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Open Source Programming Projects

Budding developers often rely on online tutorials and references to build their foundation of coding. As it is with any form of learning, this simply imparts knowledge to the learner. It is hardly a source of hands-on experience and practical application skills.

This is why all beginner developers should commit to projects that help them to apply their skills and learn more in the process. These projects can be a solo effort for them to test their skills, or as a team, with fellow devs from around the world.

Open source projects are an excellent way for coders and developers to test their mettle and learn more advanced methods. In an open-source project, there will be many contributors of varying skill levels and expertise.

Each contributor adds to the project according to their capabilities, and a combined effort leads to the fulfillment of the goal. Therefore, it is the best way for any individual to learn, gain practical experience, and understand what it’s like to work with a team of peers.

1. Apache Cassandra

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Number of contributors: 287

  • Top contributor: Jonathan Ellis, CTO & Co-Founder at DataStax | @spyced
  • Primary language: Java 
  • Number of stars: 5,700

Apache Cassandra is a distributed and decentralized database designed to manage massive amounts of structured and unstructured data across the world. It was developed at Facebook for inbox search and open sourced in July 2008. 

One of Cassandra’s most essential features is its elastic and linear scalability, which enables a consistently fast response time. Data is automatically replicated to multiple nodes for fault tolerance and easy distribution. 

Some of the open source project’s largest production deployments include Apple, Netflix, and Chinese search engine Easou. It’s also in use at Constant Contact, CERN, Comcast, eBay, GitHub, Instagram, and more than 1,500 more companies.

2. TensorFlow

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  • Number of contributors: 2,383
  • Top contributor: tensorflower-gardener
  • Primary languages: C++ and Python
  • Number of stars: 141,000

TensorFlow is an open source library for numerical computation and machine learning that was created by the Google Brain Team in 2015. TensorFlow is designed to enable the simple creation of machine learning models for desktop, mobile, web, and cloud.

One of the project’s greatest benefits is abstraction. In other words, TensorFlow allows developers to focus on the general logic of the application while the library handles the details of implementing algorithms in the background. It also provides a direct path to production. Whether on servers, edge devices, or web, TensorFlow lets you train and deploy your model easily in any language or platform.

Some of the biggest companies using TensorFlow include airbnb, Coca-Cola, DeepMind, GE Healthcare, Google, Intel, and Twitter.

3. Renovate

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  • Number of contributors: 190
  • Top contributor: Rhys Arkins, Director of Product Management at WhiteSource | @rarkins
  • Primary languages: JavaScript & TypeScript
  • Number of stars: 2,600

Renovate is the essential “keep absolutely everything up-to-date” code maintenance tool. Acquired by WhiteSource in November 2019, Renovate is designed to save developers time and reduce security risk by automating dependency updates in software projects. 

We obviously love Renovate a lot, mostly for its open-first approach and ability to support a highly coordinated and efficient open source security strategy. 

One of Renovate’s key benefit is its ability to support multiple languages and file types in order to detect dependencies wherever they’re in play. It runs continuously to detect the latest available versions, and provides changelogs and commit histories with every update. You can also run your existing suite of tests on every update to avoid regression errors.

Temenos Automates Their Manual Workflows

to Increase Agility

4. Kubernetes

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  • Number of contributors: 2,441
  • Top contributor: Jordan Liggitt, Staff Software Engineer at Google | @liggitt
  • Primary language: Go
  • Number of stars: 63,000

Over the past few years, containers have become a go-to for software development teams, helping them build, deploy, test, and deploy at scale, and keep up with the hectic speed of release cycles. Kubernetes, an OG in the container space, is an open source project that is designed to automate the deployment, scaling, and management of containerized applications. Its main objective is to simplify the work of technical teams by automating many of the processes of applications and services deployment that were formerly completed manually.

We love Kubernetes for its automation capabilities, which ultimately saves you money through more efficient use of hardware. Kubernetes allows you orchestrate containers on multiple hosts and scale resources and applications in real-time. 

Special mention goes to K9s, the Kubernetes CLI that makes it easier to navigate, observe, and manage your Kubernetes clusters. 

Some of Kubernetes’ biggest users include China Unicom, Spotify, Nav, and AppDirect

5. Ansibl

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  • Number of contributors: 4,884
  • Top contributor: Brian Coca, Sr. Software Engineer at Ansible | @brian_coca
  • Primary language: Python 
  • Number of stars: 41,700

Featured in GitHub Octoverse’s list of top open source projects by contributors since 2016, 

Ansible is an IT automation tool that “loves the repetitive work your people hate.” We love this open source project because it eliminates much of the complex, redundant tasks intrinsic to application development and delivery. 

Ansible has risen in popularity because of its simple, human-readable language and ability to automate complex, multi-tier IT application environments. Organizations that are able to eliminate some of the lamented grunt-work their developers face stand to reap the benefits of improved productivity and accelerated DevOps.

6. Geany 

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  • Number of contributors: 149
  • Top contributor: Enrico Tröger | eht16 
  • Primary languages: C & C++
  • Number of stars: 1,500

Geany is a small and lightweight IDE that runs on Linux, Windows, MacOS, and every platform that is supported by GTK libraries. We love it because it fulfills the need for a flexible, powerful, cross-platform IDE that provides helpful features without congesting your workflow.

For instance, Geany offers syntax highlighting, code folding, symbol name auto-completion, call tips, a build system to compile and execute your code, and project management, among others. Another unique resource is its extensive User Manual and crowd-sourced Wiki and full Plugin API Documentation.

7. Scrapy

Scrapy is a high level, fast and accurate data scraping tool built on a Python framework. It is used to scour cyberspace and collect the required data from many online sources, according to the user’s requirement.

It is used for data mining, monitoring purposes, and even testing. This high-level web crawler also has a rich GitHub repository that can serve as a good place for beginner level entrants to try out. This project should be interesting for Data Miners and scientists as well. 

8. Jina

Jina is a search framework that has cross-modal search implementation capabilities. It is powered by Deep Learning, and it can be used to enable text, image, and audio searches in the cloud. It can be extended using Pythonic interfaces, is plug and play, cloud-enabled, and contains great AI modals, among other capabilities.

Conclusion

Open-source software has revolutionized Computer Science in many ways. It is now a field powered by a vibrant community of developers who work on their passion projects while making a living with their skills. Open source projects drive many people from beginner to expert levels of knowledge and skill. These are vital to the growth of any aspiring programmer. 

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