This regex cheat sheet is based on Python 3’s documentation on regular expressions. If you’re interested in learning Python, we have free-to-start interactive Beginner and Intermediate Python programming courses you should check out. Regular Expressions for Data Science (PDF) Download the regex cheat sheet here. Python Cheat Sheet: Python is a multi-paradigm general-purpose, object-oriented programming languageIt is a cross-platform programming language.
Overview
Interpreted programming language developed in late 80s inspired by ABC language.Extensibility is one of its major features. Libraries such as Scapy and Requests unlock Python's potential.Basic Python scripts are fast to write and many libraries support easy creation of HTTP requests, parsing of responsesMany tools are written in Python.It is widely available and is installed natively on macOS, most Linux distributions, annd some UNIX systems.Python is easy to installed, and you can check version with python -vPython requires consistent indentation, using 2 or 4 spaces is common. Tab should be avoided.Python 2 versus Python 3
Python 2.x is legacy, Python 3.x is the present and future. The final major release of Python 2.7 was in 2010.Python 2 is still the default version on macOS and Linux, though Python 3 is often included by called 'Python 3'Python 3 Features
Major improvement is better Unicode support, all test strings being Unicode by defaultClean Unicode/byte separationException chainingFunction annotationsSyntax for keyword-only argumentsExtended tuple unpackingNon-local variable delcarationsOther changes include print and exec being statements and integers using floor division.Data Types and Syntax
Stringvar='string'
Python Programming Language Cheat Sheet
Booleanvar=TrueIntegervar=86Floatvar=3.14159if/elif/elseconditional execution of functionsinput( )returns a string by defaultint( )changes a string to an integerBoolean operatorsand, or, not as well as comparison operators ( <, <=, >, >=< )for loopsiterates through a setwhile loopsiterates until a condition metLists and Dictionaries
Lists are fundamental data structure they contain an ordered list of data.**list = ['thing1', 'thing2', 'thing3']Dictionaries are similar to lists but they are unordered key: value pairs.
**dictionary = {'key': 'value'}
In other languages, dictionaries are known as associative arrays or hashes.Web Libraries
urlliburllib2 - It can perform basic authentication, it does not handle underlying details like base-64 encoding or authorization headers. Python 3 splits functionality into urllib.request and urllib.errorurllib3httplib - Python 3 renamed this http.clienthttplib2Requests developed with a number of PEP 20 idioms in mindPEP= Python Enhancement ProposalsPEP 20 are 'The Zen of Python'
Requests follows:
1. Beautiful is better than ugly
2. Explicit is better than implicit
3. Simple is better than complex
4. Complex is better than complicated
5. Readability counts.
Requests
Abstracts many lower-level details.Supports multiple authentication methods: Basic, Digest, Kerberos, NTLM, AWS, OAuth1Supports POST with options sent via a dictionary called 'data' in {'variable': 'value'}; multiple variables can be passedRequests can also POST data from a file.Handles TLS/SSL transparently verifying x.509 certificates by default (verify=True) and will exit if it is invalid. To connec tot a site with an invalid certificate by setting verify=False.r=requests.get('https://'invalid.cert', verify=False)
print=(r.text)Example of Post script:
#! /usr/bin/python3
import requests
r=requests.post('http://security.com/form_auth/login.php', data={'user': 'admin', 'pass': 'admin', 'button': 'Login'})
Python Cheat Sheet Download
print(r.text)Hey Finxters! I have another set of cheat sheets for you! This time, I am going to focus on the more advanced aspects of Python and what you can do with it! As you know Python is a flexible language used in web development, games, and desktop applications. I am not going to waste too much of your time so let’s hop right to it and dive into these more advanced Python cheat sheets!
Cheat Sheet 0: Finxter Full Cheat Sheet Course
Cheat Sheet 1: DataQuest
This cheat sheet is from DataQuest and it shows all of the intermediate Python
Regular expressions, date/time module, and counter. This is one you will want to have pinned to the wall or in your developers binder to keep handy as you work.
Pros: Great for budding Python developers, keep it handy as you work.
Cons: None that I can see.
Cheat Sheet 2: DataCamp
It is important to know how to import data during your career no matter what stage you are at. As an intermediate Pythoner, you should keep this cheat sheet handy when working an entry level job of data entry and developing you own projects.
Pros: Great for learning importing data sets in Python.
Cons: None that I can see.
Cheat Sheet 3: DataCamp
You have to import data and you have to be able to plot it as a visual representation for businesses to understand and use to their benefit. This cheat sheet will help you to learn matplotlib and write some amazing graphical visualizations with Python.
Pros: Great to have for matplotlib development.
Cons: None that I can see.
Cheat Sheet 4: GitHub
This cheat sheet is for Machine learning and one you will want to keep in your developers binder as you work. Machine learning and Python go together like peanut butter and jelly, and Scikit is going to be your best friend. If your developers journey takes you to machine learning then make sure to keep this cheat handy for yourself.
Pros: Scikit is easily learnable with this cheat sheet
Cons: None that I can see.
Cheat Sheet 5: DataCamp
SQL is a database system used in programming for all kinds of data sets and is extremely scalable. Keep this cheat sheet handy to you! BI and other business applications rely on you being able to use SQL!
Pros: Rated ‘E’ for everyone. Easy to read and implement
Cons: None that I can see.
Cheat Sheet 6: Pytorch
This cheat sheet is more a tutorial that will teach you pytorch for deep learning projects. Here you will get hands on practice on pytorch.
Pros: You will get a deep understanding pytorch and how it used
Cons: It is an online tutorial.
Cheat Sheet 7: DataCamp
Yet another from Datacamp!! This one is called SpaCy and allows you to understand the natural text from documents. This is one I have in my development folder and is used for Natural language programming.
Pros: Rated ‘E’ for everyone.
Cons: None that I can see.
Cheat Sheet 8: Ask Python
This cheat sheet is also more a tutorial for you to learn image processing in Python. The best way to learn is to get your hands dirty! Ask Python is good for doing that so you can learn what you need to and boost your skills.
Pros: Rated ‘E’ for everyone.
Cons: None that I can see.
Cheat Sheet 9: TutorialsPoint
This cheat sheet is also a tutorial on learning database access with Python. This is an incredibly important skill when you freelance your skills or end up working for a company at a data entry position.
Pros: Rated ‘E’ for everyone. This tutorial is one I have used myself! It includes code snippets to learn from.
Cons: It is a tutorial, not a cheat sheet to print.
Cheat Sheet 10: FullStack Python
This is also a tutorial for you to learn from. This particular cheat sheet discusses Deployment of web applications in Python!! It has explanations that go into depth with tools, resources and learning checklist which is started off with an introductory on deployment what it is and why it is necessary.
Pros: Rated ‘E’ for everyone. This is important to know if you are a Pythoner in Web development.
Python Programming Cheat Sheet Pdf
Cons: Needs to be bookmarked on your browser.
These are the cheat sheets and tutorials I think you will find helpful as a Pythonista developing in your particular field. As you can see this time, I wanted to really give you a wide berth of cheat sheets that intermediate Pythonista use with their career choices. I hope at least one of these cheat sheets or tutorials is useful to you on your journey! Thank you once again for joining me and I can’t wait to see you again! 😉😉
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