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devopstemplate-0.9.0


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توضیحات

This package provides a command-line interface for setting up a Python project based on a dev-ops template
ویژگی مقدار
سیستم عامل -
نام فایل devopstemplate-0.9.0
نام devopstemplate
نسخه کتابخانه 0.9.0
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Leonard Rothacker
ایمیل نویسنده leonard.rothacker@googlemail.com
آدرس صفحه اصلی https://github.com/lrothack/dev-ops-admin
آدرس اینترنتی https://pypi.org/project/devopstemplate/
مجوز MIT
# Python Devops Template Tool Command-line interface for setting up a Python project based on a dev-ops [template](https://github.com/lrothack/dev-ops). - [Sample project](https://github.com/lrothack/dev-ops) for this template (including detailed documentation). - [Cookiecutter](https://github.com/lrothack/cookiecutter-pydevops) for this template. - Also check out [audreyr/cookiecutter-pypackage](https://github.com/audreyr/cookiecutter-pypackage) for additional Python package templates. ## Features This command-line interface supports the creation and the management of a Python dev-ops template that provides: - testing and deployment in a multi-stage [Docker](https://www.docker.com) environment, - packaging with [setuptools](https://setuptools.readthedocs.io/en/latest/), - code analysis with [pylint](https://www.pylint.org/), [bandit](https://bandit.readthedocs.io/en/latest/), [pytest](https://docs.pytest.org/en/stable/) and [coverage](https://coverage.readthedocs.io/en/latest/), - code quality monitoring with [SonarQube](https://www.sonarqube.org). The dev-ops pipeline is mostly implemented in a `Makefile` and a `Dockerfile` which are independent of your Python code. A SonarQube server is started with `docker-compose`. Creation and management of the template: - create a new instance of the template (very similar to [Cookiecutter](https://github.com/audreyr/cookiecutter)), - manage an existing instance/project by adding template components as the project evolves, - generate a Cookiecutter template (see [lrothack/cookiecutter-pydevops](https://github.com/lrothack/cookiecutter-pydevops)), - packages the template code in a Python distributions, e.g., binary wheel package, - configure the template with boolean command-line flags or in interactive mode, - resolves author information automatically with `git config`. Optional template components: - [MongoDB](https://www.mongodb.com) - [MlFlow](https://www.mlflow.org) (with [PostgreSQL](https://www.postgresql.org) and [MinIO](https://min.io) backends) These components have been developed in [jkortner/ml-ops](https://github.com/jkortner/ml-ops). ## Installation Install the latest version from [pypi.org](https://pypi.org/project/devopstemplate/): ```bash pip install -U devopstemplate ``` From source: ```bash # Obtain sources git clone --recurse-submodules https://github.com/lrothack/dev-ops-admin.git # Install and activate virtual environment cd dev-ops-admin python3 -m venv venv source venv/bin/activate # Build package make dist ``` The binary wheel package is located in the `dist` directory and can be installed with `pip`. ## Create and manage projects After installation, the executable `devopstemplate` is available. It provides the sub-commands: - create - manage - cookiecutter An overview of the functionalities is shown on the help screens: ```bash devopstemplate --help devopstemplate <sub-command> --help ``` The working directory is always the root directory of your project, for example: ```bash mkdir sampleproject cd sampleproject devopstemplate create ``` ## Using the dev-ops template After creating a new project or after switching to the project directory: - Set up a virtual environment for your project and activate it (requires Python >= 3.6). - Run `make help` in order to get an overview of the targets provided by `Makefile`. Note: Running `make` is only supported from project directory. - Run `make install-dev` in order to install the package (and all dependencies) in development mode. - Run `make lint` in order to run code analysis with pylint and bandit. - Run `make test` in order to run unit tests with pytest and coverage. - Run `make dist` in order to build a Python package (binary and source). - Make sure you have [Docker](https://www.docker.com) installed and the Docker daemon is running. Allocate at least 4GB RAM in the Docker resource configuration. - Run `docker-compose -p sonarqube -f sonarqube/docker-compose.yml up -d` in order to start a SonarQube server. Configure your server through its web interface and obtain an authentication token. The SonarQube URL can be configured through the `Makefile` variable `SONARURL`. The authentication token can be stored in the local file `.sonartoken`. - Run `make sonar` in order to run `sonar-scanner` and report results to your SonarQube server. - Run `make docker-build` in order to analyze, test, package and deploy in a multi-stage Docker build. Analysis results and test results are shown after the build. Advanced configurations can be made in the *configuration* sections of `Makefile`. See [lrothack/dev-ops](https://github.com/lrothack/dev-ops) for more information. ## Additional components - `mongodb` - `mlflow` Additional components can be installed when creating a new project or with the `manage` command at a later time (replace `<component>` with a component from the list above, also see `devopstemplate manage --help`): ```bash cd sampleproject devopstemplate manage --add-<component> ``` Start the corresponding Docker containers with `docker-compose`: ```bash docker-compose -p <component> -f <component>/docker-compose.yml up -d ``` Also check out the README file in the `<component>` directory and run the sample script.


نیازمندی

مقدار نام
- Jinja2
>=20.1.1 pip
- wheel
- pytest
- coverage
- bandit
- pylint
- autopep8
- flake8


زبان مورد نیاز

مقدار نام
>= 3.6 Python


نحوه نصب


نصب پکیج whl devopstemplate-0.9.0:

    pip install devopstemplate-0.9.0.whl


نصب پکیج tar.gz devopstemplate-0.9.0:

    pip install devopstemplate-0.9.0.tar.gz