How to add current timestamp column in pyspark dataframe 🕐 | F.current_timestamp explained in Hindi

This pyspark tutorial for beginners and data engineers in Hindi explains how to add a current timestamp column in the pyspark dataframe using withColumn and current_timestamp() pyspark standard functions.
current_timestamp pyspark date and timestamp format can vary, the default one is a timestamp with microsecond precision in the format yyyy-MM-dd HH:mm:ss.SSSSSS
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Also above pyspark Tutorial video has an example adding a new column in default format. The new column will be the part of dataframe output.
To use pyspark current_timestamp() function in your present code first you have to make sure it is imported to your code.
steps to import current timestamp pyspark function are as follows:
from pyspark.sql.functions import current_timestamp
"""with importing current_timestamp this way you can use the function directly in the code wherever you need a current timestamp column in your pyspark dataframe."""
from pyspark.sql import functions as F
""" personally, I go with this option. import pyspark SQL functions as F and then you can access literally any function just with prefix F. and in my opinion this is a better option than just importing each and every function from pyspark SQL functions individually and explicitly is a bit longer way to achieve the goal."""
Everything in this current timestamp pyspark tutorial is explained and demonstrated in Hindi language. Feel free to comment your learning experience with pyspark data engineers.