bandit VS cookiecutter

Bandit is a tool designed to find common security issues in Python code. It was developed by the OpenStack Security Project and is a great addition to any serious Python project.

For the SAST stage, I used SonarQube tool. SonarQube is an open-source platform developed by SonarSource for continuous inspection of code quality to perform automatic reviews with static analysis of code to detect bugs and code smells on more than 30 programming languages. I preferred SonarQube instead of other SAST tools because it has a detailed documentation and plugins about integration with Jenkins and SonarQube works with Java projects pretty well. Of course you can similar multi-language-supported tools such as Semgrep or language-specific tools such as Bandit.

repos: - repo: https://github.com/PyCQA/bandit rev: 1.7.7 hooks: - id: bandit args: ["-c", "pyproject.toml", "-r", "."] additional_dependencies: ["bandit[toml]"]

On the other hand, Bandit is a dedicated security scanner designed to target critical security concerns such as SQL injection and cross-site scripting exploits. It meticulously scrutinizes the codebase to identify and alert developers about possible security breaches or vulnerabilities, thus fortifying the code against potential exploitation.

Bandit: is a tool designed for Python applications to analyse your code for potential security issues like insecure use of functions, hardcoded password and much more.

Bandit (for Python, open-source and free)

Add security checks (Bandit) and dependency checks (safety)

bandit

flake8-bandit which uses bandit for security linting.

Sometimes I use this to abstract boilerplate https://github.com/cookiecutter/cookiecutter

It can use a repo as a template.

It supports some interactive questions to choose options but mostly it is jinja templates.

Having libraries would be another option.

Install the cookiecutter package using the following command:

Consider taking a look at cookiecutter to generate projects from templates. There is also cookiecutter-django. As for your environment variables you should have an example .env file containing all the environment variables required by your project (without setting them) that can be safely pushed into your repository for you and other developers to copy into the actual .env file that'll be used by your project (add this file to .gitignore)

The Python Cookiecutter library revolutionizes project development by offering streamlined approach to creating template projects and improving developer experience.

We use cookie cutter templates (the Python project, https://github.com/cookiecutter/cookiecutter ), we prompt for the module & version etc

Why not use cookiecutter or a similar tool designed for making these sorts of project templates?

Is it common? I don't know. Is it useful? Absolutely. There is a tool called cookiecutter that allows you to define your own setup. For example, my cookiecutter setup for a python library is here. You can see what it's like by first installing the cookiecutter cli and then running

Also cookiecutter.

Visual Cookiecutter enhances the functionality of cookiecutter by offering unique features such as required fields, conditional input parameters, optional descriptions, and the ability to fix mistakes easily. This package seamlessly integrates with cookiecutter so that all existing templates work out-of-the-box.