From 8692fe62d9eb7890988ed152edd67f828450dc9f Mon Sep 17 00:00:00 2001 From: satori1995 Date: Mon, 6 Jan 2025 18:33:32 +0800 Subject: [PATCH] =?UTF-8?q?import=E9=BB=91=E7=9B=92=E6=8E=A2=E6=B5=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- ...21\347\233\222\346\216\242\346\265\213.md" | 721 ++++++++++++++++++ src/SUMMARY.md | 1 + src/images/273.png | Bin 0 -> 88275 bytes src/images/274.png | Bin 0 -> 122150 bytes src/images/275.png | Bin 0 -> 147713 bytes 5 files changed, 722 insertions(+) create mode 100644 "src/83.import\346\234\272\345\210\266\347\232\204\351\273\221\347\233\222\346\216\242\346\265\213.md" create mode 100644 src/images/273.png create mode 100644 src/images/274.png create mode 100644 src/images/275.png diff --git "a/src/83.import\346\234\272\345\210\266\347\232\204\351\273\221\347\233\222\346\216\242\346\265\213.md" "b/src/83.import\346\234\272\345\210\266\347\232\204\351\273\221\347\233\222\346\216\242\346\265\213.md" new file mode 100644 index 0000000..92ac530 --- /dev/null +++ "b/src/83.import\346\234\272\345\210\266\347\232\204\351\273\221\347\233\222\346\216\242\346\265\213.md" @@ -0,0 +1,721 @@ +## 楔子 + +同 C++ 的 namespace,Python 通过模块和包来实现对系统复杂度的分解,以及保护名字空间不受污染。通过模块和包,我们可以将某个功能、某种抽象进行独立的实现和维护,在 module 对象的基础之上构建软件。这样不仅使得软件的架构清晰,而且也能很好地实现代码复用。 + +## 标准 import + +sys 这个模块恐怕是使用最频繁的 module 对象之一了,我们就从这位老铁入手。Python 有一个内置函数 dir,这个小工具是我们探测 import 的杀手锏。如果你在交互式环境下输入 dir(),那么会打印当前 local 名字空间里的所有符号,如果有参数,比如 dir(xx),则输出 xx 指向对象的所有属性。我们先来看看 import 动作对当前名字空间的影响: + +~~~Python +>>> dir() +['__annotations__', '__builtins__', '__doc__', '__loader__', '__name__', '__package__', '__spec__'] +>>> +>>> import sys +>>> +>>> dir() +['__annotations__', '__builtins__', '__doc__', '__loader__', '__name__', '__package__', '__spec__', 'sys'] +~~~ + +我们看到进行了 import 动作之后,当前的 local 名字空间增加了一个 sys 符号。 + +~~~python +>>> type(sys) + +~~~ + +而且通过 type 操作,我们看到这个 sys 符号指向一个 module对象,在底层它是一个 PyModuleObject。当然啦,虽然写着类型是 \,但是这个类无法直接使用,因为解释器没有将它暴露出来。不过它既然是一个 class,那么就一定继承 object,并且元类为 type。 + +~~~python +>>> sys.__class__.__class__ + +>>> sys.__class__.__base__ + +~~~ + +这与我们的分析是一致的。言归正传,我们看到 import 机制影响了当前的 local 名字空间,使得加载的 module 对象在 local 空间成为可见的。而引用该 module 的方法正是通过 module 的名字,即这里的 sys。 + +实际上,这和我们创建一个变量是等价的,比如 a = 123,会先创建一个 PyLongObject,然后让变量 a 指向它。而上面的 import sys 也是同理,先创建一个 PyModuleObject,然后让变量 sys 指向它。 + +不过这里还有一个问题,来看一下: + +~~~Python +>>> sys + +~~~ + +我们看到 sys 是内置的,说明模块除了可以是真实存在的文件之外,还可以内嵌在解释器里面。但既然如此,那为什么不能直接使用,还需要导入呢?其实不光是 sys,在 Python 初始化的时候,就已经将一大批的 module 对象加载到了内存中。这些 module 对象都是使用 C 编写,并内嵌在解释器里面的,因为它们对性能的要求比较严苛,比如 \_random、gc、\_pickle 等等。 + +但是为了让当前 local 名字空间能够达到最干净的效果,Python 并没有将这些符号暴露在 local 名字空间中。而是需要开发者显式地通过 import 机制将符号引入到 local 名字空间之后,才能让程序使用符号背后的对象。 + +凡是加载进内存的 module 对象都会保存在 sys.modules 里面,尽管当前的 local 空间里面没有,但 sys.modules 里面是跑不掉的。 + +~~~Python +import sys + +# sys.modules 是一个字典,里面保存了 "module 对象的名字" 到 "module 对象" 的映射 +# 里面有很多模块,这里就不打印了,但令我感到意外的是,居然把 numpy 也加载进来了 +modules = sys.modules + +np = modules["numpy"] +arr = np.array([1, 2, 3, 4, 5]) +print(np.sum(arr)) # 15 + + +# os 模块我们没有导入,但是它已经在内存中了 +# 虽然当前 local 空间没有,但它在 sys.modules 里面 +os_ = modules["os"] + +# 手动导入,会从 sys.modules 里面加载 +import os +print(id(os) == id(os_)) # True +~~~ + +一开始这些 module 对象是不在 local 空间里面的,除非显式导入,但即便我们导入,这些 module 对象也不会被二次加载。因为在解释器启动后,它们就已经被加载到内存里面了,存放在 sys.modules 中。 + +因此对于已经在 sys.modules 里面的 module 对象来说,导入的时候只是将符号暴露到 local 空间里面去,所以代码中的 os 和 os_ 指向同一个 module对象。如果我们在 Python 启动之后,导入一个 sys.modules 中不存在的 module 对象,那么才会进行加载、然后同时进入 sys.modules 和 local 空间。 + +### 自定义 module + +对于那些内嵌在解释器里面的 module 对象,如果 import,只是将符号暴露在了 local 名字空间中。下面我们看看对那些在初始化的时候没有加载到内存的 module 对象进行 import 的时候,会出现什么样的动作。 + +这里就以模块为例,当然正如我们之前说的,一个模块的载体可以是 py 文件或者二进制文件,而 py 文件可以是自己编写的、也可以是标准库中的、或者第三方库中的。那么下面我们就自己编写一个 py 文件作为例子,探探路。 + +~~~Python +# a.py +a = 1 +b = 2 +~~~ + +以上是 a.py,里面定义了两个变量,然后导入它。 + +~~~Python +import sys + +print("a" in sys.modules) # False + +import a +print("a" in sys.modules) # True +print(dir()) # [..., 'a', 'sys'] + +print(id(a)) # 2653299804976 +print(id(sys.modules["a"])) # 2653299804976 + +print(type(a)) # +~~~ + +type(a) 的结果表明 import 机制确实创建了一个新的 module对象,而且也正如我们之前所说,解释器对 a 指向的 module 对象进行导入时,会同时将其引入到 sys.modules 和当前的 local 名字空间中,它们指向的是同一个 PyModuleObject。然后我们再来看看这个 module对象: + +~~~Python +import a + +# 查看 a 里面的属性 +print(dir(a)) +""" + +['__builtins__', '__cached__', '__doc__', '__file__', '__loader__', + '__name__', '__package__', '__spec__', 'a', 'b'] +""" + +print(a.__name__) # a +print(a.__file__) # D:\satori\a.py +~~~ + +可以看到,module 对象内部实际上是通过一个字典来维护所有的属性,里面有 module 的元信息(名字、文件路径)、以及 module 对象的内容。因为 module 对象本身就是 \ 的实例对象,它有自己的属性字典,用来维护内部的属性。 + +> 另外,如果此时你查看 a.py 所在目录的 \_\_pycache\_\_ 目录,会发现里面有一个 a.pyc,说明解释器在导入的时候先生成了 pyc,然后再导入 pyc。 + +并且我们通过 dir(a) 查看的时候,发现里面有一个 \_\_builtins\_\_ 符号,那么这个 \_\_builtins\_\_ 和我们之前说的那个 \_\_builtins\_\_ 是一样的吗? + +~~~Python +# 获取 builtins 可以通过 import builtins 的方式导入 +# 但其实也可以通过 __builtins__ 获取 +print( + id(__builtins__), type(__builtins__) +) # 140265846506256 + +print( + id(a.__dict__["__builtins__"]), type(a.__dict__["__builtins__"]) +) # 140265846500608 +~~~ + +尽管它们都叫 \_\_builtins\_\_,但一个是 module对象,一个是字典。直接访问 \_\_builtins\_\_ 获取的是一个 module 对象,int、str、globals 和 \_\_builtins\_\_.int,\_\_builtins\_\_.str,\_\_builtins\_\_.globals 是等价的。 + +但 a.\_\_dict_\_["\_\_builtins\_\_"] 是一个字典,这就说明两者从性质上就是不同的东西,但即便如此,就真的一点关系也没有吗? + +~~~Python +import a + +print(id(__builtins__.__dict__)) # 2791398177216 +print(id(a.__dict__["__builtins__"])) # 2791398177216 +~~~ + +我们看到还是有一点关系的,和类、类的实例对象一样,每一个 module 对象也有自己的属性字典 \_\_dict\_\_,记录了自身的元信息、里面存放的内容等等。对于 a.\_\_dict\_\_["\_\_builtins\_\_"] 来说,拿到的就是 \_\_builtins\_\_.\_\_dict\_\_。所以说 \_\_builtins\_\_ 是一个模块,但这个模块有一个属性字典,而这个字典可以通过 module对象.\_\_dict\_\_["\_\_builtins\_\_"] 来获取。 + +因为任何一个模块都可以使用 \_\_builtins\_\_ 里面的内容,并且所有模块对应的 \_\_builtins\_\_ 都是一样的。所以当你直接打印 a.\_\_dict\_\_ 的时候会输出一大堆内容,因为输出的内容里面不仅有当前模块的内容,还有 \_\_builtins\_\_.\_\_dict\_\_。 + +~~~python +import a + +# a.__dict__["__builtins__"] 就是 __builtins__.