English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 3h 17m | 664 MB
Improve your application development process to build efficient apps with Python
Python is a widely used advanced programming language. Over the years, Python has turned out to be a boon for developers and it is very powerful, fast, can run everywhere, and offers flexibility. Hence it is also important to gain insights into this language and use the right tips and tricks while you develop an application, as this makes life easy for developers.
The course starts by dealing with performance issues and learning how to tackle them in an application. Distributing an application with Python is not easy but you will learn ways to distribute applications developed using Python along with GUIs, web applications, and more. Further, you will learn to test your application at different levels and use modern software at the development stage. You will also learn to expand productivity using standard and third-party tools. Finally, you will learn to protect your code quality from potential errors and detect any problem at an early stage, to prevent any issues later.
By the end, of course, you will have learned many tips and tricks while developing an application with Python; you’ll excel at this and avoid encountering major problems as a developer. So, grab this course and take your applications to the next level!
You will start by exploring Python issues and how to diagnose them. Then you will be introduced to the most popular ways to distribute Python applications. Next, you will test applications and use modern software in the development process. Finally, you will learn to expand your productivity and manage code quality to prevent any issues later.
What You Will Learn
- Use different tips, tricks, and techniques while developing Python application.
- Encounter performance issues in application and diagnose it.
- Explore most popular ways to distribute Python applications.
- Know the tools and formats to distribute packages, command-line, GUI and web applications.
- Use modern software and test application in the development process.
- Expand the productivity by using both standard and third-party tools.
- Manage code quality in order to find potential errors early in the development cycle.
Table of Contents
Python Performance
1 The Course Overview
2 Identifying Bottlenecks
3 Speeding Up I O-bound Tasks
4 Speeding Up CPU-bound Tasks
5 Move Time-critical Tasks to C C++ Libraries
6 Alternative Python Runtimes
Distributing Python Applications
7 Setuptools
8 Source Distribution and Wheels
9 Standalone Executables
10 Docker
Testing Python Applications with PyTest
11 Unit Testing and Coverage
12 Complex Tests and Coverage
13 Python Test Driven Development
14 Integration Testing
15 Python Behavior Driven Development
Productivity in Python Development
16 Managing Python Environments Efficiently
17 Python Package Management
18 Debugging and Navigating Python Bytecode
19 Prototyping Using the Python Shell and Jupyter
Code Quality
20 Linting
21 Static Code Analysis
22 Type Checking
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