algora-sdk 1.1.62

Algora Labs Python SDK

Algora Labs Python SDK

Algora Labs is an IDE for Quants. We provide users financial data, a research environment and visualization tools to efficiently translate research ideas into actionable insights for trading. The algora-sdk allows users to programmatically access datasets and resources on our platform.

Installation

When running locally, set the following environment variables for your username and password for Algora Labs. When running code on our platform, there is no need to set these environment variables.

ALGORA_USER=username
ALGORA_PWD=password

Auto generating Docs

To autogenerate docs we are using pdoc3. To be compatible with pdoc3 we use the Google docstring format so make sure to update pycharm to use Google as the default docstring style.

$ pdoc3 --html .\algoralabs\ --output-dir .\docs\generated

Examples

These examples can be run on our platform.

Rolling Performance

import pandas as pd

from algoralabs.data.iex.stocks import historical_prices


def calculate_returns(df: pd.DataFrame, column: str = 'high', shift: int = 1):
    return df[column].diff() / df[column].shift(shift)


def main(symbol):
    shift = 30

    df = historical_prices(symbol, range="10y")
    df['rolling_return'] = calculate_returns(df, shift=shift) * 100

    df = df.iloc[shift:]

    return df


if __name__ == '__main__':
    print(main("AAPL"))

Swap Data Repository

Note: You must have privileges to access this SDR data

from algoralabs.data.sdr.query import commodity, get_by_date, get_distinct_in_field
from algoralabs.data.sdr import AssetClass, Repository, DataFilter, DateRange, FieldFilter


def main():
    print("Querying Commodity dataset without filters")
    print(commodity())

    print("Querying Commodity dataset by date and repository")
    print(get_by_date(asset_class=AssetClass.COMMODITY, date="2022-01-01", repos=[Repository.CME]))

    print("Getting distinct values in `leg_1_asset` field. These values can be used in the FieldFilter")
    print(get_distinct_in_field(asset_class=AssetClass.COMMODITY, field="leg_1_asset"))

    commodity_filter = DataFilter(
        # data_range is optional, can be None
        date_range=DateRange(
            start_date="2022-01-01",
            end_date="2022-01-01",
            enabled=False  # set to True to enable
        ),
        filters=[
            FieldFilter(
                field="repository",
                # operator can be "NOT_IN" or "IN" or "NOT_EQUAL" or "EQUAL" or "GTE" or "GT" or "LTE" or "LT"
                operator="IN",
                selected_values=["CME", "DTCC"]
            ),
            FieldFilter(
                field="sector",
                operator="IN",
                selected_values=["Energy"]
            )
        ]
    )

    print("Querying Commodity dataset with filters")
    commodity_filter_df = commodity(commodity_filter)

    print(commodity_filter_df)


if __name__ == '__main__':
    main()

Contact

Please Contact Us if you have any questions!