Lingxian Kong f2189a0468 Fix logs query for executions
After function autoscaling support, it's impossible for qinling-engine
to get execution log because it doesn't know which pod it is talking

So, it's neccessary for the runtime to return execution logs to
qinling engine.

The qinling client is not affected.

Change-Id: I96dfd00cc83d8b8a5e8c601ee3800b1ef1a45b1b
2017-08-29 23:54:30 +12:00
Dockerfile Disable python buffer for stdout/stderr 2017-07-17 23:47:23 +12:00
README.md Support python function input 2017-06-15 22:59:27 +12:00
requirements.txt Support Keystone session in python runtime 2017-07-03 01:16:40 +12:00
server.py Fix logs query for executions 2017-08-29 23:54:30 +12:00


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 name=python2.7 image=USER/python-runtime