课程

Python 中的软件工程原理

基础技能水平

更新时间 2025年11月

了解模块化、文档和自动化测试，帮助你更快、更可靠地解决数据科学问题。

免费开始课程

PythonProgramming

4小时

15 视频

51 道练习

4,100 XP

66,499

成就证明

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课程描述

数据科学家若能学习软件工程领域的理念，将会受益良多，这能让您更轻松地复用代码并与协作者共享。在本课程中，您将系统学习模块化、文档与自动化测试等关键理念，并了解它们如何帮助您更快地解决数据科学问题，同时也让将来的您更省心。您还会运用所掌握的软件工程技能，编写一个用于文本分析的专属 Python 包。

先决条件

Introduction to Functions in Python

1

Software Engineering & Data Science

Why should you as a Data Scientist care about Software Engineering concepts? Here we'll cover specific Software Engineering concepts and how these important ideas can revolutionize your Data Science workflow!

Python, data science, & software engineering

The big ideas

Python modularity in the wild

Introduction to packages & documentation

Installing packages with pip

Leveraging documentation

Conventions and PEP 8

Using pycodestyle

Conforming to PEP 8

PEP 8 in documentation

2

Writing a Python Module

Become a fully fledged Python package developer by writing your first package! You'll learn how to structure and write Python code that you can be installed, used, and distributed just like famous packages such as NumPy and Pandas.

Writing your first package

Minimal package requirements

Naming packages

Recognizing packages

Adding functionality to packages

Adding functionality to your package

Using your package's new functionality

Making your package portable

Writing requirements.txt

Installing package requirements

Creating setup.py

Listing requirements in setup.py

3

Utilizing Classes

Object Oriented Programming is a staple of Python development. By leveraging classes and inheritance your Python package will become a much more powerful tool for your users.

Adding classes to a package

Writing a class for your package

Using your package's class

Adding functionality to classes

Writing a non-public method

Using your class's functionality

Classes and the DRY principle

Using inheritance to create a class

Adding functionality to a child class

Using your child class

Multilevel inheritance

Exploring with dir and help

Creating a grandchild class

Using inherited methods

4

Maintainability

You've now written a fully functional Python package for text analysis! To make maintaining your project as easy as possible we'll leverage best practices around concepts such as documentation and unit testing.

Documentation

Identifying good comments

Identifying proper docstrings

Writing docstrings

Readability counts

Using good function names

Using good variable names

Refactoring for readability

Unit testing

Using doctest

Using pytest

Documentation & testing in practice

Documenting classes for Sphinx

Identifying tools

Final Thoughts

Python 中的软件工程原理

课程完成

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