Free Online Compiler & Code Runner

Write, compile and run code in 30+ programming languages — Python, JavaScript, C++, SQL, and more. Sandboxed Docker execution. No install. No sign-up. Always free.

Why Use FlexyPdf Compilers?

Docker Sandboxed

Every execution runs in an isolated container — no code ever touches the host system.

Instant Results

Results appear within seconds. No compilation queues, no waiting.

5s Timeout

Infinite loops are killed automatically. Your browser stays responsive.

Monaco Editor

VSCode-grade editor with syntax highlighting for every supported language.

How It Works

01

Write Your Code

Open any compiler page and type or paste your code into the Monaco editor. Syntax highlighting and auto-indent are active immediately.

02

Click Run

Press the Run button. Your code is sent securely to a local Docker container that compiles and executes it.

03

See the Output

stdout appears in the output console in green. Errors appear in red. The container is destroyed after every run.

What is an Online Compiler?

An online compiler is a web-based tool that lets you write, compile, and run source code directly in your browser — without installing any programming language, IDE, or runtime on your computer. FlexyPdf's online compiler collection covers 30 programming languages, from widely-used languages like Python, JavaScript, and C++, to specialized ones like Haskell, COBOL, and Erlang.

How FlexyPdf Compilers Work

Every time you click Run, your code is sent to the FlexyPdf backend server which spins up a fresh Docker container, copies your code file into it, compiles or interprets it, captures stdout and stderr, then destroys the container. The entire cycle takes 1–5 seconds depending on the language. Memory is limited to 128 MB and CPU to 1 core, and a 5-second hard timeout prevents runaway programs. No code or output is stored after execution.

Benefits of Online Code Compilers

Online compilers remove the setup barrier entirely. Learning a new language no longer requires spending 30 minutes installing an SDK, configuring environment variables, and finding the right IDE. You open a browser, type code, and see it run. This makes online compilers invaluable for students, educators, developers testing small snippets, interviewers running coding challenges, and anyone who needs to quickly verify an algorithm.

Supported Languages and Runtimes

FlexyPdf currently provides fully operational execution for Python 3.11, Node.js 20 (JavaScript), GCC 13 (C++17), and SQLite (SQL). In development: Java, TypeScript, Go, Rust, C, C#, Kotlin, Swift, PHP, Ruby, R, Scala, Dart, Julia, Haskell, Elixir, Erlang, Perl, Lua, Bash, PowerShell, Assembly (NASM), Objective-C, Fortran, and COBOL.

Frequently Asked Questions

Which programming languages are supported?

FlexyPdf currently offers compilers for 30 languages: Python, JavaScript, C++, SQL, Java, TypeScript, Go, Rust, C, C#, Kotlin, Swift, PHP, Ruby, R, Scala, Groovy, Dart, Julia, Haskell, Elixir, Erlang, Perl, Lua, Bash, PowerShell, Assembly, Objective-C, Fortran, and COBOL. Python, JavaScript, C++, and SQL are fully operational today.

Are the compilers free to use?

Yes — completely free with no sign-up, no watermarks, no usage limits, and no hidden fees. Run as many programs as you need.

How is security handled?

Code runs in an ephemeral Docker container with memory (128 MB) and CPU (1 core) limits, a 5-second hard timeout, and no network access. The container is permanently deleted after each execution.

Can I use third-party libraries or packages?

Not yet — the current environment supports each language's standard library only. Package manager support (pip, npm, cargo) is on the development roadmap.

Does it work on mobile?

Yes — all compiler pages are fully responsive. The Monaco editor works on tablets and large-screen phones, though a desktop is recommended for the best coding experience.

Do I need Docker installed locally?

Only for code execution. The Monaco editor and all UI run in the browser. To execute code you need the FlexyPdf backend server running locally with Docker available on the host machine.