- No major user-facing changes. Patch release with housekeeping changes and internal changes requested by CRAN around format specification in compiled code.
- No user-facing changes. Patch release with internal changes requested by CRAN.
-
Help files below
man/
have been re-generated, so that they give rise to valid HTML5. (This is the impetus for this release, to keep the package safely on CRAN.) -
mini-gapminder-africa.csv
and friends are new example datasets accessible viareadr_example()
, which have been added to illustrate reading multiple files at once, into a single data frame.
-
read_table()
,read_log()
, andread_delim_chunked()
(and friends) gain theshow_col_types
argument found elsewhere. Allread_*()
functions now respect theshow_col_types
argument or option, even when using the first edition parsing engine (#1331). -
show_progress()
usesrlang::is_interactive()
instead ofbase::interactive()
(#1356). -
read_builtin()
does more argument checking, so that we catch obviously malformed input before passing along toutils::data()
(#1361). -
chickens.csv
andwhitespace-sample.txt
are new example datasets accessible viareadr_example()
(#1354).
-
Jenny Bryan is now the maintainer.
-
Fix buffer overflow when trying to parse an integer from a field that is over 64 characters long (#1326)
- All readr functions again read eagerly by default. Unfortunately many users
experienced frustration from the drawbacks of lazy reading, in particular
locking files on Windows, so it was decided to disable lazy reading default.
However
options(readr.read_lazy = TRUE)
can be used to set the default to by lazy if desired. - New
readr.read_lazy
global option to control if readr reads files lazily or not (#1266)
-
minor test tweak for compatibility with testthat 3.1.0 (#@lionel-, #1304)
-
write_rds()
gains atext=
argument, to control using a text based object representation, like theascii=
argument insaveRDS()
(#1270)
-
options(readr.show_col_types = FALSE)
now works as intended (#1250) -
read_delim_chunked()
now again correctly respects thechunk_size
parameter (#1248) -
type_convert()
gains aguess_integer
argument, passed toguess_parser()
(@jmbarbone, #1264) -
read_tsv()
now correctly passes thequote
andna
arguments tovroom::vroom()
(#1254, #1255) -
Avoid spurious byte compilation errors due to the programmatically generated
spec_*()
functions.
readr 2.0.0 is a major release of readr and introduces a new second edition parsing and writing engine implemented via the vroom package.
This engine takes advantage of lazy reading, multi-threading and performance characteristics of modern SSD drives to significantly improve the performance of reading and writing compared to the first edition engine.
We will continue to support the first edition for a number of releases, but eventually this support will be first deprecated and then removed.
You can use the with_edition()
or local_edition()
functions to temporarily change the edition of readr for a section of code.
e.g.
-
with_edition(1, read_csv("my_file.csv"))
will readmy_file.csv
with the first edition of readr. -
readr::local_edition(1)
placed at the top of your function or script will use the first edition for the rest of the function or script.
Edition two uses lazy reading by default.
When you first call a read_*()
function the delimiters and newlines throughout the entire file are found, but the data is not actually read until it is used in your program.
This can provide substantial speed improvements for reading character data.
It is particularly useful during interactive exploration of only a subset of a full dataset.
However this also means that problematic values are not necessarily seen immediately, only when they are actually read. Because of this a warning will be issued the first time a problem is encountered, which may happen after initial reading.
Run problems()
on your dataset to read the entire dataset and return all of the problems found.
Run problems(lazy = TRUE)
if you only want to retrieve the problems found so far.
Deleting files after reading is also impacted by laziness.
On Windows open files cannot be deleted as long as a process has the file open.
Because readr keeps a file open when reading lazily this means you cannot read, then immediately delete the file.
readr will in most cases close the file once it has been completely read.
However, if you know you want to be able to delete the file after reading it is best to pass lazy = FALSE
when reading the file.
Edition two has built-in support for reading sets of files with the same columns into one output table in a single command. Just pass the filenames to be read in the same vector to the reading function.
First we generate some files to read by splitting the nycflights dataset by airline.
library(nycflights13)
purrr::iwalk(
split(flights, flights$carrier),
~ { .x$carrier[[1]]; vroom::vroom_write(.x, glue::glue("flights_{.y}.tsv"), delim = "\t") }
)
Then we can efficiently read them into one tibble by passing the filenames directly to readr.
files <- fs::dir_ls(glob = "flights*tsv")
files
readr::read_tsv(files)
If the filenames contain data, such as the date when the sample was collected,
use id
argument to include the paths as a column in the data.
