These are the steps I normally follow to start a python project, I do it more as a reminder to myself.

1. Installation Pyenv:

   MacOS

   brew update
   brew install pyenv

   Windows || Powershell

   Invoke-WebRequest -UseBasicParsing -Uri "https://raw.githubusercontent.com/pyenv-win/pyenv-win/master/pyenv-win/install-pyenv-win.ps1" -OutFile "./install-pyenv-win.ps1"; &"./install-pyenv-win.ps1"

Having the folder/repository created

1. Set Python version, open your Terminal and execute the following commands:

   MacOS / Linux

   pyenv versions # Installed versions
       pyenv install -l #List python version list
       pyenv install <version> # Install your version if needed
   pyenv local <version> # Set the version needed
   pip install poetry # Install virtualenv
   poetry --version # Check poetry version

   Windows

   pyenv versions # Installed versions
       pyenv install -l #List python version list
       pyenv install <version> # Install your version if needed
   pyenv local <version> # Set the version needed
   pip install poetry # Install virtualenv
   poetry --version # Check poetry version

2. Init poetry project

   Poetry init new project

   MacOS / Linux / Windows

   #Init poetry project
   poetry init
   #Project data, what is in braces is the default, we can press enter if we want to use these values.
   #This command will guide you through creating your pyproject.toml config.
       Package name [init_python]:
       Version [0.1.0]:
       Description []: 
       Author [Maximiliano Fonseca <[email protected]>, n to skip]:
       License []:
       Compatible Python versions [^3.11]: #This depends on the version where you installed poetry
       Would you like to define your main dependencies interactively? (yes/no) [yes] #Here you will begin to install the dependencies/libraries that you will use in your project
           Package to add or search for (leave blank to skip): pandas #Example, installing pandas
           Enter package # to add, or the complete package name if it is not listed []:
               [ 0] pandas
               [ 1] pandas2
               [ 2] pandas007
               [ 3] Pandas3
           Enter the version constraint to require (or leave blank to use the latest version): 
       Would you like to define your development dependencies interactively? (yes/no) [yes] #The process is similar to dependencies; on this we would install poetry for example
   

   

3. Add dependencies as we progress in development If we need to add dependencies while we are developing, it is necessary to use:

   poetry add <dependency-name>

4. We have to install our project to start using on our system

   poetry install --no-root
   poetry run python main.py #With this command we would run any file using our poetry environment for the project

5. Init folders structure:

   MacOS / Linux

   mkdir -p config container secrets source test utils && touch main.py config/__init__.py config/config.py source/__init__.py test/__init__.py utils/__init__.py container/deployment.yaml

   Windows || Powershell

   # Create directories
   New-Item -ItemType Directory -Path config, container, secrets, source, test, utils
   
   # Create files
   New-Item -ItemType File -Path main.py, 'config/__init__.py', 'config/config.py', 'source/__init__.py', 'test/__init__.py', 'utils/__init__.py', 'container/deployment.yaml'

   Windows || CMD

   REM Create directories
   mkdir config & mkdir container & mkdir secrets & mkdir source & mkdir test & mkdir utils
   
   REM Create files
   echo. 2>main.py
   echo. 2>config\__init__.py
   echo. 2>config\config.py
   echo. 2>source\__init__.py
   echo. 2>test\__init__.py
   echo. 2>utils\__init__.py
   echo. 2>container\deployment.yaml
   
   

6. How I work with the folders:

   1. config: This directory is often used to store configuration files. These might include settings for different environments (like development, staging, and production), constants used throughout your application, or configuration for external services. A common way to structure this is to have Python files such as dev.py, prod.py, staging.py etc. which are loaded based on the current environment. Each file could contain settings relevant to that environment.

   2. source: This directory, often also named src, contains the main source code for your application. This could include different modules, packages, or standalone scripts, depending on the size and complexity of your application. In larger projects, the source directory often contains subdirectories corresponding to different parts of your application. For example, if you were building a web application, you might have subdirectories for routes, models, controllers, etc.

   3. test: As you might expect, this directory is used to contain tests. These could be unit tests, integration tests, or others. A common structure is to have a mirror of your source directory, but with each file replaced by a corresponding test file. So if you had a file source/routes/user.py, you might have a corresponding test file test/routes/test_user.py. This makes it easy to find the tests for a given piece of functionality.

   4. utils: This directory is usually used for utility scripts or modules that are used across your application. For example, you might have a utils.py file with common helper functions, or a logging.py file to set up logging consistently across your application.

   5. container Directory: This is geared towards containerization aspects of your project (e.g., Docker or Kubernetes).

       deployment.yaml: A YAML file, typically used for Kubernetes to define how a containerized application should be deployed.
      

7. Project schema

    init_python
    ├── pyproject.toml
    ├── main.py
    ├── README.md
    ├── config
    │   └── __init__.py
    │   └── config.py
    ├── container
    ├── secrets
    ├── source
    │   └── __init__.py
    ├── test
    ├── utils
    │   └── __init__.py