Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
ioBroker
openHAB
Home-Assistant.io
Google Home
Domoticz
Home
IP-Symcon
mediola IQONTROL
More than 500 different modules(adapters) that can be interconnected with each other. E.g. Homematic or KNX can control HUE or sonos and vice versa.
Matplotlib ioBrokerioBroker is recommended for tech-savvy users who are comfortable with DIY configurations and those looking for a cost-effective solution to integrate various smart home devices. It's also suitable for developers interested in extending its capabilities through custom scripts and adapters.
ioBroker's answer:
ioBroker's answer:
Compatibility: ioBroker supports a vast range of devices and protocols, making it one of the most versatile smart home automation systems available. It is compatible with many popular brands and can integrate with virtually any smart device, offering a level of flexibility that might not be available with other platforms.
Open Source: As an open-source platform, ioBroker is free to use and continuously updated and improved by a community of developers. This allows for greater customization, transparency, and control over your home automation setup.
Scalability: ioBroker is designed to handle complex smart home setups. No matter how many devices you have or plan to add in the future, the platform is designed to scale and manage a large and diverse range of devices efficiently.
JavaScript and Blockly support: For those comfortable with programming, ioBroker offers the option to write scripts in JavaScript. For users who prefer a graphical interface, Blockly is available. This versatility can be appealing for both beginners and experienced users.
Data Logging: ioBroker has extensive data logging capabilities, allowing users to store, analyze, and visualize data from their smart devices over long periods of time. This can be incredibly valuable for monitoring energy usage, tracking trends, and optimizing your smart home setup.
Community and Support: ioBroker has a strong and active community of users and developers who can provide assistance, share ideas, and help troubleshoot any issues you may encounter.
ioBroker's answer:
Mostly users are german speaking, but all documentation is primary in english.
ioBroker's answer:
ioBroker is an open-source Internet of Things (IoT) platform that was developed with the aim to provide a unified and flexible solution for smart home automation. It's primarily driven by a community of enthusiasts and developers contributing to its ongoing development and expansion.
The project was initiated to overcome the limitations of existing smart home platforms, particularly the inability of many platforms to integrate with a wide variety of devices and brands. ioBroker was designed with a focus on compatibility, scalability, and flexibility, aiming to provide a solution that can integrate a vast array of smart devices, regardless of manufacturer or protocol, and handle complex home automation setups.
While the platform was initially more popular among the tech-savvy due to its need for more technical involvement, over time, efforts have been made to make it more user-friendly and accessible to a wider audience.
As an open-source project, the ongoing development of ioBroker is dependent on the contributions of its community, including software developers and end-users, who continually work on refining the software, expanding its compatibility with different devices, and improving its features.
ioBroker's answer:
JavaScript, Redis, Mqtt, MUI-UI.
Based on our record, Matplotlib seems to be more popular. It has been mentiond 114 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
Numbers are useful, but sometimes itโs easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 8 months ago
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
openHAB - "empowering the smart home" - vendor and technology agnostic open source home automation
NumPy - NumPy is the fundamental package for scientific computing with Python
Home-Assistant.io - Home Assistant is an open-source home automation platform running on Python 3.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.
Google Home - Set up, manage, and control your Chromecast, Chromecast Audio and Google Home devices.