You will likely have to post-process the paths to keep only the relevant portion for your use case.
Edition two supports automatic guessing of delimiters.
Because of this you can now use read_delim()
without specifying a delim
argument in many cases.
x <- read_delim(readr_example("mtcars.csv"))
In edition one the reading functions treated any input with a newline in it or vectors of length > 1 as literal data.
In edition two vectors of length > 1 are now assumed to correspond to multiple files.
Because of this we now have a more explicit way to represent literal data, by putting I()
around the input.
readr::read_csv(I("a,b\n1,2"))
We are systematically re-licensing tidyverse and r-lib packages to use the MIT license, to make our package licenses as clear and permissive as possible.
To this end the readr and vroom packages are now released under the MIT license.
-
melt_csv()
,melt_delim()
,melt_tsv()
andmelt_fwf()
have been superseded by functions in the same name in the meltr package. The versions in readr have been deprecated. These functions rely on the first edition parsing code and would be challenging to update to the new parser. When the first edition parsing code is eventually removed from readr they will be removed. -
read_table2()
has been renamed toread_table()
, as most users expectread_table()
to work likeutils::read.table()
. If you want the previous strict behavior of theread_table()
you can useread_fwf()
withfwf_empty()
directly (#717). -
Normalizing newlines in files with just carriage returns
\r
is no longer supported. The last major OS to use only CR as the newline was 'classic' Mac OS, which had its final release in 2001.
-
read_*_chunked()
functions now include their specification as an attribute (#1143) -
All
read_*()
functions gain acol_select
argument to more easily choose which columns to select. -
All
read_*()
functions gain aid
argument to optionally store the file paths when reading multiple files. -
All
read_*()
functions gain aname_repair
argument to control how column names are repaired. -
All
read_*()
andwrite_*()
functions gain anum_threads
argument to control the number of processing threads they use (#1201) -
All
write_*()
andformat_*()
functions gainquote
andescape
arguments, to explicitly control how fields are quoted and how double quotes are escaped. (#653, #759, #844, #993, #1018, #1083) -
All
write_*()
functions gain aprogress
argument and display a progress bar when writing (#791). -
write_excel_csv() now defaults to
quote = "all"
(#759) -
write_tsv() now defaults to
quote = "none"
(#993) -
read_table()
now handles skipped lines with unpaired quotes properly (#1180)
-
The BH package is no longer a dependency. The boost C++ headers in BH have thousands of files, so can take a long time to extract and compiling them takes a great deal of memory, which made readr difficult to compile on systems with limited memory (#1147).
-
readr now uses the tzdb package when parsing date-times (@DavisVaughan, tidyverse/vroom#273)
-
Chunked readers now support files with more than
INT_MAX
(~ 2 Billion) number of lines (#1177) -
Memory no longer inadvertently leaks when reading memory from R connections (#1161)
-
Invalid date formats no longer can potentially crash R (#1151)
-
col_factor()
now throws a more informative error message if given non-character levels (#1140) -
problems()
now takes.Last.value
as its default argument. This lets you runproblems()
without an argument to see the problems in the previously read dataset. -
read_delim()
fails when sample of parsing problems contains non-ASCII characters (@hidekoji, #1136) -
read_log()
gains atrim_ws
argument (#738) -
read_rds()
andwrite_rds()
gain arefhook
argument, to pass functions that handle references objects (#1206) -
read_rds()
can now read .Rds files from URLs (#1186) -
read_*()
functions gain ashow_col_types
argument, if set toFALSE
this turns off showing the column types unconditionally. -
type_convert()
now throws a warning if the input has no character columns (#1020) -
write_csv()
now errors if given a matrix column (#1171) -
write_csv()
now again is able to write data with duplicated column names (#1169) -
write_file()
now forces its argument before opening the output file (#1158)
-
write_*()
functions first argument is nowfile
instead ofpath
, for consistency with theread_*()
functions.path
has been deprecated and will be removed in a future version of readr (#1110, @brianrice2) -
write_*()
functions now output any NaN values in the same way as NA values, controlled by thena=
argument. (#1082).
