python3把二进制图片文件包含在代码里的方法

2022-03-16 00:00:00 代码 包含 制图

我们可以把一些资源文件直接放在python的源代码里面,比如一些小的图标资源,这样就不需要携带这些资源文件了

"""
作者:皮蛋编程(http://www.pidancode.com)
创建日期:2022/3/16
修改日期:2022/3/16
功能描述:python3把二进制图片文件包含在代码里的方法
"""
import base64
import zlib

data = open('pidancode.png', 'rb').read()
encode_data = base64.b64encode(zlib.compress(data))
print(encode_data)

这段代码将皮蛋编程网站的LOGO图片文件转换成base64编码的字节,输出结果如下:

b'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'
# 把上面代码输出的结果存储在变量里面:
import base64
import zlib

logo_file = zlib.decompress(base64.b64decode(b'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'))

print("文件大小:{}".format(len(logo_file)))

显示图片:

from PIL import Image
import io
img = Image.open(io.BytesIO(logo_file))
img.show()

以上代码在Python3.9环境下测试通过。

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