Tutorials
Here you can find PyCharm tutorials and quick-start guides designed to help you write quality code, work with modern Python technologies, and run your projects reliably in local, containerized, and remote environments.
First steps
Get familiar with PyCharm and create, run, debug, and test your first Python application.
- Quick start guide
Explore the PyCharm interface and essential workflows.
- Create and run your first project
Create a Python project and get familiar with code completion, inspections, quick-fixes, and run configurations.
- Debug your first Python application
Set breakpoints, step through code, inspect variables, and use the debugger to identify and fix errors.
- Test your first Python application
Create and run tests for a Python application, inspect test results, and fix failing code with PyCharm testing tools.
Code quality and refactoring
Improve existing Python code safely with structure-aware transformations.
- PyCharm Refactoring Tutorial
Practice extracting, inlining, moving, and renaming code, changing a function signature, and extracting a superclass.
Web development
Create, run, test, and debug Python web applications with framework-aware coding assistance.
- Create and run your first Django project
Build a Django to-do application with models, views, templates, migrations, the admin interface, and tests.
- Creating Web Applications with Flask
Build a Flask application that reads data from a database, renders charts and templates, and handles authentication and editing.
Data science
Run, debug, and visualize data in a scientific Python project.
- Scientific project tutorial
Run and debug scientific Python code, execute code cells, inspect arrays, and display plots.
Version control
Learn the essential Git workflows without leaving PyCharm.
- Getting started with Git in PyCharm
Create a repository, commit and push changes, work with branches, resolve conflicts, and inspect project history.
Containers
Run and debug Python applications in Docker-based environments.
- Configure an interpreter using Docker
Configure a Docker-based Python interpreter, then run and debug a Python application inside a container.
- Configure an interpreter using Docker Compose
Configure a Docker Compose interpreter and run and debug a Django application connected to a PostgreSQL service.
Databases
Connect to a database and start working with data and SQL queries.
- Quick start with database functionality
Create a data source, connect to a database, browse objects and data, and run SQL queries in the query console.