-
It is now possible to generate a column specification from any tibble (or data.frame) with
as.col_spec()
and convert any column specification to a short representation withas.character()
s <- as.col_spec(iris) s #> cols( #> Sepal.Length = col_double(), #> Sepal.Width = col_double(), #> Petal.Length = col_double(), #> Petal.Width = col_double(), #> Species = col_factor(levels = c("setosa", "versicolor", "virginica"), ordered = FALSE, include_na = FALSE) #> ) as.character(s) #> [1] "ddddf"
-
The cli package is now used for all messages.
-
The runtime performance for tables with an extreme number of columns is greatly improved (#825)
-
Compressed files are now detected by magic numbers rather than by the file extension (#1125)
-
A memory leak when reading files is now fixed (#1092)
-
write_*()
functions gain aeol =
argument to control the end of line character used (#857). This allows writing of CSV files with Windows newlines (CRLF) if desired. -
The Rcpp dependency has been removed in favor of cpp11.
-
The build system has been greatly simplified so should work on more systems.
-
The full problem field is now displayed in the problems tibble, as intended (#444).
-
New
%h
placeholder for parsing unrestricted hours (<0 and >23) to support parsing durations (#549, @krlmlr). -
as.character.col_spec()
now handles logical columns as well (#1127) -
fwf_positions(end)
no longer has a default argument and must be specified (#996) -
guess_parser()
gains ana
argument and removes NA values before guessing (#1041). -
parse_guess()
now passes thena
argument toguess_parser()
-
read_*
functions now close properly all connections, including on errors like HTTP errors when reading from a url (@cderv, #1050). -
read_delimited()
no longer mistakenly stats literal filenames (#1063) -
read_lines()
now ignores quotations when skipping lines (#991). -
read_lines(skip_empty_rows = TRUE)
no longer crashes if a file ends with an empty line (#968) -
write_*()
functions now invisibly return the input data frame unchanged, rather than a version with factors and dates converted to strings. (@jesse-ross, #975). -
write_csv2()
now formats decimal numbers more consistently withutils::write.csv2()
(#1087) -
write_csv2()
andformat_csv2()
no longer pad number columns with whitespaces (@keesdeschepper, #1046). -
write_excel_csv()
no longer outputs a byte order mark when appending to a file (#1075). -
Uses of
tibble::data_frame
updated totibble::tibble
(tidyverse/dplyr#4069, @thays42, #1124, @brianrice2) -
read_delimited()
now returns an emptytibble::data_frame()
rather than signaling an error when given a connection with an empty file (@pralitp, #963). -
More helpful error when trying to write out data frames with list columns (@ellessenne, #938)
-
type_convert()
removes a 'spec' attribute, because the current columns likely have modified data types. The 'spec' attribute is set by functions likeread_delim()
(@jimhester, @wibeasley, #1032). -
write_rds()
now can specify the Rds version to use. The default value is 2 as it's compatible to R versions prior to 3.5.0 (@shrektan, #1001). -
Fixes for issues related to variable initialization in C++ code (@michaelquinn32, ##1133).
-
Column specifications are now coloured when printed. This makes it easy to see at a glance when a column is input as a different type then the rest. Colouring can be disabled by setting
options(crayon.enabled = FALSE)
. -
as.col_spec()
can now use named character vectors, which makesread_csv("file.csv", col_types = c(xyz = "c"))
equivalent toread_csv("file.csv", col_types = cols(xyz = col_character())
-
Fix skipping when single quotes are embedded in double quoted strings, and single quotes in skipped or commented lines (#944, #945).
-
Fix for compilation using custom architectures on macOS (#919)
-
Fix for valgrind errors (#941)
readr's blank line skipping has been modified to be more consistent and to
avoid edge cases that affected the behavior in 1.2.0. The skip parameter now
behaves more similar to how it worked previous to readr 1.2.0, but in addition
the parameter skip_blank_rows
can be used to control if fully blank lines are
skipped. (#923)
readr 1.3.0 returns results with a spec_tbl_df
subclass. This differs from a
regular tibble only that the spec
attribute (which holds the column
specification) is lost as soon as the object is subset (and a normal tbl_df
object is returned).
Historically tbl_df
's lost their attributes once they were subset. However
recent versions of tibble retain the attributes when subetting, so the
spec_tbl_df
subclass is needed to ensure the previous behavior.
