Zxpy: A Python Shell Scripts Made Simple

zxpy

Shell scripts made simple 🐚

zxpy lets you seamlessly write shell commands inside Python code, to create readable and maintainable shell scripts.

Inspired by Google's zx, but made much simpler and more accessible using Python.

Rationale

Bash is cool, and it's extremely powerful when paired with linux coreutils and pipes. But apart from that, it's a whole another language to learn, and has a (comparatively) unintuitive syntax for things like conditionals and loops.

zxpy aims to supercharge bash by allowing you to write scripts in Python, but with native support for bash commands and pipes.

Let's use it to find all TODOs in one of my other projects, and format them into a table:

#! /usr/bin/env zxpy
todo_comments = ~"git grep -n TODO"
for todo in todo_comments.splitlines():
    filename, lineno, code = todo.split(':', 2)
    *_, comment = code.partition('TODO')
    print(f"{filename:40} on line {lineno:4}: {comment.lstrip(': ')}")

Running this, we get:

$ ./todo_check.py
README.md                                on line 154 : move this content somewhere more sensible.
instachat/lib/models/message.dart        on line 7   : rename to uuid
instachat/lib/models/update.dart         on line 13  : make int
instachat/lib/services/chat_service.dart on line 211 : error handling
server/api/api.go                        on line 94  : move these to /chat/@:address
server/api/user.go                       on line 80  : check for errors instead of relying on zero value

Writing something like this purely in bash or in Python would be much harder than this. Being able to use linux utilities seamlessly with a readable, general purpose language is what makes this a really powerful tool.

A larger, practical example

You can find a comparison between a practical-ish script written in bash and zxpy in EXAMPLE.md

Installation

pip install zxpy

pipx

If you have pipx installed, you can try out zxpy without installing it, by running:

pipx run zxpy

Basic Examples

Make a file script.py (The name and extension can be anything):

#! /usr/bin/env zxpy
~'echo Hello world!'

file_count = ~'ls -1 | wc -l'
print("file count is:", file_count)

And then run it:

$ chmod +x ./script.py

$ ./script.py
Hello world!
file count is: 3

Run >>> help('zx') in Python REPL to find out more ways to use zxpy.

A slightly more involved example: run_all_tests.py

#! /usr/bin/env zxpy
test_files = (~"find -name '*_test\.py'").splitlines()

for filename in test_files:
    try:
        print(f'Running {filename:.<50}', end='')
        output = ~f'python {filename}'  # variables in your shell commands :D
        assert output == ''
        print('Test passed!')
    except:
        print(f'Test failed.')

Output:

$ ./run_all_tests.py
Running ./tests/python_version_test.py....................Test failed.
Running ./tests/platform_test.py..........................Test passed!
Running ./tests/imports_test.py...........................Test passed!

More examples are in EXAMPLE.md, and in the examples folder.

stderr and return codes

To get stderr and return code information out of the shell command, there is an alternative way of invoking the shell.

To use it, just use 3 variables on the left side of your ~'...' shell string:

stdout, stderr, return_code = ~'echo hi'
print(stdout)       # hi
print(return_code)  # 0

More examples are in the examples folder.

Quoting

Take this shell command:

$ uname -a
Linux pop-os 5.11.0 [...] x86_64 GNU/Linux

Now take this piece of code:

>>> cmd = 'uname -a'
>>> ~f'{cmd}'
/bin/sh: 1: uname -a: not found

Why does this not work?

This is because uname -a was quoted into 'uname -a'. All values passed inside f-strings are automatically quoted to avoid shell injection.

To prevent quoting, the :raw format_spec can be used:

>>> cmd = 'uname -a'
>>> ~f'{cmd:raw}'
Linux pop-os 5.11.0 [...] x86_64 GNU/Linux

This disables quoting, and the command is run as-is as provided in the string.

Note that this shouldn't be used with external data, or this will expose you to shell injection.

Interactive mode

$ zxpy
zxpy shell
Python 3.8.5 (default, Jan 27 2021, 15:41:15)
[GCC 9.3.0]

>>> ~"ls | grep '\.py'"
__main__.py
setup.py
zx.py
>>>

Also works with path/to/python -m zx

It can also be used to start a zxpy session in an already running REPL. Simply do:

>>> import zx; zx.install()

and zxpy should be enabled in the existing session.

