Search Results for "best python programming projects"

Google Styleguide is a comprehensive collection of coding style guides created and maintained by Google to ensure consistency, readability, and maintainability across its vast array of software projects. These guides define best practices and conventions for writing code in multiple programming languages, from C++ and Python to JavaScript, Go, and Swift. By adhering to these standards, developers can more easily collaborate, review code, and maintain high-quality software across teams and open source contributions. Each guide covers a wide range of topics, including naming conventions, file organization, indentation, documentation, and usage of specific language features. ...

Kotlin Multiplatform technology simplifies the development of cross-platform projects. It reduces time spent writing and maintaining the same code for different platforms while retaining the flexibility and benefits of native programming. This list contains libraries which support iOS and Android targets in first place.

Valkey General Language Independent Driver for the Enterprise (GLIDE), is an open-source Valkey client library. Valkey GLIDE is one of the official client libraries for Valkey, and it supports all Valkey commands. Valkey GLIDE supports Valkey 7.2 and above, and Redis open-source 6.2, 7.0 and 7.2. Application programmers use Valkey GLIDE to safely and reliably connect their applications to Valkey- and Redis OSS- compatible services. Valkey GLIDE is designed for reliability, optimized...

The first section is an intentionally brief, functional, data science-centric introduction to Python. The assumption is a someone with zero experience in programming can follow this tutorial and learn Python with the smallest amount of information possible. The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, command line tools, recommendation engines, Sentiment Analysis and Cloud Computing.

Assorted projects. General-purpose libraries for Python, C++, Scala, bash, and others. Meta-programming tools. System utilities. UI components. Web APIs. Configuration files. Benchmarks. Programming competition entries. And much more.

The DataScienceR repository is a curated collection of tutorials, sample code, and project templates for learning data science using the R programming language. It includes an assortment of exercises, sample datasets, and instructional code that cover the core steps of a data science project: data ingestion, cleaning, exploratory analysis, modeling, evaluation, and visualization. Many of the modules demonstrate best practices in R, such as using the tidyverse, R Markdown, modular scripting,...

Modern software systems and application are commonly written in multiple languages, include scripting engines, and are frequently build on multiple specialized frameworks and middleware for a considerable diversity of runtime environments. The latest influencing update in development paradigm is the application of multicore processors. This projects is aimed to unify the required trace and logging output and integrate into debugging environments. The target is to provide general development,...