From teaching thousands of freelancer students, we know that many freelance developers fear that unhappy clients come after their personal assets. Everyone makes mistake and these mistakes can become quite costly when submitting freelance work to a client.

You may wonder: Can you protect against unlimited liability risks?

Glad you asked.

While liability insurance covers some use cases, f you are serious about running about having an online Python business, you should also consider becoming a Limited Liability Company. Getting your LLC is beneficial to protecting yourself and your up-and-coming business. One of the benefits is its flexibility, supporting either a sole proprietorship partnership or a corporation. I want to give you the best LLC Service online for you to get started with.

DISCLAIMER: We’re programmers not lawyers or tax accountants. Please don’t take this as professional advice. We just share some services we found valuable—but that doesn’t mean that they must be valuable for you under any circumstance.

So, I would like to introduce to you a few of the best LLC formation services you can use for your upcoming business. You can use these services to help get you started in protecting yourself and keep your business compliant while some of these websites have as little as $0+ to $49+ for the state fees, which will help you cover everything that you need for your business. You can often go online and find plenty of online services which will help you file the correct documentation you need.

Any business you are looking to create, needs you to have a registered agent, a DBA, and an EIN as a part of your business, though there is much more we did not cover here. Including, a business email account and an accounting and bookkeeping application like Quickbooks to keep track of invoices and purchases made for your business. This will help you keep your affairs in order so you can take care of clients and leads as you work on your projects and work. You can form an LLC in any state you wish and can find a sitemap for.

GovDocFiling

• Price: $345 for the full package.
• Ratings: 4.7 (Excellent)

A trustworthy, professional service for creation of your LLC as a freelance developer. Here are some benefits of their LLC creation service:

• Low-fee federal and state filing
• LLC Operating Agreement
• Essential legal documents for your LLC
• Business guide to help you save up to $3,000

GovDocFiling provides an introductory video:

You can check it out here in our partner link:

If you want a simple and price-efficient solution with high customer satisfaction scores, GovDocFiling may be just the service you’ve been looking for.

Zenbusiness

• Price: Between $49 and $299 billed annually.
• Ratings: 4.8 (Excellent)

One of the most top-rated LLC formations services as a top LLC choice is Zenbusiness. It gives small businesses and sole proprietors the ability to live out their dreams. They primarily focus on woman or minority owned businesses to encourage more growth in the community. It offers 3 different plans to help you get started. One of the cons to this particular website is it does not support corporation filing until after 30 days. This is a great place to start if you are serious about your Python freelancing. I have also posted a link below that lists 7 service sites where you can obtain an LLC. Use this link to help you find some of the greatest LLC services to help entrepreneurs the opportunity to create a business with a corporation.

MyCorporation.com

• Price: Between $99 and $324 plus state fees.
• Ratings: 4.4 (Excellent)

This is a great choice for LLC formation for freelance developers because it focuses on small businesses. Here’s a screenshot of the pricing page:

LegalZoom

• Price: Starts from $79 plus states fees.
• Ratings: 4.1 (Great)

A trusted partner in creating your own freelancing business (LLC) that has already served millions of small and medium business owners like you:

Conclusion

I want to thank you for coming with me to this little article. It is important to form an LLC so you can protect yourself against bad clients. If you don’t already have one, create a business work email, get an accounting app and you will get lifetime expert business support and services. Put together an outline of what you would like your business to accomplish and see if you can’t find a plan that best fits you. I hope you find my list worthwhile as the top seven and that you will be able to use it on your developer’s journey as you continue to grow your Python business freelancing.

References

• https://www.govdocfiling.com/llc/
• https://top10legalservices.com/top/form-an-llc/
• https://www.legalzoom.com/business/business-formation/llc-overview.html
• LLC – Why create one as a freelance developer?

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Cheat Sheet 1: Visual Studio

Straight from the source of Visual Studio, this cheat sheet is specifically designed with all of the shortcuts for Windows users. Rejoice if you use Windows like I do. You can print this cheat sheet and pin it to the wall or place it in your developers binder.

Pros: Perfect cheat sheet to have, all shortcuts are available

Cons: Designed specifically for Windows.

