Welcome to an exceptional dataset meticulously crafted for training state-of-the-art language models such as Gemma, Llama 2, Orca, and more.

Dataset Highlights - Challenging Questions : Immerse your language models in various Python programming questions designed to stimulate cognitive growth. - Real-world Inputs : Provide your models with authentic input scenarios, ensuring they are well-equipped to handle practical coding challenges. - Accurate Answers : Sharpen the precision of your language models by exposing them to meticulously crafted Python code solutions.

How to Get Started - Download : Grab a copy of the dataset and inject new life into your language models. - Build Brilliance : Watch your LLMs evolve as they engage with the challenging questions and nuanced coding scenarios. - Share & Collaborate : Join the Kaggle community to discuss, share insights, and collaborate with fellow enthusiasts.

Unleash the full potential of your language models with this dataset. Elevate your LLM training experience and witness unprecedented growth in language understanding and coding prowess. Happy coding !

Dataset Card for The Stack

  Changelog

Release Description

v1.0 Initial release of the Stack. Included 30 programming languages and 18 permissive licenses. Note: Three included licenses (MPL/EPL/LGPL) are considered weak copyleft licenses. The resulting near-deduplicated dataset is 3TB in size.

v1.1 The three copyleft licenses ((MPL/EPL/LGPL) were excluded and the list of permissive licenses extended to 193 licenses in total. The list of programming… See the full description on the dataset page: https://huggingface.co/datasets/bigcode/the-stack.

license: mit language: - en tags: - programming - code - dataset - snippets - software-development pretty_name: Programming Dataset size_categories:

- n<1K

🧠 ProgrammingDataset

A high-quality, production-grade dataset of programming code snippets across multiple languages, collected and curated manually to support research in code generation, analysis, and educational tools.

📌 Dataset Summary

Each entry includes:
- id: Unique identifier
- language: The programming language used
- task_type: What kind of task the snippet solves (e.g., sorting, API call)
- description: Human-readable explanation
- code: The actual working code (formatted for readability)

🏷️ Tags

• code-generation
• multi-language
• algorithms
• educational
• dataset

📐 Size Categories

• Small (<1k samples)
• Easily extensible to thousands with our VBA macro (included in Excel).

✨ How to Use

You can open ProgrammingDataset.xlsx in Excel or load the .csv in Python:

from datasets import load_dataset

# Login using e.g. `huggingface-cli login` to access this dataset
ds = load_dataset("kaiiddo/ProgrammingDataset")

🧪 Use Cases

• Train code generation models (e.g., CodeT5, Codex)
• Build coding assistants and tutors
• Analyze cross-language patterns
• Educate students on common tasks

📄 License

This dataset is licensed under the MIT License — feel free to use, modify, and share with attribution.

📚 Citation

If you use this dataset in your research, applications, or publications, please cite it as:

@misc{kaiiddo2025programmingdataset,
 title    = {ProgrammingDataset: A Curated Collection of Code Snippets Across Languages},
 author    = {Kaiiddo Team},
 year     = {2025},
 howpublished = {\url{https://huggingface.co/datasets/kaiiddo/ProgrammingDataset}},
 note     = {Accessed July 2025}
}

Or:

"We gratefully acknowledge the use of the ProgrammingDataset curated by the Kaiiddo Team (2025) for training and evaluating programming-related models."

Want to contribute more snippets or suggest improvements? Submit a PR or reach out to the maintainers!

As of 2025, JavaScript and HTML/CSS are the most commonly used programming languages among software developers around the world, with more than 66 percent of respondents stating that they used JavaScript and just around 61.9 percent using HTML/CSS. Python, SQL, and Bash/Shell rounded out the top five most widely used programming languages around the world. Programming languages At a very basic level, programming languages serve as sets of instructions that direct computers on how to behave and carry out tasks. Thanks to the increased prevalence of, and reliance on, computers and electronic devices in today’s society, these languages play a crucial role in the everyday lives of people around the world. An increasing number of people are interested in furthering their understanding of these tools through courses and bootcamps, while current developers are constantly seeking new languages and resources to learn to add to their skills. Furthermore, programming knowledge is becoming an important skill to possess within various industries throughout the business world. Job seekers with skills in Python, R, and SQL will find their knowledge to be among the most highly desirable data science skills and likely assist in their search for employment.

