VOOZH about

URL: https://thenewstack.io/7-must-have-python-tools-for-ml-devs-and-data-scientists/

⇱ 7 Must-Have Python Tools for ML Devs and Data Scientists - The New Stack


TNS
SUBSCRIBE
Join our community of software engineering leaders and aspirational developers. Always stay in-the-know by getting the most important news and exclusive content delivered fresh to your inbox to learn more about at-scale software development.
REQUIRED
It seems that you've previously unsubscribed from our newsletter in the past. Click the button below to open the re-subscribe form in a new tab. When you're done, simply close that tab and continue with this form to complete your subscription.
The New Stack does not sell your information or share it with unaffiliated third parties. By continuing, you agree to our Terms of Use and Privacy Policy.
Welcome and thank you for joining The New Stack community!
Please answer a few simple questions to help us deliver the news and resources you are interested in.
REQUIRED
REQUIRED
REQUIRED
REQUIRED
REQUIRED
Great to meet you!
Tell us a bit about your job so we can cover the topics you find most relevant.
REQUIRED
REQUIRED
REQUIRED
REQUIRED
REQUIRED
Welcome!

We’re so glad you’re here. You can expect all the best TNS content to arrive Monday through Friday to keep you on top of the news and at the top of your game.

What’s next?

Check your inbox for a confirmation email where you can adjust your preferences and even join additional groups.

Follow TNS on your favorite social media networks.

Become a TNS follower on LinkedIn.

Check out the latest featured and trending stories while you wait for your first TNS newsletter.

PREV
1 of 2
NEXT
VOXPOP
As a JavaScript developer, what non-React tools do you use most often?
Angular
0%
Astro
0%
Svelte
0%
Vue.js
0%
Other
0%
I only use React
0%
I don't use JavaScript
0%
Thanks for your opinion! Subscribe below to get the final results, published exclusively in our TNS Update newsletter:
NEW! Try Stackie AI
From clobbered drafts to real-time sync
Apr 14th 2026 10:00am, by David Moore
TypeScript 6.0 RC arrives as a bridge to a faster future
Mar 14th 2026 9:00am, by Darryl K. Taft
Mastra empowers web devs to build AI agents in TypeScript
Jan 28th 2026 11:00am, by Loraine Lawson
2023-02-20 03:00:26
7 Must-Have Python Tools for ML Devs and Data Scientists
AI / Frontend Development / Python / Software Development

7 Must-Have Python Tools for ML Devs and Data Scientists

Python has an easy learning curve, however there are a range of development tools to consider if you're to use Python to its full potential.
Feb 20th, 2023 3:00am by Alexander T. Williams
👁 Featued image for: 7 Must-Have Python Tools for ML Devs and Data Scientists
Image via Shutterstock 

From building complex machine learning applications, to creating intuitive graphical user interfaces, Python is a popular programming language that has become the preferred choice for software developers and data scientists alike. Python’s data science capabilities continue to be explored, especially for advanced data analysis and the creation of deep learning products. Python outperforms rival programming languages, such as C++, in this regard.

Python has a relatively easy learning curve and is regarded as very beginner-friendly. However, there are also a range of tools that need to be mastered if you are to use Python to its full potential.

In this article, we will focus on seven of the best Python tools that all programmers should consider learning in 2023, to help streamline the coding process and simplify time-consuming tasks. The tools featured in this article range from integrated development environments (IDEs) such as PyCharm, to the browser testing tool Selenium.

What Can You Do With Python?

When developing with Python, it is important to compile a suite of tools that can make the process more efficient, helping you to focus on the core product without having to worry about some of the more tedious aspects of coding. This is why we have compiled a list of some of the most common project types created by Python programmers.

  • Software development — Web, game, graphical-user interface (GUI) or command-line interface (CLI). Python does not have built-in mobile development capabilities.
  • Data science and mathematics — Science computing, data analysis, visualization and web scraping.
  • Machine learning — Improving speech recognition, for example.
  • Develop embedded systems and robots — Systems can include Raspberry Pi, BBC micro:bit and MicroPython.
  • Automate and speed up workflows — DevOps, development environment, database systems, software packaging and deployment, and software testing.