Cheat Sheet 2: ShortcutFoo

Bookmark this cheat sheet from Shortcut Foo. It has all of your shortcuts listed and this is a great way to test yourself on learning the keyboard commands through finger muscle repetition.

Pros: Rated ‘E’ for everyone.

Cons: Does not print.

Cheat Sheet 3: Devhint.io

This cheat sheet is written by Rico, a fellow developer like us! He has a modest collection of cheat sheets he has written. This cheat sheet should be bookmarked and is written for VS code ver. 1.19

Pros: Rated ‘E’ for everyone.

Cons: Doesn’t print, is for an older version of VS Code.

Cheat Sheet 4: Visual Studio

This cheat sheet is also from Visual Studio like the first however this cheat sheet is designed for Linux users! Keep it on hand when you are working in VS Code. Print it and pin it to the wall behind the monitor

Pros: Perfect for Linux users with all keyboard shortcuts shown

Cons: Designed for specifically for Linux

Cheat Sheet 5: Visual Studio

Final one from Visual Studio! This cheat sheet is for Mac users. I really wanted to make sure all OS systems are covered so how could I forget the Mac users? Print this sheet and pin it to the wall or in you developers binder to keep it handy

Pros: Perfect for Mac users with all keyboard shortcuts shown.

Cons: Designed for Mac specifically.

Cheat Sheet 6: Log Rocket

Here is another cheat sheet that you can print from Log Rocket, a front-end monitoring company. This cheat sheet is for Windows, and contains the short cuts you will need to work the keyboard shortcuts.

Pros: Rated ‘E’ for everyone

Cons: None that I can see.

Cheat Sheet 7: GitTower

Git Tower has a two sheet pdf cheat sheet for the Mac Edition OS. It takes the time to explain the terminal, editor splits and keyboard shortcut preferences. This cheat sheet is really useful for Mac OS Users.

Pros: Gives explanations and infographics.

Cons: Written for Mac Operating Systems

Cheat Sheet 8: MakeUseOf

This cheat sheet is made for Windows OS and even has a free download available that is sent straight to your inbox. Print it and keep it close at hand when you go to work in Python using VS Code.

Pros: Free download straight to you inbox on useful information.

Cons: None that I can see.

Cheat Sheet 9: Kapeli

This cheat sheet is written for Mac OS for Apple users. The cheat sheet does not print but it does have everything you need from VS Code and it keyboard shortcuts on a Mac computer.

Pros: Great for Mac users.

Cons: Does not print.

Cheat Sheet 10: Arunkumar

This cheat is one that you will want to bookmark!! By far, the most comprehensive cheat sheet with shortcuts for all 3 main OS systems( Windows, Linux, Mac) it includes a quick guide to changing the keyboard shortcuts with visuals.

Pros: Rated ‘E’ for everyone. The best one by far

Cons: Does not print. Other than that, none that I can see.

I hope that these cheat sheets will be useful to you on your Python Freelance Journey. These cheat sheets cover the 3 main OS systems, most of which you can print and keep on hand as you work projects in VS Code. If you are unsure on where to start, I would humbly suggest VS Code website itself. All of the documentation is there for you to get an in depth look into VS Code as an IDE. Click the link below for a deeper look into Visual Studio Code.

Tutorial: https://code.visualstudio.com/docs/introvideos/basics

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Full PyCharm Tutorial Finxter

The Finxter tutorial contains a multi-site PyCharm introduction with video courses.

Cheat Sheet 1:  JetBrains

This cheat sheet is one you will want to save in your bookmarks! It will show you all the shortcuts you need to get Pycharm working for you! JetBrains is the place to go if you want to learn PyCharm and Python!

Pros: Rated ‘E’ for everyone. Honestly! This is a great place to start!

Cons: Can’t be printed, but honestly worth bookmarking.

Cheat Sheet 2: Cheatography

This is a cheat sheet that you can print and pin to the wall for Pycharm! This cheat sheet follows the 80/20 rule we love at Finxter! You’ll be able to learn Pycharms shortcuts quickly with this cheat sheet up on the wall.

Pros: Follows the 80/20 rule!

Cons:  None that I can see.