This should only break compatibility if you are explicitly checking the class
of the returned object. A way to get backwards compatible behavior is to
call subset with no arguments on your object, e.g. x[]
.
hms
objects with NA values are now written without whitespace padding (#930).read_*()
functions now returnspec_tbl_df
objects, which differ from regulartbl_df
objects only in that thespec
attribute is removed (and they are demoted to regulartbl_df
objects) as soon as they are subset (#934).write_csv2()
now properly respects thena
argument (#928)- Fixes compilation with multiple architectures on linux (#922).
- Fixes compilation with R < 3.3.0
This release skips the clipboard tests on CRAN servers
readr functions no longer guess columns are of type integer, instead these
columns are guessed as numeric. Because R uses 32 bit integers and 64 bit
doubles all integers can be stored in doubles, guaranteeing no loss of
information. This change was made to remove errors when numeric columns were
incorrectly guessed as integers. If you know a certain column is an integer and
would like to read them as such you can do so by specifying the column type
explicitly with the col_types
argument.
readr now always skips blank lines automatically when parsing, which may change
the number of lines you need to pass to the skip
parameter. For instance if
your file had a one blank line then two more lines you want to skip previously
you would pass skip = 3
, now you only need to pass skip = 2
.
There is now a family of melt_*()
functions in readr. These functions store
data in 'long' or 'melted' form, where each row corresponds to a single
value in the dataset. This form is useful when your data is ragged and not
rectangular.
data <-"a,b,c
1,2
w,x,y,z"
readr::melt_csv(data)
#> # A tibble: 9 x 4
#> row col data_type value
#> <dbl> <dbl> <chr> <chr>
#> 1 1 1 character a
#> 2 1 2 character b
#> 3 1 3 character c
#> 4 2 1 integer 1
#> 5 2 2 integer 2
#> 6 3 1 character w
#> 7 3 2 character x
#> 8 3 3 character y
#> 9 3 4 character z
Thanks to Duncan Garmonsway (@nacnudus) for great work on the idea an
implementation of the melt_*()
functions!
readr 1.2.0 changes how R connections are parsed by readr. In previous versions of readr the connections were read into an in-memory raw vector, then passed to the readr functions. This made reading connections from small to medium datasets fast, but also meant that the dataset had to fit into memory at least twice (once for the raw data, once for the parsed data). It also meant that reading could not begin until the full vector was read through the connection.
Now we instead write the connection to a temporary file (in the R temporary directory), than parse that temporary file. This means connections may take a little longer to be read, but also means they will no longer need to fit into memory. It also allows the use of the chunked readers to process the data in parts.
Future improvements to readr would allow it to parse data from connections in a streaming fashion, which would avoid many of the drawbacks of either method.
melt_*()
functions added for reading ragged data (#760, @nacnudus).AccumulateCallback
R6 class added to provide an example of accumulating values in a single result (#689, @blakeboswell).read_fwf()
can now accept overlapping field specifications (#692, @gergness)type_convert()
now allows character column specifications and also silently skips non-character columns (#369, #699)- The
parse_*()
functions andread_fwf()
gain atrim_ws
argument to control whether the fields should be trimmed before parsing (#636, #735). parse_number()
now parses numbers in scientific notation usinge
andE
(#684, @sambrady3).- Add
write_excel_csv2()
function to allow writing csv files with comma as a decimal separator and semicolon as a column separator (#753, @olgamie). read_*()
files now support reading from the clipboard by usingclipboard()
(#656).write_file()
gains asep
argument, to specify the line separator (#665).- Allow files to be read via FTP over SSH by recognising
sftp
as a URL protocol (#707, @jdeboer). parse_date*() accepts
%a` for local day of week (#763, @tigertoes).- Added function
read_lines_raw_chunked()
(#710, @gergness) write_csv2()
added to complementwrite_excel_csv2()
and allow writing csv file readable byread_csv2()
(#870, @cderv).as.col_spec()
is now exported (#517).write*()
functions gain aquote_escape
argument to control how quotes are escaped in the output (#854).read*()
functions now have a more informative error when trying to read a remote bz2 file (#891).spec_table2()
function added to correspond toread_table2()
(#778, @mawds).parse_factor()
now haslevels = NULL
by default (#862, @mikmart)."f"
can now be used as a shortcode forcol_factor()
incols()
and thecol_types
argument toread_delim()
and friends (#810, @mikmart).- Functions now read connections to a temporary file rather than to an in-memory object (#610, #76).
