前言：

用Pyinstaller 打包exe时，有时候得附带上一些资源，才能让程序不那么单调。在网上也有很多把依赖文件打包进exe的方法，不过都只能打包一些图片或者文本而已。还有一个就是通过修改PyInstaller配置文件*.spec来实现打包的方法，虽然挺不错，但是我使用的时候移植到其他机器运行有时会出现些问题。

所以在这里分享一个打包资源和依赖文件进exe里面的方法。
通过这个方法可以把音频，视频，图片，文本，压缩包，配置文件，脚本等各种文件打包进exe中。
运行时会自动解压到当前目录，如果程序需要调用这些文件时，就可以调用了。

效果图：

1. 转换为Base64 数据

先准备好你程序需要用的依赖文件。

这里有两个网站，都是可以将任意文件转换为 Base64 数据文本的。
进到下面这其中一个网站中，分别将你的文件进行转换，然后复制得到的数据。

https://www.giftofspeed.com/base64-encoder/
https://www.zhangxinxu.com/sp/base64.html

2.在程序中使用生成的数据

首先呢，创建一个.py自建模块，在里面创建变量，分别把从网站得到的Base64数据以字符串的形式粘贴到变量里面。

注意：
1. 变量的类型必须是字符串。
2. 一个变量的base64数据只能放在一行，不要有分行。

例如，我创建了一个叫 “DateFile.py” 的自建模块，然后我把得到的 base64数据都粘贴到对应的变量里面了。
完整代码如下：

DataFile.py

#　文本文件的base64数据
text = "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"# 压缩包的base64数据
zip_pack = "UEsDBAoAAAAAAJhtVlAAAAAAAAAAAAAAAAAPAAAAaGVsbG8gd29ybGQudHh0UEsBAj8ACgAAAAAAmG1WUAAAAAAAAAAAAAAAAA8AJAAAAAAAAAAgAAAAAAAAAGhlbGxvIHdvcmxkLnR4dAoAIAAAAAAAAQAYAAgrMjFD6dUBCCsyMUPp1QEIKzIxQ+nVAVBLBQYAAAAAAQABAGEAAAAtAAAAAAA="# 图片的base64数据
picture = "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"

例子：

下面是一个简单的运用，我创建了一个叫“get_file.py”的程序；这个程序运行时，import了刚才创建的自建模块 DataFile，然后再把将文件写入到指定的位置。程序运行末尾结束了，就删除这些文件。

get_file.py

import os
import base64
import DataFile          # 导入自建模块 "DataFile.py"def write_file(data, route):get_file = base64.b64decode(data)     # 将base64数据进行解析with open(route, 'wb') as f_Obj:       # 输出文件到指定位置f_Obj.write(get_file)#-----调用函数，传入对应的 base64数据 和 输出文件的位置，生成依赖的资源文件-----#
write_file(DataFile.text, "./测试文本.txt")
write_file(DataFile.zip_pack, "./测试压缩包.zip")
write_file(DataFile.picture, "./测试图片.jpg")#-----程序运行区域-----#
print("Hello world !")
input()  # 暂停#-----运行结束后删除目录下的依赖文件-----#
os.remove("./测试文本.txt")
os.remove("./测试压缩包.zip")
os.remove("./测试图片.jpg")

这样，每当程序运行时，就可以在程序根目录（或其他目录）自动生成所依赖的资源文件了。
当需要用的时候，就可以在程序运行区域中引用这些文件了。

3. 打包exe

首先打开CMD(或终端) ，然后CD到当前文件位置，执行下面的命令。

 pyinstaller -F 主文件.py  Base64数据.py

例如：

执行命令后，稍等一下目录里面会出现一个 “dist”文件夹，点进去，里面就是我们要得到的exe程序了。
双击打开这个程序，效果就和开头的效果图是一样的。

原创文章，如需转载请注明出处或者相关链接

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Pyinstaller 打包exe附带资源，运行时自动解压所需资源（图片文本音频等）

前言：

1. 转换为Base64 数据

2.在程序中使用生成的数据

例子：

3. 打包exe

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