python实现：从接口中读取数据，把数据以excel、pdf、图片、csv格式发送到企业微信群
接口文檔地址：https://developer.work.weixin.qq.com/document/path/99110
1.發送圖文
1.對接接口
bash
import json
import time
import requests
import time_util
rbt_key = "https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=key"
headers = {'Content-Type': 'application/json; charset=UTF-8'}
text = '未拉OA提醒'
##toke
def get_superset_token():
url = "http://hadoop102:8787/api/v1/security/login"
request_param = {
"password": "passwd",
"provider": "db",
"refresh": True,
"username": "user"
}
headers = {
"Content-Type": "application/json"
}
response = requests.post(url, data=json.dumps(request_param), headers=headers)
return response.json()["access_token"]
def get_superset_data():
access_token = get_superset_token()
# target_date = time_util.convert_to_cst(time.time(), 'Asia/Shanghai').strftime('%Y-%m-%d')
target_date = '2024-03-21'
target_user = 'ALLEN.X'
url = "http://hadoop102:8787/api/v1/chart/data"
headers = {
'Authorization': f'Bearer {access_token}', # 添加正确格式的 Bearer Token
'Content-Type': 'application/json'
}
request_param = {
"datasource": {
"id": 94,
"type": "table"
},
"queries": [
{
"columns": [
"user_name",
"日程類型",
"标题"
, "日程开始时间",
"日程结束时间",
"是否属于全天日程",
"OA状态"
],
"orderby": [
[
"user_name",
True
]
],
"row_limit": 100,
"order_desc": True,
"result_format": "string",
"form_data": "string",
"where": "user_name = '" + target_user + "' and start_date = '" + target_date + "'"
}
]
}
response = requests.post(url, data=json.dumps(request_param), headers=headers)
if response.status_code == 200:
return response.json()['result'][0]['data']
else:
return 'error'
def send_text(text): # 添加 result 參數用於傳遞消息內容
data = {
"msgtype": "markdown",
"markdown": {
"content": text + "\n<@allen>"
}
}
requests.post(rbt_key, headers=headers, json=data)
def send_image(): # 添加 result 參數用於傳遞消息內容
# send_text(text)
data = {
"msgtype": "news",
"news": {
"articles": [
{
"title": "==未拉OA提醒==",
"description": "提醒各位拉OA",
"url": "\\\\ip地址\\is-department\\小組\\myoa\\image\\schedule_table.png",
"picurl": "https://pic.616pic.com/ys_img/00/99/99/AdcfGUOyJR.jpg"
}
]
}
}
requests.post(rbt_key, headers=headers, json=data)數據時間處理
bash
from datetime import datetime, timedelta
import pytz
# 時間戳轉美國和中國時區
def convert_to_cst(timestamp, time_zone):
dt = datetime.fromtimestamp(timestamp, pytz.utc) # 将时间戳转换为datetime对象（UTC时间）
pst = dt.astimezone(pytz.timezone(time_zone)) # 转换为美国PST时区时间
return pst
# return pst.strftime('%Y-%m-%d %H:%M:%S') # 格式化为字符串
def convert_to_pst(timestamp):
dt = datetime.fromtimestamp(timestamp/1000) # 将时间戳转换为datetime对象（UTC时间）
pst = dt + timedelta(hours=7) # 增加8小时，即美国PST时间
return pst.strftime('%Y-%m-%d %H:%M:%S') # 格式化为字符串主程序
bash
import data_util, time_util
import pandas as pd
import matplotlib.pyplot as plt
if __name__ == '__main__':
data = data_util.get_superset_data()
if(len(data)>0):
# 应用函数转换时间戳
for entry in data:
entry['日程开始时间'] = time_util.convert_to_pst(entry['日程开始时间'])
entry['日程结束时间'] = time_util.convert_to_pst(entry['日程结束时间'])
# 创建DataFrame
df = pd.DataFrame(data)
# 如果不为空，则绘制表格
# 指定中文字体
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
# 保存为图片，并指定dpi参数
fig, ax = plt.subplots(figsize=(10, 6), dpi=500)
ax.axis('tight')
ax.axis('off')
ax.table(cellText=df.values, colLabels=df.columns, loc='center', cellLoc='center')