Development/Testing

To install from source, clone the repo, and do the following:

$ source ./venv/bin/activate  # Always use a virtualenv!
$ pip install -r requirements-dev.txt
Processing ./zxpy
[...]
Successfully installed zxpy-1.X.X
$ pytest  # runs tests

Download Details:
Author: tusharsadhwani
Source Code: https://github.com/tusharsadhwani/zxpy
License: MIT License

#python #shell 

What is GEEK

Buddha Community

How to Run bash scripts Using Python?

If you are using Linux, then you would definitely love the shell commands.

And if you are working with Python, then you may have tried to automate things. That’s a way to save time. You may also have some bash scripts to automate things.

Python is handy to write scripts than bash. And managing Python scripts are easy compared to bash scripts. You will find it difficult to maintain the bash scripts once it’s growing.

But what if you already have bash scripts that you want to run using Python?

Is there any way to execute the bash commands and scripts in Python?

Yeah, Python has a built-in module called subprocess which is used to execute the commands and scripts inside Python scripts. Let’s see how to execute bash commands and scripts in Python scripts in detail.

#development #python #how to run bash scripts using python #shell script from python #bash script #shell=

Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas. 

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities. 

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly. 

5 Reasons to Utilize Python for Programming Web Apps 

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks 

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions. 

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events. 

Simple to read and compose 

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building. 

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties. 

Utilized by the best 

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player. 

Massive community support 

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions. 

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking. 

Progressive applications 

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.

Summary

Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential. 

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

#python development services #python development company #python app development #python development #python in web development #python software development

Python Tricks Every Developer Should Know

Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?

In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.

Let’s get started

Swapping value in Python

Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead

>>> FirstName = "kalebu"
>>> LastName = "Jordan"
>>> FirstName, LastName = LastName, FirstName 
>>> print(FirstName, LastName)
('Jordan', 'kalebu')

#python #python-programming #python3 #python-tutorials #learn-python #python-tips #python-skills #python-development

How to Remove all Duplicate Files on your Drive via Python

Today you’re going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates.

Intro

In many situations you may find yourself having duplicates files on your disk and but when it comes to tracking and checking them manually it can tedious.

Heres a solution

Instead of tracking throughout your disk to see if there is a duplicate, you can automate the process using coding, by writing a program to recursively track through the disk and remove all the found duplicates and that’s what this article is about.

But How do we do it?

If we were to read the whole file and then compare it to the rest of the files recursively through the given directory it will take a very long time, then how do we do it?

The answer is hashing, with hashing can generate a given string of letters and numbers which act as the identity of a given file and if we find any other file with the same identity we gonna delete it.

There’s a variety of hashing algorithms out there such as

• md5
• sha1
• sha224, sha256, sha384 and sha512

#python-programming #python-tutorials #learn-python #python-project #python3 #python #python-skills #python-tips

How To Compare Tesla and Ford Company By Using Magic Methods in Python

Magic Methods are the special methods which gives us the ability to access built in syntactical features such as ‘<’, ‘>’, ‘==’, ‘+’ etc…

You must have worked with such methods without knowing them to be as magic methods. Magic methods can be identified with their names which start with __ and ends with __ like init, call, str etc. These methods are also called Dunder Methods, because of their name starting and ending with Double Underscore (Dunder).

Now there are a number of such special methods, which you might have come across too, in Python. We will just be taking an example of a few of them to understand how they work and how we can use them.

1. init

class AnyClass:
    def __init__():
        print("Init called on its own")
obj = AnyClass()

The first example is _init, _and as the name suggests, it is used for initializing objects. Init method is called on its own, ie. whenever an object is created for the class, the init method is called on its own.

The output of the above code will be given below. Note how we did not call the init method and it got invoked as we created an object for class AnyClass.

Init called on its own

2. add

Let’s move to some other example, add gives us the ability to access the built in syntax feature of the character +. Let’s see how,

class AnyClass:
    def __init__(self, var):
        self.some_var = var
    def __add__(self, other_obj):
        print("Calling the add method")
        return self.some_var + other_obj.some_var
obj1 = AnyClass(5)
obj2 = AnyClass(6)
obj1 + obj2

#python3 #python #python-programming #python-web-development #python-tutorials #python-top-story #python-tips #learn-python