__dict__ 这个属性字典 +# 而 __builtins__.__dict__["list"] 又是 __builtins__.list +# 说白了,就是我们直接输入的 list +print(a.__dict__["__builtins__"]["list"] is list) # True +print( + # 等价于 __builtins__.__dict__["list"]("abcd") + # 等价于 __builtins__.list("abcd") + # 等价于 list("abcd") + a.__dict__["__builtins__"]["list"]("abcd"), +) # ['a', 'b', 'c', 'd'] + +# 回顾之前的内容 +# 我们说,模块名是在模块的属性字典里面 +print(a.__dict__["__name__"] == a.__name__ == "a") # True + +# __builtins__ 里面的 __name__ 就是 builtins +print(__builtins__.__dict__["__name__"]) # builtins + +# 对于当前文件来说也是一个模块,它的 local 空间也有 __name__ +# 并且如果它做为启动文件,那么 __name__ 会等于 "__main__" +# 如果是被导入的,那么它的 __name__ 会等于文件名 +print(__name__) # __main__ + +# __main__ 也是一个模块 +# 注意:如果这么做的话,那么该文件必须是启动文件 +name = "古明地觉" +from __main__ import name as NAME +print(NAME) # 古明地觉 +~~~ + +所以可以把模块的属性字典,看成是 local 空间(也是 global空间)、内置空间的组合。 + +## 嵌套 import + +我们下面来看一下 import 的嵌套,所谓 import 的嵌套就是指 import a、但是在 a 中又 import b,我们来看看这个时候会发生什么有趣的动作。 + +~~~python +# a.py +import tornado +~~~ + +在 a.py 中我们导入了 tornado 模块,然后再来导入 a。 + +~~~python +import a +import sys +import tornado + +print( + a.tornado is tornado is sys.modules["tornado"] is a.__dict__["tornado"] +)  # True +~~~ + +首先 import a 之后,我们通过 a 这个符号是可以直接拿到其对应的模块的。但是在 a 中我们又 import tornado,那么通过 a.tornado 可以拿到 tornado 模块。 + +但第二次导入 tornado 的时候,会怎么样呢?首先在 a 中已经导入了 tornado,那么 tornado 就已经在 sys.modules 里面了。因此当再次导入 tornado 的时候,会直接从 sys.modules 里面查找,而不会二次加载。为了更直观的验证,我们再举一个例子: + +~~~python +# a.py +print(123) + +# b.py +import a + +# c.py +import a +~~~ + +以上是三个文件,每个文件只有一行代码,我们来导入 a、b、c。 + +~~~Python +import a +import b +import c +""" +123 +""" +~~~ + +当导入一个不在 sys.modules 里面的模块时,会先从硬盘中加载相应的文件,然后逐行解释执行里面的内容,构建 PyModuleObject 对象,最后加入到 sys.modules 和 local 空间中。当第二次导入的时候,对应的模块已经存在 sys.modules 当中了,因此直接将符号暴露到当前的 local 空间里面即可,不会再执行里面的内容。 + +所以我们可以把 sys.modules 看成是一个大仓库,里面保存了**模块名**到**模块对象**的映射,任何导入的模块都在这里面。如果导入时,发现 sys.modules 里面已存在,那么直接通过字典获取即可,这样可以避免重复加载。 + +![](./images/273.png) + +## 导入包 + +我们写的多个逻辑或者功能上相关的函数、类可以放在一个模块里面,那么多个模块是不是也可以组成一个包呢?如果说模块是管理 class、函数、变量的机制,那么包就是管理模块的机制。当然啦,多个小的包又可以聚合成一个更大的包。 + +因此在 Python 中,模块是由一个单独的文件来实现的,可以是 .py 文件、或者二进制文件。而对于包来说,则是一个目录,里面容纳了模块对应的文件,这种方式就是把多个模块聚合成一个包的具体实现。但不管是模块还是包,它们都是一个 module 对象,在虚拟机看来则都是 PyModuleObject 对象。关于这一点,一会儿会看的更加明显。 + +假设现在有一个名为 test_import 的包,里面有一个 a.py,内容如下。 + +~~~Python +a = 123 +b = 456 +print(">>>") +~~~ + +现在我们来导入它。 + +~~~Python +import test_import +print(test_import) # +~~~ + +在 Python2 中,这样是没办法导入的,因为如果一个目录要成为 Python 的包,那么里面必须要有一个 \_\_init\_\_.py 文件,但是在 Python3 中则没有此要求。而且我们发现 print 之后,显示的也是一个 module 对象,因此 Python 对模块和包的底层定义其实是很灵活的,并没有那么僵硬。 + +```Python +import test_import + +print(test_import.a) +""" +AttributeError: module 'test_import' has no attribute 'a' +""" +``` + +然而此时神奇的地方出现了,调用 test_import.a 的时候,告诉我们没有 a 这个属性。很奇怪,test_import 里面不是有 a.py 吗? + +原因是 Python 导入一个包,等价于导入包里的 \_\_init\_\_.py,只有属性在 \_\_init\_\_.py 文件中被导入了,我们才可以通过包名来访问。如果这个包里面没有 \_\_init\_\_.py 文件,那么你导入这个包,是什么属性也用不了的。 + +光说可能比较难理解,我们来演示一下。