Showing posts with the label Python Projects

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8 Ways to Optimize AWS Glue Jobs in a Nutshell

  Improving the performance of AWS Glue jobs involves several strategies that target different aspects of the ETL (Extract, Transform, Load) process. Here are some key practices. 1. Optimize Job Scripts Partitioning : Ensure your data is properly partitioned. Partitioning divides your data into manageable chunks, allowing parallel processing and reducing the amount of data scanned. Filtering : Apply pushdown predicates to filter data early in the ETL process, reducing the amount of data processed downstream. Compression : Use compressed file formats (e.g., Parquet, ORC) for your data sources and sinks. These formats not only reduce storage costs but also improve I/O performance. Optimize Transformations : Minimize the number of transformations and actions in your script. Combine transformations where possible and use DataFrame APIs which are optimized for performance. 2. Use Appropriate Data Formats Parquet and ORC : These columnar formats are efficient for storage and querying, signif

10 Exclusive Python Projects for Interviews

Here are ten Python projects along with code and possible solutions for your practice. 01. Palindrome Checker: Description: Write a function that checks if a given string is a palindrome (reads the same backward as forward). def is_palindrome(s):     s = s.lower().replace(" ", "")     return s == s[::-1] # Test the function print(is_palindrome("radar"))  # Output: True print(is_palindrome("hello"))  # Output: False 02. Word Frequency Counter: Description: Create a program that takes a text file as input and counts the frequency of each word in the file. def word_frequency(file_path):     with open(file_path, 'r') as file:         text =         words = text.split()         word_count = {}         for word in words:             word_count[word] = word_count.get(word, 0) + 1     return word_count # Test the function file_path = 'sample.txt' word_count = word_frequency(file_path) print(word_count) 03. Guess the Nu