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A clean, async-focused Python3 API for IQVIA data

Project description

🌻 pyiqvia: A clean, async-focused Python3 API for IQVIA™

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pyiqvia is an async-focused Python3 library for allergen, asthma, and disease data from the IQVIA™ family of websites (such as,, and more).

Python Versions

pyiqvia is currently supported on:

  • Python 3.6
  • Python 3.7
  • Python 3.8


pip install pyiqvia


import asyncio

from aiohttp import ClientSession

from pyiqvia import Client

async def main() -> None:
    client = Client(80012)

    # ZIP codes starting with 0 need to be provided as strings:
    client = Client('00544')

    # Get current allergen information:
    await client.allergens.current()

    # Get more information on the current allergen outlook:
    await client.allergens.outlook()

    # Get extended forecast allergen information:
    await client.allergens.extended()

    # Get historic allergen information:
    await client.allergens.historic()

    # Get current asthma information:
    await client.asthma.current()

    # Get extended forecast asthma information:
    await client.asthma.extended()

    # Get historic asthma information:
    await client.asthma.historic()

    # Get current cold and flu information:
    await client.disease.current()

    # Get extended forecast cold and flu information:
    await client.disease.extended()

    # Get historic cold and flu information:
    await client.disease.historic()

By default, the library creates a new connection to IQVIA with each coroutine. If you are calling a large number of coroutines (or merely want to squeeze out every second of runtime savings possible), an aiohttp ClientSession can be used for connection pooling:

import asyncio

from aiohttp import ClientSession

from pyiqvia import Client

async def main() -> None:
    async with ClientSession() as session:
        client = Client(80012, session=session)

        # ...


  1. Check for open features/bugs or initiate a discussion on one.
  2. Fork the repository.
  3. (optional, but highly recommended) Create a virtual environment: python3 -m venv .venv
  4. (optional, but highly recommended) Enter the virtual environment: source ./.venv/bin/activate
  5. Install the dev environment: script/setup
  6. Code your new feature or bug fix.
  7. Write tests that cover your new functionality.
  8. Run tests and ensure 100% code coverage: script/test
  9. Update with any new documentation.
  10. Add yourself to
  11. Submit a pull request!

Project details

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