SWE-Bench Dataset

The dataset comprises 8,712 files across 6 programming languages, featuring verified tasks and benchmarks for evaluating coding agents and language models. It introduces new benchmarks with real-world coding tasks, providing datasets for software engineering problems and tests. It builds upon the original swe-bench by evaluating repository-level challenges and scoring performances.

By utilizing this dataset with its multi-language test sets and golden patches, researchers and developers can advance their understanding of large language models and developer tools, comparing their performances on real software engineering challenges. - Get the data

Specifically engineered for evaluating advanced coding and software development, SWE-Bench Dataset supports research in code generation, automated patching, and fixing GitHub issues.

💵 Buy the Dataset: This is a limited preview of the data. To access the full dataset, please contact us at https://unidata.pro to discuss your requirements and pricing options.

Example of the data

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F27063537%2F6876a1091e5e4e12d330177c6ec3a0e6%2F1.PNG?generation=1759494538704549&alt=media" alt="">

The dataset provides a robust foundation for achieving higher accuracy in code generation and advancing automated software development tools, which are essential for improving developer productivity and software quality.

🌐 UniData provides high-quality datasets, content moderation, data collection and annotation for your AI/ML projects

SWE-Bench Dataset - 8,712 files

The dataset comprises 8,712 files across 6 programming languages, featuring verified tasks and benchmarks for evaluating coding agents and language models. It supports coding agents, language models, and developer tools with verified benchmark scores and multi-language test sets. - Get the data

Dataset characteristics:

Here's a sample dataset to check out. For full access, go here

Dataset structure

• Go - Files in Go
• Scala - Files in Scala

Similar Datasets:

1. LLM Text Generation Dataset
2. Synthetic Printed USA Passports Dataset
3. DeepFake Videos Dataset

About Dataset

This dataset was created during the Programming Language Ecosystem project from TU Wien using the code inside the repository https://github.com/ValentinFutterer/UsageOfProgramminglanguages2011-2023?tab=readme-ov-file.

The centerpiece of this repository is the usage_of_programming_languages_2011-2023.csv. This csv file shows the popularity of programming languages over the last 12 years in yearly increments. The repository also contains graphs created with the dataset. To get an accurate estimate on the popularity of programming languages, this dataset was created using 3 vastly different sources.

About Data collection methodology

The dataset was created using the github repository above. As input data, three public datasets where used.

github_metadata

Taken from https://www.kaggle.com/datasets/pelmers/github-repository-metadata-with-5-stars/ by Peter Elmers. It is licensed under CC BY 4.0 https://creativecommons.org/licenses/by/4.0/. It shows metadata information (no code) of all github repositories with more than 5 stars.

PYPL_survey_2004-2023

Taken from https://github.com/pypl/pypl.github.io/tree/master, put online by the user pcarbonn. It is licensed under CC BY 3.0 https://creativecommons.org/licenses/by/3.0/. It shows from 2004 to 2023 for each month the share of programming related google searches per language.

stack_overflow_developer_survey

Taken from https://insights.stackoverflow.com/survey. It is licensed under Open Data Commons Open Database License (ODbL) v1.0 https://opendatacommons.org/licenses/odbl/1-0/. It shows from 2011 to 2023 the results of the yearly stackoverflow developer survey.

All these datasets were downloaded on the 12.12.2023. The datasets are all in the github repository above

Description of the data

The dataset contains a column for the year and then many columns for the different languages, denoting their usage in percent. Additionally, vertical barcharts and piecharts for each year plus a line graph for each language over the whole timespan as png's are provided.

The languages that are going to be considered for the project can be seen here:

- Python

- C

- C++

- Java

- C#

- JavaScript

- PHP

- SQL

- Assembly

- Scratch

- Fortran

- Go

- Kotlin

- Delphi

- Swift

- Rust

- Ruby

- R

- COBOL

- F#

- Perl

- TypeScript

- Haskell

- Scala

License

This project is licensed under the Open Data Commons Open Database License (ODbL) v1.0 https://opendatacommons.org/licenses/odbl/1-0/ license.

TLDR: You are free to share, adapt, and create derivative works from this dataser as long as you attribute me, keep the database open (if you redistribute it), and continue to share-alike any adapted database under the ODbl.

Acknowledgments

Thanks go out to

- stackoverflow https://insights.stackoverflow.com/survey for providing the data from the yearly stackoverflow developer survey.

- the PYPL survey, https://github.com/pypl/pypl.github.io/tree/master for providing google search data.

