crul
drake
crul | drake | |
---|---|---|
2 | 1 | |
102 | 1,329 | |
1.0% | 0.0% | |
5.7 | 6.1 | |
about 1 month ago | 2 months ago | |
R | R | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 only |
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.
crul
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How to download many files at once from a website using R
The crul package is also worth mentioning in this context (Asynchronous HTTP requests).
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Is there a recommended library for asynchronous HTTP servers in R?
Are there R packages which do something like this? I've come across crul: https://github.com/ropensci/crul
drake
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Your impression of {targets}? (r package)
The targets package is the official successor to Drake, and has the same primary author (Will Landau). He has explained why he created targets, which includes stronger guardrails for users and better UX.
What are some alternatives?
daphne - Django Channels HTTP/WebSocket server
targets - Function-oriented Make-like declarative workflows for R
async - Asynchronous HTTP and computation in R
easystats - :milky_way: The R easystats-project
httr - httr: a friendly http package for R [Moved to: https://github.com/r-lib/httr]
tabulapdf - Bindings for Tabula PDF Table Extractor Library
httr - httr: a friendly http package for R
ncaahoopR - An R package for working with NCAA Basketball Play-by-Play Data
robinhood - Robinhood Policy Engine : a versatile tool to monitor filesystem contents and schedule actions on filesystem entries.
fiery - A flexible and lightweight web server
googleCloudStorageR - Google Cloud Storage API to R
causalglm - Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning