search
HomeBackend DevelopmentPython TutorialDetailed introduction to Python command line parsing tool Argparse

Recently I am studying pathon’s command line parsing tool, argparse, which is a tool recommended in the Python standard library for writing command line programs.

I used to do UI programs. Today I tried the command line program. It feels very good. I don’t have to spend a lot of time studying interface problems, especially in vc++, which is particularly cumbersome.

Now we use python to implement the command line. For the core computing module, we can write our own extension library in c, and the effect is quite good.

I learned argparse, found an article toturial in the official documentation, and briefly translated it.

http://docs.python.org/2/howto/argparse.html#id1

Argparse Tutorial
This tutorial briefly introduces the commands recommended by the Python standard library. Row parameter parsing module - use of Argparse.

1. Basic concepts

In this tutorial, we use a common ls command to demonstrate the function of argparse.

$ ls
cpython devguide prog.py pypy rm-unused-function.patch
$ ls pypy
ctypes_configure demo dotviewer include lib_pypy lib-python ...
$ ls -l
total 20
drwxr-xr-x 19 wena wena 4096 Feb 18 18:51 cpython
drwxr-xr-x 4 wena wena 4096 Feb 8 12:04 devguide
-rwxr-xr-x 1 wena wena 535 Feb 19 00:05 prog.py
drwxr-xr-x 14 wena wena 4096 Feb 7 00:59 pypy
-rw-r--r-- 1 wena wena 741 Feb 18 01:01 rm-unused-function.patch
$ ls --help
Usage: ls [OPTION]... [FILE]...
List information about the FILEs (the current directory by default).
Sort entries alphabetically if none of -cftuvSUX nor --sort is specified.

From the above four commands, we can understand the following basic concepts:

1), the ls command has no parameters It can also be run, and by default prints out all the contents in the current directory.
2) If we want it to display more content, then we need to give it more parameters. In this case, we want to display a different directory, pypy. What we have done is specify the common positional argument, named so because the program needs to decide what to do based on the position of the argument in the command line. This concept is closer to the command cp. Its usage is cp src dest. src represents the file you want to copy, and dest represents where you want to copy the file.
3) Now, I want to change the behavior of the program. In our case, I want to display the westward information of the file instead of just the file name. The parameter -l is the optional argument we know (optinal argument)
4), and the last sentence is to display the help document. A snippet that you can use to learn how to use a command you've never used before.

2. Basic understanding

We start with a basic program (it does nothing)

import argparse
parser = argparse.ArgumentParser()
parser.parse_args()

Running results:

$ python prog.py
$ python prog.py --help
usage: prog.py [-h]

optional arguments:
 -h, --help show this help message and exit
$ python prog.py --verbose
usage: prog.py [-h]
prog.py: error: unrecognized arguments: --verbose
$ python prog.py foo
usage: prog.py [-h]
prog.py: error: unrecognized arguments: foo

Result analysis:

1) If you run this program without giving parameters, you will not get any result.
2) The second naming shows the benefits of using argparse. You did nothing but got a good help message.
3) We can get a good help message without manually setting the --help parameter. But if other parameters (such as foo) are given, an error will be generated.

3. Positional parameters

First, give an example:

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("echo")
args = parser.parse_args()
print args.echo

Running result:

$ python prog.py
usage: prog.py [-h] echo
prog.py: error: the following arguments are required: echo
$ python prog.py --help
usage: prog.py [-h] echo

positional arguments:
 echo

optional arguments:
 -h, --help show this help message and exit
$ python prog.py foo
foo

Result analysis:

This time, we added an add_argument() method to set the command line parameters acceptable to the program.
Now to run the program, you must set a parameter.
The parse_args() method actually returns some data from our command line parameters, in the above example it is echo
This "magic"-like process is automatically completed by argparse.
Although the automatically generated help information is beautifully displayed, we still cannot know what it does based only on the echo parameter. So, we added a few things to make it more useful.

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("echo", help="echo the string you use here")
args = parser.parse_args()
print args.echo

Run result:

$ python prog.py -h
usage: prog.py [-h] echo

positional arguments:
 echo    echo the string you use here

optional arguments:
 -h, --help show this help message and exit

On this basis, let’s make more changes One point: (calculate the square of the input parameter square)

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("square", help="display a square of a given number")
args = parser.parse_args()
print args.square**2

The following is the running result:

$ python prog.py 4
Traceback (most recent call last):
 File "prog.py", line 5, in <module>
  print args.square**2
TypeError: unsupported operand type(s) for ** or pow(): &#39;str&#39; and &#39;int&#39;

This program does not run correctly because argparse will treat the input as a string, so we need to set its type: (type=int)

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("square", help="display a square of a given number",
          type=int)
args = parser.parse_args()
print args.square**2

The following is the running result:

$ python prog.py 4
16
$ python prog.py four
usage: prog.py [-h] square
prog.py: error: argument square: invalid int value: &#39;four&#39;

Now, this program can run smoothly and can handle some incorrect inputs.

The above is a simple tutorial on using the Python command line parsing tool Argparse. I hope it will be helpful to everyone.

For more detailed introduction to the Python command line parsing tool Argparse and related articles, please pay attention to 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

MantisBT

MantisBT

Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

SAP NetWeaver Server Adapter for Eclipse

SAP NetWeaver Server Adapter for Eclipse

Integrate Eclipse with SAP NetWeaver application server.

MinGW - Minimalist GNU for Windows

MinGW - Minimalist GNU for Windows

This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.

PhpStorm Mac version

PhpStorm Mac version

The latest (2018.2.1) professional PHP integrated development tool

Atom editor mac version download

Atom editor mac version download

The most popular open source editor