read_lines()
reads up to n_max
lines from a file. New lines are
not included in the output. read_lines_raw()
produces a list of raw
vectors, and is useful for handling data with unknown encoding.
write_lines()
takes a character vector or list of raw vectors, appending a
new line after each entry.
Usage
read_lines(
file,
skip = 0,
skip_empty_rows = FALSE,
n_max = Inf,
locale = default_locale(),
na = character(),
lazy = should_read_lazy(),
num_threads = readr_threads(),
progress = show_progress()
)
read_lines_raw(
file,
skip = 0,
n_max = -1L,
num_threads = readr_threads(),
progress = show_progress()
)
write_lines(
x,
file,
sep = "\n",
na = "NA",
append = FALSE,
num_threads = readr_threads(),
path = deprecated()
)
Arguments
- file
Either a path to a file, a connection, or literal data (either a single string or a raw vector).
Files ending in
.gz
,.bz2
,.xz
, or.zip
will be automatically uncompressed. Files starting withhttp://
,https://
,ftp://
, orftps://
will be automatically downloaded. Remote gz files can also be automatically downloaded and decompressed.Literal data is most useful for examples and tests. To be recognised as literal data, the input must be either wrapped with
I()
, be a string containing at least one new line, or be a vector containing at least one string with a new line.Using a value of
clipboard()
will read from the system clipboard.- skip
Number of lines to skip before reading data.
- skip_empty_rows
Should blank rows be ignored altogether? i.e. If this option is
TRUE
then blank rows will not be represented at all. If it isFALSE
then they will be represented byNA
values in all the columns.- n_max
Number of lines to read. If
n_max
is -1, all lines in file will be read.- locale
The locale controls defaults that vary from place to place. The default locale is US-centric (like R), but you can use
locale()
to create your own locale that controls things like the default time zone, encoding, decimal mark, big mark, and day/month names.- na
Character vector of strings to interpret as missing values. Set this option to
character()
to indicate no missing values.- lazy
Read values lazily? By default, this is
FALSE
, because there are special considerations when reading a file lazily that have tripped up some users. Specifically, things get tricky when reading and then writing back into the same file. But, in general, lazy reading (lazy = TRUE
) has many benefits, especially for interactive use and when your downstream work only involves a subset of the rows or columns.Learn more in
should_read_lazy()
and in the documentation for thealtrep
argument ofvroom::vroom()
.- num_threads
The number of processing threads to use for initial parsing and lazy reading of data. If your data contains newlines within fields the parser should automatically detect this and fall back to using one thread only. However if you know your file has newlines within quoted fields it is safest to set
num_threads = 1
explicitly.- progress
Display a progress bar? By default it will only display in an interactive session and not while knitting a document. The automatic progress bar can be disabled by setting option
readr.show_progress
toFALSE
.- x
A character vector or list of raw vectors to write to disk.
- sep
The line separator. Defaults to
\\n
, commonly used on POSIX systems like macOS and linux. For native windows (CRLF) separators use\\r\\n
.- append
If
FALSE
, will overwrite existing file. IfTRUE
, will append to existing file. In both cases, if the file does not exist a new file is created.- path
Value
read_lines()
: A character vector with one element for each line.
read_lines_raw()
: A list containing a raw vector for each line.
write_lines()
returns x
, invisibly.
Examples
read_lines(file.path(R.home("doc"), "AUTHORS"), n_max = 10)
#> [1] "Authors of R."
#> [2] ""
#> [3] "R was initially written by Robert Gentleman and Ross Ihaka—also known as \"R & R\""
#> [4] "of the Statistics Department of the University of Auckland."
