知微
fa45d8aa5f
- health_checklist.json: 192.168.1.122→node122
- ocr_client.py: docstring IP→node122
- docs/market-data-requirements.md: IP→node122
- 所有API调用通过ProxyHandler({})绕过系统代理
Privoxy对node122:18003返回500，直连正常
147 lines
3.8 KiB
Python
147 lines
3.8 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2021/11/16 20:40
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Desc: 艺恩-艺人
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艺人商业价值
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艺人流量价值
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https://www.endata.com.cn/Marketing/Artist/business.html
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"""
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import datetime
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import json
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import os
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import pandas as pd # type: ignore
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import requests
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import py_mini_racer # type: ignore
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def _get_js_path(name: str = "", module_file: str = "") -> str:
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"""
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get JS file path
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:param name: file name
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:type name: str
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:param module_file: filename
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:type module_file: str
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:return: 路径
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:rtype: str
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"""
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module_folder = os.path.abspath(os.path.dirname(os.path.dirname(module_file)))
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module_json_path = os.path.join(module_folder, "movie", name)
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return module_json_path
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def _get_file_content(file_name: str = "jm.js"):
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"""
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read the file content
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:param file_name: filename
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:type file_name: str
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:return: file content
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:rtype: str
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"""
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setting_file_name = file_name
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setting_file_path = _get_js_path(setting_file_name, __file__)
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with open(setting_file_path) as f:
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file_data = f.read()
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return file_data
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def decrypt(origin_data: str = "") -> str:
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"""
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解密艺恩的加密数据
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:param origin_data: 解密前的字符串
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:type origin_data: str
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:return: 解密后的字符串
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:rtype: str
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"""
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file_data = _get_file_content(file_name="jm.js")
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ctx = py_mini_racer.MiniRacer()
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ctx.eval(file_data)
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data = ctx.call("webInstace.shell", origin_data)
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return data
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def business_value_artist() -> pd.DataFrame:
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"""
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艺恩-艺人-艺人商业价值
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https://www.endata.com.cn/Marketing/Artist/business.html
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:return: 艺人商业价值
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:rtype: pandas.DataFrame
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"""
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url = "https://www.endata.com.cn/API/GetData.ashx"
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payload = {
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"Order": "BusinessValueIndex_L1",
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"OrderType": "DESC",
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"PageIndex": "1",
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"PageSize": "100",
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"MethodName": "Data_GetList_Star",
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}
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r = requests.post(url, data=payload)
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r.encoding = "utf8"
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data_json = json.loads(decrypt(r.text))
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temp_df = pd.DataFrame(data_json["Data"]["Table"])
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temp_df.columns = [
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"排名",
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"-",
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"艺人",
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"商业价值",
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"-",
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"专业热度",
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"关注热度",
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"预测热度",
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"美誉度",
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"-",
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]
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temp_df = temp_df[
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["排名", "艺人", "商业价值", "专业热度", "关注热度", "预测热度", "美誉度"]
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]
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temp_df["统计日期"] = datetime.datetime.now().date().isoformat()
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return temp_df
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def online_value_artist() -> pd.DataFrame:
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"""
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艺恩-艺人-艺人流量价值
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https://www.endata.com.cn/Marketing/Artist/business.html
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:return: 艺人流量价值
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:rtype: pandas.DataFrame
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"""
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url = "https://www.endata.com.cn/API/GetData.ashx"
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payload = {
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"Order": "FlowValueIndex_L1",
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"OrderType": "DESC",
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"PageIndex": 1,
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"PageSize": 100,
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"MethodName": "Data_GetList_Star",
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}
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r = requests.post(url, data=payload)
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r.encoding = "utf8"
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data_json = json.loads(decrypt(r.text))
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temp_df = pd.DataFrame(data_json["Data"]["Table"])
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temp_df.columns = [
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"排名",
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"-",
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"艺人",
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"-",
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"流量价值",
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"专业热度",
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"关注热度",
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"预测热度",
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"-",
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"带货力",
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]
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temp_df = temp_df[
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["排名", "艺人", "流量价值", "专业热度", "关注热度", "预测热度", "带货力"]
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]
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temp_df["统计日期"] = datetime.datetime.now().date().isoformat()
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return temp_df
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if __name__ == "__main__":
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business_value_artist_df = business_value_artist()
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print(business_value_artist_df)
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online_value_artist_df = online_value_artist()
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print(online_value_artist_df)
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