Fast CSV writer
fwrite.RdAs write.csv but much faster (e.g. 2 seconds versus 1 minute) and just as flexible. Modern machines almost surely have more than one CPU so fwrite uses them; on all operating systems including Linux, Mac and Windows.
Usage
fwrite(x, file = "", append = FALSE, quote = "auto",
sep=getOption("datatable.fwrite.sep", ","),
sep2 = c("","|",""),
eol = if (.Platform$OS.type=="windows") "\r\n" else "\n",
na = "", dec = ".", row.names = FALSE, col.names = TRUE,
qmethod = c("double","escape"),
logical01 = getOption("datatable.logical01", FALSE), # due to change to TRUE; see NEWS
scipen = getOption('scipen', 0L),
dateTimeAs = c("ISO","squash","epoch","write.csv"),
buffMB = 8L, nThread = getDTthreads(verbose),
showProgress = getOption("datatable.showProgress", interactive()),
compress = c("auto", "none", "gzip"),
compressLevel = 6L,
yaml = FALSE,
bom = FALSE,
verbose = getOption("datatable.verbose", FALSE),
encoding = "",
forceDecimal = FALSE)Arguments
- x
Any
listof same length vectors; e.g.data.frameanddata.table. Ifmatrix, it gets internally coerced todata.tablepreserving col names but not row names- file
Output file name.
""indicates output to the console.- append
If
TRUE, the file is opened in append mode and column names (header row) are not written.- quote
When
"auto", character fields, factor fields and column names will only be surrounded by double quotes when they need to be; i.e., when the field contains the separatorsep, a line ending\n, the double quote itself or (whenlistcolumns are present)sep2[2](seesep2below). IfFALSEthe fields are not wrapped with quotes even if this would break the CSV due to the contents of the field. IfTRUEdouble quotes are always included other than around numeric fields, aswrite.csv.- sep
The separator between columns. Default is
",".- sep2
For columns of type
listwhere each item is an atomic vector,sep2controls how to separate items within the column.sep2[1]is written at the start of the output field,sep2[2]is placed between each item andsep2[3]is written at the end.sep2[1]andsep2[3]may be any length strings including empty""(default).sep2[2]must be a single character and (whenlistcolumns are present and thereforesep2is used) different from bothsepanddec. The default (|) is chosen to visually distinguish from the defaultsep. In speaking, writing and in code comments we may refer tosep2[2]as simply "sep2".- eol
Line separator. Default is
"\r\n"for Windows and"\n"otherwise.- na
The string to use for missing values in the data. Default is a blank string
"".- dec
The decimal separator, by default
".". See link in references. Cannot be the same assep.- row.names
Should row names be written? For compatibility with
data.frameandwrite.csvsincedata.tablenever has row names. Hence defaultFALSEunlikewrite.csv.- col.names
Should the column names (header row) be written? The default is
TRUEfor new files and when overwriting existing files (append=FALSE). Otherwise, the default isFALSEto prevent column names appearing again mid-file when stacking a set ofdata.tables or appending rows to the end of a file.- qmethod
A character string specifying how to deal with embedded double quote characters when quoting strings.
"escape" - the quote character (as well as the backslash character) is escaped in C style by a backslash, or
"double" (default, same as
write.csv), in which case the double quote is doubled with another one.
