應朋友需要,想將某客戶的數據從某站里導出,先去某站搞個賬號,建幾條數據觀察一番,心里有底后開搞。
1.Python環境搭建
之前電腦有安裝過PyCharm Community 2019.1,具體安裝過程就不寫了,先跑個HelloWorld,輸出正常后正式開整。
2.利用抓包工具或者Google瀏覽器調試模式拿到請求參數
Cookies參數如下:
cookies = {
'JSESSIONID': 'XXX',
'phone': 'XXX',
'password': 'XXX',
'isAuto': '0', '
loginAccess': 'XXX'
}
headers請求頭信息構造:
headers = {
'Connection': 'keep-alive',
'sec-ch-ua': '"Google Chrome";v="89", "Chromium";v="89", ";Not A Brand";v="99"',
'Accept': 'application/json, text/javascript, */*; q=0.01', 'X-Requested-With': 'XMLHttpRequest', 'sec-ch-ua-mobile': '?0',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)
AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4389.90
Safari/537.36',
'Content-Type': 'application/json',
'Sec-Fetch-Site': 'same-origin',
'Sec-Fetch-Mode': 'cors',
'Sec-Fetch-Dest': 'empty',
'Referer': 'https://xxx.xxx.xxx',
'Accept-Language': 'zh-CN,zh;q=0.9',}
請求路徑:
params = ( ('method', 'getGoodsList'))
請求參數組裝:
data = '{
"pageSize":1000,
"pageNumber":1,
"searchText":"",
"sortOrder":"asc",
"isAdvancedSearch":false}'
pageSize:每頁數據數量
pageNumber:頁碼
searchText:搜索條件
sortOrder:排序
3.利用Requests模擬請求并獲取數據
response = requests.post(
'https://xxx.xxx.xxx',
headers=headers,
params=params,
cookies=cookies,
data=data
)
print(response.text.encode('utf8'))
res = json.loads(response.text)
4.創建Excel表格
t = time.time()
randStr = int(round(t * 1000))
tSheetName = "a_" + str(randStr) + ".xlsx"
workbook = xlsxwriter.Workbook(tSheetName)
worksheet = workbook.add_worksheet()
5.表頭及數據組裝
cursor = 0
picurl = ''
writeExcel(row=cursor)
for obj in res["rows"]:
cursor += 1
picurl = ''
if obj['ImageKID']:
picurl = 'https://xxx.xxx.xxx? imageKid='+obj['ImageKID']
writeExcel(row=cursor,Description=obj['Description'], Category=obj['Category'], Series=obj['Series'],BaseUnit=obj['BaseUnit'],Qty=obj['Qty'],
CostPrice=obj['CostPrice'],SalePrice=obj['SalePrice'],
RetailPrice=obj['RetailPrice'],Barcode=obj['Barcode'],
Remark=obj['Remark'], ImageKID=picurl)
6.將數據寫入Excel表格中
def writeExcel(row=0, Description='', Category='', Series='', BaseUnit='', Qty='', CostPrice='', SalePrice='', RetailPrice='', Barcode='', Remark='',ImageKID=''):
if row == 0:
worksheet.write(row, 0, '名稱')
worksheet.write(row, 1, '貨號')
worksheet.write(row, 2, '規格')
worksheet.write(row, 3, '單位')
worksheet.write(row, 4, '庫存')
worksheet.write(row, 5, '成本')
worksheet.write(row, 6, '批發價')
worksheet.write(row, 7, '零售價')
worksheet.write(row, 8, '條碼')
worksheet.write(row, 9, '備注')
worksheet.write(row, 10, '圖片')
else:
if ImageKID!='':
image_data = io.BytesIO(urllib.urlopen(ImageKID).read())
worksheet.insert_image(row, 10, ImageKID, {'image_data': image_data})
worksheet.write(row, 0, Description)
worksheet.write(row, 1, Category)
worksheet.write(row, 2, Series)
worksheet.write(row, 3, BaseUnit)
worksheet.write(row, 4, Qty)
worksheet.write(row, 5, CostPrice)
worksheet.write(row, 6, SalePrice)
worksheet.write(row, 7, RetailPrice)
worksheet.write(row, 8, Barcode)
worksheet.write(row, 9, Remark)
worksheet.set_column(10, 10, 23)
worksheet.set_row(row, 150)
注意圖片路徑不存在的情況,否則會執行異常
write方法:
def write(self, row, col, *args):
"""
Write data to a worksheet cell by calling the appropriate write_*()
method based on the type of data being passed.
