SKA SDP TMLITE Server

https://readthedocs.org/projects/ska-telescope-sdp-tmlite-server/badge/?version=latestDocumentation Status

There is likely to be a wider implementation of a more capable telescope model - however for the purposes of quick SDP development this is fastAPI based server - which will deliver JSON formatted products - backed by a JSON formatted telescope model.

I have decided to isolate the server, the model and the model maintainer into three objects. The server will be this repository. The physical form of the model will be a JSON structure, The creation and maintenance of the JSON structure is provided by a third product.

Requirements

The system used for development needs to have Python 3 and pip installed.

Install

Always use a virtual environment. Pipenv is now Python’s officially recommended method, but we are not using it for installing requirements when building on the CI Pipeline. You are encouraged to use your preferred environment isolation (i.e. pip, conda or pipenv while developing locally.

For working with Pipenv, follow these steps at the project root:

First, ensure that ~/.local/bin is in your PATH with:

> echo $PATH

In case ~/.local/bin is not part of your PATH variable, under Linux add it with:

> export PATH=~/.local/bin:$PATH

or the equivalent in your particular OS.

Then proceed to install pipenv and the required environment packages:

> pip install pipenv # if you don't have pipenv already installed on your system
> pipenv install
> pipenv shell

You will now be inside a pipenv shell with your virtual environment ready.

Use exit to exit the pipenv environment.

Testing

  • Put tests into the tests folder

  • Use PyTest as the testing framework

  • Run tests with python setup.py test

    • Configure PyTest in setup.py and setup.cfg

  • Running the test creates the htmlcov folder

    • Inside this folder a rundown of the issues found will be accessible using the index.html file

  • All the tests should pass before merging the code

Code analysis

  • Use Pylint as the code analysis framework

  • By default it uses the PEP8 style guide

  • Use the provided code-analysis.sh script in order to run the code analysis in the module and tests

  • Code analysis should be run by calling pylint ska_python_skeleton. All pertaining options reside under the .pylintrc file.

  • Code analysis should only raise document related warnings (i.e. #FIXME comments) before merging the code

Writing documentation

  • The documentation generator for this project is derived from SKA’s SKA Developer Portal repository

  • The documentation can be edited under ./docs/src

  • If you want to include only your README.md file, create a symbolic link inside the ./docs/src directory if the existing one does not work:

$ cd docs/src
$ ln -s ../../README.md README.md

  • In order to build the documentation for this specific project, execute the following under ./docs:

$ make html

  • The documentation can then be consulted by opening the file ./docs/build/html/index.html

Development

PyCharm

As this project uses a src folder structure, under Preferences > Project Structure, the src folder needs to be marked as “Sources”. That will allow the interpreter to be aware of the package from folders like tests that are outside of src. When adding Run/Debug configurations, make sure “Add content roots to PYTHONPATH” and “Add source roots to PYTHONPATH” are checked.