standardise_path()
now uses a case-insensitive comparison for the file extensions (#794).parse_guess()
now guesses logical types when given (lowercase) 'true' and 'false' inputs (#818).read_*()
now do not print a progress bar when running inside a RStudio notebook chunk (#793)read_table2()
now skips comments anywhere in the file (#908).parse_factor()
now handles the case of empty strings separately, so you can have a factor level that is an empty string (#864).read_delim()
now correctly reads quoted headers with embedded newlines (#784).fwf_positions()
now always returnscol_names
as a character (#797).format_*()
now explicitly marks it's output encoding as UTF-8 (#697).read_delim()
now ignores whitespace between the delimiter and quoted fields (#668).read_table2()
now properly ignores blank lines at the end of a file likeread_table()
andread_delim()
(#657).read_delim()
,read_table()
andread_table()
now skip blank lines at the start of a file (#680, #747).guess_parser()
now guesses a logical type for columns which are all missing. This is useful when binding multiple files together where some files have missing columns. (#662).- Column guessing will now never guess an integer type. This avoids issues where double columns are incorrectly guessed as integers if they have only integer values in the first 1000 (#645, #652).
read_*()
now converts stringfile
s to UTF-8 before parsing, which is convenient for non-UTF-8 platforms in most cases (#730, @yutannihilation).write_csv()
writes integers up to 10^15 without scientific notation (#765, @zeehio)read_*()
no longer throws a "length of NULL cannot be changed" warning when trying to resize a skipped column (#750, #833).read_*()
now handles non-ASCII paths properly with R >=3.5.0 on Windows (#838, @yutannihilation).read*()
'strim_ws
parameter now trims both spaces and tabs (#767)
- Point release for test compatibility with tibble v1.3.1.
- Fixed undefined behavior in localtime.c when using
locale(tz = "")
after loading a timezone due to incomplete reinitialization of the global locale.
parse_factor()
gains ainclude_na
argument, to includeNA
in the factor levels (#541).parse_factor()
will now can acceptlevels = NULL
, which allows one to generate factor levels based on the data (like stringsAsFactors = TRUE) (#497).parse_numeric()
now returns the full string if it contains no numbers (#548).parse_time()
now correctly handles 12 AM/PM (#579).problems()
now returns the file path in additional to the location of the error in the file (#581).read_csv2()
gives a message if it updates the default locale (#443, @krlmlr).read_delim()
now signals an error if given an empty delimiter (#557).write_*()
functions witting whole number doubles are no longer written with a trailing.0
(#526).
fwf_cols()
allows for specifying thecol_positions
argument ofread_fwf()
with named arguments of either column positions or widths (#616, @jrnold).fwf_empty()
gains ann
argument to control how many lines are read for whitespace to determine column structure (#518, @Yeedle).read_fwf()
gives error message if specifications have overlapping columns (#534, @gergness)read_table()
can now handlepipe()
connections (#552).read_table()
can now handle files with many lines of leading comments (#563).read_table2()
which allows any number of whitespace characters as delimiters, a more exact replacement forutils::read.table()
(#608).
write_*()
functions now support writing to binary connections. In addition output filenames with.gz
,.bz2
or.xz
will automatically open the appropriate connection and to write the compressed file. (#348)write_lines()
now accepts a list of raw vectors (#542).
col_euro_double()
,parse_euro_double()
,col_numeric()
, andparse_numeric()
have been removed.guess_encoding()
returns a tibble, and works better with lists of raw vectors (as returned byread_lines_raw()
).ListCallback
R6 Class to provide a more flexible return type for callback functions (#568, @mmuurr)tibble::as.tibble()
now used to construct tibbles (#538).read_csv
,read_csv2
, andread_tsv
gain aquote
argument, (#631, @noamross)
parse_factor()
now converts data to UTF-8 based on the supplied locale (#615).read_*()
functions with theguess_max
argument now throw errors on inappropriate inputs (#588).read_*_chunked()
functions now properly end the stream ifFALSE
is returned from the callback.read_delim()
andread_fwf()
when columns are skipped usingcol_types
now report the correct column name (#573, @cb4ds).spec()
declarations that are long now print properly (#597).read_table()
does not printspec
whencol_types
is notNULL
(#630, @jrnold).guess_encoding()
now returns a tibble for all ASCII input as well (#641).
