Unleash the power of PyCharm to craft business, scientific, and web applications in Python with this definitive guide
Key Features
Learn basic to advanced PyCharm concepts to improve developer efficiency on your Python projects
Learn with practical examples that focus on efficient application development
Explore features such as code automation, graphical debugging, and remote development
Purchase of the print or Kindle book includes a free PDF eBook
Book Description
In the quest to develop robust, professional-grade software with Python and meet tight deadlines, it’s crucial to have the best tools at your disposal. In this second edition of Hands-on Application Development with PyCharm, you’ll learn tips and tricks to work at a speed and proficiency previously reserved only for elite developers.
To achieve that, you’ll be introduced to PyCharm, the premiere professional integrated development environment for Python programmers among the myriad of IDEs available. Regardless of how Python is utilized, whether for general automation scripting, utility creation, web applications, data analytics, machine learning, or business applications, PyCharm offers tooling that simplifies complex tasks and streamlines common ones. In this book, you'll find everything you need to harness PyCharm's full potential and make the most of Pycharm's productivity shortcuts. The book comprehensively covers topics ranging from installation and customization to web development, database management, and data analysis pipeline development helping you become proficient in Python application development in diverse domains.
By the end of this book, you’ll have discovered the remarkable capabilities of PyCharm and how you can achieve a new level of capability and productivity.
What you will learn
Explore basic and advanced PyCharm features
Set up, configure, and customize your Python projects in PyCharm
Develop web applications with Flask, Django, FastAPI, and Pyramid
Discover PyCharm's capabilities for database management and data visualization
Explore code automation, debugging, and remote development in PyCharm
Perform data science tasks using Jupyter notebooks, NumPy, and pandas
Who This Book Is For
This book is for Python practitioners and learners looking to boost their productivity and proficiency by harnessing the features and capabilities of PyCharm, all while gaining insights into best practices for modern application development. Basic knowledge of Python is required, making the book accessible to both newcomers and experienced Python developers.
Author(s): Bruce M. Van; Horn II Quan Nguyen
Edition: 2
Publisher: Packt
Year: 20232
Language: English
Pages: 652
Cover
Title Page
Copyright and Credits
Contributors
Table of Contents
Preface
Part 1: The Basics of PyCharm
Introduction to PyCharm – the Most Popular IDE for Python
Technical requirements
The continued success of Python
The philosophy of IDEs
PyCharm as a Python IDE
Intelligent coding assistance
Streamlined programming tools
Web development options
Scientific computing support
Understanding the Professional, Community, and Educational editions
Summary
Questions
Further reading
Installing and Configuring PyCharm
Technical requirements
Downloading PyCharm the traditional way
JetBrains Toolbox
Installing Toolbox in Windows
Installing Toolbox in macOS
Installing PyCharm with Toolbox
Launching PyCharm using Toolbox
Installing an alternate version or uninstalling
Updating PyCharm using Toolbox
Launching and registering PyCharm
Setting up PyCharm
Appearance and behavior
Working with projects
Creating a new project
Running a PyCharm project
Cloning this book’s code from GitHub
Setting up your GitHub account
Cloning the book’s repository
Summary
Questions
Further reading
Part 2: Improving Your Productivity
Customizing Interpreters and Virtual Environments
Technical requirements
Virtual environments
Creating a virtual environment by hand
Creating a project in PyCharm (revisited)
Using an existing virtual environment
Changing the interpreter for a project
Activating virtualenv
Using the integrated terminal
Working with the REPL in the console window
Working with third-party package libraries
Adding third-party libraries in PyCharm
Removing third-party libraries in PyCharm
Using a requirements.txt file
The new Python Packages window
Professional features important to virtual environments
Importing projects into PyCharm
Importing a project cloned from a repository
Dealing with invalid interpreters
Working with run configurations
PyCharm’s project files
Summary
Questions
Further reading
Editing and Formatting with Ease in PyCharm
Technical requirements
Code analysis, inspection, and suggestion
It duzunt assewm yew cna spel
It understands your code
Postfix code completion
Hippie completion
Indexing
Power Save Mode
Customizing code completion
Match case
Sorting suggestions alphabetically
Machine learning assisted completions
Showing the documentation popup in [...] ms
Parameter info
Code analysis and automated fixes
Problem detection
Syntax errors
Duplicated code
PEP-8 problems
Dead code
Method signature mismatches
The road to good code is paved with PyCharm’s intentions
Refactoring
What is refactoring?
