List of the Top 10 IDE Software for Code With Me in 2025

JetBrains' IntelliJ IDEA serves as a powerful IDE specifically tailored for expert Java and Kotlin programming. It enhances your productivity and simplifies the process of writing high-quality code. Crafted to ensure you complete your tasks efficiently, it encompasses all the necessary tools and resources for utilizing the latest technologies. With its user-friendly interface and seamless workflow, it allows you to code confidently while prioritizing your privacy and security. This combination of features makes IntelliJ IDEA a top choice for developers who value both efficiency and safety in their work environment.

All your Python development requirements are brought together in a single application. While PyCharm efficiently manages routine tasks, it enables you to save valuable time and focus on more important projects, allowing you to leverage its keyboard-focused interface to discover numerous productivity enhancements. This IDE is highly knowledgeable about your code and can be relied upon for features such as intelligent code completion, real-time error detection, and quick-fix recommendations, in addition to easy project navigation and other functionalities. With PyCharm, you can produce structured and maintainable code, as it helps uphold quality through PEP8 compliance checks, support for testing, advanced refactoring options, and a wide array of inspections. Designed by developers for developers, PyCharm provides all the essential tools needed for efficient Python development, enabling you to concentrate on what truly matters. Moreover, PyCharm's powerful navigation capabilities and automated refactoring tools significantly improve your coding experience, guaranteeing that you stay productive and efficient throughout your projects while consistently adhering to best practices.

Presenting DataGrip, an innovative integrated development environment tailored for SQL experts. This advanced tool facilitates query execution in multiple modes while preserving a local history that tracks all actions, ensuring your work is well-protected. Users can easily access tables, views, or procedures by name through targeted actions or directly from their utilization in SQL code. Furthermore, DataGrip provides comprehensive insights into query performance and database engine behavior, empowering you to refine your queries for improved efficiency. The context-sensitive code completion feature significantly accelerates SQL writing, as it understands the table structures, foreign keys, and database objects pertinent to your current work. Additionally, the IDE effectively detects potential errors in your code and offers prompt suggestions for corrections, fostering a more seamless coding journey. It also alerts you to any unresolved objects by utilizing keywords as identifiers and consistently provides solutions for any issues that may emerge. These combined functionalities position DataGrip as an essential resource for developers seeking to boost their productivity and elevate the quality of their code while navigating complex database environments. Whether you are a seasoned professional or just starting, DataGrip adapts to your needs, making database management more intuitive and efficient.

Supermaven enhances your coding speed by leveraging artificial intelligence, allowing you to program at double the usual rate. You have the opportunity to interact with several sophisticated models, including GPT-4o, Claude 3.5 Sonnet, and GPT-4. The platform's hotkeys facilitate immediate comparison of code variations, applying modifications, initiating discussions, and switching between different models with ease. Attaching recently edited files to your messages is straightforward, as Supermaven Chat links the model's coding suggestions directly to your original code for effortless evaluation and updates. Furthermore, correcting errors becomes a breeze; you can upload your code alongside any compiler error messages with a single click, which significantly simplifies the debugging process. This cohesive integration of features not only accelerates coding but also enhances overall productivity and accuracy. By streamlining these essential tasks, Supermaven allows developers to focus more on creativity and problem-solving.

AppCode offers a deep understanding of your coding environment, helping to simplify repetitive tasks and minimize unnecessary typing. With its ability to swiftly navigate through files, classes, and symbols in your project, you can effortlessly explore the architecture using both hierarchical and structural perspectives. It provides two distinct types of code completion: a basic on-the-fly option and an advanced SmartType completion, which delivers precise and context-aware suggestions. You can confidently refactor your code at any moment, thanks to reliable and accurate options that maintain safety throughout the process. By continuously monitoring the quality of your code, AppCode identifies errors and code smells, offering automatic quick-fixes for quick resolutions. The tool encompasses a wide range of code inspections for various languages, including Objective-C, Swift, and C/C++, as well as numerous checks for additional supported languages, all performed in real time. You can easily rename variables, constants, functions, type names, and classes, with the assurance that AppCode will update every reference across your codebase without missing a beat. Its user-friendly interface further contributes to a more efficient coding experience, ultimately boosting your productivity and workflow. Additionally, AppCode's robust features allow developers to focus more on creative problem-solving rather than mundane tasks.

Datalore serves as a collaborative data science and analytics platform designed to enhance the analytics workflow, making data interaction more enjoyable for both data scientists and business teams with analytical skills. This platform prioritizes the efficiency of data teams, enabling technically skilled business users to engage with data teams through no-code and low-code solutions alongside the robust capabilities of Jupyter Notebooks. With Datalore, business users can enjoy analytic self-service by utilizing SQL or no-code cells, generating reports, and exploring data in depth. This functionality also allows core data teams to concentrate on more complex tasks, thus streamlining their workflow. Moreover, Datalore facilitates seamless collaboration between data scientists and analysts, enabling them to share their findings with ML Engineers. Users can effortlessly share their code with ML Engineers who have access to powerful CPUs and GPUs, all while collaborating in real time with colleagues for improved productivity and creativity. Ultimately, Datalore seeks to bridge the gap between technical and non-technical users, fostering a truly collaborative environment in the data science field.