我们在 test_import 里面创建一个 \_\_init\_\_.py 文件,但是文件里面什么也不写。 + +~~~python +import test_import + +print(test_import) +""" + +""" +~~~ + +此时又看到了神奇的地方,我们在 test_import 目录里面创建了 \_\_init\_\_.py 之后,再打印 test_import,得到的结果又变了,告诉我们这个包来自于包里面的 \_\_init\_\_.py 文件。所以就像之前说的,Python 对包和模块的概念区分的不是很明显,我们就把包当做该包下面的 \_\_init\_\_.py 文件即可,\_\_init\_\_.py 中定义了什么,那么这个包里面就有什么。 + +我们往 \_\_init\_\_.py 里面写点内容: + +~~~python +# test_import/__init__.py + +import sys +from . import a + +name = "satori" +~~~ + +from . import a 表示在 \_\_init\_\_.py 的同级目录中导入 a.py,但是问题来了,直接像 import sys 那样 import a 不行吗?答案是不行的,至于为什么我们后面说。 + +总之我们在 \_\_init\_\_.py 中导入了 sys 模块、a 模块,定义了 name 变量,那么就等于将 sys、a、name 加入到 test_import 这个包的 local 空间里面了。因为 Python 的包等价于它里面的 \_\_init\_\_.py 文件,这个文件有什么,那么这个包就有什么。 + +既然在 \_\_init\_\_.py 中导入了 sys、a,定义了 name,那么这个文件的属性字典里面、或者也可以说 local 空间里面就多了三个 entry,key 分别为 "sys"、"a"、"name"。而 \_\_init\_\_.py 里面有什么,那么通过包名就能够获取什么。 + +~~~python +# 导入一个包会执行内部的 __init__.py +# 而在 __init__.py 里面导入了 a +# a 里面有一个 print,所以会直接执行 +import test_import +""" +>>> +""" + +print(test_import.a) +""" + +""" +print(test_import.a.a) # 123 +print(test_import.a.b)  # 456 + +print(test_import.sys) # +print(test_import.name)  # satori + + + +# 二次导入 +import test_import +# 我们看到 a 里面的 print 没有打印,证明模块、包不管以怎样的方式被导入 +# 对应的文件只会被加载一遍,第二次导入只是从 sys.modules 里面进行了一次键值对查找 +~~~ + +### 相对导入与绝对导入 + +我们刚才使用了 from . import a 的方式导入模块 a,这个 **.** 表示当前文件所在的目录。因此这行代码的含义就是,我要导入 a 这个模块,不是从别的地方导入,而是从该文件所在的目录里面导入。如果是 **..** 就表示当前文件所在目录的上一层目录,**...** 和 **....** 依次类推。 + +另外模块 a 里面还有一个变量 a,那如果我想在 \_\_init\_\_.py 中导入这个变量该怎么办呢?很简单,直接 from .a import a 即可,表示导入当前目录里面的模块 a 里面的变量 a。 + +但如果我们导入的时候没有 **.** 的话,则表示绝对导入,虚拟机就会按照 sys.path 定义的路径进行查找。那么问题来了,假设我们在 \_\_init\_\_.py 中写的不是 from . import a,而是 import a,那么会发生什么后果呢? + +~~~Python +import test_import + +""" + import a +ModuleNotFoundError: No module named 'a' +""" +~~~ + +我们发现报错了,提示没有 a 这个模块,可是我们明明在包里面定义了呀。还记得之前说的导入一个模块、导入一个包会做哪些事情吗?导入一个模块,会将该模块里面的内容 "拿过来" 执行一遍,导入包会将该包里面的 \_\_init\_\_.py 文件 "拿过来" 执行一遍。注意:这里把 "拿过来" 三个字加上了引号。 + +我们在和 test_import 目录同级的 py 文件中导入了 test_import,那么就相当于把里面的 \_\_init\_\_ 拿过来执行一遍(当然只有第一次导入的时候才会这么做)。但是它们具有单独的空间,是被隔离的,访问时需要使用符号 test_import 来访问。 + +但是正如之前所说,是 "拿过来" 执行,所以这个 \_\_init\_\_.py 里面的内容是"拿过来",在当前的 .py 文件(在哪里导入的就是哪里)中执行的。所以由于 import a 这行代码表示绝对导入,就相当于在当前模块里面导入,会从 sys.path 里面搜索,但模块 a 是在 test_import 包里面,那么此时还能找到这个 a 吗?显然是不能的,除非我们将 test_import 所在路径加入到 sys.path 中。 + +那 from . import a 为什么就好使呢?因为这种导入方式是相对导入,表示要在 \_\_init\_\_.py 所在目录里面找,那么不管在什么地方导入这个包,由于 \_\_init\_\_.py 的位置是不变的,所以 from . import a 这种相对导入的方式总能找到对应的 a。 + +至于标准库、第三方模块、第三方包,因为它们在 sys.path 里面,在哪儿都能找得到,所以直接绝对导入即可。并且我们知道每一个模块都有一个 \_\_file\_\_ 属性(除了内嵌在解释器里面的模块),当然包也是。如果你在一个模块里面 print(\_\_file\_\_),那么不管在哪里导入这个模块,打印的永远是这个模块的路径;包的话,则是指向内部的 \_\_init\_\_.py 文件。 + +另外关于相对导入,一个很重要的一点,一旦一个模块出现了相对导入,那么这个模块就不能被执行了,它只可以被导入。 + +~~~python +import sys +from . import a + +name = "satori" +""" + from . import a +ImportError: attempted relative import with no known parent package +""" +~~~ + +此时如果试图执行 \_\_init\_\_.py,那么就会报出这个错误,所以出现相对导入的模块不能被执行,只能被导入。