Cortex ML Models Python Library
NOTE: cortex-client has been deprecated. Please migrate to cortex-python instead.
The Cortex Python Library provides an SDK to easily integrate and deploy ML algorithms into Cortex.
Refer to the Cortex documentation for details on how to use the SDK:
Installation
To install the Cortex Client:
> pip install cortex-client
or from source code:
> git clone git@bitbucket.org:cognitivescale/cortex-python-lib.git
> cd cortex-python-lib
> pip install -e .
To install the Cortex Client with the optional visualization component:
> pip install cortex-client[viz]
Development
Setup
When developing, it's a best practice to work in a virtual environment. Create and activate a virtual environment:
> virtualenv --python=python3.6 _venv
> source _venv/bin/activate
Install Python SDK in editable mode, and all developer dependencies:
> git clone git@bitbucket.org:cognitivescale/cortex-python-lib.git
> cd cortex-python-lib
> make dev.setup
> make dev.install
There's a convenience Makefile
that has commands to common tasks, such as build, test, etc. Use it!
Testing
Unit Tests
Follow above setup instructions (making sure to be in the virtual environment and having the necessary dependencies)
make dev.test
to run test suite
if you get this cryptic error message: RuntimeError: Python is not installed as a framework.
create a file ~/.matplotlib/matplotlibrc
and write inside of it: backend: TkAgg
To run an individual file or class method, use pytest. Example tests shown below:
- file:
pytest test/unit/agent_test.py
- class method:
pytest test/unit/agent_test.py::TestAgent::test_get_agent
Using the New SDK
Suppose you made some changes to the SDK, and you want to try/test the new SDK before committing your changes to dev. We need to use an alpha version of the new SDK. The below changes will push our new SDK docker image to the pypi registry. The below steps are necessary if you wish to run ActionBuilder and commands that require pulling from the private cortex docker registry.
- we need to create and push an alpha release:
- get credentials to the
cortex-client
pypi cortex5 account (via lastpass) - run
make dev.push TAG=<alpha release number>
. Example: make dev.push TAG=1
We are going to be testing our new SDK in skill lab. Go to https://docs.cortex-dev.insights.ai/docs/skill-development/pre-skill-development/import-run-notebooks/#load-example-notebooks to get
a working example notebook in skill lab (if you don't have one already). We are going to use cortex-examples/skill-lab/skills_hello_world.ipynb
as a reference.
In the hello world notebook:
- create and run a new cell with the command
!pip show cortex-client
- this will show our current cortex-client.
Run that command, and you'll see under Location, it currently points to the old SDK. We need to point it to our new sdk. Take note of this. - create another cell and run the command
!which python
- this will show which python version (and likely virutalenv) you're using.
Take note of this.
Create a terminal tab in skill lab. We need to point the python version in the terminal session to be the same one as the hello world note book. This process will be specific to the user, but possible steps include having to run conda deactivate
and conda actviate <python virtual env the hello world notebook is in>
Now, in the terminal tab you should be in the correct python environment. Next, We need to use our new local sdk. pip install -e <localdirectory location/cortex-python-lib>
. Make sure to update setup.py
version to the alpha release.
Finally: if you go back to the hello world notebook, and run !pip show cortex-client
, you should see the new SDK version and location. You can now test your new, local SDK on skill-lab.
Note, If changes don't show up, try restarting the kernel.
Contribution
After contributing to the SDK, and before you submit changes as a PR, please do the following
- Run unit tests via
make dev.test
- Manually verified SDK (i.e. try the new SDK out in skill lab) to make sure everything is going well. Not required, but highly encouraged.
- Bump up
setup.py
version and update the CHANGELOG.md
Documentation
The Python client documentation is built with Sphinx. To build the documentation:
cd
to the root directory of the Python SDK project:
> cd <cortex-python-sdk source dir>
Activate your virtual environment:
> source _venv/bin/activate
Setup your environment, if you have not done so:
> make dev.install
Build the docs:
> make docs.build
The documentation will be rendered in HTML format under the docs/_build/html
directory.
Pre-release to staging
- Create and push an alpha release:
> make dev.push TAG=1
Where TAG
is the alpha version number. This will build an alpha-tagged package. - Merge
develop
to staging
branch:
> make stage
- In Bitbucket, create a pull request from
staging
to master
.