History

Lingxian Kong c19c4dca00 Improve function execution performance - Improve/Simplify python runtime - Use non-locking for communication with db when invoking function. - Add config option to run job handler. - Pre-fetch runtime when query function in db. Change-Id: I9e791aecf03d5bf64a39548e6c9bad1b678882af		2017-12-07 10:49:12 +13:00
..
Dockerfile	Limit resource consumption of function	2017-12-04 23:26:13 +13:00
README.md	Support python function input	2017-06-15 22:59:27 +12:00
custom-entrypoint.sh	Limit resource consumption of function	2017-12-04 23:26:13 +13:00
requirements.txt	Limit resource consumption of function	2017-12-04 23:26:13 +13:00
server.py	Improve function execution performance	2017-12-07 10:49:12 +13:00

README.md

Qinling: Python Environment

This is the Python environment for Qinling.

It's a Docker image containing a Python 2.7 runtime, along with a dynamic loader. A few common dependencies are included in the requirements.txt file. End users need to provide their own dependencies in their function packages through Qinling API or CLI.

Rebuilding and pushing the image

You'll need access to a Docker registry to push the image, by default it's docker hub. After modification, build a new image and upload to docker hub:

docker build -t USER/python-runtime . && docker push USER/python-runtime

Using the image in Qinling

After the image is ready in docker hub, create a runtime in Qinling:

http POST http://127.0.0.1:7070/v1/runtimes name=python2.7 image=USER/python-runtime