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Current Affairs – 08 September 2025 Top Headlines 1. France Political Crisis PM François Bayrou lost confidence vote in Parliament. Defeat: 364 votes against vs. 194 in support. President Macron under pressure to pick a new PM. Trigger: public anger over austerity measures & protests. 2. Norway General Election Centre-left Labour Party led by Jonas Gahr Støre wins narrowly. Secured 89 seats vs. 80 for centre-right. Indicates fragile governance & coalition challenges. 3. Nepal Unrest – Flights Suspended Major protests in Nepal force airport closures. Indian airlines IndiGo & Air India suspend flights to Kathmandu. Passengers stranded; Air India cancels flights for 2nd day. 4. Punjab Schools Reopening Delayed Due to heavy floods, reopening postponed to 09 September. DCs ordered to inspect schools for safety before allowing classes. 5. EU Delegation Visit to India Announced EU Political & Security Committee to visit India (10–14 Sept). Focus: defense, security & foreig...

Python for Data Compression: Key Features Readability and Simplicity Clear syntax, making code easy to write and understand. Reduced development time compared to other languages. Extensive Libraries `zlib`, `gzip`, `bz2`, for common compression algorithms. `lzma` for advanced LZMA compression. `zipfile` for managing compressed archives. Cross-Platform Compatibility Runs smoothly on various operating systems (Windows, macOS, Linux). Facilitates easy deployment of data compression solutions. Community Support and Resources Abundant online tutorials, documentation, and community forums. Easier troubleshooting and faster problem-solving. Integration with other tools Seamlessly integrates with other data science tools (NumPy, Pandas). Simplifies data preprocessing and post-processing steps.

Python Dictionaries: A Data Compression Perspective What is a Python Dictionary? A dictionary is a fundamental data structure in Python. It stores data in key-value pairs. Keys must be immutable (e.g., strings, numbers, tuples). Values can be of any data type. Dictionaries are unordered (before Python 3.7) and mutable. Dictionaries and Data Compression Dictionaries facilitate efficient data representation. They can be used to build symbol tables for encoding/decoding in compression algorithms. Representing frequent data with shorter keys saves space. Key-value pairs can map original data to compressed representations. Example: Huffman Coding with Dictionaries Create a dictionary mapping characters to their Huffman codes. { 'A': '00', 'B': '01', 'C': '10', 'D': '11'} Use this dictionary to encode a string. Decode using the same dictionary, reversing the mapping. Example: Run-Length Encoding (RL...

Data Compression: Mastering Type Conversion in Python What is Type Conversion? Type conversion, also known as type casting, is the process of changing a variable's data type from one to another. Python supports both implicit (automatic) and explicit (manual) type conversion. Implicit Type Conversion Python automatically converts data types in certain situations to prevent errors. Example: Adding an integer to a float results in a float. Explicit Type Conversion We use built-in functions like `int()`, `float()`, `str()`, `bool()` etc. to explicitly change data types. Example: Converting a string "10" to an integer using `int("10")`. Example: Data Compression Context Imagine you're storing compressed file sizes (originally floats) in a database designed for integers. Explicit type conversion (using `int()`) would truncate the decimal part, losing precision but saving space. This is a type of lossy compression. Converting from a larger data t...

Understanding Local and Global Variables in Python: A Data Compression Perspective What are Local Variables? Local variables are declared inside a function. Their scope is limited to that function. They are created when the function is called and destroyed when the function exits. This localized nature can be relevant in optimizing data structures within a function, aiding compression strategies. Improper use can lead to unnecessary data duplication if not handled carefully in recursive functions or complex data structures. What are Global Variables? Global variables are declared outside any function. Their scope extends throughout the entire program. They are accessible from any function within the program. Overuse can negatively impact data compression efforts by increasing memory usage unnecessarily, especially in large applications. Careful management is crucial for maintaining modularity and data integrity in complex systems, a key factor in efficient compressi...

Decoding the Magic of LZW Compression: A Data Compression Deep Dive What is LZW Compression? Lempel-Ziv-Welch (LZW) is a lossless data compression algorithm. It works by replacing repeating sequences of data with shorter codes. It's widely used in GIF image format and other applications. Highly effective for data with repeating patterns. How LZW Compression Works: A Step-by-Step Guide Starts with a dictionary containing single characters. Reads the input data character by character. Concatenates characters to form strings. When a string is not found, it's added to the dictionary with a new code. The code for the longest matching string is written to the output. This process continues until the entire input is processed. LZW Compression Example: Initial Dictionary: {'A': 1, 'B': 2, 'C': 3} Input String: "ABABCABABCACC" Processing: - 'A' is encoded as 1. - 'AB' is encoded as 4 (added to diction...