Cheat Sheet 3: TutorialsPoint

This cheat sheet will guide you through Pycharm. From installation to Django. You will learn everything that you need to learn including shortcuts, writing HTML and CSS integration and Javascript support. Read all of it in one go or read the section that you need when you need it. You can either bookmark the pdf page or print it to save in your developers binder to keep on hand when you’re working.

Pros: Perfect for introducing and going in depth with Pycharm

Cons: None that I can see.

Cheat Sheet 4: ShortcutFoo

ShortcutFoo has a list of shortcuts made for Pycharm on debugging and editing, navigation and refactoring. You should bookmark this page and keep it handy online when you work in Pycharm.

Pros: ShortcutFoo will show how to work with these shortcuts and train you in them.

Cons: None that I can see.

Cheat Sheet 5: RealPython

This is more an online guide than a cheat sheet that you can learn Pycharm from.  You can build, debug, edit, and test. This guide even dives deeper into the database support and scientific mode.

Pros: Deep dives into Pycharm includes a professional module

Cons: Not an actual cheat sheet to download.

Cheat Sheet 6: ShortCut World

Another quick sheet for you to learn shortcuts from when you’re using Pycharm! This is presented by JetBrains! I would suggest bookmarking for your developers binder when you are working in Pycharm.

Pros: Quick guide into shortcuts

Cons: Does not download as a pdf

Cheat Sheet 7: pngkey

Here is another cheat sheet that you will be able to print after downloading it. It will give you all the shorthand you can use on your keyboard for Pycharm.

Pros: Great for pinning to the wall or in the Developers journal

Cons: None that I can see.

Cheat Sheet 8: AugmentedMinds

This cheat sheet is presented by Augmented Minds and is combined with an article that will help boost productivity in developing software in Pycharm

Pros: This cheat sheet is presented with an article.

Cons: None that I can see.

Cheat Sheet 9: AWS

This is another tutorial presented by Amazon through its AWS. It will go over the development endpoint in Pycharm.

Pros: Shows you how to Pycharm Professionally

Cons: Is not a cheat sheet that can be printed.

Cheat Sheet 10: Edureka

This is the final tutorial instead of a cheat sheet for you to learn Pycharm and all of the shortcuts there at the bottom of the tutorial. This tutorial will help you download Pycharm and teach you important tools and features.

Pros: It will go over Python and Pycharm.

Cons: None that I can see.

Python and Pycharm are very powerful when used together. These cheat sheet and tutorials, I hope will help you in learning Pycharm, its shortcuts, and master it! With that being said I want to leave you with a pdf book from this github repository link posted below. It will help you master pycharm! Keep Pythoning and Keep on developing!!

Bonus Resource

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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.

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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Cheat Sheet 1: Devhints.io

This cheat sheet is written by a developer by the name of Rico. His collection of cheat sheets is extensively modest. This is one I would keep in a folder in my bookmarks online! This cheat sheet goes over GoLangs syntax, functions, and flow control. This cheat sheet also includes official resources and other links to give you more information on GoLang.

Pros: Great for beginners learning Go, or if you need a quick syntax lookup.

Cons: It is a website cheat sheet.

Cheat Sheet 2: Cheat-Sheet.org

This cheat sheet is printable and will take through basic syntax to more advanced functions and methods using code examples. It does have the link to A Tour of Go which is an excellent introduction to GoLang.

Pros: Gives a very generous overview of GoLang language

Cons: Minimal explanations on what is happening in the code.

Cheat Sheet 3: Simplecheatsheet.com

This cheat sheet will help you download the Go Archive and install them on 4 different OS modules. It contains tables for keywords, data types, variables and others. It also includes Go code examples and step-by-step explanations.

Pros: Perfect for beginners.

Cons: Keep it bookmarked, it isn’t printable.

Cheat Sheet 4: Cheatograph

This cheat sheet will show you GoLang and its syntax including examples and code snippets for Go. It has a brief introduction on how it came to be. This one is downloadable to print, then pin to the wall or keep it in your programmers binder like I do.

Pros: Perfect for beginners since it includes simple examples.

Cons:  None that I can see.

Cheat Sheet 5: GitHub

Always from Github can you find amazing things including cheat sheets! This cheat sheet is one you can download and print. Keep it near in hand when you need to program in Go.

Pros: Perfect for reference on functions and syntax.

Cons: Minimal explanations on what the function does.

