This is the Python environment for Fission.
It's a Docker image containing a Python 3.5 runtime, along with a dynamic loader. A few common dependencies are included in the requirements.txt file.
Looking for ready-to-run examples? See the Python examples directory.
To add package dependencies, edit requirements.txt to add what you need, and rebuild this image (instructions below).
You also may want to customize what's available to the function in its request context. You can do this by editing server.py (see the comment in that file about customizing request context).
You'll need access to a Docker registry to push the image: you can sign up for Docker hub at hub.docker.com, or use registries from gcr.io, quay.io, etc. Let's assume you're using a docker hub account called USER. Build and push the image to the the registry:
docker build -t USER/python-env . && docker push USER/python-env
You can add this customized image to fission with "fission env create":
fission env create --name python --image USER/python-env
Or, if you already have an environment, you can update its image:
fission env update --name python --image USER/python-env
After this, fission functions that have the env parameter set to the same environment name as this command will use this environment.
Python environment build and start a WSGI server, to support high HTTP
traffic. As it is applied in different use cases, this provides two server
frameworks: bjoern and gevent. They all support high concurrency request.
bjoern has good performance on RPS, to be ideal for most light resource
utilization cases.
gevent is a good supplement because of its internal multi-threads. It
supports heavy resource load functions, with well distribution of response
time.
Python environment pod remains bjoern framework by default. And it runs gevent
framework by setting the container environment WSGI_FRAMEWORK value to GEVENT.
The environment value is configured normally in two ways. One way is to set in Dockerfile and build it into image. The other way is to set in Kubernetes deployment spec during pod running and restart it.