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pyfetch-mimic

  • This is a simple module that mimics pyodide.http.pyfetch to make local development for shinylive projects easier. It may work with pyodide in general, but that use case hasn't been tested.
  • For more information on Shinylive for Python, and general information on how to use additional third party libraries (like this one), see: https://shiny.posit.co/py/docs/shinylive.html

Install

  • PyPI: pip install pyfetch-mimic
  • Vendoring:
    • Copy pyfetch_mimic.py into your own project

How to use

  • Include the following conditional import statement at the beginning of the module that will use http.pyfetch: 
    import sys
if "pyodide" in sys.modules:
    from pyodide import http
else:
    from pyfetch_mimic import http
  • Use http.pyfetch as usual
  • NOTE: This is a work in progress and does not support all pyodide.http.pyfetch functionality yet. I use this in my own production work, and the functionality that currently exists is simply the functionality that I need. If there is a need for additional functionality, please open an issue or pull request.

pyfetch examples

  • These should all work with python pyodide.http.pyfetch and pyfetch_mimic.http.pyfetch
# Download, save extracted file to local virtual fs
import sys
if "pyodide" in sys.modules:
    from pyodide import http
else:
    from pyfetch_mimic import http

async def sample():
    response = await http.pyfetch("https://some_url/myfiles.zip")
    await response.unpack_archive()
# Download text file to local virtual fs, load into pandas
import pandas as pd
import sys
if "pyodide" in sys.modules:
    from pyodide import http
else:
    from pyfetch_mimic import http

async def sample():    
    response = await http.pyfetch(url())
    with open("test.json", mode="wb") as file:
        file.write(await response.bytes())
    df = pd.read_json("test.json")
# Download text file into BytesIO memory buffer, load into pandas
from io import BytesIO
import sys
import pandas as pd
if "pyodide" in sys.modules:
    from pyodide import http
else:
    from pyfetch_mimic import http

async def sample():
    response = await http.pyfetch("<URL>")
    buf = BytesIO(await response.bytes())
    df = pd.read_json(buf)

Testing

Install Test Dependencies

  • pip install -e '.[tests]'

Run regular tests (verifies test endpoints and tests pyfetch-mimic)

  • activate venv: source .venv/bin/activate
  • start fastapi app: python3 src_test_webserver/main.py
  • run pytest: pytest -vv -x test

Run pyodide tests with pyfetch calls written identical to pyfetch-mimc

Manually

  • activate venv and start test fastapi app using step above
  • export shinylive app: shinylive export ./test/tests_shinylive ./src_test_webserver/shinyapps
  • open shinylive app in edit mode: http://localhost8000/apps/edit/
  • Click "Run tests"
  • If all function names at the bottom are followed by "passed", then everything should be ok

Using Robot Framework

  • activate venv
  • export shinylive app: shinylive export ./test/tests_shinylive ./src_test_webserver/shinyapps
  • run robot: robot test/robot_tests/