Posts

Showing posts with the label regular-expressions

Featured Post

14 Top Data Pipeline Key Terms Explained

-
Image
 Here are some key terms commonly used in data pipelines 1. Data Sources Definition: Points where data originates (e.g., databases, APIs, files, IoT devices). Examples: Relational databases (PostgreSQL, MySQL), APIs, cloud storage (S3), streaming data (Kafka), and on-premise systems. 2. Data Ingestion Definition: The process of importing or collecting raw data from various sources into a system for processing or storage. Methods: Batch ingestion, real-time/streaming ingestion. 3. Data Transformation Definition: Modifying, cleaning, or enriching data to make it usable for analysis or storage. Examples: Data cleaning (removing duplicates, fixing missing values). Data enrichment (joining with other data sources). ETL (Extract, Transform, Load). ELT (Extract, Load, Transform). 4. Data Storage Definition: Locations where data is stored after ingestion and transformation. Types: Data Lakes: Store raw, unstructured, or semi-structured data (e.g., S3, Azure Data Lake). Data Warehous...
Post a Comment
Read more

How to Search for Single CHAR in Python Using Regular-expression

-
Image
Here is the logic for searching single CHAR using regular expression(Regex). For instance, we use wildcards to search for anything on our computers. The Regex in Python works similarly. Regular expression People use asterisk * for searching any document. For instance, if you type *.pdf, it returns all the pdfs available in the location (where you are conducting your search). Similar way, in Python, you can search using regular expressions. Import Regex  The first thing you need to do is import 're' if you want to work with regular expressions. import re The Python regular expression library, you can use to improve your skills. Example program: search for single CHAR To match any single character, you can use  [….] . Below, you will find an example to search for: 'l' or 'a' or 'b' import re pattern = r'[lab]' sequence = 'we love python' obj = re.search(pattern,sequence) if obj: print("We found a match here @",obj.group()) else: p...
Post a Comment
Read more

How to write Regular expression Quickly in python and Examples

-
Image
Regular Expressions purpose is to find matching string in another string. You will get either 'True' or 'False' as a response. I am not sharing here how to play tennis. My intention is if you just follow ideas, you can play tennis today.   Python Regular Expressions What is a regular expression How does python support Best examples 1. What is regular expression >>> haystack = 'My phone number is 213-867-5309.'  >>> '213-867-5309' in haystack True This is just a fundamental use of the regular expression. The real use of Regular Expression comes here. That is - to find if the main has any valid phone number. Regular expressions also called regexes. 2. Why do we need regx Data mining - to get required data if it is present are not Data validations - to get an answer if the received string is valid or not. Python support Python has its own regular expression library. That is called re . What you need to do is just import it. >>>imp...
Post a Comment
Read more