librosa is a python package for music and audio analysis. It provides the building blocks necessary to create music information retrieval systems.
Open-source library and tools for audio and music analysis, description and synthesis
Engineering managers and maintainers of large code bases are starting to realize the potential of Code as Data or how source code can be treated as an analyzable dataset proving valuable information. Think Business Intelligence and processes optimization based on the source code engineers write, rather than adjacent metrics.
A single distribution of libraries that automatically collects traces and metrics from your app, displays them locally, and sends them to any analysis tool.
Zipkin is a distributed tracing system. It helps gather timing data needed to troubleshoot latency problems in microservice architectures. It manages both the collection and lookup of this data. Zipkin’s design is based on the Google Dapper paper.
Applications are instrumented to report timing data to Zipkin. The Zipkin UI also presents a Dependency diagram showing how many traced requests went through each application. If you are troubleshooting latency problems or errors, you can filter or sort all traces based on the application, length of trace, annotation, or timestamp. Once you select a trace, you can see the percentage of the total trace time each span takes which allows you to identify the problem application.
Jaeger, inspired by Dapper and OpenZipkin, is a distributed tracing system released as open source by Uber Technologies. It is used for monitoring and troubleshooting microservices-based distributed systems, including:
Distributed context propagation Distributed transaction monitoring Root cause analysis Service dependency analysis Performance / latency optimization
Superset is a data exploration platform designed to be visual, intuitive and interactive.
Superset's main goal is to make it easy to slice, dice and visualize data. It empowers users to perform analytics at the speed of thought.
A quick way to intuitively visualize datasets by allowing users to create and share interactive dashboards
A rich set of visualizations to analyze your data, as well as a flexible way to extend the capabilities
An extensible, high granularity security model allowing intricate rules on who can access which features, and integration with major authentication providers (database, OpenID, LDAP, OAuth & REMOTE_USER through Flask AppBuiler)
A simple semantic layer, allowing to control how data sources are displayed in the UI, by defining which fields should show up in which dropdown and which aggregation and function (metrics) are made available to the user
Deep integration with Druid allows for Superset to stay blazing fast while slicing and dicing large, realtime datasets
Fast loading dashboards with configurable caching
Mirador is a tool for visual exploration of complex datasets. It enables users to discover correlation patterns and derive new hypotheses from the data.
TextBlob is a Python (2 and 3) library for processing textual data. It provides a simple API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, classification, translation, and more.
csscss will parse any CSS files you give it and let you know which rulesets have duplicated declarations.