An overview of the Python programming language

Introduction

Python is a fairly straightforward programming language used by YouTube. It’s also used by analysts to understand data, and by scientists to build models and make predictions. Python is used to write bots, create simple games, and train neural networks. For example, you can use it to write a script that will automatically examine all provided files, find the necessary words, extract the relevant fragments, and compile the data into an Excel spreadsheet.

Syntax

Python’s syntax is intuitive and easy to read. Unlike some other languages, you don’t need to enclose every line in parentheses or specify variable types—you just write what you want to do.

Here’s a simple example asking for a username:

name = input("What is your name? ")
print("Hello, " + name + "!")

Here’s the Junior level code, but with elements that show the specialist has some familiarity with the structure and logic of the language:

import csv

def filter_expensive_orders(input_file, output_file, min_total=10000):
    with open(input_file, mode='r', encoding='utf-8') as infile:
        reader = csv.DictReader(infile)
        filtered = [row for row in reader if float(row['total']) > min_total]

    if filtered:
        with open(output_file, mode='w', encoding='utf-8', newline='') as outfile:
            writer = csv.DictWriter(outfile, fieldnames=filtered[0].keys())
            writer.writeheader()
            writer.writerows(filtered)
            print(f"Found and saved {len(filtered)} orders are more expensive {min_total}")
    else:
        print("No matching orders found.")

# Usage example
filter_expensive_orders("orders.csv", "expensive_orders.csv")

This code opens a CSV file of orders, finds those with a total greater than 10,000, and saves them to a new file.

Although Python is used in a variety of fields, its syntax remains largely unchanged. This is why it’s often called universal: developers don’t need to switch programming languages, and they can solve a wide variety of problems while remaining within a familiar environment. For example, if you need to find all PDF files in a folder, you can write code like this:

import os

for file in os.listdir("reports"):
    if file.endswith(".pdf"):
        print("File found:", file)

Here’s an example for web development: a small API server that responds to requests:

from flask import Flask

app = Flask(__name__)

@app.route("/")
def hello():
    return "Hello, Artem!"

Now, an example from machine learning. Here’s how to train a linear regression model:

from sklearn.linear_model import LinearRegression

model = LinearRegression()
model.fit(X, y)

You can learn more about Python syntax in our Python course. This course will introduce you to the fundamentals of the Python programming language and provide a solid foundation for writing meaningful programs. The material is suitable for both those just starting and those looking to refresh their knowledge.

Python frameworks

We’ve compiled a table of popular Python frameworks. We explain their purpose and provide examples of projects using them:

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Five Reasons Why Python Is Indispensable

Every language has its strengths. We’ve compiled five advantages of Python.

There is a ready-made module for any task

The Python Package Index (PyPI) is the official repository for libraries. As of early 2025, it contained over 600,000 projects covering virtually every area—from machine learning (TensorFlow, PyTorch) to web development (Django, Flask) and data analysis (Pandas, NumPy). There’s a solution for virtually every task, making it easier for beginner developers.

Suitable for data analysis and machine learning

Python has become the standard in data science and machine learning, two of the most in-demand tech fields today. Libraries like Scikit-learn, TensorFlow, and PyTorch provide tools that are difficult to find in such a convenient and integrated form in other languages.

For example, Jupyter Notebook allows you to write and execute code piecemeal, instantly see the results, and add explanations in text format. For example, you can write code to process data, plot a graph, and add a description, all in a single document.

Parses, automates, and simplifies routine tasks

Python is great for automating routine tasks. It makes it easy to work with files, parse data from web pages, manage systems, and even solve DevOps problems. Thanks to its simplicity and clear syntax, Python is often more convenient than Bash or PowerShell.

Integrates into other languages

For example, you can use Python to create C/C++ extensions to speed up critical parts of your program. This is especially useful for tasks that require high performance, such as complex mathematical calculations, real-time processing of large amounts of data, graphics processing, or highly complex machine learning algorithms. Conversely, Jython allows you to combine Python with Java to use Python code in Java applications.

It is used for non-trivial tasks

Some Python libraries have become indispensable in their fields—so much so that there are few comparable libraries in other languages ​​with the same level of usability, support, and community. For example:

• OpenCV is one of the most popular computer vision tools, and is also available in C++, but it was its Python wrapper (a way to use a complex library in another language through simple Python code) that made it popular.
• NLTK and spaCy are powerful tools for natural language processing, especially useful when paired with Python.
• Django and Flask are frameworks that allow you to quickly deploy a web application, and it is in the Python ecosystem that they have become as simple and accessible as possible.

What can’t be done in Python?

Python is inferior to other programming languages ​​in the following areas:

• Create something at a “low” level, for example, write drivers, firmware, or work with hardware.
• Build a mobile app. This is possible in Python, and there are frameworks like Kivy. For example, there’s a case study on Habr where someone actually built a working app. But in practice, other tools are more often chosen: Swift for iOS, Kotlin for Android, or the cross-platform Flutter.
• Develop a high-performance game. Simple games can be written in Python, while complex games with 3D graphics and complex physics are developed in engines like Unity and Unreal.

Another thing: Python is an interpreted language, meaning it runs slower than compiled languages ​​like C++ or Rust. Therefore, if speed is a priority, critical sections of code are written in the aforementioned languages, and the rest is written in Python. For example, this approach is used in machine learning projects, where a model is trained and tested in Python, and its core is rewritten in C++ to speed up production.

Python is otherwise easy to understand, but using it confidently requires practice. 365education courses are specifically designed to apply knowledge to real-world situations: students are writing code almost from the very first day of training, understanding common work-related problems, and learning to think like a developer.

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