Based on our record, Jupyter seems to be a lot more popular than RRDTool. While we know about 205 links to Jupyter, we've tracked only 3 mentions of RRDTool. 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.
For anyone interested in how the graphs were made: https://oss.oetiker.ch/rrdtool/ Happy to see people still using RRD after all these years. - Source: Hacker News / over 1 year ago
(I actually implemented the firmware for this... Using the Arduino port for ESP8266 because I was impatient, but discovered that either my DHT11 modules are junk or I'm misusing them, because the humidity measurement drifts as they keep running. I need to write the Rust+rrdtool app meant to receive the reports and then do some comparative tests between the DHT11 and some BME280s, and between the current firmware... Source: about 2 years ago
Nice! This is giving me some ideas. Here's what my old school rrdtool-based system looks like:. Source: over 2 years ago
JupyterLab: JupyterLab is an interactive development environment that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It's particularly well-suited for data science and research-oriented projects. - Source: dev.to / 8 days ago
Jupyter Lab web-based interactive development environment. - Source: dev.to / 19 days ago
Choosing IDE: Selecting a suitable Integrated Development Environment (IDE) is crucial for efficient coding. Consider popular options such as PyCharm, Visual Studio Code, or Jupyter Notebook. Install your preferred IDE and ensure it's configured to work with Python. - Source: dev.to / 14 days ago
Jupyter Notebooks is very popular among data people specially Python users. So, I tried to find a way to run the Groovy kernel inside a Jupyter Notebook, and to my surprise, I found a way, BeakerX! - Source: dev.to / 2 months ago
Note. Nowadays, there are many flavors of notebooks (Jupyter, VSCode, Databricks, etc.), but they’re all built on top of IPython. Therefore, the Magics developed should be reusable across environments. - Source: dev.to / 2 months ago
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