Python Environment Variables

Python is a popular and powerful programming language used for developing a wide range of applications. Python applications often depend on environment variables to function properly. Environment variables are variables that are set in the operating system environment and can be accessed by programs running on the system.

In this blog post, we will discuss what Python environment variables are, how to set them, and how to access them in your Python code.

What are Python Environment Variables?

Python environment variables are variables that are set in the operating system environment and can be accessed by Python programs running on the system. Environment variables are typically used to store configuration settings or other information that needs to be accessed by multiple programs.

In Python, environment variables are accessed using the os module. The os module provides a set of functions for working with the operating system, including functions for accessing environment variables.

How to Set Python Environment Variables?

Environment variables can be set in a variety of ways, depending on your operating system and your needs. Here are some ways to set environment variables in Python:

Setting Environment Variables in Linux

In Linux, you can set environment variables by adding the following lines to your .bashrc file:

export MY_VAR=value

Setting Environment Variables in Windows

In Windows, you can set environment variables by following these steps:

1. Open the Start menu and search for “Environment Variables”.
2. Click on “Edit the system environment variables”.
3. Click on the “Environment Variables” button.
4. Under “User Variables” or “System Variables”, click on “New”.
5. Enter the variable name and value and click on “OK”.

Setting Environment Variables in Docker

In Docker, you can set environment variables using the ENV command in your Dockerfile:

ENV MY_VAR=value

How to Access Python Environment Variables?

Once you have set an environment variable, you can access it in your Python code using the os module. The os module provides two functions for accessing environment variables:

• os.environ: This function returns a dictionary containing all the environment variables and their values.
• os.getenv: This function returns the value of a specific environment variable.

Here is an example of how to access environment variables in Python:

import os

# Get the value of an environment variable

my_var = os.getenv("MY_VAR")

# Print the value of the environment variable

print(my_var)

# Get all the environment variables

env_vars = os.environ

# Print all the environment variables

print(env_vars)

In the example above, we use the os.getenv function to get the value of an environment variable named MY_VAR, and the os.environ function to get all the environment variables.

List of Python environment variables

Here’s a complete list of Python environment variables, with descriptions and examples:

1. PYTHONPATH: This environment variable is used to specify additional directories where Python should look for modules when importing them. This can be useful when you have custom modules or packages that you want to use in your code.

Example: export PYTHONPATH=/path/to/my/modules

2. PYTHONHOME: This environment variable is used to specify the root directory of the Python installation. This can be useful if you have multiple Python installations and want to use a specific one.

Example: export PYTHONHOME=/usr/local/python3

3. PYTHONBUFFERED: This environment variable is used to control the buffering of stdout and stderr. When set to a non-zero value, it forces output to be written immediately instead of being buffered. This can be useful for debugging.

Example: export PYTHONBUFFERED=1

4. PYTHONIOENCODING: This environment variable is used to specify the encoding used for stdin, stdout, and stderr. This can be useful when working with non-ASCII characters.

Example: export PYTHONIOENCODING=utf-8

5. VIRTUAL_ENV: This environment variable is used to specify the directory of the virtual environment that your Python code is running in. This can be useful when working with multiple virtual environments.

Example: export VIRTUAL_ENV=/path/to/my/virtualenv

6. PIPENV_VENV_IN_PROJECT: This environment variable is used to specify whether Pipenv should create the virtual environment inside the project directory or in a separate directory. This can be useful for organizing your project files.

Example: export PIPENV_VENV_IN_PROJECT=1

7. FLASK_APP: This environment variable is used to specify the name of the Python module that contains your Flask application. This can be useful when working with multiple Flask applications.

Example: export FLASK_APP=myapp

8. FLASK_ENV: This environment variable is used to specify the environment that your Flask application is running in, such as “development” or “production”. This can be useful for configuring your application differently depending on the environment.

Example: export FLASK_ENV=development

9. PYTHONSTARTUP: This environment variable specifies a Python script that will be executed when the interactive interpreter is started. It can be useful for defining common functions or importing modules that you use frequently.

Example: export PYTHONSTARTUP=/path/to/startup.py

10. PYTHONFAULTHANDLER: This environment variable enables the fault handler in Python, which prints a stack trace and error message when a fatal error occurs.

Example: export PYTHONFAULTHANDLER=1

11. PYTHONHASHSEED: This environment variable sets the hash seed used by Python’s hash function. It can be useful for ensuring reproducible results when hashing objects.

Example: export PYTHONHASHSEED=12345

12. PYTHONMALLOC: This environment variable sets the memory allocator used by Python. It can be useful for debugging memory issues.

Example: export PYTHONMALLOC=debug

13. PYTHONASYNCIODEBUG: This environment variable enables debugging for the asyncio library in Python. It can be useful for debugging issues with asynchronous code.

Example: export PYTHONASYNCIODEBUG=1

14. PYTHONVERBOSE: This environment variable enables verbose mode in Python, which prints more information about the program’s execution.

Example: export PYTHONVERBOSE=1

15. PYTHONOPTIMIZE: This environment variable sets the optimization level used by the Python interpreter. It can be useful for improving the performance of your code.

Example: export PYTHONOPTIMIZE=2

16. PYTHONDEVMODE: This environment variable enables development mode in Python, which disables some performance optimizations to make debugging easier.

Example: export PYTHONDEVMODE=1

17. PYTHONWARNINGS: This environment variable sets the level of warnings printed by Python. It can be useful for debugging issues with your code.

Example: export PYTHONWARNINGS=once

18. PYTHONBREAKPOINT: This environment variable sets the debugger used by Python. It can be useful for debugging issues with your code.

Example: export PYTHONBREAKPOINT=pdb.set_trace

19. DJANGO_SETTINGS_MODULE: This environment variable is used by the Django web framework to specify the Python module that contains the settings for the application. It can be useful when you have multiple Django applications in the same project.

Example: export DJANGO_SETTINGS_MODULE=myproject.settings

20. AWS_ACCESS_KEY_ID: This environment variable is used by the AWS SDK for Python to specify the access key ID for accessing AWS services. It can be useful when you are working with AWS services.

Example: export AWS_ACCESS_KEY_ID=your_access_key_id

21. AWS_SECRET_ACCESS_KEY: This environment variable is used by the AWS SDK for Python to specify the secret access key for accessing AWS services. It can be useful when you are working with AWS services.

Example: export AWS_SECRET_ACCESS_KEY=your_secret_access_key

22. AWS_DEFAULT_REGION: This environment variable is used by the AWS SDK for Python to specify the default region for accessing AWS services. It can be useful when you are working with AWS services.

Example: export AWS_DEFAULT_REGION=us-west-2

Quick view of Python Environment Variable List

Here is a complete list of Python environment variables in a tabular form, along with their descriptions and examples:

Conclusion:

Understanding and using these environment variables in your Python projects can help you configure your Python environment to work better suit your needs and improve your development workflow efficiently and effectively.