Cheat Sheet 6: Programming-idioms.org

This cheat sheet will get you rocking and rolling on Go and its syntax. On the left, it has the explanations of the code example on the right. You will be able to get yourself up and running in Go in no time. You can print it in landscape mode or bookmark the page.

Pros: Perfect for beginners.

Cons: None that I can see.

Cheat Sheet 7: Comparitech

This cheat sheet will walk through network programming in Go! How cool is that? It will show you the basics, TCP socket programming, AWS Function Lambda function hander and bucket list examples in Go.

Pros: Perfect for beginners to Go.

Cons: None that I can see.

Cheat Sheet 8: Medium

These 4 cheat sheets will make it easy for you to work in GoLang as it touches all of the syntax and formatting. These cheat sheets will be perfect for saving to the desktop, printing and pinning to the wall or keep in your developers binder.

Pros: Perfect reference for beginners.

Cons: These are pictures that will need to be saved to your computer if you want to print them.

Cheat Sheet 9: Guru99

This is more a tutorial with a cheat sheet at the very bottom but it will take you through the basics of Go, file creation and much more. This is a great place to start if you want to learn Go as a programming language.

Pros: Perfect for beginners wanting to learn Go

Cons: The actual cheat sheet is at the bottom of the tutorial.

Cheat Sheet 10: Programming.guide

This cheat sheet should be bookmarked since it is a string functions reference card for Go.

Pros: Perfect reference card for Go and all it has to offer.

Cons: The only thing wrong is you can’t print it!

That is it! Those are the cheat sheets (some with tutorials) that I have found to be the best for GoLang. Go is a simple language to learn and a statically typed language. It has the capability to write dynamically but it is best used for scripting, where Python (the wonderful language that it is), is more like a swiss army knife you keep in your pocket to do all kinds of jobs you need to get done. Get yourself up and running with Go and add this language secondary to Python.

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Cheat Sheet 1: Cheatography

This cheat sheet was written by thatguyandy27 on Cheatography. It is separated into different modules, gives clear example code and quick explanation. This pdf is worth hanging on your wall or placed in your developer binder.

Pros: Rated ‘E’ for everyone. This is a great place to start.

Cons: It says it is still in draft form. There could be future updates.

Cheat Sheet 2: GitHub

This cheat sheet is found on Github! A great place for a developer to find really useful information and build a portfolio! This cheat sheet is a condensed version of everything you need to know for OpenCV in Python! It is packed with tons of great information and one you should most definitely have on the wall!

Pros: Rated ‘E’ for everyone.

Cons: It is a super dense cheat sheet.

Cheat Sheet 3: AIM

This cheat sheet specifically focuses on blurring an image using three types: Gaussian, Bilateral and Median blurs. This cheat focuses on the code with a photo at the bottom to show the output of each different method.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Cheat Sheet 4: HeartBeat Fritz

This cheat sheet explains OpenCV from installation to face detection and distorting. All explained in one sheet. You will learn valuable skills along the way for OpenCV in Python. Great for the beginner and refresher.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Cheat Sheet 5: Alver Valley Software Limited

This cheat sheet has code snippets with quick explanations on what each snippet does in the program. It is a very light read and is solely focused on the code used in OpenCv

Pros: Rated ‘E’ for everyone.

Cons: Written for C++, so you will need to import C into you python program.

Cheat Sheet 6: Read the Docs

Here you will learn the core operations of GUI features, image processing and so much from this cheat. It will show you code and give you an explanation on opencv in python

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Cheat Sheet 7: Analytics Vidhya

This cheat sheet dives right into installing the correct libraries you are going to need for you program, including a virtual environment. Code snippets, and examples are clear and well written for you to learn from when working with OpenCV

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Cheat Sheet 8: OverAPI

This cheat sheet will be one you can hang on the walls. It will take you from the very beginning until the last module. It has good explanation to the code snippets.

Pros: Rated ‘E’ for everyone

Cons: It is written C++

Cheat Sheet 9: Coding for Entrepreneurs

Here on this cheat sheet, you can learn to Learn to create a REST API microservice for extracting faces from images using OpenCV, OpenCV-python, Flask, Docker, and Heroku.

Pros: Rated ‘E’ for everyone

Cons: None that I can see.

