# Develop ## 1. Code Style We adopt [PEP8](https://www.python.org/dev/peps/pep-0008/) as the preferred code style. We use the following toolsseed isortseed isortseed isort for linting and formatting: - [flake8](http://flake8.pycqa.org/en/latest/): linter - [yapf](https://github.com/google/yapf): formatter - [isort](https://github.com/timothycrosley/isort): sort imports Style configurations of yapf and isort can be found in [setup.cfg](../../setup.cfg). We use [pre-commit hook](https://pre-commit.com/) that checks and formats for `flake8`, `yapf`, `seed-isort-config`, `isort`, `trailing whitespaces`, fixes `end-of-files`, sorts `requirments.txt` automatically on every commit. The config for a pre-commit hook is stored in [.pre-commit-config](../../.pre-commit-config.yaml). After you clone the repository, you will need to install initialize pre-commit hook. ```bash pip install -r requirements/tests.txt ``` From the repository folder ```bash pre-commit install ``` After this on every commit check code linters and formatter will be enforced. If you want to use pre-commit to check all the files, you can run ```bash pre-commit run --all-files ``` If you only want to format and lint your code, you can run ```bash make linter ``` ## 2. Test ### 2.1 Test level There are mainly three test levels: * level 0: tests for basic interface and function of framework, such as `tests/trainers/test_trainer_base.py` * level 1: important functional test which test end2end workflow, such as `tests/pipelines/test_image_matting.py` * level 2: scenario tests for all the implemented modules such as model, pipeline in different algorithm filed. Default test level is 0, which will only run those cases of level 0, you can set test level via environment variable `TEST_LEVEL`. For more details, you can refer to [test-doc](https://alidocs.dingtalk.com/i/nodes/mdvQnONayjBJKLXy1Bp38PY2MeXzp5o0?dontjump=true&nav=spaces&navQuery=spaceId%3Dnb9XJNlZxbgrOXyA) ```bash # run all tests TEST_LEVEL=2 make test # run important functional tests TEST_LEVEL=1 make test # run core UT and basic functional tests make test ``` When writing test cases, you should assign a test level for your test case using following code. If left default, the test level will be 0, it will run in each test stage. File test_module.py ```python from modelscope.utils.test_utils import test_level class ImageCartoonTest(unittest.TestCase): @unittest.skipUnless(test_level() >= 1, 'skip test in current test level') def test_run_by_direct_model_download(self): pass ``` ### 2.2 Run tests 1. Run your own single test case to test your self-implemented function. You can run your test file directly, if it fails to run, pls check if variable `TEST_LEVEL` exists in the environment and unset it. ```bash python tests/path/to/your_test.py ``` 2. Remember to run core tests in local environment before start a codereview, by default it will only run test cases with level 0. ```bash make tests ``` 3. After you start a code review, ci tests will be triggered which will run test cases with level 1 4. Daily regression tests will run all cases at 0 am each day using master branch. ### 2.3 Test data storage As we need a lot of data for testing, including images, videos, models. We use git lfs to store those large files. 1. install git-lfs(version>=2.5.0) for mac ```bash brew install git-lfs git lfs install ``` for centos, please download rpm from git-lfs github release [website](https://github.com/git-lfs/git-lfs/releases/tag/v3.2.0) ```bash wget http://101374-public.oss-cn-hangzhou-zmf.aliyuncs.com/git-lfs-3.2.0-1.el7.x86_64.rpm sudo rpm -ivh git-lfs-3.2.0-1.el7.x86_64.rpm git lfs install ``` for ubuntu ```bash curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash sudo apt-get install git-lfs git lfs install ``` 2. track your data type using git lfs, for example, to track png files ```bash git lfs track "*.png" ``` 3. add your test files to `data/test/` folder, you can make directories if you need. ```bash git add data/test/test.png ``` 4. commit your test data to remote branch ```bash git commit -m "xxx" ``` To pull data from remote repo, just as the same way you pull git files. ```bash git pull origin branch_name ``` ## Development and Code Review 1. Get the latest master code and checkout a new branch for local development. ```shell git pull origin master --rebase git checout -b dev/my-dev-branch ``` note: replace "dev/my-dev-branch" with a meaningful branch name. We recommend using a new dev branch for every change. 2. Make your local changes. 3. Commit your local changes. ```shell git add . git commit -m "[to #42322933] my commit message" ``` note: you may replace [to #42322933] with your own aone issue id (if any). 4. Push your change: ```shell git push --set-upstream origin dev/my-dev-branch ``` Note that you may push multiple times to the same branch with 'git push' commands later. 5. Open the remote url `https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/new` to create a new merge request that merges your development branch (aka, the "dev/my-dev-branch in this example) into master branch. Please follow the instruction on aone page to submit the merge request a code review. ## Build pip package ```bash make whl ```