Zlib

stats.print_stats() end_time = datetime.datetime.now() latency = calculate_latency(start_time, end_time) print(f"Latency: {latency} hours") if __name__ == "__main__": main() ``` ### Steps to Follow 1. **Run the Scrip…

- Process feedback data on-demand and store only the necessary data in memory. 5. **Profile and Analyze**: - Use logging to monitor memory usage and identify areas for optimization. ### Additional Tips 1. **Use Generators**: - U…

- Zlib is a widely used compression library that provides a good balance between compression ratio and speed. - It is part of the Python standard library, so no additional installation is required. 2. **Gzip Compression**: - Gzip …

print(decompressed_data.shape) ``` #### LZ4 Compression ```python import lz4.frame import numpy as np # Example feedback data feedback_data = np.random.rand(10000, 10) # Compress the data compressed_data = lz4.frame.compress(feedback_da…

- Compress large data structures using libraries like `zlib`, `gzip`, `brotli`, or `lz4`. - Store compressed data and decompress it on-the-fly when needed. 5. **Caching**: - Use in-memory caching solutions like Redis or Memcached …

processed_feedback = process_feedback(feedback_data) ``` #### Lazy Loading and Chunking ```python def load_data_in_chunks(chunk_size=1000): for i in range(0, len(feedback_data), chunk_size): yield feedback_data[i:i + chunk_siz…

Use memory profiling tools to identify memory leaks and inefficient memory usage. Tools like `memory_profiler` in Python can help you pinpoint areas where memory usage can be optimized. ### 6. **Compression** Compress data that is stored i…

Reuse objects instead of creating new ones. Object pooling can be particularly effective for objects that are frequently created and destroyed. ### 5. **Garbage Collection Tuning** Tune the garbage collector to better suit your application…