此外,导入一个内部具有"相对导入"的模块,还要求当前模块被导入模块不能在同一个包内,我们要执行的当前模块至少在被导入模块的上一级,否则执行当前模块也会报出这种错误。 + +因此出现相对导入的模块要在一个包里面,然后在包外面使用,所以当前模块出现相对导入的被导入模块绝对不能在同一个包里面。 + +### import 的另一种方式 + +我们要导入 test_import 包里面的 a 模块,除了可以 import test_import(前提是 \_\_init\_\_.py 里面导入了 a)之外,还可以直接 import test_import.a。 + +另外如果是这种导入方式,那么包里面可以没有 \_\_init\_\_.py 文件。因为之前导入 test_import 包的时候,是通过 test_import 来获取 a,所以必须要有 \_\_init\_\_.py、并且里面导入 a。但是在导入 test_import.a 的时候,就是找 test_import.a,所以此时是可以没有 \_\_init\_\_.py文件的。 + +~~~Python +# test_import/__init__.py +__version__ = "1.0" + +# test_import/a.py +name = "古明地觉" +print("古明地恋") +~~~ + +此时 test_import 包的 \_\_init\_\_.py 里面只定义了一个变量,下面我们来通过 test_import.a 的形式导入。 + +~~~Python +import test_import.a + +print(test_import.a.name) +""" +古明地恋 +古明地觉 +""" + +# 当 import test_import.a 的时候,会执行里面的 print +# 然后可以通过 test_import.a 获取 a.py 里面的属性,这很好理解 + +# 但是,没错,我要说但是了 +print(test_import.__version__) # 1.0 +~~~ + +惊了,我们在导入 test_import.a 的时候,也把 test_import 导入进来了,为了更直观地看到现象,我们在 \_\_init\_\_.py 里面打印一句话。 + +~~~python +import test_import.a +""" +我是 test_import 下面的 __init__ +古明地恋 +""" +~~~ + +导入一个包等价于导入包里面的 \_\_init\_\_.py,而 \_\_init\_\_.py 里面的内容都可以通过包来获取。而打印结果显示在导入 test_import.a 时,会先把 test_import 导入进来。如果我们在 \_\_init\_\_.py 中也导入了 a 会怎么样? + +~~~python +# test_import/__init__.py +print("我是 test_import 下面的 __init__") +from . import a + +# test_import/a.py +print("我是 test_import 下面的 a") +~~~ + +导入一下看看: + +~~~python +import test_import.a +""" +我是 test_import 下面的 __init__ +我是 test_import 下面的 a +""" +~~~ + +我们看到 a.py 里面的内容只被打印了一次,说明没有进行二次加载,在 \_\_init\_\_.py 中将 a 导入进来之后,就加入到 sys.modules 里面了。再看一下 sys.modules: + +~~~python +import sys +import test_import.a +""" +我是 test_import 下面的 __init__ +我是 test_import 下面的 a +""" + +print(sys.modules["test_import"]) +print(sys.modules["test_import.a"]) +""" + + +""" +~~~ + +通过 test_import.a 的方式来导入,即使 test_import 里面没有 \_\_init\_\_.py 文件依旧可以访问。 + +不过问题来了,为什么在导入 test_import.a 的时候,会将 test_import 也导入进来呢?并且还可以直接使用 test_import,毕竟这不是我们期望的结果。因为导入 test_import.a 的话,那么我们只是想使用 test_import.a,不打算使用 test_import,那 Python 为什么要这么做呢? + +事实上,这对 Python 而言是必须的,根据我们对虚拟机执行原理的了解,要想获取 test_import.a,那么肯定要先从 local 空间中找到 test_import,然后才能找到 a。如果不找到 test_import 的话,那么对 a 的查找也就无从谈起。 + +虽然 sys.modules 里面有一个 test_import.a,但并不是说有一个模块叫 test_import.a。准确的说 import test_import.a 表示先导入 test_import,然后再将 test_import 下面的 a 加入到 test_import 的属性字典里面。 + +我们说当包里面没有 \_\_init\_\_.py 的时候,那这个包是无法使用的,因为属性字典里面啥也没有。但是当 import test_import.a 的时候,虚拟机会先导入 test_import 这个包,然后再把 a 这个模块加入到包的属性字典里面。而 sys.modules 里面之所以会有 "test_import.a" 这个 key,显然也是为了解决重复导入的问题。 + +假设 test_import 里面有 a 和 b 两个 .py 文件,那么执行 import test_import.aimport test_import.b 会进行什么样的动作应该了如指掌了。 + +执行 import test_import.a,会先导入 test_import,然后把 a 加入到 test_import 的属性字典里面。执行 import test_import.b,还是会先导入包 test_import,但是 test_import 在上一步已经被导入了,所以此时会直接从 sys.modules 里面获取,然后再把 b 加入到 test_import 的属性字典里面。 + +所以如果 \_\_init\_\_.py 里面有一个 print 的话,那么两次导入显然只会 print 一次,这种现象是由 Python 对包内模块的动态加载机制决定的。