Stonks.jl
Chain.jl
| Stonks.jl | Chain.jl | |
|---|---|---|
| 1 | 8 | |
| 50 | 349 | |
| - | - | |
| 0.0 | 4.2 | |
| over 1 year ago | 3 months ago | |
| Julia | Julia | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stonks.jl
-
Julia for finance - retrieving and persisting financial data
For that, I've created [Stonks.jl](https://github.com/alinski29/Stonks.jl) . It aims to find the best free resources for historical financial data and retrieve them into a standard data model, regardless of the API client used. Currently only 2 API clients supported, yahoo finance and alphavantage.
Chain.jl
-
Pains of Julia compared to python
The [Chain.jl package](https://github.com/jkrumbiegel/Chain.jl) is becoming idiomatic for these kind of pipelines.
-
Transition from R Tidyverse to Julia (VS Code)
If you do have tabular data in a dataframe you have a few options for data manipulation, the most popular packages are probably DataFramesMeta and Query, although in my opinion the best way to manipulate dataframes is with the functions built in to DataFrames.jl and using a package like Chain.jl or Pipe.jl to pipe the functions into each other like magrittr in R.
-
The (updated) history of the pipe operator in R
The Julia community built a better piping method than any other language has AFAIK: Chain.jl.
-
What are some of your favourite macros?
@chain and @match.
-
Why is piping so well-accepted in the R community compared to those in Julia and Python?
Have you ever tried Infiltrator.jl and Chain.jl?
-
https://np.reddit.com/r/Julia/comments/nnu6if/julia_object_oriented_programming_with_dot/h0anaru/
You are right. However, sometimes well used is very useful, and readable. One suggestion, in Julia I suggest Chain.jl, because it allows intercalate easily the output for debugging:
-
Julia Update: Adoption Keeps Climbing; Is It a Python Challenger?
I also like pipe syntax and I've found there is nice support for it in Julia. There are some nice packages to improve it over base [1].
Have you checked queryverse [2]?
[1] https://github.com/jkrumbiegel/Chain.jl
What are some alternatives?
Requires.jl - Lazy code loading for Julia
Pipe.jl - An enhancement to julia piping syntax
TableIO.jl - A glue package for reading and writing tabular data. It aims to provide a uniform api for reading and writing tabular data from and to multiple sources.
Genie.jl - 🧞The highly productive Julia web framework
Revise.jl - Automatically update function definitions in a running Julia session
JLD2.jl - HDF5-compatible file format in pure Julia
PaddedViews.jl - Add virtual padding to the edges of an array
Infiltrator.jl - No-overhead breakpoints in Julia
RCall.jl - Call R from Julia
StatsPlots.jl - Statistical plotting recipes for Plots.jl
AlgebraOfGraphics.jl - Combine ingredients for a plot
cmssw - CMS Offline Software