Python编程入门教程：从基础到高级

Python

Beginning

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"《Python基础教程》是一本适合新手入门的Python编程书籍，作者Dave Kuhlman，书中详细讲解了Python的基础、高级话题以及大量的练习题。" 在Python编程的世界里，初学者需要掌握的基本概念和语法是至关重要的。本书《A Python Book Beginning Python》正是为此目的而编写，旨在帮助新手快速理解和上手Python编程。书中涵盖的内容广泛且深入浅出，适合对编程有一定兴趣但没有Python基础的人群。 1. **基础Python**：这部分从介绍开始，引导读者了解Python语言的基础知识。书中提到的资源部分可能包括各种学习平台和工具，以辅助学习。作者强调Python是一种简洁明了的编程语言，易于阅读和编写。书中还介绍了如何通过交互式Python环境进行实践操作，这对于初学者来说是理解Python语法的好方法。 2. **词汇问题（Lexical Matters）**：这是编程语言的基础，包括行的处理、注释的使用、命名规则和令牌识别。Python中的行划分、注释的插入方式（如#开始的单行注释和三引号包裹的多行注释）是学习的重点。此外，了解Python中的名字（变量）和块结构（通过缩进表示代码块）也是理解Python代码逻辑的关键。 3. **文档字符串（Docstrings）**：Python鼓励良好的代码文档习惯，docstrings用于为函数、类或模块提供内嵌的文档，方便其他开发者理解代码功能。这在编写可维护的代码时尤为重要。 4. **程序结构与语句**：书中会讲解Python的控制流语句，如条件判断（if-else）、循环（for、while）以及异常处理（try-except）。这些是构建任何程序的基础。 5. **运算符**：Python支持多种运算符，包括算术运算符、比较运算符和逻辑运算符，理解这些运算符的优先级和作用对于编写正确的表达式至关重要。 6. **代码评估**：书中将讨论Python的解释执行机制，帮助读者理解代码是如何被逐行解析和执行的。 7. **高级话题**：除了基础内容，书籍还涵盖了高级主题，可能是面向对象编程、模块化、装饰器、生成器等，这些对于提高编程技巧和解决复杂问题十分有用。 8. **练习题**：作为学习的巩固，书中包含大量练习题，帮助读者实践所学，提升编程技能。《A Python Book Beginning Python》是一本全面的Python学习资料，它不仅介绍了Python的基础知识，还提供了深入话题的探讨和实践机会，对于想要踏入Python编程领域的学习者来说，无疑是一本理想的教材。

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A Python Book

following line a continuation of the current line. But, note that an opening

"context" (parenthesis, square bracket, or curly bracket) makes the back-slash

unnecessary.

1.2.2 Comments

Everything after "#" on a line is ignored. No block comments, but doc strings are a

comment in quotes at the beginning of a module, class, method or function. Also, editors

with support for Python often provide the ability to comment out selected blocks of code,

usually with "##".

1.2.3 Names and tokens

● Allowed characters: a-z A-Z 0-9 underscore, and must begin with a letter or

underscore.

● Names and identifiers are case sensitive.

● Identifiers can be of unlimited length.

● Special names, customizing, etc. -- Usually begin and end in double underscores.

● Special name classes -- Single and double underscores.

○ Single leading single underscore -- Suggests a "private" method or variable

name. Not imported by "from module import *".

○ Single trailing underscore -- Use it to avoid conflicts with Python keywords.

○ Double leading underscores -- Used in a class definition to cause name

mangling (weak hiding). But, not often used.

● Naming conventions -- Not rigid, but:

○ Modules and packages -- all lower case.

○ Globals and constants -- Upper case.

○ Classes -- Bumpy caps with initial upper.

○ Methods and functions -- All lower case with words separated by underscores.

○ Local variables -- Lower case (with underscore between words) or bumpy

caps with initial lower or your choice.

○ Good advice -- Follow the conventions used in the code on which you are

working.

● Names/variables in Python do not have a type. Values have types.

1.2.4 Blocks and indentation

Python represents block structure and nested block structure with indentation, not with

begin and end brackets.

The empty block -- Use the pass no-op statement.

Benefits of the use of indentation to indicate structure:

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A Python Book

● Reduces the need for a coding standard. Only need to specify that indentation is 4

spaces and no hard tabs.

● Reduces inconsistency. Code from different sources follow the same indentation

style. It has to.

● Reduces work. Only need to get the indentation correct, not both indentation and

brackets.

● Reduces clutter. Eliminates all the curly brackets.

● If it looks correct, it is correct. Indentation cannot fool the reader.

Editor considerations -- The standard is 4 spaces (no hard tabs) for each indentation level.