- logical01
Should
logicalvalues be written as1and0rather than"TRUE"and"FALSE"?- scipen
integerIn terms of printing width, how much of a bias should there be towards printing whole numbers rather than scientific notation? See Details.- dateTimeAs
How
Date/IDate,ITimeandPOSIXctitems are written."ISO" (default) -
2016-09-12,18:12:16and2016-09-12T18:12:16.999999Z. 0, 3 or 6 digits of fractional seconds are printed if and when present for convenience, regardless of any R options such asdigits.secs. The idea being that if milli and microseconds are present then you most likely want to retain them. R's internal UTC representation is written faithfully to encourage ISO standards, stymie timezone ambiguity and for speed. An option to consider is to start R in the UTC timezone simply with"$ TZ='UTC' R"at the shell (NB: it must be one or more spaces betweenTZ='UTC'andR, anything else will be silently ignored; this TZ setting applies just to that R process) orSys.setenv(TZ='UTC')at the R prompt and then continue as if UTC were local time."squash" -
20160912,181216and20160912181216999. This option allows fast and simple extraction ofyyyy,mm,ddand (most commonly to group by)yyyymmparts using integer div and mod operations. In R for example, one line helper functions could use%/%10000,%/%100%%100,%%100and%/%100respectively. POSIXct UTC is squashed to 17 digits (including 3 digits of milliseconds always, even if000) which may be read comfortably asinteger64(automatically byfread())."epoch" -
17056,65536and1473703936.999999. The underlying number of days or seconds since the relevant epoch (1970-01-01, 00:00:00 and 1970-01-01T00:00:00Z respectively), negative before that (see?Date). 0, 3 or 6 digits of fractional seconds are printed if and when present."write.csv" - this currently affects
POSIXctonly. It is written aswrite.csvdoes by using theas.charactermethod which heedsdigits.secsand converts from R's internal UTC representation back to local time (or the"tzone"attribute) as of that historical date. Accordingly this can be slow. All other column types (includingDate,IDateandITimewhich are independent of timezone) are written as the "ISO" option using fast C code which is already consistent withwrite.csv.
The first three options are fast due to new specialized C code. The epoch to date-part conversion uses a fast approach by Howard Hinnant (see references) using a day-of-year starting on 1 March. You should not be able to notice any difference in write speed between those three options. The date range supported for
DateandIDateis [0000-03-01, 9999-12-31]. Every one of these 3,652,365 dates have been tested and compared to base R including all 2,790 leap days in this range.
This option applies to vectors of date/time in list column cells, too.
A fully flexible format string (such as"%m/%d/%Y") is not supported. This is to encourage use of ISO standards and because that flexibility is not known how to make fast at C level. We may be able to support one or two more specific options if required.- buffMB
The buffer size (MiB) per thread in the range 1 to 1024, default 8MiB. Experiment to see what works best for your data on your hardware.
- nThread
The number of threads to use. Experiment to see what works best for your data on your hardware.
- showProgress
Display a progress meter on the console? Ignored when
file=="".- compress
If
compress = "auto"and iffileends in.gzthen output format is gzipped csv else csv. Ifcompress = "none", output format is always csv. Ifcompress = "gzip"then format is gzipped csv. Output to the console is never gzipped even ifcompress = "gzip". By default,compress = "auto".- compressLevel
Level of compression between 1 and 9, 6 by default. See https://www.gnu.org/software/gzip/manual/html_node/Invoking-gzip.html for details.
- yaml
If
TRUE,fwritewill output a CSVY file, that is, a CSV file with metadata stored as a YAML header, usingas.yaml. SeeDetails.- bom
If
TRUEa BOM (Byte Order Mark) sequence (EF BB BF) is added at the beginning of the file; format 'UTF-8 with BOM'.- verbose
Be chatty and report timings?
- encoding
The encoding of the strings written to the CSV file. Default is
"", which means writing raw bytes without considering the encoding. Other possible options are"UTF-8"and"native".- forceDecimal
Should decimal points be forced for whole numbers in numeric columns? When
FALSE, the default, whole numbers likec(1.0, 2.0, 3.0)will be written as 1, 2, 3 i.e., droppingdec.
Details
fwrite began as a community contribution with pull request #1613 by Otto Seiskari. This gave Matt Dowle the impetus to specialize the numeric formatting and to parallelize: https://h2o.ai/blog/2016/fast-csv-writing-for-r/. Final items were tracked in issue #1664 such as automatic quoting, bit64::integer64 support, decimal/scientific formatting exactly matching write.csv between 2.225074e-308 and 1.797693e+308 to 15 significant figures, row.names, dates (between 0000-03-01 and 9999-12-31), times and sep2 for list columns where each cell can itself be a vector.
To save space, fwrite prefers to write wide numeric values in scientific notation – e.g. 10000000000 takes up much more space than 1e+10. Most file readers (e.g. fread) understand scientific notation, so there's no fidelity loss. Like in base R, users can control this by specifying the scipen argument, which follows the same rules as options('scipen'). fwrite will see how much space a value will take to write in scientific vs. decimal notation, and will only write in scientific notation if the latter is more than scipen characters wider. For 10000000000, then, 1e+10 will be written whenever scipen<6.
