Create fenCi.py

Author: rory0807

jobSkill/fenCi.py

@@ -0,0 +1,52 @@
+from jieba import analyse
+from PIL import Image
+from wordcloud import WordCloud, ImageColorGenerator
+import matplotlib.pyplot as plt
+import numpy as np
+
+fenCi = {}
+ciYunArray = []
+def main():
+
+    # 负责过滤的词语
+    filterWords = ['熟悉', '熟练', '经验', '优先', '应用开发', '相关', '工作', '开发', '能力', '负责', '技术', '具备', '精通', '数据', 'ETC']
+
+    # 结巴分词基于 TF-IDF 算法的关键词
+    tfidf = analyse.extract_tags
+
+    for zpInfo in open('sh.txt', 'r', encoding='utf-8'):
+
+        if zpInfo.strip() == '':
+            continue
+        # 详情数据是用&&&分割的
+        infos = zpInfo.split("&&&")
+        words = tfidf(infos[-1])
+
+        words = [x.upper() for x in words if x.upper() not in filterWords]
+
+        for word in words:
+            word = word.upper()
+            num = fenCi.get(word, 0) + 1
+            fenCi[word] = num
+
+    print(sorted(fenCi.items(), key=lambda kv: (kv[1], kv[0]), reverse=True))
+    print('分出了' + str(len(fenCi)) + '了词语')
+
+
+def getWordCloud():
+   path_img = "python.jpg"
+   background_image = np.array(Image.open(path_img))
+
+   wordcloud = WordCloud(
+       font_path="/System/Library/Fonts/STHeiti Light.ttc", # 字体
+       background_color="white",
+       mask=background_image).generate(" ".join(list(fenCi.keys())))
+   image_colors = ImageColorGenerator(background_image)
+   plt.imshow(wordcloud.recolor(color_func=image_colors), interpolation="bilinear")
+   plt.axis("off")
+   plt.show()
+
+
+if __name__ == '__main__':
+    main()
+    getWordCloud()