有人在 openSUSE 中文论坛询问他的输入法打出的「妩媚」的「妩」字为什么显示成「女」+「元」。怀疑是字体的问题,于是空闲时用好友写的 python-fontconfig 配合 Pillow (PIL 的一个 fork)写了个脚本,使用系统上所有包含这个「妩」字的字体来显示这个字,看看到底是哪些字体有问题。
(更新后的)脚本如下:
Google Chrome / Chromium 用户请注意:如果复制得到的代码中含有不间断空格(0xa0),请手动替换下。
#!/usr/bin/env python3
# vim:fileencoding=utf-8
from PIL import Image, ImageDraw, ImageFont
import fontconfig
ch = '妩'
def get_fonts():
ret = []
for f in fontconfig.query():
f = fontconfig.FcFont(f)
if f.has_char(ch):
ret.append((f.file, f.bestname))
return ret
w, h = 800, 20000
image = Image.new('RGB', (w, h), 'white')
draw = ImageDraw.Draw(image)
pos = 0
w = 0
strs = ch
for fontfile, fontname in get_fonts():
font = ImageFont.truetype(fontfile, 24)
s = '%s: %s' % (fontname, strs)
font_width, font_height = font.getsize(s)
w = max((font_width, w))
draw.text((10, pos), s, font=font, fill='black')
pos += font_height
h = pos
image = image.crop((0, 0, w+10, h))
image.save('fonts.png')
寻找字体,然后渲染到当前目录下的fonts.png文件中。寻找字体的过程挺花时间的,要耐心等待。最后结果如下:
我这里,文泉驿微米黑、方正魏碑ref、某个 Droid Sans Fallback 字体中「妩」字的字形不对。(我这里有三个字体文件都叫「Droid Sans Fallback」……)>

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

Python's real-world applications include data analytics, web development, artificial intelligence and automation. 1) In data analysis, Python uses Pandas and Matplotlib to process and visualize data. 2) In web development, Django and Flask frameworks simplify the creation of web applications. 3) In the field of artificial intelligence, TensorFlow and PyTorch are used to build and train models. 4) In terms of automation, Python scripts can be used for tasks such as copying files.

Python is widely used in data science, web development and automation scripting fields. 1) In data science, Python simplifies data processing and analysis through libraries such as NumPy and Pandas. 2) In web development, the Django and Flask frameworks enable developers to quickly build applications. 3) In automated scripts, Python's simplicity and standard library make it ideal.

Python's flexibility is reflected in multi-paradigm support and dynamic type systems, while ease of use comes from a simple syntax and rich standard library. 1. Flexibility: Supports object-oriented, functional and procedural programming, and dynamic type systems improve development efficiency. 2. Ease of use: The grammar is close to natural language, the standard library covers a wide range of functions, and simplifies the development process.

Python is highly favored for its simplicity and power, suitable for all needs from beginners to advanced developers. Its versatility is reflected in: 1) Easy to learn and use, simple syntax; 2) Rich libraries and frameworks, such as NumPy, Pandas, etc.; 3) Cross-platform support, which can be run on a variety of operating systems; 4) Suitable for scripting and automation tasks to improve work efficiency.

Yes, learn Python in two hours a day. 1. Develop a reasonable study plan, 2. Select the right learning resources, 3. Consolidate the knowledge learned through practice. These steps can help you master Python in a short time.


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