Skip to main content

Algora Labs Python SDK

Project description

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

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!

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

algora-sdk-1.1.38.tar.gz (20.9 kB view details)

Uploaded Source

Built Distribution

algora_sdk-1.1.38-py3-none-any.whl (34.7 kB view details)

Uploaded Python 3

File details

Details for the file algora-sdk-1.1.38.tar.gz.

File metadata

  • Download URL: algora-sdk-1.1.38.tar.gz
  • Upload date:
  • Size: 20.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.5

File hashes

Hashes for algora-sdk-1.1.38.tar.gz
Algorithm Hash digest
SHA256 f00ac94064998510d78daa7bd428969ebd32a32b3bc28cf1773827cbe81a94eb
MD5 75bb99dc492217374a9fa36acef9e47c
BLAKE2b-256 670df010a3c2493e0b397bc761846958c5b980340e96de1aa7de669abb6655fd

See more details on using hashes here.

File details

Details for the file algora_sdk-1.1.38-py3-none-any.whl.

File metadata

  • Download URL: algora_sdk-1.1.38-py3-none-any.whl
  • Upload date:
  • Size: 34.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.5

File hashes

Hashes for algora_sdk-1.1.38-py3-none-any.whl
Algorithm Hash digest
SHA256 2d280940329a4b72b7dd53a245dec18febf6ad0c1a2fc8583090acb2d2d1780b
MD5 01e14a749c95ea607541950cc381e9be
BLAKE2b-256 dc8bfac3d337c86fc999e95031ff556c9280090f6a508ad8e912baedb4e0ee34

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page