Gain insights into Pythonic programming techniques. Learn about documentation, data types, safety, performance, and function design to write fast, maintainable, and correct Python code.

python3.8.tar.gz

Python3.8

Python3.8Code

This course is an invaluable resource for anyone who wants to learn the correct Pythonian way of writing highly performant code that is easy to maintain and grow.

The course is divided into six chapters: documentation tips, data types/data structures tips, safety tips, performance tips, function design tips, and general tips. Throughout each chapter, you will get hands-on experience working with real Python code to help ingrain each concept.

By the end, you will know how to make your programs correct, safe, fast, and easy to maintain.

Pythonic Programming Tips for Software Engineers

## Import wisely
Modules are the building blocks of the Python ecosystem. A typical Python program imports dozens of modules, but we should always try to minimize how many modules we import. 

If nothing in a file depends on some module, that module shouldn’t be imported. Importing a module takes time that we could better use for something else. Also, any import statement introduces a dependency. If the module goes unused, it's a false dependency. If the unnecessary  module is removed from the system, such as when it becomes obsolete, the importing code won’t run even if the module wasn't used in the actual code.

Python is efficient at recognizing whether a module has already been imported. If it was, the system ignores the import statement that attempts to import it again. It still takes time to parse the statement and check the module status, however. It’s a good reason not to import a module within a function, especially if we plan to call the function in a loop.

Finally, Python Enhancement Proposal 8 (PEP 8), essentially the Python style guide, recommends that “imports are always put at the top of the file, just after any module comments and docstrings, and before module globals and constants.” The reason for this recommendation is so that our code reader can evaluate the module dependencies at once, without going through the entire file.

That’s where readability meets performance.



# Import wisely
Modules are the building blocks of the Python ecosystem. A typical Python program imports dozens of modules, but we should always try to minimize how many modules we import. 

If nothing in a file depends on some module, that module shouldn’t be imported. Importing a module takes time that we could better use for something else. Also, any import statement introduces a dependency. If the module goes unused, it's a false dependency. If the unnecessary  module is removed from the system, such as when it becomes obsolete, the importing code won’t run even if the module wasn't used in the actual code.

Python is efficient at recognizing whether a module has already been imported. If it was, the system ignores the import statement that attempts to import it again. It still takes time to parse the statement and check the module status, however. It’s a good reason not to import a module within a function, especially if we plan to call the function in a loop.

Finally, Python Enhancement Proposal 8 (PEP 8), essentially the Python style guide, recommends that “imports are always put at the top of the file, just after any module comments and docstrings, and before module globals and constants.” The reason for this recommendation is so that our code reader can evaluate the module dependencies at once, without going through the entire file.

That’s where readability meets performance.



Learn how to import anything more efficiently in Python.

Introduction

Documentation Tips

General Tips

Data Types and Data Structures Tips

Function Tips

Performance Tips

Safety Tips

Wrapping Up

Import Tips

Import wisely