Vince's CSV Parser
A modern C++ library for reading, writing, and analyzing CSV (and similar) files. (by vincentlaucsb)
vroom
Fast reading of delimited files (by tidyverse)
| Vince's CSV Parser | vroom | |
|---|---|---|
| 4 | 3 | |
| 831 | 608 | |
| - | 0.2% | |
| 4.6 | 7.6 | |
| about 1 month ago | 3 months ago | |
| C++ | C++ | |
| MIT License | GNU General Public License v3.0 or later |
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.
Vince's CSV Parser
Posts with mentions or reviews of Vince's CSV Parser.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-03-30.
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CSV Parser
How does it compare to this https://github.com/vincentlaucsb/csv-parser
- Turning CSV rows into a vector of maps, with column names as keys
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A tuple oriented C++ csv parser
csv-parser - 4.847 +- 0.197 [s]
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
What are some alternatives?
When comparing Vince's CSV Parser and vroom you can also consider the following projects:
Fast C++ CSV Parser - fast-cpp-csv-parser
rstan - RStan, the R interface to Stan
Rapidcsv - C++ CSV parser library
tree-sitter-html - HTML grammar for Tree-sitter
csvdecoder - Go library for parsing and deserialising CSV files into Go objects
csv
wasmr - Execute WebAssembly from R using wasmer
nvParse - Fast, gpu-based CSV parser
lazycsv - A fast, lightweight and single-header C++ csv parser library
miller - Miller is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON