Purpose:

The Python script processes and exports account data from a primary data source without modifications.

To Elaborate

The Python script is designed to handle account data by taking input from a specified data source and exporting it without making any changes. The script ensures that the column headers in the output match those of the input data, maintaining consistency in the data structure. This process is useful for scenarios where data needs to be transferred or backed up without alteration. The script also includes a feature to skip output validations, allowing for flexibility in handling the data. The primary goal is to facilitate the seamless transfer of data while preserving its original format and structure.

Walking Through the Code

1. Importing Libraries and Setting Up Environment:
   • The script begins by importing the datetime module to handle date and time operations.
   • It sets the current date based on the client’s timezone, although this part is not directly relevant to the data processing task.
2. Data Source Initialization:
   • The script retrieves the primary data source, referred to as inputDf, from a dictionary named dataSourceDict using the key "2_1".
   • This data frame serves as the input for further processing.
3. Data Export and Column Management:
   • A copy of the input data frame, inputDf, is created and assigned to outputDf.
   • The column headers of outputDf are explicitly set to match those of inputDf, ensuring that the structure remains unchanged.
4. Custom Output Handling:
   • A flag skip_output_validations is set to True, indicating that any output validation steps are bypassed. This allows for more flexible handling of the output data.
5. Displaying Data:
   • The script concludes by printing the first few rows of the outputDf using a function tableize, which formats the data for display purposes.

Vitals

• Script ID : 1491
• Client ID / Customer ID: 1306927965 / 60270405
• Action Type: Revenue Upload (Preview)
• Item Changed: None
• Output Columns: Date, Keyword ID, Creative ID, Keyword, Match Type, Group ID, Campaign ID, Property Published (Conv Date) Conv, Property Registered (Conv Date) Conv, Property Validated (Conv Date) Conv
• Linked Datasource: FTP/Email Feed
• Reference Datasource: Google Sheets
• Owner: Tom McCaughey (tmccaughey@marinsoftware.com)
• Created by Tom McCaughey on 2024-11-07 11:10
• Last Updated by Tom McCaughey on 2024-11-07 11:26

> See it in Action

Python Code

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##
## name: Offline Account Data
## description:
##  
## 
## author: 
## created: 2024-11-07
## 

import datetime

today = datetime.datetime.now(CLIENT_TIMEZONE).date()

# primary data source and columns
inputDf = dataSourceDict["2_1"]

# Export inputDf without any changes
outputDf = inputDf.copy()
outputDf.columns = inputDf.columns  # Set column headers to match those of inputDf

#allow for custom output columns
skip_output_validations = True

# user code start here
print(tableize(outputDf.head()))

Post generated on 2025-03-11 01:25:51 GMT