如何用Python制作微信好友个性签名词云图

制作微信好友个性签名词云图是一项很有趣的Python项目。下面是详细的制作攻略。

1. 准备数据

要制作词云图，首先需要获取微信好友的签名数据。可以使用itchat这个Python库来获取微信好友信息。使用以下代码获取微信好友信息并将签名数据保存到文本文件中：

import itchat

# 登录微信
itchat.auto_login()

# 获取好友列表（含详细信息）
friends = itchat.get_friends(update=True)

# 从好友列表中提取签名信息
signature_list = []
for friend in friends:
    signature = friend["Signature"].strip().replace("emoji", "")
    if signature != "":
        signature_list.append(signature)

# 将签名信息保存到文件中
with open("signature.txt", "w", encoding="utf-8") as f:
    for signature in signature_list:
        f.write(signature + "\n")

2. 分词

接下来需要将签名数据进行分词处理。这里可以使用jieba这个Python库。使用以下代码进行分词：

import jieba

# 读取签名数据
with open("signature.txt", "r", encoding="utf-8") as f:
    text = f.read()

# 分词
word_list = jieba.cut(text)

# 将分词结果保存到文件中
with open("word_list.txt", "w", encoding="utf-8") as f:
    for word in word_list:
        f.write(word + " ")

3. 生成词云图

接下来需要使用词云生成库wordcloud来生成词云图。使用以下代码生成词云图：

import matplotlib.pyplot as plt
from wordcloud import WordCloud

# 读取分词结果
with open("word_list.txt", "r", encoding="utf-8") as f:
    text = f.read()

# 生成词云图
wordcloud = WordCloud().generate(text)

# 显示词云图
plt.imshow(wordcloud, interpolation="bilinear")
plt.axis("off")
plt.show()

# 保存词云图
wordcloud.to_file("signature_wordcloud.png")

以上是制作微信好友个性签名词云图的完整攻略。下面给出两个示例说明。

示例一

如果你想定制词云图背景颜色和字体，请使用以下代码：

import numpy as np
from PIL import Image
import matplotlib.pyplot as plt
from wordcloud import WordCloud, ImageColorGenerator
import jieba

# 读取签名数据
with open("signature.txt", "r", encoding="utf-8") as f:
    text = f.read()

# 分词
word_list = jieba.cut(text)

# 读取自定义图片
mask = np.array(Image.open("mask.png"))

# 设置字体路径
font_path = "msyh.ttc"

# 生成词云图
wordcloud = WordCloud(font_path=font_path, mask=mask,
                      background_color="white", mode="RGBA").generate(text)
color = ImageColorGenerator(mask)

# 显示词云图
plt.imshow(wordcloud.recolor(color_func=color), interpolation="bilinear")
plt.axis("off")
plt.show()

# 保存词云图
wordcloud.to_file("signature_wordcloud_custom.png")

示例二

如果你希望词云图中的词语按照字体大小排序，请使用以下代码：

import numpy as np
from PIL import Image
import matplotlib.pyplot as plt
from wordcloud import WordCloud, ImageColorGenerator
import jieba

# 读取签名数据
with open("signature.txt", "r", encoding="utf-8") as f:
    text = f.read()

# 分词
word_list = jieba.cut(text)

# 读取自定义图片
mask = np.array(Image.open("mask.png"))

# 设置字体路径
font_path = "msyh.ttc"

# 生成词云图
wordcloud = WordCloud(font_path=font_path, mask=mask, max_words=100,
                      max_font_size=200, background_color="white", mode="RGBA").generate(text)
color = ImageColorGenerator(mask)

# 显示词云图
fig, ax = plt.subplots()
ax.imshow(wordcloud.recolor(color_func=color), interpolation="bilinear")
ax.axis("off")

# 排序
words = list(wordcloud.words_.keys())
counts = list(wordcloud.words_.values())
idx = np.argsort(np.array(counts))[::-1]

# 生成legend
for i, w in enumerate(np.array(words)[idx][:10]):
    ax.text(250, 100+i*50, w, fontsize=20, color="black", ha="center", va="center")

plt.show()

# 保存词云图
wordcloud.to_file("signature_wordcloud_sorted.png")