The process by which readr guesses the types of columns has received a substantial overhaul to make it easier to fix problems when the initial guesses aren't correct, and to make it easier to generate reproducible code. Now column specifications are printing by default when you read from a file:
challenge <- read_csv(readr_example("challenge.csv"))
#> Parsed with column specification:
#> cols(
#> x = col_integer(),
#> y = col_character()
#> )
And you can extract those values after the fact with spec()
:
spec(challenge)
#> cols(
#> x = col_integer(),
#> y = col_character()
#> )
This makes it easier to quickly identify parsing problems and fix them (#314). If the column specification is long, the new cols_condense()
is used to condense the spec by identifying the most common type and setting it as the default. This is particularly useful when only a handful of columns have a different type (#466).
You can also generating an initial specification without parsing the file using spec_csv()
, spec_tsv()
, etc.
Once you have figured out the correct column types for a file, it's often useful to make the parsing strict. You can do this either by copying and pasting the printed output, or for very long specs, saving the spec to disk with write_rds()
. In production scripts, combine this with stop_for_problems()
(#465): if the input data changes form, you'll fail fast with an error.
You can now also adjust the number of rows that readr uses to guess the column types with guess_max
:
challenge <- read_csv(readr_example("challenge.csv"), guess_max = 1500)
#> Parsed with column specification:
#> cols(
#> x = col_double(),
#> y = col_date(format = "")
#> )
You can now access the guessing algorithm from R. guess_parser()
will tell you which parser readr will select for a character vector (#377). We've made a number of fixes to the guessing algorithm:
-
New example
extdata/challenge.csv
which is carefully created to cause problems with the default column type guessing heuristics. -
Blank lines and lines with only comments are now skipped automatically without warning (#381, #321).
-
Single '-' or '.' are now parsed as characters, not numbers (#297).
-
Numbers followed by a single trailing character are parsed as character, not numbers (#316).
-
We now guess at times using the
time_format
specified in thelocale()
.
We have made a number of improvements to the reification of the col_types
, col_names
and the actual data:
-
If
col_types
is too long, it is subsetted correctly (#372, @jennybc). -
If
col_names
is too short, the added names are numbered correctly (#374, @jennybc). -
Missing column name names are now given a default name (
X2
,X7
etc) (#318). Duplicated column names are now deduplicated. Both changes generate a warning; to suppress it supply an explicitcol_names
(settingskip = 1
if there's an existing ill-formed header). -
col_types()
accepts a named list as input (#401).
The date time parsers recognise three new format strings:
-
%I
for 12 hour time format (#340). -
%AD
and%AT
are "automatic" date and time parsers. They are both slightly less flexible than previous defaults. The automatic date parser requires a four digit year, and only accepts-
and/
as separators (#442). The flexible time parser now requires colons between hours and minutes and optional seconds (#424).
%y
and %Y
are now strict and require 2 or 4 characters respectively.
Date and time parsing functions received a number of small enhancements:
-
parse_time()
returnshms
objects rather than a customtime
class (#409). It now correctly parses missing values (#398). -
parse_date()
returns a numeric vector (instead of an integer vector) (#357). -
parse_date()
,parse_time()
andparse_datetime()
gain anna
argument to match all other parsers (#413). -
If the format argument is omitted
parse_date()
orparse_time()
, date and time formats specified in the locale will be used. These now default to%AD
and%AT
respectively. -
You can now parse partial dates with
parse_date()
andparse_datetime()
, e.g.parse_date("2001", "%Y")
returns2001-01-01
.
parse_number()
is slightly more flexible - it now parses numbers up to the first ill-formed character. For example parse_number("-3-")
and parse_number("...3...")
now return -3 and 3 respectively. We also fixed a major bug where parsing negative numbers yielded positive values (#308).
parse_logical()
now accepts 0
, 1
as well as lowercase t
, f
, true
, false
.
-
read_file_raw()
reads a complete file into a single raw vector (#451). -
read_*()
functions gain aquoted_na
argument to control whether missing values within quotes are treated as missing values or as strings (#295). -
write_excel_csv()
can be used to write a csv file with a UTF-8 BOM at the start, which forces Excel to read it as UTF-8 encoded (#375). -
write_lines()
writes a character vector to a file (#302). -
write_file()
to write a single character or raw vector to a file (#474). -
Experimental support for chunked reading a writing (
read_*_chunked()
) functions. The API is unstable and subject to change in the future (#427).
