Comments (4)
Hello, this is blocking me and colleagues from running a program that relies on CSV files and is important to our work. Is there a version of CSV that I should revert to that does not conflict with Parsers?
Also, if the problem is not replicable that would be good to know. Our team has tried to look for conflicts with other packages but so far it seems to be solely a problem with CSV's use of Parsers.
Thank you.
from csv.jl.
One thing I know has happened to people in the past is somehow their editor tooling is loading, for example, the JSON package which also depends on Parsers and a certain version gets loaded. Then when CSV loads, it's the wrong version compat-wise and you get an error like you're showing. If you're on Julia 1.9, can you show the output of pkgversion(Parsers)
and pkgversion(CSV)
? We can also do some additional investigating, but it seems like something is out of sync from the recent groupmark
support in both Parsers and CSV, so perhaps @LilithHafner may also have an idea of what's going on.
from csv.jl.
Thanks very much @quinnj. I'm on Julia 1.7, so I used Pkg.status() and get v2.7.1 for Parsers and v0.10.11 for CSV.
from csv.jl.
Thanks again for the tip @quinnj: I may have found the culprit. I'll close and reopen if this doesn't solve it.
from csv.jl.
Related Issues (20)
- Formatting issues in examples
- Cannot compile this package on Julia 1.9.1 in Ubuntu 22.04 container HOT 3
- "Missing" Values HOT 2
- Keyword `decimal` not respected for AbstractFloats in CSV.write()
- Can't transfer CSV.jl v0.10.11 from Windows to Linux HOT 2
- CSV.write somehow cannot write file with name `con.csv` in Windows?! HOT 5
- Add Zenodo badge to README HOT 6
- Segfault on Julia 1.9 on Intel Sapphire Rapids during precompilation
- `bufsize` of `write` is defined to be length of row but actually cells
- can not read the csv with large cells written by itself HOT 1
- Formatting broken on Examples page in documentation HOT 2
- CSV.jl fails to precompile on Ubuntu server, v0.10.5 and up. HOT 2
- Error on CSV.read attempt HOT 4
- `emptyvalue` keyword option
- CSV.Chunks splits file into uneven chunks
- CSV.jl errors on nightly
- Incorrect results for `argmax` with multithreaded parsing HOT 1
- CSV is failing PkgEval HOT 4
- Error when combining single row with multiple row CSV file into a DataFrame with pooling on. HOT 1
- `Date` types should not be inferred from column
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from csv.jl.