Python module to read data from a CSV file and write validation responses to an output CSV file with results appended to each row.
This was written with a specific use case: given a CSV file with n rows, validate that the correct data for an account is returned from an API, as per the CSV file. While this is a specific use case, this module can be adapted for any kind of mass data validation against an API call.
For my use case, the CSV file is expected to be formatted as follows:
[Col 1] [Col 2] [Col 3] [Col 4]
Account # data_to_verify Account Type CSV File Name
Use a virtual environment to run Python3. From the root of this repo, run the following:
virtualenv -p python3 ENV
source ENV/bin/activate
pip install -r requirements.txt
In order to run verify.py successfully, a config.py file needs to be created. Copy config.example.py as config.py and fill it in with your specific values. See config.example.py for more details on setting up the config file.
Run python verify.py to start the script on the command line.
It will first prompt for the input CSV file, this is the file that you want to test. Make sure the columns are in the format discussed above, or change the script to suit your needs. Save the input CSV file under the input_csv_files/ folder.
The second prompt will ask for the output CSV file name and full extension. No need to create this file before running the script, just provide a name, EX: test_output.csv, and it will be saved under the output_results/ folder.
The third and final prompt will ask for the environment you want to test in, which is set in the config file. See config.example.py to set up properly.
verify_tiers
├── config.example.py # config template
├── config.py # config file used to run script
├── input_csv_files
│ └── example_input.csv # put CSV file to test here
├── output_results
│ └── example_output.csv # output dropped in here
└── verify.py # main file to execute