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PyCharm vs. Spyder: Choosing the Right Python IDE

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PyCharm vs Spyder: Choosing the Right Python IDE

Python is immensely popular among developers and data scientists due to its simplicity, versatility, and robustness, making it one of the most used programming languages in 2023.  With around 147,000 packages, the Python ecosystem continues to evolve with better tools, plugins, and community support.

When we talk about Python development, Integrated Development Environments (IDEs) take center stage, allowing developers to enhance their coding experience. Two popular IDEs for Python development are PyCharm and Spyder. This article briefly compares Python vs. Spyder to help developers make an informed choice.

A Brief Look Into Pycharm & Spyder

Before comparing PyCharm vs. Spyder to determine the best IDE for Python development, it’s essential to understand what these tools entail.

PyCharm: Python IDE for Professional Developers

PyCharm Dashboard UI

PyCharm is a product by JetBrains that offers a feature-rich integrated development environment for Python. The IDE has two editions – PyCharm Community and PyCharm Professional. The former is a free, open-source version, while the latter is a paid version for full-stack development. Both versions support several features, including code completion, code analysis, debugging tools, and integration with various version control systems. The professional edition further includes frameworks for web development and data science.

Spyder: Python IDE for Scientists, Engineers & Data Analysts

Spyder dashboard UI

Spyder, or Scientific Python Development Environment, is an open-source IDE primarily focusing on data science and scientific computing in Python. It’s part of the Anaconda distribution, a popular package manager and distribution platform for Python. Spyder provides comprehensive tools for advanced data analysis, visualization, and scientific development. It features automatic code completion, code analysis, and vertical/horizontal screen splits with a multi-language editor pane that developers can use for creating and modifying source files. Moreover, developers can extend Spyder’s functionality with powerful plugins.

Pycharm vs. Spyder Comparison – Who Wins?

Pycharm vs. Spyder Comparison - Who Wins?

Several similarities and differences exist between these two IDEs. Below, we compare them against various dimensions, including code editing and navigation features, debugging capability, support for integrated tools, customizability, performance, usability, community support, and pricing.

Code Editing & Navigation

Both PyCharm and Spyder offer powerful code editing and navigation features, making it easy for developers to write and understand code across files. While Spyder provides similar code completion and navigation ability, it is less robust than PyCharm's code editing features, which offer context-based recommendations for faster development. For instance, developers get code completion suggestions (sorted by priority) based on other developers' work in a similar scenario.

PyCharm leads this category with its advanced code analysis and completion capabilities. 


PyCharm’s professional version has a Javascript-based debugger that supports various debugging modes, including remote debugging. It also provides a visual debugger with breakpoints, variable inspection, and step-by-step execution.

Spyder includes a PDB debugger. PDB is a source debugging library for Python that lets developers set conditional breakpoints and inspect stack frames. Its variable explorer is particularly helpful for checking variable states at several breakpoints.

While Spyder’s debugging capabilities are robust, PyCharm’s visual debugger is better as it helps in more complex debugging scenarios.

Integrated Tools

PyCharm has extensive integration with third-party tools and services. For instance, it has built-in support for version control systems like Git, SVN, Perforce, etc. The professional edition supports web development frameworks, such as Django, Flask, Angular, etc., making it an excellent choice for full-stack development.

Spyder, primarily a data science and scientific computing utility, comes with numerous libraries and tools, such as NumPy, SciPy, Matplotlib, and Jupyter Notebooks. Also, it shares all libraries that come with the Anaconda distribution. However, Spyder only supports Git for version control.

Overall, PyCharm overtakes Spyder in this category since the former offers integration with diverse tools through plugins.


PyCharm offers a high level of visual customization, allowing developers to tailor the IDE according to their workflow and preferences. They can change font type and color, code style, configure keyboard shortcuts, etc.

Spyder is relatively less customizable compared to PyCharm. The most a user can do is change the user interface’s (UI’s) theme using a few options among light and dark styles.

Again, PyCharm takes the win in the customization category.


While performance can vary depending on the size and complexity of the projects, Spyder is relatively faster than PyCharm. Since PyCharm has many plugins installed by default,  it consumes more system resources than Spyder.

As such, Spyder's lightweight architecture can make it a better choice for data scientists who work on large datasets and complex data analysis.

Spyder is the clear winner in the performance category.

Usability & Learning Curve

PyCharm has many customization options for its user interface (UI). Developers benefit from an intuitive navigation system with a clean layout. However, its extensive feature set means it has a steep learning curve, especially for beginners.

In contrast, Spyder's interface is much more straightforward. Like R, it has a variable navigation pane, a console, a plot visualization section, and a code editor, all on a single screen. The simplified view is best for data scientists who want a holistic view of model results with diagnostic charts and data frames. Also, Spyder's integration with Jupyter Notebooks makes data exploration and visualization easier for those new to data science.

Overall, Spyder is ideal for beginners, while PyCharm is more suited to experienced Python developers.


PyCharm has a free and paid version. The free community version is suitable for individual developers and teams working on a small scale. The paid version, the Professional Edition, comes in two variants – for organizations and individuals. The organization version costs US 24.90 monthly, while the individual one costs USD 9.90 monthly.

In contrast, Spyder is open-source and entirely free to use. It comes as part of the Anaconda distribution, which is also open-source and free.

In terms of cost, Sypder is a clear winner. However, in Python development, it is up to the practitioners and organizations to choose based on their business requirements.

Community Support

Both PyCharm and Spyder have active communities that provide extensive support to users. PyCharm benefits from JetBrains' strong reputation and rich experience in building Python development tools. As such, developers can utilize its large user community and get help from a dedicated support team. They also have access to many tutorials, help guides, and plugins.

Spyder leverages the Anaconda community for user support. With an active data science community, Spyder benefits from the frequent contributions of data scientists who provide help through forums and online resources, data science tutorials, frameworks, and computation libraries.

Again, it is up to the practitioners and organizations to choose a community that aligns with their task or business requirements.

PyCharm vs. Spyder: Ideal Use Cases

PyCharm vs. Spyder: Ideal Use Cases

Choosing between PyCharm and Spyder can be challenging. It’s helpful to consider some of their use cases so practitioners can decide which IDE is better for their task.

PyCharm is ideal for full-stack developers as the IDE features several web and mobile app development tools and supports end-to-end testing. It’s best for working on large-scale projects requiring extensive collaboration across several domains.

Spyder, in contrast, is suitable for data scientists, researchers, and statisticians. Its lightweight architecture allows users to perform exploratory data analysis and run simple ML models for experimentation. Instructors can use this IDE to teach students the art of data storytelling and empower them to train machine learning models efficiently.

PyCharm vs. Spyder: The Final Choice

The choice between PyCharm and Spyder ultimately depends on user needs, as both IDEs offer robust features for specific use cases.

PyCharm is best for experienced professionals who can benefit from its advanced web development tools, making it an excellent choice for building web and mobile apps. Users wishing to learn data science or work on related projects should go for Spyder.

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