How to perform ETL Automation using Selenium

Extracting information from large datasets or sources is an integral part of various organizations where the data is fetched from various sources and meaningful insights are drawn from the same. Or simply, the data is fed to the next processes in the pipeline. The entire process in which the data is extracted, transformed, and loaded into the program is essentially the most significant and initial step in any software development process. Therefore, in this article, we will learn how we can automate the ETL process using selenium. 

What is ETL?

ETL means Extract, Transform, and Load, which essentially means fetching the data from various sources to a common repository or data warehouse. The entire process stresses the need to create a standard procedure for data analytics and machine learning problems among many other applications where the data is extracted from various sources, transformed according to a business requirement, and then loaded into the workflows for the desired output or results. The main objective of the ETL process is to leverage the entire process and catapult only the useful and necessary information for further tasks to reduce delay and improve efficiency. 

What is ETL Automation?

The process of automating the entire process of extracting the data, basic transformations and loading the data points is called ETL automation. The entire process eliminated the manual coding to extract, transform and load the data for various business requirements. 

ETL automation helps the data flow in the following ways:

1. Reduces delivery time and helps in budget management by reducing waste during the entire process. 
2. Helps validate data before the migration after automating complex processes.
3. Transformation of data becomes automated helps in ETL process efficiency.
4. Data cleaning process is automated with repeated migrations that can be easily performed.

There are several automation tools that can be used to facilitate ETL automation for your processes. Some of the functionalities that automation tools provide are as follows:

1. Database Connectivity
2. Test cases or rules to test functionality, transformations, etc
3. Integration with various project management tools
4. Deployment support with AWS, GCP, Azure, etc. 

Let us take a look at various scenarios that we can have in ETL automation. 

Scenarios in ETL Automation

There are several scenarios we can have while doing ETL automation. Some of the scenarios are listed below.

1. The case where we are checking the structure of the data. In this scenario we will go through the source of the data, various data points like fields, columns names, etc.
2. In The case where we are going to validate the constraints, we basically test various constraints that we are supposed to apply to specific tables, columns, etc. 
3. The case where we validate the mapping document. In this scenario, we will validate the mapping document to ensure all the required information is provided in the mapping document. 
4. The case where we validate the null values in the data. Here, we analyze the null values and transformation of null values where the imputations applied to the data are valid or not.
5. The case to check date time variables. The validation of date time variables to ensure there is no inconsistency in time series data.
6. The case to check the completeness of data points. Ensure all the records have been loaded as per the requirements.
7. The case to validate the transformation of data. Ensure that the data is transformed according to the required format before loading it into the workflow. 
8. The case to validate the presence of duplicate records in the data. 

These are some of the scenarios where ETL automation test cases are created to ensure a seamless flow of data. Let’s take a look at how we can automate a simple ETL process using selenium and python. 

ETL Automation Using Selenium 

In this section, we will perform a simple ETL automation process where we will perform the following:

1. Extract the data from a source, i.e local computer.
2. Transform the data before loading it into the workflow. 
3. Validate the data after asserting the structure of the data by matching column names. 
4. Automate the entire process using Selenium and Selenium WebDriver. 

For the following script to run seamlessly, you will need to solve the following dependencies:

1. Install Python, Selenium, and Pandas
2. Install relevant webdriver with compatible version
3. Make sure the webdriver is in the path, or you can specify the path of the webdriver as shown in the code below. 

[python]
from selenium import webdriver
import time
from os import listdir
from selenium.common.exceptions import WebDriverException
import pandas as pd


def main():
dataset_source = r'C:\Users\HP\Downloads\datasets\Advertising'
driver = webdriver.Chrome(r'C:\Users\HP\Desktop\chromedriver\chromedriver.exe')
for file in listdir(dataset_source):
if file.endswith('csv'):
df = pd.read_csv(dataset_source +"\\" + file)
columns = df.columns
assert "Sales ($)" in columns
time.sleep(5)
driver.quit()


if __name__ == "__main__":
main()

[/python]

In the above python script, the code executes the process with exit code 0, which asserts that our data was loaded from the directory source. You can also run the selenium webdriver in the headless mode to reduce computational time as well. It was transformed into a data frame using the pandas library from python, and the structure of the data was validated by asserting the column name in the table loaded from the directory. Hence, the entire ETL process was automated using selenium and a simple scenario was tested to see if the structure of the data in the ETL process was accurate or not. Similarly, we can perform endless scenarios for our ETL process using selenium.

Conclusion

ETL is the backbone of any project or venture that includes data points i.e majority of processes. Therefore, automation of the entire ETL process calls for a safeguard when it comes to the validation of accurate information being catapulted into workflows that are eventually migrated into live services. Selenium being a very primitive option provides a lot of support for ETL automation but isn’t a first choice for ETL automation amongst the QA community.