search
HomeBackend DevelopmentPython TutorialDetailed explanation of Python's ConfigParser configuration file

Detailed explanation of Python's ConfigParser configuration file

Sep 04, 2017 pm 01:57 PM
configparserpythonConfiguration file

1. Basic reading configuration file

-read(filename) directly reads the ini file content

-sections() to get all the sections and list them The form returns

-options(section) to get all the options of the section

-items(section) to get all the key-value pairs of the section

-get(section,option ) Get the value of option in section and return it as string type

-getint(section,option) Get the value of option in section and return it as int type. There are also corresponding getboolean() and getfloat() functions.

2. Basic writing configuration file

-add_section(section) Add a new section

-set(section, option, value ) To set the option in the section, you need to call write to write the content into the configuration file.

3. Basic example

test.conf

[sec_a] 
a_key1 = 20 
a_key2 = 10 
  
[sec_b] 
b_key1 = 121 
b_key2 = b_value2 
b_key3 = $r 
b_key4 = 127.0.0.1

parse_test_conf.py

import ConfigParser 
cf = ConfigParser.ConfigParser() 
#read config 
cf.read("test.conf") 
# return all section 
secs = cf.sections() 
print 'sections:', secs 
  
opts = cf.options("sec_a") 
print 'options:', opts 
  
kvs = cf.items("sec_a") 
print 'sec_a:', kvs 
  
#read by type 
str_val = cf.get("sec_a", "a_key1") 
int_val = cf.getint("sec_a", "a_key2") 
  
print "value for sec_a's a_key1:", str_val 
print "value for sec_a's a_key2:", int_val 
  
#write config 
#update value 
cf.set("sec_b", "b_key3", "new-$r") 
#set a new value 
cf.set("sec_b", "b_newkey", "new-value") 
#create a new section 
cf.add_section('a_new_section') 
cf.set('a_new_section', 'new_key', 'new_value') 
  
#write back to configure file 
cf.write(open("test.conf", "w"))

Get the terminal output:

sections: ['sec_b', 'sec_a'] 
options: ['a_key1', 'a_key2'] 
sec_a: [('a_key1', "i'm value"), ('a_key2', '22')] 
value for sec_a's a_key1: i'm value 
value for sec_a's a_key2: 22

Updated test.conf

[sec_b] 
b_newkey = new-value 
b_key4 = 127.0.0.1 
b_key1 = 121 
b_key2 = b_value2 
b_key3 = new-$r 
  
[sec_a] 
a_key1 = i'm value 
a_key2 = 22 
  
[a_new_section] 
new_key = new_value

4. Python’s ConfigParser Module defines three classes to operate on INI files. They are RawConfigParser, ConfigParser and SafeConfigParser respectively. RawCnfigParser is the most basic INI file reading class. ConfigParser and SafeConfigParser support the parsing of %(value)s variables.

Set the configuration file test2.conf

[portal] 
url = http://%(host)s:%(port)s/Portal 
host = localhost 
port = 8080

Use RawConfigParser:

import ConfigParser 
 
cf = ConfigParser.RawConfigParser() 
 
print "use RawConfigParser() read" 
cf.read("test2.conf") 
print cf.get("portal", "url") 
 
print "use RawConfigParser() write" 
cf.set("portal", "url2", "%(host)s:%(port)s") 
print cf.get("portal", "url2")

Get the terminal output:

use RawConfigParser() read 
http://%(host)s:%(port)s/Portal 
use RawConfigParser() write 
%(host)s:%(port)s

Use ConfigParser instead:

import ConfigParser 
 
cf = ConfigParser.ConfigParser() 
 
print "use ConfigParser() read" 
cf.read("test2.conf") 
print cf.get("portal", "url") 
 
print "use ConfigParser() write" 
cf.set("portal", "url2", "%(host)s:%(port)s") 
print cf.get("portal", "url2")

Get terminal output:

use ConfigParser() read 
http://localhost:8080/Portal 
use ConfigParser() write 
localhost:8080

Use SafeConfigParser instead:

import ConfigParser 
 
cf = ConfigParser.SafeConfigParser() 
 
print "use SafeConfigParser() read" 
cf.read("test2.conf") 
print cf.get("portal", "url") 
 
print "use SateConfigParser() write" 
cf.set("portal", "url2", "%(host)s:%(port)s") 
print cf.get("portal", "url2")

Get terminal output (the effect is the same as ConfigParser):

use SafeConfigParser() read 
http://localhost:8080/Portal 
use SateConfigParser() write 
localhost:8080

The above is the detailed content of Detailed explanation of Python's ConfigParser configuration file. For more information, please follow other related articles on the PHP Chinese website!

Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
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

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

SublimeText3 Linux new version

SublimeText3 Linux new version

SublimeText3 Linux latest version

Dreamweaver Mac version

Dreamweaver Mac version

Visual web development tools

ZendStudio 13.5.1 Mac

ZendStudio 13.5.1 Mac

Powerful PHP integrated development environment

SecLists

SecLists

SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)