The Best Python Development Tools of 2023

Our list of seven Python development tools can help programmers maximize the potential of Python, helping them to develop complex and efficient products in less time and using less code.

1. PyCharm IDE

Created by JetBrains, PyCharm is regarded as the best IDE available for Python, allowing developers to code and install packages extremely quickly.

With PyCharm, developers can create efficient code with an autocomplete feature suggesting usable code to save a lot of time. It also highlights code syntaxes so they can be easily located, as well as flagging up any errors such as typos or missing code elements.

PyCharm is the most popular IDE for Python due to its extensive range of tools and features, making the process as hassle-free as possible.

2. Jupyter Notebook

Much loved by data scientists and machine learning engineers, Jupyter Notebook is another IDE that makes creating and executing code much easier. This is because Jupyter allows programmers to test just one cell of the code instead of the whole program, speeding up the process significantly.

Jupyter Notebook works within the browser, and titles and notes can be added to help contributors understand your code better, making it one of the best collaboration IDEs out there. In addition, your organized code and notes can all be exported as a PDF, or .ipynp if you are planning to create a 3D visual.

3. Pip Package

Knowing how to program in Python is just part of the puzzle. To become a Python specialist in regards to data science, data analysis and machine learning, you will need to install a range of additional packages. Pip Package is a great tool that allows you to install them easily.

Pip is used by the majority of Python developers who generally consider it a must-have tool. It can quickly and simply install any Python package with an easy search function.

Note: Update Pip regularly to ensure you have access to the latest packages and to make sure the tool works to its optimal ability.

4. Keras

Keras works as an API built into the machine learning library TensorFlow as well as other libraries such as CNTK and Theano, making it a powerful artificial intelligence (AI) tool. Keras effectively creates a comprehensive neural network that can help to recreate brain processes, meaning it can be used to develop a range of machine learning or AI products.

It is entirely open source and is backed by a strong community of contributors who have introduced new features to make the creation of these neural networks even easier. In some cases, networks can be created with a simple command-line system and stacking layers.

5. Selenium

Selenium is a tool that allows developers to test web applications across multiple browsers. Using Python, the programmer can design simple scripts or conduct automation testing across any browser of their choosing, also working alongside other programming languages such as Java, Ruby and C#.

Selenium supports platforms such as Windows, Mac iOS and Linux, and of course supports all the top browsers, including Chrome, Firefox and Safari.

6. Python Anywhere

If you want to test Python without downloading it onto your computer, then Python Anywhere allows you to host and run your code online.

This is great for beginners or anyone who is just curious about what Python can do, allowing you to create code within your web browser. The basic version of Python Anywhere allows developers to test code elements and check the results. However, if this is not enough, a premium version offers more processing power, which costs $5 a month.

7. Sphinx

Code hosting websites like GitHub provide extensive libraries of code that can be applied to Python, plus many developers create their own open source software that is available to anyone. For people to apply this code or execute open source applications, documentation is required to instruct the user on how to use them.

This is where Sphinx comes in. Sphinx is a tool that generates documentation for code and programs written in Python, working on the terminal or cmd for Windows. It does this by asking questions about who has developed the program, its name, what it does, its release date and more.

Once Sphinx has gathered enough information, it will then generate documentation that is available in a range of file formats. This includes HTML so it can be directly published on a web page, or PDF so it can be packaged with the code.

Python Development Tools to Learn in 2023

Python is an extremely popular programming language that can be used to create projects that range anywhere from artificial intelligence to automating workflows. To improve Python further and speed up development times, check out the above tools to automate and simplify a range of tasks.

For example, Pip helps users effortlessly install new packages, while Sphinx can generate high-quality documentation to be packaged with any open source code or programs. Making use of such tools can help developers tackle much more ambitious and innovative projects in 2023.

TRENDING STORIES
Alexander Williams is a full stack developer and technical writer with a background working as an independent IT consultant and helping new business owners set up their websites.
Read more from Alexander T. Williams
SHARE THIS STORY
TRENDING STORIES
SHARE THIS STORY
TRENDING STORIES
TNS DAILY NEWSLETTER Receive a free roundup of the most recent TNS articles in your inbox each day.
The New Stack does not sell your information or share it with unaffiliated third parties. By continuing, you agree to our Terms of Use and Privacy Policy.