Refactoring tools in PyCharm
Documentation
Working with docstrings
Summary
Questions
Further reading
Version Control with Git in PyCharm
Technical requirements
Version control and Git essentials
Setting up Git on your computer
Setting your default username and email address
Generating an SSH key
Adding your SSH key to your GitHub account
Setting up a repository manually
Master versus main branches in GitHub
Manually initializing the repository
Working with remotes
Adding a remote on GitHub
The first push
Making, committing, and pushing a change
Working with Git in the IDE
Version control in PyCharm
Creating a new project from scratch using VCS tooling in PyCharm
Initializing the local Git repository
Adding a remote on GitHub
Adding project files
Adding a .gitignore file
Pulling and pushing
Branching and merging
Creating a branch
Switching between branches
Merging
Viewing the branch diagram
Diffs and conflict resolution
Viewing diffs
Summary
Questions
Further reading
Seamless Testing, Debugging, and Profiling
Technical requirements
Testing, testing, 1-2-3
Unit testing in Python using PyCharm
Choosing a test library
Adding a bank account class
Testing the bank account class
Running the tests
Fixing the failing tests
Testing the fault paths
Generating tests automatically
Generating the transaction test
Working with PyCharm’s debugger
Using the debugger to find and fix our test problem
Checking test coverage
Test coverage output
Profiling performance
Profiling in PyCharm
Comparing performance versus the built-in sum() function
Viewing the call graph
Navigating using the performance profile
Performance cProfile snapshots
Summary
Questions
Further reading
Part 3: Web Development in PyCharm
Web Development with JavaScript, HTML, and CSS
Technical requirements
Introduction to HTML, JavaScript, and CSS
Writing code with HTML
Creating HTML in PyCharm
Creating an empty project
Previewing web pages
Reloading the browser view on save
Using the PyCharm HTML preview
Configuring the available browsers
Navigating structure code with the structure window
Adding the CSS
Using color selectors
Adding JavaScript
Adding some JavaScript code
Adding the elements to the HTML file
Debugging client-side JavaScript
Working with Emmet templating
HTML project types in PyCharm Professional
HTML 5 Boilerplate
Previewing and editing graphics with external tools
Uploading your site to a server
Creating a Bootstrap project
Working with modern JavaScript and NodeJS
Creating a NodeJS project
Creating a React project
Other frontend frameworks
Summary
Questions
Building a Dynamic Web Application with Flask
Technical requirements
Web basics – client-server architecture
Exploring the request-response mechanism in HTTP – how clients and servers communicate
What is Flask?
Request-response handling and routing with Werkzeug
Templating with Jinja2
A note on naming files and folders
Creating a Flask application in PyCharm Professional
Creating a dynamic web application
Setting up the static parts
Running the Flask app
Let’s make it look a little better
Adding some CSS
Making the page dynamic
Editor enhancements for working with Flask and Jinja2
Summary
Further reading
Creating a RESTful API with FastAPI
Technical requirements
There is no REST in a wicked stateless world
Creating a FastAPI project in PyCharm Professional
Running the FastAPI project
Working with PyCharm’s HTTP Requests
Examining the details of the return
We just generated a new run configuration
Using Before launch actions in run configurations
Working with HTTP Request environments
Let’s get CRUDdier and then get testier!