还是那句话,一个包你就看成是里面的 \_\_init\_\_.py 文件即可,Python 对于包和模块的区分不是特别明显。 + +~~~python +# test_import 目录下有 __init__.py 文件 +import test_import + +print(test_import.__file__) +print(test_import) +""" +D:\satori\test_import\__init__.py + +""" + +# test_import 目录下没有 __init__.py 文件 +import test_import + +print(test_import.__file__) +print(test_import) +""" +None + +""" +~~~ + +如果包里面有 \_\_init\_\_.py 文件,那么这个包的 \_\_file\_\_ 属性就是其内部的 \_\_init\_\_.py 文件的完整路径。如果没有 \_\_init\_\_.py 文件,那么这个包的 \_\_file\_\_ 就是 None。 + +一个模块(即使里面什么也不写)的属性字典里面肯定是有 \_\_builtins\_\_ 属性的,因此可以直接使用内置函数等等。而 \_\_init\_\_.py 也属于一个模块,所以它也有 \_\_builtins\_\_ 属性,由于一个包指向了内部的 \_\_init\_\_.py,所以这个包的属性字典也是有 \_\_builtins\_\_ 属性的。但如果这个包没有 \_\_init\_\_.py 文件,那么就没有 \_\_builtins\_\_ 属性了。 + +~~~python +# 没有 __init__.py 文件 +import test_import +print( + test_import.__dict__.get("__builtins__") +) # None + + +# 有 __init__.py 文件 +import test_import +print( + test_import.__dict__.get("__builtins__")["int"] +) # +~~~ + +### 路径搜索树 + +假设有这样一个目录结构: + +![](./images/274.png) + +那么 Python 会将这个结构进行分解,得到一个类似于树状的节点集合: + +![](./images/275.png) + +然后从左到右依次去 sys.modules 中查找每一个符号所对应的 module 对象是否已经被加载,如果一个包被加载了,比如说包 test_import 被加载了,那么在包 test_import 对应的 PyModuleObject 中会维护一个元信息 \_\_path\_\_,表示这个包的路径。比如搜索 A.a,当 A 加载进来之后,对 a 的搜索只会在 A.\_\_path\_\_ 中进行,而不会在 Python 的所有搜索路径中进行了。 + +~~~Python +import test_import + +print(test_import.__path__) # ['D:\\satori\\test_import'] + +# 导入 sys 模块 +try: + import test_import.sys +except ImportError as e: + print(e) # No module named 'test_import.sys' +~~~ + +显然这样是错的,因为导入的是 test_import.sys,那么就将搜索范围只限定在 test_import 的 \_\_path\_\_ 下面了,而它下面没有 sys 模块,因此报错。 + +## from 与 import + +在 Python 的 import 中,有一种方法可以精确控制所加载的对象,通过 from 和 import 的结合,可以只将我们期望的 module 对象、甚至是 module 对象中的某个符号,动态地加载到内存中。这种机制使得虚拟机在当前名字空间中引入的符号可以尽可能地少,从而更好地避免名字空间遭到污染。 + +按照我们之前所说,导入 test_import 下面的模块 a,可以使用 import test_import.a 的方式,但此时 a 是在 test_import 的名字空间中,不是在我们当前模块的名字空间中。也就是说我们希望能直接通过符号 a 来调用,而不是 test_import.a,此时通过 from ... import ... 联手就能完美解决。 + +~~~python +import sys +# test_import 是一个目录,里面有一个 __init__.py 和一个 a.py +# 在 __init__.py 中导入了 a.py +from test_import import a + +print(sys.modules.get("test_import") is not None) # True +print(sys.modules.get("test_import.a") is not None) # True +print(sys.modules.get("a") is not None) # False +~~~ + +我们看到,确确实实将 a 这个符号加载到当前的名字空间里面了,但是在 sys.modules 里面却没有 a。还是之前说的,a 这个模块在 test_import 这个包里面,我们不可能不通过包就直接拿到包里面的模块,因此在 sys.modules 里面的形式其实还是 test_import.a。 + +只不过在当前模块的名字空间中是 a,并且 a 被映射到 sys.modules["test_import.a"]。另外除了 test_import.a,test_import 也导入了,这个原因之前也说过了,不再赘述。所以我们发现即便是 from ... import ...,还是会触发整个包的导入,只不过包在导入之后,没有暴露在当前的 local 空间中。 + +所以我们导入谁,就把谁加入到了当前模块的 local 空间里面,假设从 a 导入 b,那么会把 b 加入到当前的 local 空间中。但是在 sys.modules 里面是没有 "b" 这个 key 的,key 应该是 "a.b",这么做的原因就是为了防止模块重复加载。当然,此时名字空间中的符号 b,和 sys.modules["a.b"] 都会指向同一个 module 对象。 + +此外我们 from test_import import a,导入的这个 a 是一个模块,但是模块 a 里面还有一个变量也叫 a。如果不加 from,只通过 import 的话,那么最深也只能 import 到一个模块,不可能说直接 import 模块里面的某个变量、函数什么的。