search
HomeBackend DevelopmentPython TutorialAccess the value of environment variables in Python

Access the value of environment variables in Python

Aug 25, 2023 pm 10:17 PM
pythonenvironment variablesaccess value

Access the value of environment variables in Python

Environment variables in Python are configuration values ​​stored outside the code and used by the application at runtime. These variables exist as key-value pairs, just like dictionaries in Python. These variables can be set, updated, or deleted in the configuration file without changing the application code. Python provides a number of operating system functions to access environment variables without affecting the application code. In this article, we will learn how to access environment variables in Python.

Using operating system modules

To interact with the operating system, python has an os module with the help of which you can interact with the operating system and access environment variables. os.environ The dictionary contains all environment variables in key-value pairs.

We can use os.environ to access the path to the environment variable as well as any new environment variable values.

Example

import os

# get the value of the PATH environment variable
path = os.environ['PATH']
print(path)

# set a new environment variable
os.environ['MY_VAR'] = 'my value'

# get the value of the new environment variable
my_var = os.environ['MY_VAR']
print(my_var)

Output

/opt/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/tools/node/bin:/tools/google-cloud-sdk/bin
my value

Example

If the environment variable is not found, the code raises a critical error. To avoid such errors, we can use the os.environ.get() function to access environment variables and avoid key errors when the key is not found.

import os

# get the value of the MY_VAR environment variable, or return None
my_var = os.environ.get('MY_VAR')
print(my_var)

Output

None

Using Dotenv module

In the industry, we use different environments for development, staging, and production code bases. There is a separate environment variable file for each environment. Dotenv is a third-party library for accessing environment variables in multiple environments.

Install

To use the dotenv module, we must first install python-dotenv through the following command

pip install python-dotenv

Pip is a python package manager. Pip install python-dotenv Installs the dotenv module into the local file system.

After installing the python-dotenv module, we must create a .env file in the root directory of the project and create environment values ​​in it as key-value pairs.

MY_KEY_VAR=my_value

My_KEY_VAR is the key of the environment variable, and my_value is the corresponding value.

Now, we can load the .env file into our Python code wherever needed using the dotenv.load_dotenv() function, which reads the .env file and loads all environment variables into in the os.environ module.

Example

from dotenv import load_dotenv
import os

# load the environment variables from the .env file
load_dotenv()

# get the value of the MY_VAR environment variable
my_var = os.environ['MY_KEY_VAR']
print(my_var)

Output

my_value

Use Argparse module

argparse is a standard library in Python for parsing command line arguments. We can pass environment variables as command line arguments in Python using the argparse library.

algorithm

  • Define a command line parameter for each environment variable we want to pass.

  • Then use the args object returned by argparse to access the environment variables.

  • Pass environment variables and their values ​​when running the file.

Example

import argparse

parser = argparse.ArgumentParser()
parser.add_argument('--my-var')
args = parser.parse_args()

my_var = args.my_var
print(my_var)

Output

None

When running the above file, we need to pass the environment value through the key name.

python script.py --my-var "my value"

When we pass the –my-var option and its value "my value" on the command line, the parse_args() method of the argparse module parses the option and gets its value, i.e. "my_value".

Using the configuration parser module

Configuration Parser is a Python library for reading configuration files in Python applications.

algorithm

To use the configure parser module we must

  • Create a configuration file and declare environment variables as needed in the form of key-value pairs for each part (such as development, production, and staging).

  • Use the os.getenv() function in the Python file to access the current environment.

  • In Python files that need to access environment variables, we can use the ConfigParser module to access the environment variables of the current environment.

[development]
MY_VAR=my value

[production]
MY_VAR=another value

import configparser
import os

# get the current environment
env = os.getenv('ENVIRONMENT', 'development')

# read the configuration file
config = configparser.ConfigParser()
config.read('config.ini')

# get the value of the MY_VAR environment variable for the current environment
my_var = config.get(env, 'MY_VAR')
print(my_var)

in conclusion

In this article, we explored different ways to access environment variables in Python files. We learned how to use the os module to access environment variables, how to use the dotenv library to access environment variables in multiple environments, how to use the argparse module to pass environment variables as Command line parameter passing, and how to use the ConfigParser module to access the current environment's environment variables from multiple environments.

The above is the detailed content of Access the value of environment variables in Python. For more information, please follow other related articles on the PHP Chinese website!

Statement
This article is reproduced at:tutorialspoint. If there is any infringement, please contact admin@php.cn delete
Python vs. C  : Learning Curves and Ease of UsePython vs. C : Learning Curves and Ease of UseApr 19, 2025 am 12:20 AM

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

Python vs. C  : Memory Management and ControlPython vs. C : Memory Management and ControlApr 19, 2025 am 12:17 AM

Python and C have significant differences in memory management and control. 1. Python uses automatic memory management, based on reference counting and garbage collection, simplifying the work of programmers. 2.C requires manual management of memory, providing more control but increasing complexity and error risk. Which language to choose should be based on project requirements and team technology stack.

Python for Scientific Computing: A Detailed LookPython for Scientific Computing: A Detailed LookApr 19, 2025 am 12:15 AM

Python's applications in scientific computing include data analysis, machine learning, numerical simulation and visualization. 1.Numpy provides efficient multi-dimensional arrays and mathematical functions. 2. SciPy extends Numpy functionality and provides optimization and linear algebra tools. 3. Pandas is used for data processing and analysis. 4.Matplotlib is used to generate various graphs and visual results.

Python and C  : Finding the Right ToolPython and C : Finding the Right ToolApr 19, 2025 am 12:04 AM

Whether to choose Python or C depends on project requirements: 1) Python is suitable for rapid development, data science, and scripting because of its concise syntax and rich libraries; 2) C is suitable for scenarios that require high performance and underlying control, such as system programming and game development, because of its compilation and manual memory management.

Python for Data Science and Machine LearningPython for Data Science and Machine LearningApr 19, 2025 am 12:02 AM

Python is widely used in data science and machine learning, mainly relying on its simplicity and a powerful library ecosystem. 1) Pandas is used for data processing and analysis, 2) Numpy provides efficient numerical calculations, and 3) Scikit-learn is used for machine learning model construction and optimization, these libraries make Python an ideal tool for data science and machine learning.

Learning Python: Is 2 Hours of Daily Study Sufficient?Learning Python: Is 2 Hours of Daily Study Sufficient?Apr 18, 2025 am 12:22 AM

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Python for Web Development: Key ApplicationsPython for Web Development: Key ApplicationsApr 18, 2025 am 12:20 AM

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python vs. C  : Exploring Performance and EfficiencyPython vs. C : Exploring Performance and EfficiencyApr 18, 2025 am 12:20 AM

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Tools

Dreamweaver Mac version

Dreamweaver Mac version

Visual web development tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

mPDF

mPDF

mPDF is a PHP library that can generate PDF files from UTF-8 encoded HTML. The original author, Ian Back, wrote mPDF to output PDF files "on the fly" from his website and handle different languages. It is slower than original scripts like HTML2FPDF and produces larger files when using Unicode fonts, but supports CSS styles etc. and has a lot of enhancements. Supports almost all languages, including RTL (Arabic and Hebrew) and CJK (Chinese, Japanese and Korean). Supports nested block-level elements (such as P, DIV),

Safe Exam Browser

Safe Exam Browser

Safe Exam Browser is a secure browser environment for taking online exams securely. This software turns any computer into a secure workstation. It controls access to any utility and prevents students from using unauthorized resources.

SAP NetWeaver Server Adapter for Eclipse

SAP NetWeaver Server Adapter for Eclipse

Integrate Eclipse with SAP NetWeaver application server.