Getting testier
Creating the tests
Editing and debugging a full stack app by attaching projects
Creating a React app in a separate project
Attaching the project to your FastAPI project we created earlier
Summary
Questions
Further reading
More Full Stack Frameworks – Django and Pyramid
Technical requirements
What’s all this fuss about Django?
Django framework components
Creating a Django project
Structure of a Django project
Initial configuration
Running the Django project
Creating Django models
Performing migrations using manage.py
The Django admin interface
Creating a superuser and logging in
Adding the Author and Book models to the admin interface
Creating Django views
What’s with the weird Python icon in the template gutter?
Run it!
Building Pyramid applications with PyCharm
Creating a Pyramid project
Summary
Questions
Further reading
Understanding Database Management in PyCharm
Technical requirements
Relational databases in a nutshell
Structured Query Language
The two halves of SQL
Relationships
More relational structures
Database terminology uses simple English plurals
Database tooling in PyCharm
Setting up a MySQL database server with Docker
Installing and running the MySQL container
Stopping and starting the container
Connecting to data sources using PyCharm
Creating a new database
Setting the SQL dialect (this is crucial)
Grouping and color coding data sources
Database design and manipulation
Creating a table
Altering existing structures
Generating scripts
Querying the data source using SQL
Ad hoc queries
Generating SQL statements
Running the query
Exporting query results
Working with SQL files
Summary
Further reading
Part 4: Data Science with PyCharm
Turning On Scientific Mode
Technical requirements
Creating a scientific project in PyCharm
Additional configuration for science projects in PyCharm
Markdown plugins
Adding images
Installing the CSV plugin
Installing the cell mode plugin
Installing packages
Backfill your requirements.txt file
Adding some sciency code
Toggling scientific mode
Understanding the advanced features of PyCharm’s scientific projects
The documentation viewer
Using code cells in PyCharm
Using PyCharm code cells
The cell mode plugin
Summary
Questions
Dynamic Data Viewing with SciView and Jupyter
Technical requirements
Data viewing made easy with PyCharm’s SciView panel
Viewing and working with plots
Heatmaps and correlational data
Viewing and working with data
Filtering in the Data tab
Understanding IPython and magic commands
Installing and setting up IPython
Introducing IPython magic commands
Leveraging Jupyter notebooks
Understanding Jupyter basics
The idea of iterative development
Jupyter notebooks in PyCharm
Creating a notebook and adding our code
Documenting with Markdown and LaTeX
Adding our plots
Executing the cells
Odds and ends
Summary
Questions
Building a Data Pipeline in PyCharm
Technical requirements
Working with datasets
Starting with a question
Archived user data
Tappy data
Data collection
Downloading from an external source
Manually collecting/web scraping
Collecting data via third parties
Database exports
Version control for datasets
Using Git Large File Support
Data cleansing and preprocessing
A toxic data example peripherally involving ninjas
Exploratory analysis in PyCharm
Data cleansing
Exploring the second dataset
Refactoring for scale
Data analysis and insights
Starting the notebook and reading in our processed data
Using charts and graphs
Machine learning-based insights
Scripts versus notebooks in data science
Summary
Questions
Further reading
Part 5: Plugins and Conclusion
More Possibilities with Plugins
Technical requirements
Bundled plugins and JetBrains Marketplace
The plugins window
Bundled plugins
JetBrains Marketplace
Making your own plugins
Requiring plugins for your projects
Useful miscellaneous plugins
Code with me (and never be lonely again)
Remote development
Configuring remote development in PyCharm
Creating a remote project
Let’s try that again
Creating a virtual environment on the remote
Other considerations
Working with Docker
The bundled Docker plugin
Create the project
Add a Docker run configuration
Summary
Your Next Steps with PyCharm
Miscellaneous topics in PyCharm
Remote virtual environments
Working with HashiCorp Vagrant
Tracking your time
TODO list
Macros
Notifications
New features in 2023.2
Black integration
GitLab integration
Run anywhere
AI Assistant
Jupyter Notebook support for Polars
Summary and closing remarks
Further reading
Index
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