-
Printing double values now uses an implementation of the grisu3 algorithm which speeds up writing of large numeric data frames by ~10X. (#432) '.0' is appended to whole number doubles, to ensure they will be read as doubles as well. (#483)
-
readr imports tibble so that you get consistent
tbl_df
behaviour (#317, #385). -
New example
extdata/challenge.csv
which is carefully created to cause problems with the default column type guessing heuristics. -
default_locale()
now sets the default locale inreadr.default_locale
rather than regenerating it for each call. (#416). -
locale()
now automatically sets decimal mark if you set the grouping mark. It throws an error if you accidentally set decimal and grouping marks to the same character (#450). -
All
read_*()
can read into long vectors, substantially increasing the number of rows you can read (#309). -
All
read_*()
functions return empty objects rather than signaling an error when run on an empty file (#356, #441). -
read_delim()
gains atrim_ws
argument (#312, noamross) -
read_fwf()
received a number of improvements:-
read_fwf()
now can now reliably read only a partial set of columns (#322, #353, #469) -
fwf_widths()
accepts negative column widths for compatibility with thewidths
argument inread.fwf()
(#380, @leeper). -
You can now read fixed width files with ragged final columns, by setting the final end position in
fwf_positions()
or final width infwf_widths()
toNA
(#353, @ghaarsma).fwf_empty()
does this automatically. -
read_fwf()
andfwf_empty()
can now skip commented lines by setting acomment
argument (#334).
-
-
read_lines()
ignores embedded null's in strings (#338) and gains ana
argument (#479). -
readr_example()
makes it easy to access example files bundled with readr. -
type_convert()
now accepts onlyNULL
or acols
specification forcol_types
(#369). -
write_delim()
andwrite_csv()
now invisibly return the input data frame (as documented, #363). -
Doubles are parsed with
boost::spirit::qi::long_double
to work around a bug in the spirit library when parsing large numbers (#412). -
Fix bug when detecting column types for single row files without headers (#333).
- Fix bug when checking empty values for missingness (caused valgrind issue and random crashes).
- Fixes so that readr works on Solaris.
readr now has a strategy for dealing with settings that vary from place to place: locales. The default locale is still US centric (because R itself is), but you can now easily override the default timezone, decimal separator, grouping mark, day & month names, date format, and encoding. This has lead to a number of changes:
-
read_csv()
,read_tsv()
,read_fwf()
,read_table()
,read_lines()
,read_file()
,type_convert()
,parse_vector()
all gain alocale
argument. -
locale()
controls all the input settings that vary from place-to-place. -
col_euro_double()
andparse_euro_double()
have been deprecated. Use thedecimal_mark
parameter tolocale()
instead. -
The default encoding is now UTF-8. To load files that are not in UTF-8, set the
encoding
parameter of thelocale()
(#40). Newguess_encoding()
function uses stringi to help you figure out the encoding of a file. -
parse_datetime()
andparse_date()
with%B
and%b
use the month names (full and abbreviate) defined in the locale (#242). They also inherit the tz from the locale, rather than using an explicittz
parameter.
See vignette("locales")
for more details.
-
cols()
lets you pick the default column type for columns not otherwise explicitly named (#148). You can refer to parsers either with their full name (e.g.col_character()
) or their one letter abbreviation (e.g.c
). -
cols_only()
allows you to load only named columns. You can also choose to override the default column type incols()
(#72). -
read_fwf()
is now much more careful with new lines. If a line is too short, you'll get a warning instead of a silent mistake (#166, #254). Additionally, the last column can now be ragged: the width of the last field is silently extended until it hits the next line break (#146). This appears to be a common feature of "fixed" width files in the wild. -
In
read_csv()
,read_tsv()
,read_delim()
etc:-
comment
argument allows you to ignore comments (#68). -
trim_ws
argument controls whether leading and trailing whitespace is removed. It defaults toTRUE
(#137). -
Specifying the wrong number of column names, or having rows with an unexpected number of columns, generates a warning, rather than an error (#189).
-
Multiple NA values can be specified by passing a character vector to
na
(#125). The default has been changed tona = c("", "NA")
. Specifyingna = ""
now works as expected with character columns (#114).
-
Readr gains vignette("column-types")
which describes how the defaults work and how to override them (#122).
