a zero-dependency, low-latency c++ ingestion engine. designed to parse massive network datasets and flag anomalous behavior using strict rule-based heuristics.
built to mirror python/pandas data manipulation logic, but executed at hardware-level speeds to demonstrate memory-safe data structuring and
-
memory management: uses
std::vectorwith pre-allocated memory reserves to completely eliminate dynamic reallocation lag during data ingestion. -
rapid string parsing: implements native
std::stringstreamfor lightweight, low-level csv tokenization. -
algorithmic efficiency: utilizes
std::unordered_mapfor instant$O(1)$ time complexity when tracking network traffic volumes per ip. - aesthetic ui: features a minimalist, 24-bit truecolor terminal interface mapped with custom soft lavender, sage green, and navy rgb values.
requires a native c++ compiler (g++).
# 1. compile and generate the mock dataset
g++ src/generate_mock.cpp -o build/generate_mock
./build/generate_mock
# 2. run the anomaly engine
g++ src/scraper.cpp -o build/scraper
./build/scraper