Dragoș Moldovan-Grünfeld created ARROW-15912:
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Summary: [C++] Is CSV reader's TimestampParser usable elsewhere?
Key: ARROW-15912
URL: https://issues.apache.org/jira/browse/ARROW-15912
Project: Apache Arrow
Issue Type: Improvement
Components: C++
Reporter: Dragoș Moldovan-Grünfeld
The {{TimestampParser}} is be able to cycle through several formats. This sort
of functionality would be very useful for some of the lubridate bindings that
need to behave in a similar way.
{code:r}
library(arrow)
library(fs)
library(readr)
library(tibble)
tf <- fs::file_temp(ext = "csv")
fs::file_create(tf)
sample_times <- tibble(a = c("09/13/2013", "25/12/1998", "09-13-13",
"23_Feb_2022", "09/13/2018"))
write_csv(sample_times, tf)
read_csv_arrow(tf,
as_data_frame = TRUE,
timestamp_parsers = c("%m/%d/%Y", "%d/%m/%Y", "%m-%d-%y",
"%d_%b_%Y"))
#> # A tibble: 5 × 1
#> a
#> <dttm>
#> 1 2013-09-13 01:00:00
#> 2 1998-12-25 00:00:00
#> 3 2013-09-13 01:00:00
#> 4 2022-02-23 00:00:00
#> 5 2018-09-13 01:00:00
{code}
For example, in lubridate, the {{ymd()}} cycles through all possible formats
that have year-month-date components in the right order (e.g. {{"%Y-%m-%d",
"%y-%m-%d", "%Y-%b-%d", "%y-%b-%d", "%Y-%B-%d", "%y-%b-%d"}}, etc).
I guess my question is can we factor this CSV reader feature to be usable
elsewhere?
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