This library provides basic infrastructure for development of services and concrete implemementation of services.
The following libraries are provided:
- Database abstraction
- Task Queue Worker/Node abstraction
- Utilities
- File tree walker with filtering
- One-to-many dictionary
- Shell command wrapper with timeout support
See workers/README.md for a listing of the concrete services.
See our contributing guidelines for more info.
There are two sets of workers - API and ingestion. API workers serve requests that are passed from API endpoint. Ingestion workers are used for background data ingestion. To run them use:
$ docker-compose up worker-api worker-ingestionRun the tests in a container using the helper script:
$ ./runtests.sh(The above command assumes you have passwordless docker invocation configured -
if you don't, then sudo will be necessary to enable docker invocation).
If you're changing dependencies rather than just editing source code locally,
you will need images to be rebuilt when invoking runtest.sh. You
can set environment variable REBUILD=1 to request image rebuilding.
If the offline virtualenv based tests have been run, then this may complain about mismatched locations in compiled files. Those can be deleted using:
$ find -name *.pyc -deleteNOTE: Running the container based tests is likely to cause any already running local Fabric8-Analytics instance launched via Docker Compose to fall over due to changes in the SELinux labels on mounted volumes, and may also cause spurious test failures.
Test cases marked with pytest.mark.offline may be executed without having a
Docker daemon running locally.
To configure a virtualenv (called f8a-worker in the example) to run these
tests:
(f8a-worker) $ python -m pip install -r requirements.txt
(f8a-worker) $ python -m pip install -r tests/requirements.txtThe marked offline tests can then be run as:
(f8a-worker) $ py.test -m offline tests/If the Docker container based tests have been run, then this may complain about mismatched locations in compiled files. Those can be deleted using:
(f8a-worker) $ sudo find -name *.pyc -deleteReusing an existing virtualenv for multiple test runs
When a virtualenv already is setup you can run tests like so:
source /path/to/python_env/bin/activate
NOVENV=1 ./runtest.sh
This will not create a virtualenv every time.
Forcing image builds while testing
When some changes are made to code that will change the docker image, it is good to rebuild images locally for testing. This can re-build can be forced like so:
REBUILD=1 ./runtest.sh
- You can use scripts
run-linter.shandcheck-docstyle.shto check if the code follows PEP 8 and PEP 257 coding standards. These scripts can be run w/o any arguments:
./run-linter.sh
./check-docstyle.sh
The first script checks the indentation, line lengths, variable names, white space around operators etc. The second script checks all documentation strings - its presence and format. Please fix any warnings and errors reported by these scripts.
The scripts measure-cyclomatic-complexity.sh and measure-maintainability-index.sh are used to measure code complexity. These scripts can be run w/o any arguments:
./measure-cyclomatic-complexity.sh
./measure-maintainability-index.sh
The first script measures cyclomatic complexity of all Python sources found in the repository. Please see this table for further explanation how to comprehend the results.
The second script measures maintainability index of all Python sources found in the repository. Please see the following link with explanation of this measurement.
The script named check-bashscripts.sh can be used to check all BASH scripts (in fact: all files with the .sh extension) for various possible issues, incompatibilies, and caveats. This script can be run w/o any arguments:
./check-bashscripts.sh
Please see the following link for further explanation, how the ShellCheck works and which issues can be detected.