Cheat Sheet 10: jeh-tech

This cheat sheet was written by a fellow developer online! He has placed in notes and code using Python in OpenCV. He has clear explanations and graphics with his code.

Pros: Rated ‘E’ for everyone

Cons: None that I can see.

So as you can see OpenCV has a ton of material you can use to create your own machine learning models that can use OpenCV and know the difference between an apple and an orange! And hey guess what? You have learned a new skill! That’s even cooler right? As a thank you for coming with me on this fantastic journey I have included BONUS OpenCV Material!! Nothing is better than having a bonus!! It’s like an extra present under the tree! This website will help you dive even deeper into what OpenCV is and what you can do with it! You’ll be able to master the open source library in Python in no time using this website! Maybe even a niche for your Python Freelancing? (Did I just give you a clue? ?) Enjoy and again thanks for joining me.

Check out Bonus

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Tutorial 1: Real Python

Real Python is the place to go for tutorials on Python of all kinds! This Requests tutorial will take you over installation and the other methods of Requests including checking authentication and inspecting your requests.

Pros: Perfect for the beginner learning the Requests Library.

Cons: None that I can see.

Tutorial 2: Hartley Brody

This tutorial was written for beginners but it could also be used for the developer who needs a refresher on the Requests Library. It goes over the basics and includes code snippets for you to use for practice.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Tutorial 3: Read the Docs

This tutorial goes in depth in Requests by starting with some background on requests then goes over a step by step tutorial on how to get the most out of the Requests library.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Tutorial 4: Edureka!

This tutorial focuses on the get() and post() methods from Request. You will learn how to not only call these but also how to handle images, insert headers and cookies into a request and learn about session objects.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Tutorial 5: Digital Ocean

This tutorial was created by Digital Ocean to give an overview of requests and what can be done with it. In this tutorial, you can learn about status codes and use the requests library to translate API error cases.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Tutorial 6: Python for Beginners

This Python tutorial on requests is straightforward and simple in that in goes over what can be done with this library and how. By the end of this tutorial, you will have enough basic knowledge to scrape the web yourself.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Tutorial 7: Tutorials Point

Tutorials Point is another great site for learning Python and its libraries.Here you can go slowly through each aspect of learning requests in-depth. It is perfect for the beginner and the advanced developer.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Tutorial 8: Geeks for Geeks

This tutorial will also take you through the basics of the requests library. You’ll learn authentication using python requests, SSL certificate authentication and session objects

Pros: Rated ‘E’ for everyone

Cons: None that I can see.

Tutorial 9: DataCamp

DataCamp is another source to learn the Requests Library from. Here you will learn HTTPs requests and how they work in Python. You’ll let the get() function and downloading images.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Tutorial 10: W3Schools

W3Schools is the perfect place to learn Python and its libraries. In this module you will learn to download, install and the methods in Requests.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

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So, I have found the top 10 Python math cheat sheets for you to pin to your wall as you develop! We only have 10, but there is a lot to cover! Without further ado, let us dive right into it!

Cheat Sheet 1: SquareSpace

This cheat sheet has everything you need to learn probability and the formulas. I would keep this handy as you are writing your ML models.

Pros: Nicely written with explanations on each formula.

Cons: Not for the beginner ML developer.

Cheat Sheet 2: MiniReference

This cheat sheet will take you through understanding linear algebra, opening the gateway to the study of higher mathematics. This 4 page pdf is an excerpt from the No Bullshit Guide to Linear Algebra. It will give you everything you need to know on the subject.

Pros: Rated ‘E’ for everyone!

Cons: None that I can see.

Cheat Sheet 3: MIT

This pdf from MIT teaches you about statistics. This is a super important pdf for those of you looking to become Data Scientists. Keep it handy in a notebook to pull out when writing your programs.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Cheat Sheet 4: LIMSI

This cheat sheet uses the 80/20 principle and touches base on everything you need to know for python. The maths module is one you should pay close attention to and highlight as it will help you when using math in Python.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Cheat Sheet 5: ReadtheDocs.org

This pdf is one you will want to keep in the binder on the desk and keep it handy. This is material for an introductory Python course for first year undergraduate Mathematics students at the University of Southampton as it goes over certain aspects you learn in Python and mathematics, including using these particular notes, Spyder.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Cheat Sheet 6: Cheatography

This cheat sheet has a list of Python functions from file handling to math. This cheat sheet is nice to keep handy!