CSVY Support:
The following fields will be written to the header of the file and surrounded by --- on top and bottom:
source- Contains the R version anddata.tableversion used to write the filecreation_time_utc- Current timestamp in UTC time just before the header is writtenschemawith elementfieldsgivingname-type(class) pairs for the table; multi-class objects (e.g.c('POSIXct', 'POSIXt')) will have their first class written.header- same ascol.names(which isheaderon input)sepsep2eolna.strings- same asnadecqmethodlogical01
References
https://howardhinnant.github.io/date_algorithms.html
https://en.wikipedia.org/wiki/Decimal_mark
Examples
DF = data.frame(A=1:3, B=c("foo","A,Name","baz"))
fwrite(DF)
#> A,B
#> 1,foo
#> 2,"A,Name"
#> 3,baz
write.csv(DF, row.names=FALSE, quote=FALSE) # same
#> A,B
#> 1,foo
#> 2,A,Name
#> 3,baz
fwrite(DF, row.names=TRUE, quote=TRUE)
#> "","A","B"
#> "1",1,"foo"
#> "2",2,"A,Name"
#> "3",3,"baz"
write.csv(DF) # same
#> "","A","B"
#> "1",1,"foo"
#> "2",2,"A,Name"
#> "3",3,"baz"
DF = data.frame(A=c(2.1,-1.234e-307,pi), B=c("foo","A,Name","bar"))
fwrite(DF, quote='auto') # Just DF[2,2] is auto quoted
#> A,B
#> 2.1,foo
#> -1.234e-307,"A,Name"
#> 3.14159265358979,bar
write.csv(DF, row.names=FALSE) # same numeric formatting
#> "A","B"
#> 2.1,"foo"
#> -1.234e-307,"A,Name"
#> 3.14159265358979,"bar"
DT = data.table(A=c(2,5.6,-3),B=list(1:3,c("foo","A,Name","bar"),round(pi*1:3,2)))
fwrite(DT)
#> A,B
#> 2,1|2|3
#> 5.6,foo|"A,Name"|bar
#> -3,3.14|6.28|9.42
fwrite(DT, sep="|", sep2=c("{",",","}"))
#> A|B
#> 2|{1,2,3}
#> 5.6|{foo,"A,Name",bar}
#> -3|{3.14,6.28,9.42}
if (FALSE) { # \dontrun{
set.seed(1)
DT = as.data.table( lapply(1:10, sample,
x=as.numeric(1:5e7), size=5e6)) # 382MiB
system.time(fwrite(DT, "/dev/shm/tmp1.csv")) # 0.8s
system.time(write.csv(DT, "/dev/shm/tmp2.csv", # 60.6s
quote=FALSE, row.names=FALSE))
system("diff /dev/shm/tmp1.csv /dev/shm/tmp2.csv") # identical
set.seed(1)
N = 1e7
DT = data.table(
str1=sample(sprintf("%010d",sample(N,1e5,replace=TRUE)), N, replace=TRUE),
str2=sample(sprintf("%09d",sample(N,1e5,replace=TRUE)), N, replace=TRUE),
str3=sample(sapply(sample(2:30, 100, TRUE), function(n)
paste0(sample(LETTERS, n, TRUE), collapse="")), N, TRUE),
str4=sprintf("%05d",sample(sample(1e5,50),N,TRUE)),
num1=sample(round(rnorm(1e6,mean=6.5,sd=15),2), N, replace=TRUE),
num2=sample(round(rnorm(1e6,mean=6.5,sd=15),10), N, replace=TRUE),
str5=sample(c("Y","N"),N,TRUE),
str6=sample(c("M","F"),N,TRUE),
int1=sample(ceiling(rexp(1e6)), N, replace=TRUE),
int2=sample(N,N,replace=TRUE)-N/2
) # 775MiB
system.time(fwrite(DT,"/dev/shm/tmp1.csv")) # 1.1s
system.time(write.csv(DT,"/dev/shm/tmp2.csv", # 63.2s
row.names=FALSE, quote=FALSE))
system("diff /dev/shm/tmp1.csv /dev/shm/tmp2.csv") # identical
unlink("/dev/shm/tmp1.csv")
unlink("/dev/shm/tmp2.csv")
} # }