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- Functions in Python- Syntax, execution, examples
- Functional Programming concepts in Python — Lambda functions and Decorators — with examples, data engineering use cases
- Recursion in Python – Deep Dive into Recursive Functions
- Python ALL Eyes on Strings- String Data Type & For Loop Combined
- Date and Time Functions- Pyspark Dataframes & Pyspark Sql Queries
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Category: Tutorials
Functions in Python- Definition Functions in Python are blocks of code that perform a specific task, and they can be defined using the def keyword. Function template Definition: Function Call: Function Name: Parameters Function Body Docstring Return Statement Pass Statement Lambda Functions Default Argument Values Variable-Length Arguments Keyword-Only Arguments Python 3.x Example: Combination of *args,…
Here’s a full explanation of Functional Programming concepts in Python — Lambda functions and Decorators — with examples, data engineering use cases, and pro tips to make your pipelines smarter, cleaner, and reusable. 🔹 1. Lambda Functions in Data Engineering ✅ What it is: A lambda is an anonymous, one-line function — useful for quick…
Recursion is a programming technique where a function calls itself directly or indirectly. It is extremely useful in solving divide-and-conquer problems, tree/graph traversals, combinatorics, and dynamic programming. Let’s explore it in detail. 🔎 Key Concepts of Recursion ✅ 1. Base Case The condition under which the recursion ends. Without it, recursion continues infinitely, leading to…
Here’s a comprehensive Python string function cheat sheet in tabular format: Function Syntax Description Example Return Type capitalize str.capitalize() Capitalizes the first character of the string. “hello”.capitalize() → “Hello” str casefold str.casefold() Converts to lowercase, more aggressive than lower(). “HELLO”.casefold() → “hello” str center str.center(width, fillchar=’ ‘) Centers the string, padded with fillchar. “hello”.center(10, ‘-‘) → “–hello—” str count str.count(sub, start=0, end=len(str)) Counts occurrences of sub in…
A quick reference for date manipulation in PySpark:– Function Description Works On Example (Spark SQL) Example (DataFrame API) to_date Converts string to date. String TO_DATE(‘2024-01-15’, ‘yyyy-MM-dd’) to_date(col(“date_str”), “yyyy-MM-dd”) to_timestamp Converts string to timestamp. String TO_TIMESTAMP(‘2024-01-15 12:34:56’, ‘yyyy-MM-dd HH:mm:ss’) to_timestamp(col(“timestamp_str”), “yyyy-MM-dd HH:mm:ss”) date_format Formats date or timestamp as a string. Date, Timestamp DATE_FORMAT(CURRENT_DATE, ‘dd-MM-yyyy’) date_format(col(“date_col”), “dd-MM-yyyy”)…
To determine the optimal number of CPU cores, executors, and executor memory for a PySpark job, several factors need to be considered, including the size and complexity of the job, the resources available in the cluster, and the nature of the data being processed. Here’s a general guide: 1. Number of CPU Cores per Executor 2. Number…
Suppose If i am given a maximum of 20 cores to run my data pipeline or ETL framework, i will need to strategically allocate and optimize resources to avoid performance issues, job failures, or SLA breaches. Here’s how you can accommodate within a 20-core limit, explained across key areas: 🔹 1. Optimize Spark Configurations Set…
Here’s a complete blueprint to help you develop and maintain CI/CD pipelines using GitHub for automated deployment, version control, and DevOps best practices in data engineering — particularly for Azure + Databricks + ADF projects. 🚀 PART 1: Develop & Maintain CI/CD Pipelines Using GitHub ✅ Technologies & Tools Tool Purpose GitHub Code repo +…
Here’s a complete guide to building and managing data workflows in Azure Data Factory (ADF) — covering pipelines, triggers, linked services, integration runtimes, and best practices for real-world deployment. 🏗️ 1. What Is Azure Data Factory (ADF)? ADF is a cloud-based ETL/ELT and orchestration service that lets you: 🔄 2. Core Components of ADF Component…
Here’s a complete guide to architecting and implementing data governance using Unity Catalog on Databricks — the unified governance layer designed to manage access, lineage, compliance, and auditing across all workspaces and data assets. ✅ Why Unity Catalog for Governance? Unity Catalog offers: Feature Purpose Centralized metadata Unified across all workspaces Fine-grained access control Table,…