Args:
row: The cell row (zero indexed).
col: The cell column (zero indexed).
*args: Args to pass to sub functions.
Returns:
0: Success.
-1: Row or column is out of worksheet bounds.
other: Return value of called method.
"""
return self._write(row, col, *args)
通過set_row方法設置表格行高
def set_row(self, row, height=None, cell_format=None, options=None):
"""
Set the width, and other properties of a row.
Args:
row: Row number (zero-indexed).
height: Row height. (optional).
cell_format: Row cell_format. (optional).
options: Dict of options such as hidden, level and collapsed.
Returns:
0: Success.
-1: Row number is out of worksheet bounds.
......
"""
通過set_column方法設置圖片列寬度:
def set_column(self, first_col, last_col, width=None, cell_format=None,
options=None):
"""
Set the width, and other properties of a single column or a
range of columns.
Args:
first_col: First column (zero-indexed).
last_col: Last column (zero-indexed). Can be same as first_col.
width: Column width. (optional).
cell_format: Column cell_format. (optional).
options: Dict of options such as hidden and level.
Returns:
0: Success.
-1: Column number is out of worksheet bounds.
......
"""
通過insert_image插入網絡圖片:
def insert_image(self, row, col, filename, options=None):
"""
Insert an image with its top-left corner in a worksheet cell.
Args:
row: The cell row (zero indexed).
col: The cell column (zero indexed).
filename: Path and filename for image in PNG, JPG or BMP format.
options: Position, scale, url and data stream of the image.
Returns:
0: Success.
-1: Row or column is out of worksheet bounds.
"""
# Check insert (row, col) without storing.
if self._check_dimensions(row, col, True, True):
warn('Cannot insert image at (%d, %d).' % (row, col))
return -1
if options is None:
options = {}
x_offset = options.get('x_offset', 0)
y_offset = options.get('y_offset', 0)
x_scale = options.get('x_scale', 1)
y_scale = options.get('y_scale', 1)
url = options.get('url', None)
tip = options.get('tip', None)
anchor = options.get('object_position', 2)
image_data = options.get('image_data', None)
description = options.get('description', None)
decorative = options.get('decorative', False)
# For backward compatibility with older parameter name.
anchor = options.get('positioning', anchor)
if not image_data and not os.path.exists(filename):
warn("Image file '%s' not found." % force_unicode(filename))
return -1
self.images.append([row, col, filename, x_offset, y_offset,
x_scale, y_scale, url, tip, anchor, image_data,
description, decorative])
return 0
注意insert_image(row, colunmNum, ‘xx.png', {‘url': xxx})并不能插入網絡圖片,只是給本地圖片一個url路徑
7.關閉表格
8.附引入的包
# -*- coding: UTF-8 -*-
# 批量獲取XX數據
import io
import json
import requests
import sys
import xlsxwriter
import time
import urllib
9.代碼跑起來

在看下Excel表格中導出的信息

到此這篇關于Python中Cookies導出某站用戶數據的方法的文章就介紹到這了,更多相關Python Cookies導出數據內容請搜索腳本之家以前的文章或繼續瀏覽下面的相關文章希望大家以后多多支持腳本之家!
您可能感興趣的文章:- python爬蟲之Appium爬取手機App數據及模擬用戶手勢
- Python爬取用戶觀影數據并分析用戶與電影之間的隱藏信息!
- Python編寫檢測數據庫SA用戶的方法
- 如何用Python數據可視化來分析用戶留存率