-
parse_character()
gains better support for embedded nulls: any characters after the first null are dropped with a warning (#202). -
parse_integer()
andparse_double()
no longer silently ignore trailing letters after the number (#221). -
New
parse_time()
andcol_time()
allows you to parse times (hours, minutes, seconds) into number of seconds since midnight. If the format is omitted, it uses a flexible parser that looks for hours, then optional colon, then minutes, then optional colon, then optional seconds, then optional am/pm (#249). -
parse_date()
andparse_datetime()
:-
parse_datetime()
no longer incorrectly reads partial dates (e.g. 19, 1900, 1900-01) (#136). These triggered common false positives and after re-reading the ISO8601 spec, I believe they actually refer to periods of time, and should not be translated in to a specific instant (#228). -
Compound formats "%D", "%F", "%R", "%X", "%T", "%x" are now parsed correctly, instead of using the ISO8601 parser (#178, @kmillar).
-
"%." now requires a non-digit. New "%+" skips one or more non-digits.
-
You can now use
%p
to refer to AM/PM (and am/pm) (#126). -
%b
and%B
formats (month and abbreviated month name) ignore case when matching (#219). -
Local (non-UTC) times with and without daylight savings are now parsed correctly (#120, @andres-s).
-
-
parse_number()
is a somewhat flexible numeric parser designed to read currencies and percentages. It only reads the first number from a string (using the grouping mark defined by the locale). -
parse_numeric()
has been deprecated because the name is confusing - it's a flexible number parser, not a parser of "numerics", as R collectively calls doubles and integers. Useparse_number()
instead.
As well as improvements to the parser, I've also made a number of tweaks to the heuristics that readr uses to guess column types:
-
New
parse_guess()
andcol_guess()
to explicitly guess column type. -
Bumped up row inspection for column typing guessing from 100 to 1000.
-
The heuristics for guessing
col_integer()
andcol_double()
are stricter. Numbers with leading zeros now default to being parsed as text, rather than as integers/doubles (#266). -
A column is guessed as
col_number()
only if it parses as a regular number when you ignoring the grouping marks.
-
Now use R's platform independent
iconv
wrapper, thanks to BDR (#149). -
Pathological zero row inputs (due to empty input,
skip
orn_max
) now return zero row data frames (#119). -
When guessing field types, and there's no information to go on, use character instead of logical (#124, #128).
-
Concise
col_types
specification now understands?
(guess) and-
(skip) (#188). -
count_fields()
starts counting from 1, not 0 (#200). -
format_csv()
andformat_delim()
make it easy to render a csv or delimited file into a string. -
fwf_empty()
now works correctly whencol_names
supplied (#186, #222). -
parse_*()
gains ana
argument that allows you to specify which values should be converted to missing. -
problems()
now reports column names rather than column numbers (#143). Whenever there is a problem, the first five problems are printing out in a warning message, so you can more easily see what's wrong. -
read_*()
throws a warning instead of an error iscol_types
specifies a non-existent column (#145, @alyst). -
read_*()
can read from a remote gz compressed file (#163). -
read_delim()
defaults toescape_backslash = FALSE
andescape_double = TRUE
for consistency.n_max
also affects the number of rows read to guess the column types (#224). -
read_lines()
gains a progress bar. It now also correctly checks for interrupts every 500,000 lines so you can interrupt long running jobs. It also correctly estimates the number of lines in the file, considerably speeding up the reading of large files (60s -> 15s for a 1.5 Gb file). -
read_lines_raw()
allows you to read a file into a list of raw vectors, one element for each line. -
type_convert()
gainsNA
andtrim_ws
arguments, and removes missing values before determining column types. -
write_csv()
,write_delim()
, andwrite_rds()
all invisibly return their input so you can use them in a pipe (#290). -
write_delim()
generaliseswrite_csv()
to write any delimited format (#135).write_tsv()
is a helpful wrapper for tab separated files.-
Quotes are only used when they're needed (#116): when the string contains a quote, the delimiter, a new line or NA.
-
Double vectors are saved using same amount of precision as
as.character()
(#117). -
New
na
argument that specifies how missing values should be written (#187) -
POSIXt vectors are saved in a ISO8601 compatible format (#134).
-
No longer fails silently if it can't open the target for writing (#193, #172).
-
-
write_rds()
andread_rds()
wrap aroundreadRDS()
andsaveRDS()
, defaulting to no compression (#140, @nicolasCoutin).