# 自定义保存路径
save_path = 'image/schedule_table.png'
print(save_path)
plt.savefig(save_path)
# 可选：显示保存成功的提示
print(f"图片已保存至：{save_path}")
else:
print("error")
data_util.send_image()2.發送純圖片
主程序
bash
import data_util, time_util
import pandas as pd
import matplotlib.pyplot as plt
import base64
import hashlib
if __name__ == '__main__':
data = data_util.get_superset_data()
if (len(data) > 0):
# 应用函数转换时间戳
for entry in data:
entry['日程开始时间'] = time_util.convert_to_pst(entry['日程开始时间'])
entry['日程结束时间'] = time_util.convert_to_pst(entry['日程结束时间'])
# 创建DataFrame
df = pd.DataFrame(data)
# 如果不为空，则绘制表格
# 指定中文字体
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
# 保存为图片，并指定dpi参数
fig, ax = plt.subplots(figsize=(10, 6), dpi=500)
ax.axis('tight')
ax.axis('off')
ax.table(cellText=df.values, colLabels=df.columns, loc='center', cellLoc='center')
# 自定义保存路径
save_path = 'image/schedule_table.png'
# print(save_path)
plt.savefig(save_path)
# 可选：显示保存成功的提示
print(f"图片已保存至：{save_path}")
# 1. 读取图片文件内容
with open("image/schedule_table.png", "rb") as f:
image_data = f.read()
# 2. 对图片内容进行Base64编码
base64_image = base64.b64encode(image_data).decode('utf-8')
# 3. 计算图片内容的MD5值
md5_hash = hashlib.md5(image_data).hexdigest()
data_util.send_image(base64_image, md5_hash)
else:
print("error")數據接口
bash
def send_image(data, md5): # 添加 result 參數用於傳遞消息內容
# send_text(text)
data = {
"msgtype": "image",
"image": {
"base64": data,
"md5": md5
}
}
requests.post(rbt_key, headers=headers, json=data)3.發送excel，csv，pdf
主程序
bash
import data_util, time_util
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
if __name__ == '__main__':
data = data_util.get_superset_data()
df = ''
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
if (len(data) > 0):
# 应用函数转换时间戳
for entry in data:
entry['日程开始时间'] = time_util.convert_to_pst(entry['日程开始时间'])
entry['日程结束时间'] = time_util.convert_to_pst(entry['日程结束时间'])
if isinstance(data, dict):
if data:
df = pd.DataFrame.from_records([data])
else:
print("Data is an empty dictionary")
df = pd.DataFrame()
elif isinstance(data, list):
dfs = [pd.DataFrame.from_records([item]) for item in data if isinstance(item, dict)]
df = pd.concat(dfs, ignore_index=True)
else:
print("Data is not a list or a dictionary")
df = pd.DataFrame()
# print(df)
df.to_excel('media.xlsx', index=False)
df.to_csv('media.csv', index=False)
# 创建一个PDF文件
with PdfPages('media.pdf') as pdf:
# 将DataFrame绘制成表格
fig, ax = plt.subplots(figsize=(8.27, 11.69), dpi=400) # 设置dpi为300，提高图像质量
ax.axis('tight')
ax.axis('off')
ax.table(cellText=df.values, colLabels=df.columns, loc='top', cellLoc='center')
pdf.savefig(dpi=400) # 将当前图形保存到PDF，并设置dpi
plt.close()
print("PDF文件已生成")
data = data_util.send_file('media.pdf')
if data != 'error':
data_util.get_file(data)調用接口
bash
def send_file(file):
# 设置请求参数
url = "https://qyapi.weixin.qq.com/cgi-bin/webhook/upload_media?key=key&type=file"
data = {'file': open(file, 'rb')} # post jason
response = requests.post(url=url, files=data) # post 请求上传文件
if response.status_code == 200:
return response.json()['media_id']
else:
return 'error'
def get_file(media_id): # 添加 result 參數用於傳遞消息內容
data = {
"msgtype": "file",
"file": {
"media_id": media_id
}
}
requests.post(rbt_key, headers=headers, json=data)