Nim Mustache Projects
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
Jupyter notebook is indeed very important. It mainly provides data scientists with two things: a literate programming environment (mixing text, code and outputs) and a way to hold state of data in memory (so that you can perform computation interactively).
As a different take to literate programming we have created a library and an ecosystem around it: https://github.com/pietroppeter/nimib
For holding state a Nim repl (which is on the roadmap as secondary priority after completing incremental compilation) is definitely an option.
Another option could be to create a library framework for caching (or be able to serialize and deserialize quickly) large data and objects. One way to see it, could be to build something similar to streamlit cache (streamlit indeed provides great interactivity)
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1 | nimib | 171 |
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