """ | ||
| Request a new adjustment factors time series from Databento. | ||
| Makes a `POST /adjustment_factors.get_range` HTTP request. | ||
| The `ex_date` column will be used to filter the time range and order the records. | ||
| It will also be set as the index of the resulting data frame. | ||
| Parameters | ||
| ---------- | ||
| start : pd.Timestamp or date or str or int | ||
| The start datetime of the request time range (inclusive) based on `ex_date`. | ||
| Assumes UTC as timezone unless passed a tz-aware object. | ||
| If an integer is passed, then this represents nanoseconds since the UNIX epoch. | ||
| end : pd.Timestamp or date or str or int, optional | ||
| The end datetime of the request time range (exclusive) based on `ex_date`. | ||
| Assumes UTC as timezone unless passed a tz-aware object. | ||
| If an integer is passed, then this represents nanoseconds since the UNIX epoch. | ||
| symbols : Iterable[str] or str, optional | ||
| The 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 select **all** symbols. | ||
| stype_in : SType or str, default 'raw_symbol' | ||
| The input symbology type to resolve from. | ||
| Use any of 'raw_symbol', 'nasdaq_symbol', 'isin', 'us_code'. | ||
| countries : Iterable[str] or str, optional | ||
| The listing countries to filter for. | ||
| Takes any number of two letter ISO 3166-1 alpha-2 country codes per request. | ||
| If not specified then will select **all** listing countries by default. | ||
| See [CNTRY](https://databento.com/docs/standards-and-conventions/reference-data-enums#cntry) enum. | ||
| security_types : Iterable[str] or str, optional | ||
| The security types to filter for. | ||
| Takes any number of security types per request. | ||
| If not specified then will select **all** security types by default. | ||
| See [SECTYPE](https://databento.com/docs/standards-and-conventions/reference-data-enums#sectype) enum. | ||
| Returns | ||
| ------- | ||
| pandas.DataFrame | ||
| The data converted into a data frame. | ||
| """ | ||
| symbols_list = optional_symbols_list_to_list(symbols, SType.RAW_SYMBOL) | ||
| countries = optional_string_to_list(countries) | ||
| security_types = optional_string_to_list(security_types) | ||
|
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| data: dict[str, object | None] = { | ||
| "start": datetime_to_string(start), | ||
| "end": optional_datetime_to_string(end), | ||
| "symbols": ",".join(symbols_list), | ||
| "stype_in": stype_in, | ||
| "countries": ",".join(countries) if countries else None, | ||
| "security_types": ",".join(security_types) if security_types else None, | ||
| "compression": str(Compression.ZSTD), # Always request zstd | ||
| } | ||
|
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| response = self._post( | ||
| url=self._base_url + ".get_range", | ||
| data=data, | ||
| basic_auth=True, | ||
| ) | ||
|
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| df = convert_ndjson_to_df(response.content, compressed=True) | ||
| if df.empty: | ||
| return df | ||
|
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| convert_datetime_columns(df, ADJUSTMENT_FACTORS_DATETIME_COLUMNS) | ||
| convert_date_columns(df, ADJUSTMENT_FACTORS_DATE_COLUMNS) | ||
|
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| df.set_index("ex_date", inplace=True) | ||
| df.sort_index(inplace=True) | ||
|
|
||
| return df |
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