Search Results for "logic analysis"

Automation of Unit and System Tests. Tests can be implemented in any language and on many platforms. The flexible approach enables the inclusion of many types of tests, such as memory leak checks (using valgrind), coding rule checks, complexity checks, etc. Tests are run by a simple call to hwut in a base directory of a project. In particular for C, HWUT supports make file generation using 'sos' and 'sols' modes. Remote control-able function stubs may be generated using the 'stub' mode....

...The repo is evidently tied to a popular video series (on Bilibili) that reportedly drew substantial attention, suggesting the material is meant to be both educational and hands-on. The README and associated lessons walk the user through implementing algorithms, likely covering data handling, backtesting, and maybe simple trading logic. As an open-source educational resource, it’s designed for Python users interested in automatic trading, algorithmic strategies, and financial data analysis.

StreamAlert is a serverless, real-time data analysis framework that empowers you to ingest, analyze, and alert on data from any environment, using data sources and alerting logic you define. Computer security teams use StreamAlert to scan terabytes of log data every day for incident detection and response. Incoming log data will be classified and processed by the rules engine. Alerts are then sent to one or more outputs.

pyhanlp is a Python interface for HanLP (Han Language Processing) that lets you use a mature Java-based NLP toolkit from Python workflows without rebuilding the underlying algorithms. It is commonly used for Chinese-language NLP tasks where you want production-grade tokenization and linguistic analysis, but still want the convenience of Python scripting. The project focuses on making HanLP’s capabilities accessible through a Python-friendly API surface, so you can integrate NLP steps into data pipelines, notebooks, and downstream ML or information-extraction code. In practice, it serves as a bridge layer: Python calls are translated into the corresponding HanLP operations, so you can keep your application logic in Python while relying on HanLP’s implementations. ...