A Python 3 module that does one thing and one thing very well: Calculate linear regressions of arrays of data.
It's not that other energy monitors are bad, but they are different in that they are mostly closed systems that provide limited data and require that you use their cloud and phone app platforms. IoTaWatt collects many more metrics and stores that usage history locally. With it's integrated web-server you can manage setup, view real-time status or create detailed graphs using the browser on your computer, tablet or phone. It's your data, in your own home, and subject only to your own privacy and retention policy. You don't need the cloud to get a handle on your hot-tub, EV, solar or heat-pump.
IoTaWatt can, however, easily upload usage data to any of several third party databases with associated apps and analytic tools. For instance PVoutput is a free service that connects easily with IoTaWatt and provides world-class solar energy analytics. There is full support for uploading to influxDB. There is also an API interface for those who want to query data for their own applications or to use in spreadsheets, and there are integrations available for home automation software like Home Assistant.
Can be used to monitor just about any power system on the planet. USian 120/240VAC, European, 230 VAC single-phase, 230VAC three-phase in Australia, Germany, and Norway.
IoTaWatt measures each circuit using a passive sensor that clips around one of the insulated wires. The output of each of these current-transformers is very low-voltage and plugs into any one of IoTaWatt's 14 inputs. Sensors plug into the unit with regular phono plugs.
Fully tested and in compliance with regulatory and safety standards of North America and Europe.
Github: https://github.com/boblemaire/IoTaWatt
Online store: https://stuff.iotawatt.com/
If you only want to monitor power for the whole house, you only need the base kit and two induction sensors (one for each side of the split-phase). $260us
Agent that monitors a flow of data and uses Isolation Forest techniques to identify statistical outliers and anomalies.
Go from graph data to a secure and interactive visual graph app in 15 minutes. Batteries-included self-hosting of graph data apps with Streamlit, Graphistry, RAPIDS, and more!
This open source effort puts together patterns the Graphistry team has reused across many graph projects as teams go from code-heavy Jupyter notebook experiments to deploying streamlined analyst tools. Whether building your first graph app, trying an idea, or wanting to check a reference, this project aims to simplify that process. It covers pieces like: Easy code editing and deployment, a project stucture ready for teams, built-in authentication, no need for custom JS/CSS at the start, batteries-included data + library dependencies, and fast loading & visualization of large graphs.
GPU enabled.
Seems to be Docker-only.
Jupyter recompiled into WASM so that it'll run in a web browser natively.
JupyterLite is a JupyterLab distribution that runs entirely in the browser built from the ground-up using JupyterLab components and extensions. Not all the usual features available in JupyterLab and the Classic Notebook will work with JupyterLite, but many already do!
Can be installed with pip.
Bokeh is a Python library for creating interactive visualizations for modern web browsers. It helps you build beautiful graphics, ranging from simple plots to complex dashboards with streaming datasets. With Bokeh, you can create JavaScript-powered visualizations without writing any JavaScript yourself.
Can run as a server - that's what you'll want to grep the docs to figure out how to do.
A repository for your personal data, and an extensible analysis engine.
There already exist many apps and fitness trackers that gather and attempt to make sense of your data. Most of these services are isolated - your phone's fitness tracking software knows nothing about your browser's time-tracking extension. Furthermore, each app and service has its own method for downloading data (if they offer raw data at all!), which makes an all-encompassing analysis of life extremely tedious. Heedy offers a self-hosted open-source way to put all of this data together into a single system.
Open-source and self-hosted. Extensible.
Most heedy plugins use Python.
Hey! I'm @rstacruz and this is a modest collection of cheatsheets I've written.
Map Maker is a powerful but easy-to-use Web application for creating custom maps. You can upload your data, customize how the data is visualized, then export the map or share it with others for editing. Bulk import, filtering, geocoding, custom icons.
The aim of this database is explicitly not to provide up-to-date fundamentals or stock data as those can be obtained with ease (with the help of this database) by using FundamentalAnalysis or yfinance. Instead, it gives insights into the products that exist in each country, industry and sector and gives the most essential information about each product. With this information, you can analyse specific areas of the financial world and/or find that product that is hard to find. See for examples on how you can combine this database and the earlier mentioned packages the section Examples.
SigNoz is an opensource observability platform. SigNoz uses distributed tracing to gain visibility into your systems and powers data using Kafka (to handle high ingestion rate and backpressure) and Apache Druid (Apache Druid is a high performance real-time analytics database), both proven in industry to handle scale.
Built using ReactTS and Go.
Dogsheep is a collection of tools for personal analytics using SQLite and Datasette.
Big internet companies know a lot about us. By exporting that data back out of them we can see what they know and maybe learn something interesting about ourselves.
ONYPHE is a search engine for open-source and cyber threat intelligence data collected by crawling various sources available on the Internet or by listening to Internet background noise. ONYPHE correlates this information with data gathered by performing active Internet scanning for connected devices. It then normalizes information and make it available via an API and its search language.
Visualization and exploration software for all kinds of graphs and networks. Map and explore data points and entities. Trace links between entities. Analyze graph data for patterns. Can be extended with plugins (https://gephi.org/plugins/).
A tool for Mastodon users that will scan all the toots you've favorited and find the 30 people whose toots you've favorited most often. Entirely client-side, stores nothing.
An awesome list of resources for building bots.