但是 from ... import ... 的话,却是可以的,比如我们 from test_import.a import a,这就表示要导入 test_import.a 模块里面的变量 a。 + +~~~Python +import sys +from test_import.a import a + +modules = sys.modules +print("a" in modules) # False +print("test_import.a" in modules) # True +print("test_import" in modules) # True +~~~ + +此时导入的 a 是一个变量,并不是模块,所以 sys.modules 里面不会有 test_import.a.a 这样的东西存在。但是这个 a 毕竟是从 test_import.a 里面导入的,所以 test_import.a 会在 sys.modules 里面,同理 test_import.a 表示从 test_import 的属性字典里面查找 a,所以 test_import 也会进入 sys.modules 里面。 + +最后还可以使用 from test_import.a import \* 这样的机制把一个模块里面所有的内容全部导入进来。但是在 Python 中还有一个特殊的机制,如果模块里面定义了 \_\_all\_\_,那么只会导入 \_\_all\_\_ 里面指定的属性。 + +~~~Python +# test_import/a.py + +a = 123 +b = 456 +c = 789 +__all__ = ["a", "b"] +~~~ + +我们注意到在 \_\_all\_\_ 里面只指定了 a 和 b,那么后续通过 from test_import.a import \* 的时候,只会导入 a 和 b,而不会导入 c。 + +~~~python +from test_import.a import * + +print("a" in locals() and "b" in locals()) # True +print("c" in locals()) # False + +from test_import.a import c +print("c" in locals()) # True +~~~ + +通过 from ... import \* 导入的时候,是无法导入 c 的,因为 c 没有在 \_\_all\_\_ 中。但即便如此,我们也可以通过单独导入的方式,把 c 导入进来。只是不推荐这么做,像 PyCharm 也会提示:'c' is not declared in \_\_all\_\_。因为既然没有在 \_\_all\_\_ 里面,就证明这个变量是不希望被导入的,但是一般导入了也没关系。 + +## 符号重命名 + +导入模块的时候一般为了解决符号冲突,往往会起别名,或者说符号重命名。比如包 a 和包 b 下面都有一个模块叫做 m,如果是 from a import mfrom b import m 的话,那么两者就冲突了,后面的 m 会把前面的 m 覆盖掉,不然 Python 怎么知道要找哪一个 m 呢。 + +所以这个时候我们会起别名,比如 from a import m as m1from b import m as m2。所以符号重命名是一种通过 as 关键字控制包、模块、变量暴露给 local 空间的方式,但是 from a import \* 是不支持 as 的。 + +~~~python +import sys +import test_import.a as a + +print(a) # +print("test_import.a" in sys.modules) # True +print("test_import" in sys.modules) # True +print("test_import" in locals()) # False +~~~ + +到这里我相信就应该心里有数了,不管我们有没有 as,既然 import test_import.a,那么 sys.modules 里面就一定有 test_import.a 和 test_import。其实理论上有 test_import 就够了,但 a 是一个模块,为了避免多次导入所以也要加到 sys.modules 里面,由于 a 在 test_import 下面,因此 sys.modules 里面还会有一个 key 叫 "test_import.a"。 + +而 import test_import.a 后面还有个 as a,那么 a 这个符号就暴露在了当前模块的 local 空间里面,而且这个 a 跟之前的 test_import.a 一样,都指向了 test_import 包下面的 a 模块,无非是名字不同罢了。 + +当然这不是重点,之前 import test_import.a 的时候,会自动把 test_import 也加入到当前模块的 local 空间里面,也就是说通过 import test_import.a 是可以直接使用 test_import 的。但是当我们加上了 as 之后,发现 test_import 已经不能访问了。尽管都在 sys.modules 里面,但是对于加了 as 来说,此时的 test_import 已经不在 local 空间里面了。 + +## 符号的销毁和重载 + +为了使用一个模块,无论是内置的还是自己写的,都需要先通过 import 动态加载。使用之后,我们也可能会删除,删除的原因一般是释放内存啊等等。而在 Python 中,删除一个变量可以使用 del 关键字,遇事不决 del。 + +~~~python +l = [1, 2, 3] +d = {"a": 1, "b": 2} + +del l[0] +del d["a"] + +print(l) # [2, 3] +print(d) # {'b': 2} + + +class A: + + def foo(self): + pass + +print("foo" in dir(A)) # True +del A.foo +print("foo" in dir(A)) # False +~~~ + +不光是列表、字典,好多东西 del 都能删除,当然这里的删除不是直接删掉了,而是将对象的引用计数减一。或者说符号的销毁符号关联的对象的销毁不是一个概念,del 只能删除某个符号,无法删除一个具体的对象,比如 del 123 就是非法的。而 import 本质上也是创建一个变量,所以它同样可以被删除,至于变量指向的模块对象是否被删除,则看它的引用计数是否为 0。 + +因此 Python 向我们隐藏了太多的动作,也采取了太多的缓存策略,当然对于使用者来说是好事情,因为把复杂的特性隐藏起来了。