My friend, if you‘ve done any amount of Python programming, you know an integrated development environment (IDE) can make a huge difference in your productivity and overall experience. As Python has exploded in popularity over the past 30 years, incredible IDEs have emerged to support developers building the next generation of apps, tools and platforms.
But with so many options to choose from, how do you determine the best Python IDE for your needs? Based on my 10+ years as a Python developer, I‘ve created this guide to save you some research time by summarizing the 10 best Python IDEs available in 2023. For each popular IDE, I‘ll give you an insider‘s view of the background, key features, and use cases where it really shines.
By the end, you‘ll have a clear framework for evaluating Python IDEs and matching one to your specific requirements as a developer, data scientist, or hobbyist coder. Let‘s get started!
A Quick History of Python
First, a quick Python history lesson. The language was conceived in the late 1980s by Guido van Rossum as a successor to ABC programming language. After going through a few early iterations, Van Rossum released Python 1.0 to the public in 1994.
Over the next decade, Python saw steady adoption especially in academic and scientific computing circles. But it truly hit an inflection point with the release of Python 2.7 in 2010 and Python 3.0 a year later, which improved support for unicode and cleaner syntax.
Python has seen meteoric growth since as a ubiquitous language powering major platforms from Instagram to Spotify to quantum computing by Rigetti. Python‘s versatility, ease of use and vibrant ecosystem of libraries make it a popular first language for aspiring coders even as it meets demands of complex enterprise applications.
So where does that leave us in 2023? Python now ranks as a top 5 language on nearly every index with over 11 million developers using it worldwide. All signs point to continued popularity.
Why Choose an IDE Over a Text Editor?
Before we dive into the IDE breakdown, it‘s important to define what sets an integrated development environment apart from regular text editors.
At a basic level, any text editor like Notepad or TextEdit allows you to write and edit code. But they lack the more advanced capabilities that accelerate coding cycles and improve organization. Chief IDE features include:
✅ Syntax highlighting – Colorization of elements like keywords and variables
✅ Autocompletion – Automatic suggestions to finish code blocks
✅ Visual debugging – Step through code to identify issues
✅ Refactoring – Safely restructure existing code
✅ Version control – Tie into systems like Git and SVN
✅ Customizability – Extend core functionality with plugins
For coding full-fledged Python applications beyond basic scripts, an IDE removes friction at every stage from writing to testing to deployment. The experience gain simply makes you a more productive developer.
Now let‘s dive into the elite options that exist today for Python coding. I‘ve ranked them according to a combination of popularity, features, and ease of use.
1. PyCharm
In my experience building Python projects over the years, JetBrain‘s PyCharm stands clearly as the most versatile and robust IDE available. While it originated with a focus on pure Python, PyCharm has evolved into a flexible IDE for not just Python but full-stack web development.
First released in 2010 by developer tools maker JetBrains, PyCharm has matured over the past decade with frequent updates that maintain impressive reliability along with cutting-edge capabilities. Simple things like project set up, running code, and debugging happen fluidly while it offers extensive depth for hardcore coders.
As Python core developer Brett Cannon said:
"PyCharm helps me focus on coding and not environment configuration while also making it easier to grasp foreign code."
Let‘s break down some of PyCharm‘s leading features:
💡 Intelligent Editor – PyCharm‘s editor makes writing clean, valid code easier through highlights for errors and code inspections with quick fixes. There‘s also top-notch auto-completion drawing from code context versus just keywords.
🔎 Code Navigation – Easily trace variables across all usages with a click while navigating directly to declarations and implementations. Useful for analyzing complex code.
🐞 Debugging – No IDE matches PyCharm‘s debugger in my opinion with the ability to debug multiple threads, processes, and remote applications. Interactive debugging helps diagnose the root cause of issues quicker.
🔌 Extensions – Take advantage of many plugins created by JetBrains and others around testing, frameworks like Django, themes, collaboration and more.
While it has a steeper learning curve than some other Python IDEs, PyCharm pays dividends for programmers working on medium to large-scale projects. Developers at Google, Amazon and NASA are among the power users.
After the 30-day free trial, a personal license costs $199 per year while a free community edition provides great function despite some limitations. For professional developers, PyCharm is an easy choice providing amazing ROI.
2. Visual Studio Code
Over the last 5 years, Visual Studio Code (VS Code) from Microsoft has likely seen the fastest adoption of any development environment in history. It has become many programmers‘ go-to code editor for its speed, ease of use and breadth of language support.
As an open-source project, VS Code benefits from contributions by developers across the industry. This allows Microsoft to focus squarely on the core user experience leading to very rapid iteration. New releases ship monthly!
Here are some standout features for working with Python:
📘 IntelliSense – Code completion and other insights aid discovery of APIs and faster statement writing.
⏱️ Lightning Fast – Blazing editor speed achieved through fine-tuned use of Electron framework.
🔬 Jupyter Notebook – Deep integration with Jupyter for data exploration and visualization right inside VS Code.
📑 Zen Mode – Distraction-free coding by hiding all interface components except editor (personal favorite feature).
