vroom
Fast reading of delimited files (by tidyverse)
csvdecoder
Go library for parsing and deserialising CSV files into Go objects (by stefantds)
| vroom | csvdecoder | |
|---|---|---|
| 3 | 1 | |
| 609 | 10 | |
| 0.3% | - | |
| 7.6 | 1.8 | |
| 3 months ago | over 3 years ago | |
| C++ | Go | |
| GNU General Public License v3.0 or later | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
vroom
Posts with mentions or reviews of vroom.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-03-02.
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Read in from a CSV only those lines which meet a certain condition?
Try Vroom
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Is there a way to load a large SAS7BDAT dataset into R efficiently with fair speed?
You can use an `rds` file. You have to read it in then write it out though. If you care about speed, then just use `readr::write_rds`, which is similar to the base `saveRDS`, but with compression off, but the file size will be much larger. You can also use random access objects, such as `fst`: https://www.fstpackage.org/, but again, need to write it out. I tried a quick benchmark and `haven` is much faster than `sas7bdat` package. If it's in a plain text delimited file, you can also look into `vroom`: https://github.com/r-lib/vroom
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what is the difference between read_csv and read.csv other than the speed ?
If you are looking for speed, I’d thoroughly recommend vroom: https://github.com/r-lib/vroom
csvdecoder
Posts with mentions or reviews of csvdecoder.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Yet another CSV parsing library
My slightly different take on CSV parsing library: https://github.com/stefantds/csvdecoder
What are some alternatives?
When comparing vroom and csvdecoder you can also consider the following projects:
rstan - RStan, the R interface to Stan
VBA-CSV-interface - The power you need to cleanse, filter, sort, reshape, manage and analyze data from CSV files.
Rapidcsv - C++ CSV parser library
sq - sq data wrangler
Vince's CSV Parser - A high-performance, fully-featured CSV parser and serializer for modern C++.
csvtk - A cross-platform, efficient and practical CSV/TSV toolkit in Golang
wasmr - Execute WebAssembly from R using wasmer
cascadia - Go cascadia package command line CSS selector
csv
csvutil - csvutil provides fast and idiomatic mapping between CSV and Go (golang) values.