As of 2024, JavaScript and HTML/CSS were the most commonly used programming languages among software developers around the world, with more than 62 percent of respondents stating that they used JavaScript and just around 53 percent using HTML/CSS. Python, SQL, and TypeScript 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.

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.

🧠 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

Field Description

Rows 100+ code samples

Languages Python, JavaScript, C++, Java, etc.

Tasks Data structures, algorithms, system utilities

Format Excel (.xlsx) and CSV

License MIT

Each entry includes:

id:… See the full description on the dataset page: https://huggingface.co/datasets/kaiiddo/ProgrammingDataset.

programming languages statistics: The tech market which is also booming along with digital marketing is pretty good for a better income source. The tech market has many other things including programming languages. Programming languages are the basis for the formation of various websites, games, software, mobile applications, etc... There are nearly 9,000 programming languages around the world with each language with its own feature. In this most popular programming language statistics, we will have a look at statistical information and general knowledge about worldwide available various programming languages. Programming Languages Statistics (Editor’s Choice) There are 8,945 programming languages as stated by most popular Programming languages statistics. As of 2022, JavaScript is one of the most popular programming languages as around 47.86% of recruiters are demanding JavaScript language skills. A basic python developer earns between $70,000 to $1,00,00 a year. As per the most popular programming languages statistics Python has ranked number 1 in the United States of America, India, Germany, France, and the United Kingdom

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 languages… See the full description on the dataset page: https://huggingface.co/datasets/bigcode/the-stack.

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/.

In Dublin City University, students learn how to code by taking a variety of programming modules. Students develop code algorithms for problems proposed by Faculty. Many of these courses or modules are delivered through a custom Virtual Learning Environment (VLE) built for the purpose of teaching and learning computer programming. This custom VLE enables students to access course information, material and slides for each module. In addition, our system integrates an automatic grading platform where students can verify their code submissions for programming exercises. Students typically develop solutions locally for laboratory sheets for the computer programming courses. Then, they submit their programs online to the automatic grading platform which runs a number of testcases specified by the lecturer on each exercise. This provides instant feedback to students based on the suite of testcases run and ultimately tells the student whether the program is considered correct or incorrect if any of the testcases fail. This information is invaluable to their learning and such a platform is needed to verify their programs work as expected. The computer programming grading system has been used for several years on a variety of programming courses at our University. This allowed researchers and Faculty to gather a fine-grained digital footprint of students learning programming at our University. Recently, research in Learning Analytics has focused on Predictive Modelling and identifying those students having difficulties with course material, also in programming courses, and offering remediation, personalized feedback and interventions to students using Machine Learning techniques. Prior work has reported that customized notifications sent to students regarding their performance and offering resources such as further learning material, code solutions from peers in their class and university support services helped students to increase their differential performance and engagement on these programming courses. However, there is a limit to this prior work where most of the models use little or no programming work as features for the learning algorithms or feedback sent to students. In this work we explore different mechanisms to represent students’ code to predict its correctness and to better analyze students’ progress using their interactions which can be exploited to provide effective feedback and support better recommendations. Every time a student submits a code solution for verification, the system stores the code submission, the student identifier, the IP used on the network for the upload, the results of the testcases run with inputs and outputs, the course the submission belongs to, the exercise and the task name the student is attempting by using the submission’s filename. In total, we collected more than half a million programming submissions (591,707) for 666 students from 5 Python programming courses over 3 academic years.

The global market for programming language learning platforms is experiencing robust growth, driven by the increasing demand for skilled software developers and the proliferation of online learning resources. The market's expansion is fueled by several key factors, including the rising adoption of digital technologies across various industries, the increasing accessibility of internet connectivity, and the growing preference for flexible and convenient online learning options. Furthermore, the continuous evolution of programming languages and the need for professionals to upskill and reskill are significant contributors to market growth. While precise figures for market size and CAGR are unavailable, reasonable estimations based on industry reports suggest a market valued at approximately $10 billion in 2025, exhibiting a compound annual growth rate (CAGR) of around 15% from 2025 to 2033. This growth is further segmented across various learning platforms, catering to diverse learning styles and technical proficiencies. The competitive landscape is characterized by established players like Coursera, Udemy, and Udacity, alongside specialized platforms such as DataCamp and smaller, niche providers. The market's growth trajectory is expected to remain positive throughout the forecast period (2025-2033), though certain restraints may influence the rate of expansion. These restraints could include challenges associated with maintaining high-quality educational content, ensuring platform accessibility for diverse learners, managing competitive pricing strategies, and addressing concerns related to the effectiveness of online learning compared to traditional classroom settings. However, continuous innovation in educational technologies, the integration of immersive learning experiences (such as virtual reality and gamification), and the development of personalized learning pathways are poised to mitigate these constraints and sustain the market's upward momentum. The geographical distribution of the market is likely to be diverse, with North America and Europe currently holding significant market share, followed by Asia-Pacific and other regions experiencing rapidly increasing adoption rates.

The most popular programming language used in the past 12 months by software developers worldwide is JavaScript as of 2024, according to ** percent of the software developers surveyed. This is followed by Python at ** percent of the respondents surveyed.

The dataset is a block-based programming dataset used to train a code classification model to predict students' success on a given problem.

Snapshot img

Programming Language Training Market Size 2024-2028

The programming language training market size is forecast to increase by USD 8.53 billion, at a CAGR of 19.31% between 2023 and 2028. Market growth hinges on several factors: rising adoption of boot camps in developing economies, heightened emphasis on blended learning methods, and integration of programming languages into school curricula. Meanwhile, online language learning tools leverage learning management systems and smart devices to promote language fluency and proficiency. These trends reflect a global shift towards practical, skills-based education tailored to meet evolving industry demands. Boot camps offer intensive, hands-on training that accelerates career readiness, particularly in the tech and digital sectors. Blended learning combines online and in-person instruction, catering to diverse learning styles and enhancing accessibility. Meanwhile, embedding programming languages in school curricula equip students with essential computational skills early on, fostering a future-ready workforce. Together, these factors drive innovation in education, preparing individuals and industries alike for the challenges and opportunities of a digitally-driven world.

What will be the size of the Market During the Forecast Period?

To learn more about this report, Download Report Sample

Market Dynamic

In the digital era, the landscape of software programs and scripts is enriched by versatile languages like C, Python, Ruby, PHP, and Java. These languages serve as foundational tools for developing everything from basic scripts to sophisticated applications. With the rise of machine learning and AI technologies, these languages play pivotal roles in building intelligent systems that automate processes and enhance decision-making. Cloud solutions further enable scalability and accessibility, supporting seamless deployment and management of applications globally. From computer-assisted learning to mobile-assisted language learning via cell phones, these tools offer personalized learning experiences. Self-assessment modules gauge progress, while software-enabled technology enhances interactivity and engagement. This integrated approach not only empowers learners but also caters to diverse educational needs, bridging language barriers and fostering global communication. As demand grows for flexible, tech-driven learning solutions, this market continues to innovate, shaping the future of language education worldwide.

Key Market Driver

The increased emphasis on blended learning is notably driving market growth. Blended learning has many benefits both in academic and corporate training. It helps companies and colleges cut their training costs. It also provides learners with real-time access and allows them the benefits of live learning. It gives more control to learners and allows them to learn at their own pace. It provides the training institutes with a consistent medium of training; in the corporate training scenario, it can lead to higher employee retention. As a result, many companies have significant scope to develop various learning technology solutions that can be effectively implemented in the blended learning framework.

Moreover, the blended learning model involves learning from traditional activities in the classroom along with web-enabled courses. Blended learning blends face-to-face learning with online learning and is becoming an attractive model in the higher education sector, especially in programming. Increasing emphasis on online training is one of the factors driving the growth of this model. Corporate companies are adopting the blended learning model to train their employees. The major reason for the adoption of the blended model of programming language training is the flexibility and convenience that the model provides to learners. As programming language training involves extensive practical learning methods, integrating new learning technologies has only made the overall learning process more effective. With these new learning frameworks, students understand concepts faster, providing them the flexibility to learn more advanced levels in the same subjects. The blended learning model is expected to grow during the forecast period due to its increased adoption in the academic as well as non-academic sectors leading to market growth.

Significant Market Trend

Increased integration of e-learning is a major trend in the market. In its early stages, e-learning relied heavily on desktop computers and networks. However, currently, it has evolved into systems that encompass a variety of channels, such as wireless communications and technologies, such as smartphones, AR, VR, and wearables. E-learning provides organizations with the convenience of flexible timings for training schedules, which can be accessed anytime and anywhere, with just an Internet connection.

Moreover, this helps the employees to

The dataset scraped from Twitter contains people's opinions about programming languages. The purpose of this dataset is to visualize people's opinion about different programming languages.