Who wouldn't desire the ability to code as quickly as their mind races while their integrated development environment (IDE) takes care of the monotonous aspects? The question arises: is this level of efficiency possible with a sophisticated programming language like C++, particularly given its advanced features and complex templated libraries? Absolutely! Experience it firsthand as you can rapidly produce extensive boilerplate code and effortlessly override or implement functions with merely a few keystrokes. Furthermore, constructors, destructors, getters, setters, and various operators, including equality and relational operators, can be generated in no time. You'll find it simple to wrap code blocks in statements or create declarations based on their usage. The ability to design custom live templates also empowers you to effectively reuse common code snippets across your projects, streamlining your workflow and maintaining a consistent coding style. Not only can you rename symbols, inline functions, variables, or macros, but you can also reorganize members within hierarchies, adjust function signatures, and extract functions, variables, parameters, or typedefs effortlessly. With these tools at your disposal, the art of coding transforms into a faster and far more pleasurable experience, making it a rewarding pursuit for any programmer.

Accessing JetBrains IDEs and Swing applications through a network is made possible by utilizing Swing, a graphical widget toolkit for Java, which powers current JetBrains IDEs and other IntelliJ-based applications, including Android Studio. Projector stands out as a groundbreaking self-hosted solution that allows IntelliJ-based IDEs and Swing applications to run on a server, providing users the capability to connect from anywhere via web browsers or specific applications. For example, the IntelliJ IDEA Community Edition can be executed in the Safari browser on macOS, enabling code execution closer to the runtime or database, which effectively reduces latency. This arrangement is particularly advantageous in high-security settings and corporate environments, where thin clients and affordable hardware, such as Android tablets, can be utilized. Users can conveniently power down their local machines while their applications continue to run on the server, thus optimizing resource usage. Additionally, it permits the execution of the IDE in a GNU/Linux environment on Windows systems or even on more unusual operating systems like ChromeOS. By making use of VM or Docker images that come preloaded with debug sources and a configured IDE, developers can achieve seamless remote debugging from the server side, catering to both development testing and production needs. This flexibility significantly boosts productivity, streamlining workflows, and making it an essential asset for contemporary software development. Furthermore, the ease of access to powerful development tools from virtually any device expands opportunities for collaboration and innovation in programming projects.

Built from scratch, JetBrains Fleet leverages twenty years of expertise in developing integrated development environments (IDEs). It employs the powerful IntelliJ code-processing engine, boasting a distributed architecture alongside a modern user interface tailored for today's developers. The primary objective behind Fleet was to design a fast and effective text editor that facilitates rapid code browsing and editing. It opens almost instantaneously, allowing users to commence their tasks without any interruptions, and it possesses the ability to transform into a comprehensive IDE, with the IntelliJ engine functioning separately from the editing interface. Fleet includes all the popular features associated with IntelliJ-based IDEs, including context-specific code completion, straightforward navigation to definitions and usages, real-time evaluations of code quality, and handy quick-fixes. The thoughtful architecture of Fleet is crafted to support a range of configurations and workflows, which means it can operate locally on your device or delegate certain processes to the cloud, highlighting its adaptability for various development tasks. This inherent flexibility guarantees that developers can select the configuration that aligns perfectly with their workflow preferences, ultimately enhancing productivity levels. In a landscape where efficiency is paramount, Fleet stands out as a tool that can evolve alongside the needs of the developer.

Effortlessly toggle between command and editor modes with a single keystroke while using arrow keys to navigate through cells. Utilize the full range of standard Jupyter shortcuts to create a more seamless workflow. Enjoy the benefit of interactive outputs displayed immediately below the cell, improving visibility and comprehension. While working on code cells, take advantage of smart code suggestions, real-time error detection, quick-fix features, and efficient navigation, among other helpful tools. You can work with local Jupyter notebooks or easily connect to remote Jupyter, JupyterHub, or JupyterLab servers straight from the IDE. Execute Python scripts or any expressions interactively in a Python Console, allowing you to see outputs and variable states as they change. Divide your Python scripts into code cells using the #%% separator, which enables you to run them sequentially like in a traditional Jupyter notebook. Furthermore, delve into DataFrames and visual displays in real time with interactive controls, while benefiting from extensive support for a variety of popular Python scientific libraries, such as Plotly, Bokeh, Altair, and ipywidgets, among others, ensuring a thorough data analysis process. This robust integration not only streamlines your workflow but also significantly boosts your coding productivity. As you navigate this environment, you'll find that the combination of features enhances your overall coding experience.