使用 Python 将目录中的 CSV 文件导入 MySql 表

Question

我想读取文件夹/路径中的多个 CSV 文件并将它们放入 mysql 表中。我在这里找到了几个解决方案，指向将单个 csv 文件读取到 mysql 中，但我需要解析多个文件。你能帮我从哪里开始吗？我已经使用下面的脚本来阅读 csv .. 但我愿意接受您的建议。示例单个 csv 文件；列将是：TimeStamp,Message/Event,Server Totals,Client Totals1564981556,INVITE Requests,39967,377871564981556,100 Trying          ,39896,377581564981556,180 Ringing         ,1113,11131564981556,181 Forwarded       ,0,01564981556,182 Queued          ,1,11564981556,183 Progress        ,251,2511564981556,1xx Provisional     ,0,01564981556,200 OK              ,913,9131564981556,202 Accepted        ,0,01564981556,2xx Success         ,0,01564981556,30x Moved           ,0,01564981556,400 Bad Request     ,2,21564981556,401 Unauthorized    ,252,2521564981556,403 Forbidden       ,320,3241564981556,404 Not Found       ,487,4871564981556,405 Not Allowed     ,0,01564981556,406 Not Acceptable  ,0,01564981556,407 Proxy Auth Req  ,998,9981564981556,408 Request Timeout ,5220,52171564981556,415 Bad Media Type  ,0,01564981556,423 Too Brief       ,0,01564981556,480 Unavailable     ,49,491564981556,481 Does Not Exist  ,0,01564981556,482 Loop Detected   ,0,01564981556,483 Too Many Hops   ,6738,67381564981556,484 Address Incompl ,1039,10391564981556,485 Ambiguous       ,0,01564981556,486 Busy Here       ,159,1741564981556,487 Terminated      ,2530,25301564981556,488 Not Acceptable  ,8199,81991564981556,489 Bad Event       ,0,01564981556,491 Req Pending     ,0,0import pandas as pdimport globpath = r'C:\\Users\\xxx\\Documents\\files\\' # use your pathall_files = glob.glob(path + "\*.csv")li = []for filename in all_files:    df = pd.read_csv(filename, index_col=None, header=0)    li.append(df)frame = pd.concat(li, axis=0, ignore_index=True)print(frame)

Answer 1

import d6tstack

import glob

c = d6tstack.combine_csv.CombinerCSV(glob.glob('*.csv'))

c.to_mysql_combine('mysql+mysqlconnector://usr:pwd@localhost/db', 'tablename'

使用 d6stack 库，您可以存储它！！