How to Automate Your GitHub Profile README with Python

Showcase Your Skills Through Automating Your Readme Profile

Background

Lately, I have been seeing an increasing number of developers on Github with a profile level README.md, and I wanted to create the same thing. I saw this as another opportunity to communicate what I am about. I also feel like it’s a great place to funnel a technical audience towards things that are important to me, which right now are these articles that I have been working on over these past few weeks. Also, if you as a reader are currently looking increase your authority amongst your peers, clients or potential employer this could be yet another opportunity to impress. As a hiring manager in tech, I would also be measurably impressed by anyone who took the extra effort to showcase their skills through their Github profile.

One of the things that I wanted to showcase were articles like this one that I am working on. I am creating a number of articles every week which would require me to remember to go and update these every time I publish. As a developer this was going to be unacceptable as I expect would be the reaction for a number of you reading 😉.

This led me to search for what the greats before me that have done for this type of automation already. During this search, I found a number of Go tutorials, and a really nice JavaScript tutorial which I have linked in the footer.

Using this as inspiration I figured that I would build this myself, as I had not been able to find someone doing this with Python in a way that I liked. With this challenge accepted I now needed to search for the required components to keep my Github Profile Readme up-to-date.

For those of you not willing to wait to see the results. You can take a look at the results for yourself in the image below.

Image by Author

Getting Started

The part of my README page that I want to automate, as you can see above, is going to be the feed of recent articles on Medium. In order to easily do this, I will need a python library for parsing an RSS feed. In addition to that, I would like to append a footer with the current timestamp in my timezone to indicate when the last update has been pushed since this isn’t illustrated anywhere within the Github profile landing page. All of this will happen in my language of choice at the moment, Python 3.8, so if you are following along make sure to use Python 3 as there’s some file I/O that is Python 3 specific.

Libraries

Here are the libraries that I decided to use based upon what has been mentioned earlier that were needed to achieve this.

feedparser —A library with a parser for Atom and RSS feeds. I could have built out my own parser and used urlib or requests, but I am okay adding this dependency.

pytz — Allows us to provide a human readable name for the timezone we want to so that we have a timezone aware timestamp. This is probably achievable via the tzinfo from the standard library, but this library is a crutch that I am willing to use for this purpose.

Concepts

Though you should be able to pretty much clone my repo, and work from that or just copy and paste from this article. It will be useful to know what the following concepts are. If anything else within this article deserves to be here let me know in the comments, and I can add it for any future readers interested in automating parts of their Github Readme profile.

Github Actions — Github’s CI/CD solution allowing for us to create, and a workflow to update our Github readme profile.

Really Simple Syndication (RSS) — A standardized feed format that allows users or applications, in this case, to automatically check for new content.

Start Building

My first step for building this out will be the same for you if you haven’t already done this. I needed to create a self-named Github repository take advantage of the Github Profile feature. So with the following repo, I was ready to start building out my README.md file.

#python #programming #github #developer

What is GEEK

Buddha Community

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

Creating a README with Statistics for your GitHub Profile.

So you noticed that some GitHub accounts have statistics on their profile and wondered how they did it. In this article, you will learn how easy it is to create one for your own profile.

In late 2020, GitHub released a new feature which allows users to create a README file for their profiles. This file is quite useful especially in marketing yourself. You can put an introduction about yourself, your work, skills, experiences, and more.

Some people also put their GitHub statistics, which I will show you how to do in this article.

The statistics that will be shown will be an overview of your GitHub account. It shall display information such as total stars, forks, repository views, languages you used, and more.

A sample README.md for a GitHub user’s profile

Let’s begin by learning how to create a README file that shows up in your profile.

#readme #github-profile #github #statistics #profile-readme

How to Create an Adept and Impressive Github README.md Profile?

Best Gadgets + Guide.

As everyone knows that Github has added a special repository. Its README.md will appear on your_ public profile_!

We can modify and make this as expressive as we want. It can contain all the information related to your skills, contributions projects plus much more. This article will guide you on how to create your _Github_Profile.

Follow along with these steps :

Step 1:_ Create a new repository with the same name as your __Github_username.

Choose public option and Select Initialize this repository with a _README_.

For example: born69confused/[born69confused]

I had already created a repository hence showing the already existing warning.

Creating the new repository

#javascript #coding #github-profile #github-profile-readme #github

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