While lighter weight than traditional IDEs, VS Code punches above its class through expansive functionality via extensions. There are thousands of extensions for added languages, debuggers, linters, and code generators.
As Wes McKinney, creator of Pandas, put it:
“Fully customizable, VS Code feels like the most modern Python editor available with first-class support.”
I encourage new Python coders to make VS Code their default development environment for the your first 6 months before exploring heavier tools. It‘s beginner-friendly out of the box yet infinitely expandable.
Did I mention it‘s 100% free for personal and commercial use? VS Code is a gift that keeps on giving.
3. Spyder IDE
Shifting gears a bit, Spyder serves as an excellent complementary IDE for Python-centric scientific computing and data science versus general development. Its focus allows customization specifically for interactive workflows to experiment, test hypotheses, and visualize outcomes.
Originally created in the mid-2000s by Stanford roboticist Carlos Cordoba, Spyder started as an academic project before adoption broadened. By 2017, it joined the NumFOCUS nonprofit umbrella along with libraries like Jupyter, NumPy and Pandas for long-term support.
Spyder differentiates itself through native data/science offerings:
🔬 Variable Explorer – Interactively work with data pipelines from data frames to matrices.
📈 Interactive Graphics – Render stunning visuals like plots, histograms and time series from test data.
⚙️ Profiler – Measure code performance by querying runtime statistics.
When analytics expert Wes McKinney needs to debug a gnarly issue with Pandas, Spyder is often his toolkit of choice.
“No IDE makes it easier to inspect data and objects interactively for solving data problems,” he said.
For programmers applying Python for mission-critical modeling, simulations and analytics, check out Spyder.
4. Jupyter Notebook
No list of Python IDEs is complete without Jupyter Notebook invented by data scientist Fernando Pérez in 2014. It‘s uniquely geared for fast prototyping and sharing results through documents blending live code, equations, visualizations and explanatory text.
Rapid experimentation meets instant documentation!
Under the leadership of Brian Granger, Project Jupyter was spun out in early 2015 with backing from institutions like Cal Poly, NYU and UC Berkeley. This support expanded features and accessibility for Jupyter notebooks which have become integral to scientific computing and AI research.
Notable aspects include:
📝 Notebook Documents – Combine narrative text, executable Python, and rich media within sharable notebook documents.
🔢 Over 40 Languages – Originally designed for Python, now supports R, Julia, Javascript, Ruby, C++ among other languages.
☁️ Client-Server Model – Run Jupyter as a local app or hosted notebooks running in the cloud across devices.
In recent years, Jupyter has broadened from pure academics into wider business analytics usage facilitated by managed services like AWS SageMaker Studio Lab. Jupyter notebooks and its descendants like Jupyter Book are now ubiquitous for codifying complex workflows.
UC Berkeley data science instructor Rachel Thomas sums it up best:
“Jupyter Notebook is unmatched for rapid exploration and collaboration at the bleeding edge of data science.”
So aspiring data scientists should definitely add Jupyter to their toolkit!
5. Wing Python IDE
As we round out my top 5 Python IDE picks, Wing from Wingware brings impressive depth of functionality across various aspects of Python coding — from writing to testing code and deploying larger programs.
Founded in 1996 and based in New York, Wingware takes pride in attending to working developers‘ everyday pain points. For 26 years and running, they‘ve fine-tuned an IDE that cuts down frustration while staying nimble. Customers range from federal space agencies to automotive and manufacturing giants.
Standout capabilities include:
💼 Project Management – Well-designed system for organizing files and accessing tools like source control.
🔍️ Code Intelligence – Comprehensive tooling via static analysis to hint at runtime types and structures.
🐞 Debugger – Can debug code launched outside the IDE or remotely over SSH. Lifesaver feature!
In addition, Wing raises the bar for customizability through schemes, layouts and130+ settings to adapt to any programmer‘s flow. It offers strong support for web frameworks like Django and Flask with code quality checks.
Brett Cannon is a fan:
"I‘m constantly amazed at the breadth and quality of Wing‘s Python code intelligence!"
For enterprise-grade capability across debugging, code navigation, and refactoring, be sure to trial Wing IDE.
Honorable Mentions
Beyond the top 5, many other Python IDE options exist that may better match a developer‘s specific needs:
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Thonny – Streamlined for new coders to learn Python with interactive features.
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Atom – Highly customizable text editor with strong extension ecosystem.
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Eclipse + Pydev – Legendary Java IDE adapted for Python.
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Sublime Text – Blazing fast and lightweight editor.
I encourage you to trial 1-2 IDEs over a few weeks as a key step to improve your coding productivity and unlock more creative programming. The time invested upfront pays back exponentially over your career. Happy Python coding my friend!
Key Takeaways
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Python has seen immense growth over 30 years to become a top 5 global programming language.
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Integrated development environments (IDEs) streamline coding with features like autocompletion, debugging and extensions.
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Leading Python IDEs include PyCharm, Visual Studio Code, Spyder, Jupyter Notebook and Wing IDE.
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Carefully evaluate options based on your goals and skill level to determine the best IDE fit.