Final Project Programming 4

## Overview

Final Project Programming 4 is a dataset for object detection tasks - it contains Human Things annotations for 221 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

The programming education market is projected to witness significant growth in the coming years. In 2025, the market was valued at million, and it is estimated to reach million by 2033, exhibiting a CAGR of % during the forecast period. The growth of this market is primarily driven by the increasing demand for skilled programmers in various industries, the shift towards online learning, and the growing popularity of coding as a hobby. Key trends in the programming education market include the rise of online learning platforms such as Coursera, Udemy, and Pluralsight; the development of new programming languages and technologies; the increasing adoption of gamified learning approaches; and the growing focus on STEM education in schools and universities. The market is dominated by a few major players such as Coursera, Roblox, CSDN, Github, Udacity, Tynker, and Programming Hub. However, there are also a number of small and medium-sized companies offering programming education services. The market is expected to continue to grow in the coming years, as the demand for skilled programmers remains high.

The online programming education market is experiencing robust growth, driven by the increasing demand for skilled software developers and the accessibility of online learning platforms. While precise market size figures for 2025 aren't provided, a reasonable estimate, considering industry trends and the presence of large, established players like Coursera and Udemy, along with rapidly growing platforms like BitDegree, would place the market value in the billions of US dollars in 2025. A Compound Annual Growth Rate (CAGR) of, for example, 15% over the forecast period (2025-2033) suggests a substantial increase in market value by 2033. This growth is fueled by several key factors, including the rising adoption of technology across various industries, the increasing affordability and accessibility of online courses, and the flexibility offered by asynchronous learning. Furthermore, the shift towards remote work and the gig economy has created a significant demand for individuals with programming skills, further bolstering market expansion. The market is segmented by course type (e.g., web development, data science, cybersecurity), learning level (beginner, intermediate, advanced), and target audience (students, professionals, hobbyists). Competitive pressures are high, with both established players and new entrants vying for market share through innovative course offerings, pricing strategies, and marketing efforts. The market's growth is, however, subject to certain restraints. These include the need for continuous updates to curricula to reflect the rapidly evolving nature of programming languages and technologies. Ensuring quality and credibility of online courses, combatting the proliferation of low-quality content, and addressing the digital divide, particularly in terms of access to technology and reliable internet connectivity in certain regions, all pose challenges. Despite these challenges, the overall outlook for the online programming education market remains positive, promising continued expansion driven by sustained demand and technological advancements. The competitive landscape will likely see further consolidation and innovation as companies seek to differentiate themselves and capture market share within this dynamic sector.

Context

This project was born reading Wikipedia and Kaggle .

Acknowledgements

Thank you to Wikipedia beacuae of his work.

Inspiration

• What are the most felixble languaes?
• For aone use case, what''s the best language and paradigm?

Programming Education Market Outlook

The global programming education market size is anticipated to expand significantly, exhibiting a compound annual growth rate (CAGR) of 11.8% from 2024 to 2032. The market was valued at approximately USD 12.5 billion in 2023 and is projected to reach USD 29.5 billion by 2032. This growth is driven by several factors, including the increasing demand for coding proficiency across multiple sectors, the rise of digital transformation initiatives, and the growing availability of online learning platforms.

One of the critical growth factors in the programming education market is the burgeoning demand for digital skills across various industries. As businesses increasingly adopt digital technologies, there is a growing necessity for employees proficient in programming and coding. This demand is not confined to the IT sector alone but extends to healthcare, finance, manufacturing, and even creative industries. Moreover, the rise of emerging technologies such as artificial intelligence, machine learning, and big data analytics is further amplifying the need for skilled programmers who can develop, deploy, and maintain sophisticated software solutions.

Another significant driver is the increasing availability and sophistication of online learning platforms. Over the past decade, online education has revolutionized the way people acquire new skills, making learning more accessible, flexible, and affordable. Platforms such as Coursera, Udacity, and edX offer a plethora of programming courses catering to different skill levels, from beginners to advanced programmers. These platforms often collaborate with prestigious universities and tech companies, providing high-quality content that meets industry standards. Additionally, the advent of interactive and gamified learning experiences has made programming education more engaging and effective.

The emphasis on STEM (Science, Technology, Engineering, and Mathematics) education in the K-12 segment is also propelling the programming education market. Governments and educational institutions worldwide are increasingly recognizing the importance of integrating coding and programming into the school curriculum. Initiatives such as Hour of Code and Code.org are making significant strides in this direction. By introducing programming at an early age, these initiatives aim to equip students with critical problem-solving skills and prepare them for future careers in technology-driven fields.

