SKA SDP TMLITE Server
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
folderUse PyTest as the testing framework
Reference: PyTest introduction
Run tests with
python setup.py test
Configure PyTest in
setup.py
andsetup.cfg
Running the test creates the
htmlcov
folderInside 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 themodule
andtests
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.