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Cheat Sheet 7: Finxter

Who could forget Finxter in all of these cheat sheets? This is an ultimate guide on the math module!! If you want to know Python and the Math module this is the place to go!

Pros: Rated ‘E’ for everyone!

Cons: None that I can see!!

Cheat Sheet 8: Data Quest

Numpy is used in Python in support of the math module. The numpy functions are used in statistics, vector and scalar math. Shorthand functions are your best friend when you don’t need to write out the functions.

Pros: Rated ‘E’ for everyone!

Cons: None that I can see.

Cheat Sheet 9: DataCamp

Scikit is another library of Python for machine learning. In this cheat sheet you will use predictions, regression and clustering metrics alongside the math module to give you what you want when building your supervised/unsupervised machine learning algorithms.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Cheat Sheet 10: DataCamp

This cheat sheet is all about Scipy and the linear algebra used for its functions in Python. Scipy was built as an extension of Numpy allowing you to interact with it. You should keep this one available pinned to the wall.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

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Problem Formulation: How to iterate over a generator twice?

Then we will look at three solutions on how we can iterate twice, or even multiple times, over a generator or iterator.

First, we must understand that a generator in python is a special routine that can be used to control the iteration behaviour of a loop.

In this article we are going to focus on the itertool module and the various ways it is used in the real world. This module is preinstalled in Python so we only need to import it. We will be looking closely at itertools.repeat(), itertool.count and itertools.product. Each one of these generate different ways that we can iterate through a list, tuple or dictionary.

Method 1

In this first example, we are going to use the itertools.repeat() and how it is used in iteration. itertools.repeat() makes an iterator that returns an object over and over again. 

It runs indefinitely unless the times argument is specified. It is used as an argument to map() for invariant parameters to the called function. It can also be used with zip() to create an invariant part of a tuple record. This makes it invaluable for what we are about to do.

Take a look at the code below:

def repeat(object, times=None):
    # repeat(10, 3) --> 10 10 10
    if times is None:
        while True:
            yield object
    else:
        for i in range(times):
            yield object

list(map(pow, range(10), repeat(2)))
[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

Above, I have defined two arguments inside the definition of repeat(object, times=None), given my if-else statement, asking repeat to see how many times I want to have it go over my object, and if I do not want anything to happen (None), it will yield that objects expression list back to me, in this case nothing or it will go over my object a number of times before it returns back to me a repeated object. I have called my solution inside of the above function that asks for a list of 10 numbers to their powers then repeated two times.

Method 2

The way it is written above does certainly look nice but it is also one that a beginner programmer would write. The following example will do what the above code example can but with less code for a truly pythonic code:

import itertools
squares = list(map(pow, range(10), itertools.repeat(2)))
print(squares)

The output is:

squares = [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

Those three lines represent the same code as above. Isn’t that amazing! We took less code to get the same results as the one above!

The left-to-right evaluation order of the iterables is guaranteed. This makes possible an idiom for clustering a data series into n-length groups using zip(*[iter(s)]*n). This repeats the same iterator n times so that each output tuple has the result of n calls to the iterator. This has the effect of dividing the input into n-length chunks. Since, I asked for 10 numbers with a repeat of 5 my output above is correct.

Method 3

Yet another example of using itertools.repeat() is:

import itertools

data = list(zip(range(10), itertools.repeat(5)))
print(data)

It returns an iterator of tuples where the number of iterables from list 1 is matched with list 2. The iterator stops when the shortest list is exhausted. So, the output to this code is:

data = [ (0,5),
	 (1,5),
	 (2,5),
	 (3,5),
	 (4,5),
	 (5,5),
	 (6,5),
	 (7,5),
	 (8,5),
         (9,5)]

This method is used if you would like to have a repeat of a particular value or have an invariant part of a tuple record.

Conclusion

As we can see, itertools is an important tool to use if we want to create repeats with a generator in Python. We can create squares as we saw above in two different methods and we can zip together two lists with an invariant value and print the output.