In terms of regional outlook, North America leads the programming education market, driven by strong demand from the corporate sector and the presence of several leading educational technology companies. Europe is also witnessing substantial growth, supported by government initiatives to promote digital literacy. The Asia Pacific region is emerging as a lucrative market, owing to the increasing penetration of internet and mobile devices, coupled with a young, tech-savvy population. Latin America and the Middle East & Africa, though smaller in comparison, are showing promising growth, driven by increasing investments in educational infrastructure and a growing awareness of the importance of digital skills.

Component Analysis

In the programming education market, components are broadly categorized into software and services. The software segment comprises various tools and platforms used for coding education, including integrated development environments (IDEs), coding simulators, and gamified learning platforms. The services segment includes instructor-led training, online tutorials, workshops, and bootcamps. Both segments are critical to the overall growth and adoption of programming education.

The software segment is experiencing robust growth due to the increasing availability of sophisticated coding tools and platforms. Integrated Development Environments (IDEs) like Visual Studio Code, PyCharm, and Eclipse offer comprehensive environments where learners can write, test, and debug their code. These tools often come with built-in tutorials, sample projects, and community support, making them ideal for self-paced learning. Additionally, gamified learning platforms like Codecademy and CodeCombat are gaining traction for their interactive and engaging approach to coding education. These platforms use game mechanics to teach programming concepts, making learning fun and effective.

On the services side, instructor-led training and coding bootcamps are becoming increasingly popular, especially among professionals looking to upskill or switch careers. Coding bootcamps like Gen

This dataset is about books. It has 3 rows and is filtered where the book is Essentials of programming languages. It features 7 columns including author, publication date, language, and book publisher.

These files accompany the book entitled: An Introduction to Programming Languages: Simultaneous Learning in Multiple Coding Environments. This work is an introductory textbook in several computer languages. It describes the most well-known and popular programming environments such as: C#, C++, Java, JavaScript, PERL, PHP, Python, Ruby, and Visual Basic (VB) or Visual Basic for Applications (VBA). Therefore, the main objective of this unique guide is to provide code examples reflected in these nine computer languages. Readers can easily understand the connection and universality between the syntax of different environments and be adept at translating code. This learning experience can be ideal for upper-undergraduate introductory courses, researchers, doctoral students, and sociologists or engineers charged with implementing data analysis. Graphical illustrations are used for technical details about the computation examples to aid in an in-depth understanding of their inner workings. Moreover, the book contains original material that has been class-tested by the author and numerous cases are examined. Readers will also benefit from the inclusion of: a) Historical and philosophical perspectives on the past, present and future of computer languages. b) A total of 448 additional files freely available online, from which a total of 44 files are poster presentations (i.e. PowerPoint and PDF files). c) A total of 404 code examples reflected in nine computer languages, namely: C#, C++, Java, JavaScript, PERL, PHP, Python, Ruby and VB. This work first begins with a general introduction to history and presents the natural inevitable pathway from mechanical automatons to present electronic computers. Following this historical introduction, an in-detail look is made on philosophical questions, implementations, entropy and life. More often than not, there is a genuine amazement of the younger generations regarding the advancement of computer technology. Historical events that led to the development of technologies have been distilled down to the essence. However, the essence of any story is made with massive loss of detailed information. The essence of essences even more so. Over time, the lack of detail leads to a collective amnesia that can prevent us from understanding the naturalness by which technology has evolved. Thus, new constructs are always built upon older constructs to fit the evolutionary chain of technological progress, which boils down to the same fundamental rules as biological evolution. In the first stage, this book discusses the natural path of programming constructs by starting from time immemorial and ending with examples up to the present times. In the end, naturally driven constructs of all kinds also drive our society today. In the second part, the emphasis is made on the technical side where a total of nine computer languages are used simultaneously for mirrored examples. Simultaneous learning of multiple computer languages can be regarded as an asset in the world of science and technology. Thus, the reader can get used to the majority of known programming or scripting languages. Moreover, a basic knowledge of software implementation in several computer languages, even in an introductory way, helps the versatility and adaptability of the reader to new situations that may arise in industry, education, or research. Thus, this work is meant to bring a more concrete understanding of the similarities and differences between computer languages. Paul A. Gagniuc. An Introduction to Programming Languages: Simultaneous Learning in Multiple Coding Environments. Synthesis Lectures on Computer Science. Springer International Publishing, 2023, pp. 1-280.

This dataset is about book subjects. It has 2 rows and is filtered where the books is Programming with PL/1. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.