- Peter Elmers, for crawling metadata on github repositories and providing the data https://www.kaggle.com/datasets/pelmers/github-repository-metadata-with-5-stars/.

A table listing common programming languages used in data science, their purpose, and key capabilities.

The full CJ Jones' synthetic dataset catalog is available at: https://datadeveloper1.gumroad.com Want more? 🚀 Get the AI Startup Bundle from Gumroad.

  Java Programming Examples Dataset







  Dataset Description

This dataset contains 8 distinct Java programs with 10 conversational examples each, synthetically generated from a larger dataset of 80+ programs. Each program has 10,000 variants, providing a diverse set of Java code examples covering various programming… See the full description on the dataset page: https://huggingface.co/datasets/CJJones/Synthetic_Java_Dialog_And_Programs_LLM_Training.

NehaMatani/programming-glossary-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community

This dataset titled "Programming Languages Search over Time" provides weekly search interest scores for three prominent programming languages - Python, Java, and C++ - over a period spanning from April 21, 2019, to April 23, 2024. The search interest scores represent the relative popularity of each programming language as determined by search engine queries.

This dataset can be used to analyze and visualize trends and patterns in the popularity of these programming languages over time, providing valuable insights into their usage and adoption in the software development community.

JavaScript and Java were some of the most tested programming languages on the DevSkiller platform as of 2024. SQL and Python ranked second and fourth, with ** percent and ** percent of respondents testing this language in 2024, respectively. Nevertheless, the tech skill developers wanted to learn the most in 2024 was related to artificial intelligence, machine learning, and deep learning. At the same time, the fastest growing IT skills among DevSkiller customers were C/C++ and data science, while cybersecurity ranked third. Software skills When it came to the most used programming language among developers worldwide, JavaScript took the top spot, chosen by 62 percent of surveyed respondents. Most software developers learn how to code between 11 and 17 years old, with some of them writing their first line of code by the age of 5. Moreover, seven out of 10 developers learned how to program by accessing online resources such as videos and blogs. Software skills pay In 2024, the average annual software developer’s salary in the U.S. amounted to nearly ** thousand U.S. dollars, while in Germany, it totaled above ** thousand U.S. dollars. The programming languages associated with the highest salaries worldwide in 2024 were Clojure and Erlang.

12K+ DSA codebases and 200+ legacy codebases is an InfoBay corpus for enterprise AI teams that need traceable, expert-curated coding training data. DSA, SQL, machine coding, low-level design, competitive mathematics, and repository-history datasets.

Weekly rankings of programming language demand by active job listings. Covers Python, SQL, TypeScript, Java, Go, Rust and more.

Programming languages ranked by usage and popularity in 2025, based on the TIOBE Index, Stack Overflow Developer Survey, and GitHub activity. Python has cemented itself as the most popular programming...

Programming-Language/codeagent-python dataset hosted on Hugging Face and contributed by the HF Datasets community

Multi-Round Programming Conversations

Based on previous evol-codealpaca-v1 dataset with added sampled questions from stackoverflow, crossvalidated and make it multiround! It should be more suited to train a code assistant which works side by side.

  Tasks included in here:

Data science, statistic, programming questions

Code translation : translate a short function from Python, Golang, C++, Java, Javascript

Code fixing : Fix randomly corrupts characters with no tab… See the full description on the dataset page: https://huggingface.co/datasets/theblackcat102/multiround-programming-convo.

Quantum Programming Language Market size was valued at USD 150 Million in 2025 and is expected to reach USD 1.4 Billion by 2035, expanding at a CAGR of 25% during the forecast period.

In 2024 around ** percent of software development organizations used over ** programming languages. In the majority of companies with fewer than ***** employees and up to ***** employees, around *** languages were being utilized. More than 10,000 employees. Organizations with over 10,000 employees used a different number of programming languages with almost an equal share.

This dataset contains amounts shown in the TIF District Programming 2023-2027 reports as well as from 2028 through the planned expiration of each TIF district. The report and corresponding dataset show estimated fund and project balances through the end of FY 2022. Amounts shown in columns 2023 and later reflect known obligations and proposed projects as well as estimates of revenue based on the current equalized assessed value data for each TIF district produced by the Cook County Clerk.

Versions of this dataset are produced periodically for the then-relevant time periods, which will partially overlap, with newer versions having updated numbers. The immediately previous and next (if available) datasets are shown in the Featured Content cards for this dataset. All versions of this dataset can be found at https://data.cityofchicago.org/browse?tags=tif+district+programming.