Rocket.jl
JLD2.jl
| Rocket.jl | JLD2.jl | |
|---|---|---|
| 2 | 2 | |
| 168 | 525 | |
| 0.6% | 1.3% | |
| 7.4 | 8.1 | |
| 19 days ago | 7 days ago | |
| Julia | Julia | |
| MIT License | GNU General Public License v3.0 or later |
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Rocket.jl
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Using QuestDB to Build a Crypto Trade Database in Julia
I was thinking about applying https://github.com/biaslab/Rocket.jl for this sort of tasks. The idea is to create stream of events and use subscription model to filter data and do all necessary transformations. Authors promise that the library is fast, so it can be good.
- Rocket.jl – Reactive extensions library for Julia
JLD2.jl
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Machine learning with Julia - Solve Titanic competition on Kaggle and deploy trained AI model as a web service
First, you need to save the model from the notebook to a file. For this you can use JLD2.jl module. This module used to serialize Julia object to HDF5-compatible format (which is well known by Python data scientists) and save it to a file.
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Best format to save matrices to a text file? (R interop)
I didn't realize this was the Julia subreddit. HDF5 or multiple CSV files would be my suggestion. As a side note, check out the JLD2 package. It's a HDF5 compatible format where the package is written in pure Julia.
What are some alternatives?
ObservableComputations - Cross-platform .NET library for computations whose arguments and results are objects that implement INotifyPropertyChanged and INotifyCollectionChanged (ObservableCollection) interfaces.
julia - The Julia Programming Language
Chain.jl - A Julia package for piping a value through a series of transformation expressions using a more convenient syntax than Julia's native piping functionality.
Makie.jl - Interactive data visualizations and plotting in Julia
Plots.jl - Powerful convenience for Julia visualizations and data analysis
ReactiveUI - An advanced, composable, functional reactive model-view-viewmodel framework for all .NET platforms that is inspired by functional reactive programming. ReactiveUI allows you to abstract mutable state away from your user interfaces, express the idea around a feature in one readable place and improve the testability of your application.
StatsWithJuliaBook
Genie.jl - 🧞The highly productive Julia web framework
PlotDocs.jl - Documentation for Plots.jl
julia_titanic_model - Titanic machine learning model and web service
seaborn - Statistical data visualization in Python