Python 3 library to store memory mappable objects into pickle-compatible files

A thread-safe queue which queues items on disk, with an optional in memory buffer. Can put and get any pickle-able object into a buffer of a specified size (optional), any overflow will get put to a gzip file to keep excessive amounts of queued items out of memory

A Model Context Protocol server that gives AI agents precise memory for project management.

A pickleable wrapper for sharing NumPy ndarrays between processes using POSIX shared memory.

Benchmark repository that traces the peaktime memory usage of numpy array pickling

A demonstration of pickler memory leak

A memory-friendly warpper of pickle with better compression.

A Python application that manages students and disciplines using object-oriented-architecture and a setting property file( that allows the user to choose in-memory, text files, or pickle methods of working with data)

Create temporary files in memory using json, pickle and other possible ways.

A Retrieval-Augmented Generation (RAG) chatbot that answers questions from multiple PDF documents using semantic search. Built with LangChain, ChromaDB, HuggingFace embeddings, and Groq LLM with persistent chat memory stored in pickle files.

A Python package that provides a disk-backed list implementation for handling large datasets efficiently. When your data gets too large for memory, paged-list automatically chunks it into pickle files on disk, only loading relevant chunks when needed.

In this project, I have created a model to predict the sentiment of a given tweet and also deployed the same using Streamlit. Due to the heavy memory consumption and large pickle files >>25mb, the heroku does not process the vectorizing of the data and results are not obtained . Hence I request you to watch the ML-appstreamlit mp4 video where i ran the app successfully using local host.