The 本製品 can be used to create ETL applications and pipelines for CSV data in Python using Petl.

Install Required Modules

Install the Petl modules using the pip utility.

pip install petl

Connecting

Import the modules, including the CData Python Connector for Twitter. You can then use the 本製品's connect function to create a connection using a valid Twitter connection string. A SQLAlchemy engine may also be used instead of a direct connection.

import petl as etl
import cdata.twitter as mod
cnxn = mod.connect("InitiateOAuth=GETANDREFRESH;")

Extract, Transform, and Load the Twitter Data

Create a SQL query string and store the query results in a DataFrame.

sql = "SELECT	From_User_Name, Text FROM Tweets "
table1 = etl.fromdb(cnxn,sql)

Loading Data

With the query results stored in a DataFrame, you can load your data into any supported Petl destination. The following example loads the data into a CSV file.

etl.tocsv(table1,'output.csv')

Modifying Data

Insert new rows into Twitter tables using Petl's appenddb function.

table1 = [['From_User_Name','Text'],['My twitter message','My twitter message 2']]
etl.appenddb(table1,cnxn,'Tweets')