但是当我们想彻底地了解 Python 的行为时,则必须要把这些隐藏的东西挖掘出来。 + +~~~python +import sys +import test_import.a as a + +# 对于模块来说,dir()、locals()、globals() 的 keys 是一致的 +print("a" in dir()) # True +del a +print("a" in locals()) # False + +print(id(sys.modules["test_import.a"])) # 1576944838432 +import test_import.a as 我不叫a了 +print(id(我不叫a了)) # 1576944838432 +~~~ + +在 del 之后,a 这个符号确实从 local 空间消失了,或者说 dir 已经看不到了。但是我们发现,消失的仅仅是 a 这个符号,至于指向的 PyModuleObject 依旧在 sys.modules 里面岿然不动。然而,尽管它还存在于 Python 系统中,但程序再也无法感知到。所以此时 Python 就成功地隐藏了这一切,我们的程序认为: test_import.a 已经不存在了。 + +不过为什么 Python 要采用这种看上去类似**模块池**的缓存机制呢?答案很简单,因为组成一个完整系统的多个 .py 文件可能都要对某个 module 对象进行 import 动作。所以要是从 sys.modules 里面删除了,那么就意味着需要重新从文件里面读取,如果不删除,那么只需要将其从 sys.modules 里面暴露给当前的 local 空间即可。 + +所以 import 实际上并不等同于我们所说的动态加载,它的真实含义是希望某个模块被感知,也就是将这个模块以某个符号的形式引入到某个名字空间。这些都是同一个模块,如果 import 等同于动态加载,那么就等于 Python 对同一个模块执行多次导入,并且内存中保存一个模块的多个镜像,这显然是非常愚蠢的。 + +为此 Python 引入了全局的 module 对象集合 sys.modules 作为**模块池**,保存了模块的唯一值。当通过 import 声明希望感知到某个 module 对象时,虚拟机将在这个池子里面查找,如果被导入的模块已经存在于池子中,那么就引入一个符号到当前模块的名字空间中,并将其关联到导入的模块,使得被导入的模块可以透过这个符号被当前模块感知到。而如果被导入的模块不在池子里,Python 这才执行动态加载的动作。 + +不过这就产生了一个问题,这不等于说一个模块在被加载之后,就不能改变了吗?假如在加载了模块 a 之后,我们修改了模块 a,难道 Python 程序只能先暂停再重启,然后才能使用修改之后的模块 a 吗?显然不是这样的,Python 的动态特性不止于此,它提供了一种重新加载的机制,使用 importlib 模块,通过 importlib.reload(module),可以实现重新加载。并且这个函数是有返回值的,会返回加载之后的模块。 + +~~~python +>>> import sys +>>> sys.path.append(r"D:\satori") +>>> +>>> from test_import import a +>>> a.name # 不存在 name 属性 +Traceback (most recent call last): + File "", line 1, in +AttributeError: module 'test_import.a' has no attribute 'name' +>>> +>>> +>>> import importlib +# 增加一个赋值语句 name = "古明地觉" +>>> a = importlib.reload(a)   +>>> a.name +'古明地觉' +>>> +# 将 name = "古明地觉" 语句删除 +>>> a = importlib.reload(a)   +>>> a.name +'古明地觉' +>>> +~~~ + +首先模块 test_import.a 里面没有 name 变量,但之后在 a.py 里面增加了 name,然后重新加载模块,发现 a.name 正常打印。接着在 a.py 里面再删除 name,然后重新加载,但我们看到 name 还在里面,还可以被访问。 + +那么根据这个现象我们是不是可以大胆猜测,Python 在 reload 一个模块的时候,只是将模块里面新的符号加载进来,而删除的则不管了。那么这个猜测到底正不正确呢,别急我们下一篇文章就来揭晓,并通过源码来剖析 import 的实现机制。 + +------ + +  + +**欢迎大家关注我的公众号:古明地觉的编程教室。** + +![](./images/qrcode_for_gh.jpg) + +**如果觉得文章对你有所帮助,也可以请作者吃个馒头,Thanks♪(・ω・)ノ。** + +![](./images/supports.png) diff --git a/src/SUMMARY.md b/src/SUMMARY.md index 63ab385..c568b50 100644 --- a/src/SUMMARY.md +++ b/src/SUMMARY.md @@ -83,3 +83,4 @@ + [80. 实例对象的属性访问](80.实例对象的属性访问.md) + [81. 为什么实例在调用方法时会将自身传给 self 参数](81.为什么实例在调用方法时会将自身传给self参数.md) + [82. 模块是如何导入的?](82.模块是如何导入的?.md) ++ [83. import 机制的黑盒探测](83.import机制的黑盒探测.md) diff --git a/src/images/273.png b/src/images/273.png new file mode 100644 index 0000000000000000000000000000000000000000..acfd09fcd7f2da9cd4d50286871abfd309885781 GIT binary patch literal 88275 zcmdRV^Al)$<1rd<$Mi3@l(p@4g(y>jtH+qAy z@l5@Ezt0cPU-0~Jzg}ne+3x$C>sBDfRkt;6CDO>N zlJbY1KK!Wqk|3PM`uVHcqL`aiW-n?A%h{rtZ`E2F&<((i>BxC__pExV+R5;}77RLl zJ6+)zgq$5#Vr#j@2Cty$r1%$;E^Vl(N**8Qe7>jvcc$X*4N`f0qGrNRf(dF8+S)64 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