Python Programming Language

Python is a powerful programming language that can be used for almost any computer work. Python programs tend to be shorter and easier to read than programs written in C, Java, or C++. The tradeoff is that Python programs tend to run 100x slower than programs written in other languages. Therefore, Python is often used as a “glue” language, to glue together modules written in higher-performing languages. Python has a huge “batteries included” standard library, so you don’t have to install extra software to accomplish many tasks, and you can easily install numerous mature software packages if you need more functionality.

Companies tend to use Python for data analysis and prototyping. They rewrite slow parts in a faster language like C or C++ for production work.

Should I Learn Python?

Python is a great choice for:

• intro programming courses
• data analysis
• rapid prototyping
• scripting
• coding interviews

Beginners will love how much they can accomplish with just a few lines of Python code.

What’s So Hard About Python?

Beginners tend to struggle with:

• References: Python uses objects and references everywhere. Beginners may think they are making a copy when they do an assignment statement, but that would be wrong.
• Data Types: Just because you don’t see them in your code, doesn’t mean you can ignore them.
• Strings vs Bytes: You must be careful not to mix bytes with strings, since strings contain Unicode code points, and bytes just contain 8-bit values.
• Dunder Methods: Double-underscore methods implement many special Python behaviors.
• Messy Standard Library: Python’s standard library contains dozens of modules, many of which are decades old. Therefore, there are often many ways to accomplish the same goal.
• Dynamic Structure: Python allows objects to add methods and attributes at runtime, which means you can’t always tell what the properties of an object will be by just looking at the source code.

How Can You Help Me?

Our help starts where artificial intelligence tools like Claude®, Microsoft Copilot®, and ChatGPT® fall short:

• Deep Analysis: If your AI tools can’t find the bug, we can walk you through the debugging process.
• Popular Tools: We can help you use Python with Pycharm for development, Pydantic for data modeling, the new uv tool from Astral for package management, and popular data science tools like seaborn, matplotlib, pyplot, numpy, scipy, etc.
• Test-Taking Tips: Your course will usually expect you to use specific Python libraries and functions. Therefore, you can’t just use any techniques you find online. We can help you learn just the knowledge you need for projects and tests.
• Deep Knowledge: Our tutors have experience using Python at work or on personal projects. Get answers to your questions when artificial intelligence tools can’t help you.