Python has many tools that can make it easier to do your work on a daily basis. From creating a record and squares using a map() function. We are able to do this with Python in a short amount of code and make it simple. I encourage you to read Python’s official documentation and practice around a little bit playing with itertools until you are comfortable with using it in your programming.

Thank you for joining me on this journey of itertools.repeat(). There are a ton of other tools you can use in place of repeat(). Though I would be careful! Some of these methods can only be used once in a program so you need to be careful when using them! Others will repeat indefinitely unless told otherwise! Carefully review which one would fit your application the best then use that method. This takes a little trial and error but it will make you a better Python programmer in the end!

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Cheat Sheet 1: DataCamp

The first cheat sheet is from DataCamp.com and is chock full of information for you to consume. You will learn to interact with Numpy and know which functions and methods to use for linear algebra and of course a help section. This is one I would hang behind my monitor behind the wall!

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Cheat Sheet 2: Quandl

This cheat sheet covers the three main data science libraries used in Python: Pandas, Numpy, and Scipy. It goes over the functions call but has explanations on each one. Near the end it shows how to import data sets for you to use! Great for a beginner project!

Pros: Rated ‘E’ for everyone. Bonus Python project included!

Cons: None that I can see.

Cheat Sheet 3: Elite Data Science

This cheat sheet will walk you through some of the most common and useful functionality from these libraries. From importing data to a taste of Machine learning you can get a feel of what Python can do of the code examples.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Cheat Sheet 4: Cheatography

If you ever needed help understanding how to test a hypothesis in Scipy using code examples and clear explanations on what is happening when you write the code.

Pros: Rated ‘E’ for everyone.

Cons: None that I can see.

Cheat Sheet 5: Intellipaat

This cheat sheet is more a tutorial from Intellipaat.com It has full explanations with code examples to work. It has sufficient information about the scientific and technical library in Python, that is, Scipy. Nonetheless, it is more than worth your time to investigate and learn Scipy.

Pros: Rated ‘E’ for everyone.

Cons: It is more a tutorial than a cheat sheet.

Cheat Sheet 6: Scipy.org

From the mouth of Scipy, this cheat sheet will show you all of the methods needed to perform different functions in Scipy and Python with explanations. This Comprehensive list has everything sorted neatly into the different functions to make it easy to look up as you are working in Scipy. This is one you will want in your notebook on the desk as an easy reference guide.

Pros: Rated ‘E’ for everyone. Recommended for the wall or notebook for daily use!

Cons: None that I can see.

Cheat Sheet 7: Packt>

This is more a book than it is a cheat sheet. It focuses hard on mastering scipy giving you a project to work through so you can really get a grasp on Scipy and how it is implemented in Python. I recommend subscribing to the website for all of the information you will receive.

Pros: Rated ‘E’ for everyone.

Cons: It is an ebook not a cheat sheet, but worth your time.

Cheat Sheet 8: Scipy.org

This is another ebook that I recommend keeping on hand to learn Scipy from beginner levels to advanced. This book contains code for you to work on in order to learn scipy in python building your skills. This is important for you to learn the skill you need for your data science career. I suggest reading the book, highlight the parts you don’t understand and print the code example to pin to the wall for help and minimize searching.

Pros: Rated ‘E’ for everyone.

Cons: This is an ebook, but one of the best ways to learn.

Cheat Sheet 9: Packt>

This one is also a ebook from packt>. This ebook will teach you numerical and scientific computing in Python. You will also learn how to use Scipy in signal processing and how applications of Scipy can be used to collect, organize, analyze,a dn interpret data. By the end of the book, you will have fast, accurate, and easy-to-code solutions for numerical and scientific computing applications.

Pros: Rated ‘E’ for everyone.

Cons: This is an ebook so you will be spending time reading and coding.

Cheat Sheet 10: Packt>

Recipes are great in that you can find the exact one you are looking for without having to wade through all the other code snippets you do not need. In this ebook, you can play around with each one of these codes and gain a hands-on understanding of Scipy and its real-world problem applications.

Pros: Rated ‘E’ for everyone. The independent nature of the recipes allows you to hop around from each example making this book very versatile.

Cons: It is an ebook but a great one if you want to practice the different stacks of Scipy in Python.

Programmer Humor – Blockchain

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