#> [5] ""
#> [6] "Since mid-1997 there has been a core group with write access to the R"
#> [7] "source, currently consisting of"
#> [8] ""
#> [9] "John Chambers"
#> [10] "Peter Dalgaard"
read_lines_raw(file.path(R.home("doc"), "AUTHORS"), n_max = 10)
#> [[1]]
#> [1] 41 75 74 68 6f 72 73 20 6f 66 20 52 2e
#>
#> [[2]]
#> raw(0)
#>
#> [[3]]
#> [1] 52 20 77 61 73 20 69 6e 69 74 69 61 6c 6c 79 20 77 72 69 74 74 65 6e
#> [24] 20 62 79 20 52 6f 62 65 72 74 20 47 65 6e 74 6c 65 6d 61 6e 20 61 6e
#> [47] 64 20 52 6f 73 73 20 49 68 61 6b 61 e2 80 94 61 6c 73 6f 20 6b 6e 6f
#> [70] 77 6e 20 61 73 20 22 52 20 26 20 52 22
#>
#> [[4]]
#> [1] 6f 66 20 74 68 65 20 53 74 61 74 69 73 74 69 63 73 20 44 65 70 61 72
#> [24] 74 6d 65 6e 74 20 6f 66 20 74 68 65 20 55 6e 69 76 65 72 73 69 74 79
#> [47] 20 6f 66 20 41 75 63 6b 6c 61 6e 64 2e
#>
#> [[5]]
#> raw(0)
#>
#> [[6]]
#> [1] 53 69 6e 63 65 20 6d 69 64 2d 31 39 39 37 20 74 68 65 72 65 20 68 61
#> [24] 73 20 62 65 65 6e 20 61 20 63 6f 72 65 20 67 72 6f 75 70 20 77 69 74
#> [47] 68 20 77 72 69 74 65 20 61 63 63 65 73 73 20 74 6f 20 74 68 65 20 52
#>
#> [[7]]
#> [1] 73 6f 75 72 63 65 2c 20 63 75 72 72 65 6e 74 6c 79 20 63 6f 6e 73 69
#> [24] 73 74 69 6e 67 20 6f 66
#>
#> [[8]]
#> raw(0)
#>
#> [[9]]
#> [1] 4a 6f 68 6e 20 43 68 61 6d 62 65 72 73
#>
#> [[10]]
#> [1] 50 65 74 65 72 20 44 61 6c 67 61 61 72 64
#>
tmp <- tempfile()
write_lines(rownames(mtcars), tmp)
read_lines(tmp, lazy = FALSE)
#> [1] "Mazda RX4" "Mazda RX4 Wag" "Datsun 710"
#> [4] "Hornet 4 Drive" "Hornet Sportabout" "Valiant"
#> [7] "Duster 360" "Merc 240D" "Merc 230"
#> [10] "Merc 280" "Merc 280C" "Merc 450SE"
#> [13] "Merc 450SL" "Merc 450SLC" "Cadillac Fleetwood"
#> [16] "Lincoln Continental" "Chrysler Imperial" "Fiat 128"
#> [19] "Honda Civic" "Toyota Corolla" "Toyota Corona"
#> [22] "Dodge Challenger" "AMC Javelin" "Camaro Z28"
#> [25] "Pontiac Firebird" "Fiat X1-9" "Porsche 914-2"
#> [28] "Lotus Europa" "Ford Pantera L" "Ferrari Dino"
#> [31] "Maserati Bora" "Volvo 142E"
read_file(tmp) # note trailing \n
#> [1] "Mazda RX4\nMazda RX4 Wag\nDatsun 710\nHornet 4 Drive\nHornet Sportabout\nValiant\nDuster 360\nMerc 240D\nMerc 230\nMerc 280\nMerc 280C\nMerc 450SE\nMerc 450SL\nMerc 450SLC\nCadillac Fleetwood\nLincoln Continental\nChrysler Imperial\nFiat 128\nHonda Civic\nToyota Corolla\nToyota Corona\nDodge Challenger\nAMC Javelin\nCamaro Z28\nPontiac Firebird\nFiat X1-9\nPorsche 914-2\nLotus Europa\nFord Pantera L\nFerrari Dino\nMaserati Bora\nVolvo 142E\n"
write_lines(airquality$Ozone, tmp, na = "-1")
read_lines(tmp)
#> [1] "41" "36" "12" "18" "-1" "28" "23" "19" "8" "-1" "7"
#> [12] "16" "11" "14" "18" "14" "34" "6" "30" "11" "1" "11"
#> [23] "4" "32" "-1" "-1" "-1" "23" "45" "115" "37" "-1" "-1"
#> [34] "-1" "-1" "-1" "-1" "29" "-1" "71" "39" "-1" "-1" "23"
#> [45] "-1" "-1" "21" "37" "20" "12" "13" "-1" "-1" "-1" "-1"
#> [56] "-1" "-1" "-1" "-1" "-1" "-1" "135" "49" "32" "-1" "64"
#> [67] "40" "77" "97" "97" "85" "-1" "10" "27" "-1" "7" "48"
#> [78] "35" "61" "79" "63" "16" "-1" "-1" "80" "108" "20" "52"
#> [89] "82" "50" "64" "59" "39" "9" "16" "78" "35" "66" "122"
#> [100] "89" "110" "-1" "-1" "44" "28" "65" "-1" "22" "59" "23"
#> [111] "31" "44" "21" "9" "-1" "45" "168" "73" "-1" "76" "118"
#> [122] "84" "85" "96" "78" "73" "91" "47" "32" "20" "23" "21"
#> [133] "24" "44" "21" "28" "9" "13" "46" "18" "13" "24" "16"
#> [144] "13" "23" "36" "7" "14" "30" "-1" "14" "18" "20"