You will need a text editor that helps you respect that.

1.2.5 Doc strings

Doc strings are like comments, but they are carried with executing code. Doc strings can

be viewed with several tools, e.g. help(), obj.__doc__, and, in IPython, a question

mark (?) after a name will produce help.

A doc string is written as a quoted string that is at the top of a module or the first lines

after the header line of a function or class.

We can use triple-quoting to create doc strings that span multiple lines.

There are also tools that extract and format doc strings, for example:

● pydoc -- Documentation generator and online help system --

http://docs.python.org/lib/module-pydoc.html.

● epydoc -- Epydoc: Automatic API Documentation Generation for Python --

http://epydoc.sourceforge.net/index.html

● Sphinx -- Can also extract documentation from Python doc strings. See

http://sphinx-doc.org/index.html.

See the following for suggestions and more information on doc strings: Docstring

conventions -- http://www.python.org/dev/peps/pep-0257/.

1.2.6 Program structure

● Execution -- def, class, etc are executable statements that add something to the

current name-space. Modules can be both executable and import-able.

● Statements, data structures, functions, classes, modules, packages.

● Functions

● Classes

● Modules correspond to files with a "*.py" extension. Packages correspond to a

directory (or folder) in the file system; a package contains a file named

"__init__.py". Both modules and packages can be imported (see section import

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A Python Book

statement).

● Packages -- A directory containing a file named "__init__.py". Can provide

additional initialization when the package or a module in it is loaded (imported).

1.2.7 Operators

● See: http://docs.python.org/ref/operators.html. Python defines the following

operators:

+ - * ** / // %

<< >> & | ^ ~

< > <= >= == != <>

The comparison operators <> and != are alternate spellings of the same operator.

!= is the preferred spelling; <> is obsolescent.

● Logical operators:

and or is not in

● There are also (1) the dot operator, (2) the subscript operator [], and the

function/method call operator ().

● For information on the precedences of operators, see the table at

http://docs.python.org/2/reference/expressions.html#operator-precedence, which

is reproduced below.

● For information on what the different operators do, the section in the "Python

Language Reference" titled "Special method names" may be of help:

http://docs.python.org/2/reference/datamodel.html#special-method-names

The following table summarizes the operator precedences in Python, from lowest

precedence (least binding) to highest precedence (most binding). Operators on the

same line have the same precedence. Unless the syntax is explicitly given,

operators are binary. Operators on the same line group left to right (except for

comparisons, including tests, which all have the same precedence and chain from

left to right -- see section 5.9 -- and exponentiation, which groups from right to

left):

Operator Description

======================== ==================

lambda Lambda expression

or Boolean OR

and Boolean AND

not x Boolean NOT

in, not in Membership tests

is, is not Identity tests

<, <=, >, >=, <>, !=, == Comparisons

| Bitwise OR

^ Bitwise XOR

& Bitwise AND

<<, >> Shifts

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A Python Book

+, - Addition and subtraction

*, /, % Multiplication, division,

remainder

+x, -x Positive, negative

~x Bitwise not

** Exponentiation

x.attribute Attribute reference

x[index] Subscription

x[index:index] Slicing

f(arguments...) Function call

(expressions...) Binding or tuple display

[expressions...] List display

{key:datum...} Dictionary display

`expressions...` String conversion

● Note that most operators result in calls to methods with special names, for

example __add__, __sub__, __mul__, etc. See Special method names

http://docs.python.org/2/reference/datamodel.html#special-method-names

Later, we will see how these operators can be emulated in classes that you define

yourself, through the use of these special names.

1.2.8 Also see

For more on lexical matters and Python styles, see:

● Code Like a Pythonista: Idiomatic Python --

http://python.net/~goodger/projects/pycon/2007/idiomatic/handout.html.

● Style Guide for Python Code -- http://www.python.org/dev/peps/pep-0008/

● The flake8 style checking program. See https://pypi.python.org/pypi/flake8. Also

see the pylint code checker: https://pypi.python.org/pypi/pylint.

1.2.9 Code evaluation

Understanding the Python execution model -- How Python evaluates and executes your

code.

Evaluating expressions.

Creating names/variables -- Binding -- The following all create names (variables) and

bind values (objects) to them: (1) assignment, (2) function definition, (3) class definition,

(4) function and method call, (5) importing a module, ...

First class objects -- Almost all objects in Python are first class. Definition: An object is

first class if: (1) we can put it in a structured object; (2) we can pass it to a function; (3)

we can return it from a function.

References -- Objects (or references to them) can be shared. What does this mean?

● The object(s) satisfy the identity test operator is.

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Python编程入门教程：从基础到高级

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