Functional Programming Tools

A complete and consistent functional programming toolkit for R.

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purrr enhances R's functional programming (FP) toolkit by providing a complete and consistent set of tools for working with functions and vectors. If you've never heard of FP before, the best place to start is the family of map() functions which allow you to replace many for loops with code that is both more succinct and easier to read. The best place to learn about the map() functions is the iteration chapter in R for data science.


# Alternatively, install just purrr:
# Or the the development version from GitHub:
# install.packages("devtools")


The following example uses purrr to solve a fairly realistic problem: split a data frame into pieces, fit a model to each piece, compute the summary, then extract the R2.

mtcars %>%
  split(.$cyl) %>% # from base R
  map(~ lm(mpg ~ wt, data = .)) %>%
  map(summary) %>%
#>         4         6         8 
#> 0.5086326 0.4645102 0.4229655

This example illustrates some of the advantages of purrr functions over the equivalents in base R:

  • The first argument is always the data, so purrr works naturally with the pipe.

  • All purrr functions are type-stable. They always return the advertised output type (map() returns lists; map_dbl() returns double vectors), or they throw an errror.

  • All map() functions either accept function, formulas (used for succinctly generating anonymous functions), a character vector (used to extract components by name), or a numeric vector (used to extract by position).


purrr 0.2.5

This is a maintenance release following the release of dplyr 0.7.5.

purrr 0.2.4

  • Fixes for R 3.1.

purrr 0.2.3

Breaking changes

We noticed the following issues during reverse dependencies checks:

  • If reduce() fails with this message: Error: `.x` is empty, and no `.init` supplied, this is because reduce() now returns .init when .x is empty. Fix the problem by supplying an appropriate argument to .init, or by providing special behaviour when .x has length 0.

  • The type predicates have been migrated to rlang. Consequently the bare-type-predicates documentation topic is no longer in purrr, which might cause a warning if you cross-reference it.


purrr no longer depends on lazyeval or Rcpp (or dplyr, as of the previous version). This makes the dependency graph of the tidyverse simpler, and makes purrr more suitable as a dependency of lower-level packages.

There have also been two changes to eliminate name conflicts between purrr and dplyr:

  • order_by(), sort_by() and split_by() have been removed. order_by() conflicted with dplyr::order_by() and the complete family doesn't feel that useful. Use tibbles instead (#217).

  • contains() has been renamed to has_element() to avoid conflicts with dplyr (#217).


The plucking mechanism used for indexing into data structures with map() has been extracted into the function pluck(). Plucking is often more readable to extract an element buried in a deep data structure. Compare this syntax-heavy extraction which reads non-linearly:


to the equivalent pluck:

x %>% pluck(1, accessor, "foo")

Map helpers

  • as_function() is now as_mapper() because it is a tranformation that makes sense primarily for mapping functions, not in general (#298). .null has been renamed to .default to better reflect its intent (#298). .default is returned whenever an element is absent or empty (#231, #254).

    as_mapper() sanitises primitive functions by transforming them to closures with standardised argument names (using rlang::as_closure()). For instance + is transformed to function(.x, .y) .x + .y. This results in proper argument matching so that map(1:10, partial(-, .x = 5)) produces list(5 - 1, 5 - 2, ...).

  • Recursive indexing can now extract objects out of environments (#213) and S4 objects (#200), as well as lists.

  • attr_getter() makes it possible to extract from attributes like map(list(iris, mtcars), attr_getter("row.names")).

  • The argument list for formula-functions has been tweaked so that you can refer to arguments by position with ..1, ..2, and so on. This makes it possible to use the formula shorthand for functions with more than two arguments (#289).

  • possibly(), safely() and friends no longer capture interrupts: this means that you can now terminate a mapper using one of these with Escape or Ctrl + C (#314)

Map functions

  • All map functions now treat NULL the same way as an empty vector (#199), and return an empty vector if any input is an empty vector.

  • All map() functions now force their arguments in the same way that base R does for lapply() (#191). This makes map() etc easier to use when generating functions.

  • A new family of "indexed" map functions, imap(), imap_lgl() etc, provide a short-hand for map2(x, names(x)) or map2(x, seq_along(x)) (#240).

  • The data frame suffix _df has been (soft) deprecated in favour of _dfr to more clearly indicate that it's a row-bind. All variants now also have a _dfc for column binding (#167). (These will not be terribly useful until dplyr::bind_rows()/dplyr::bind_cols() have better semantics for vectors.)

Modify functions

A new modify() family returns the same output of the type as the input .x. This is in contrast to the map() family which always returns a list, regardless of the input type.

The modify functions are S3 generics. However their default methods should be sufficient for most classes since they rely on the semantics of [<-. modify.default() is thus a shorthand for x[] <- map(x, f).

  • at_depth() has been renamed to modify_depth().

  • modify_depth() gains new .ragged argument, and negative depths are now computed relative to the deepest component of the list (#236).

New functions

  • auto_browse(f) returns a new function that automatically calls browser() if f throws an error (#281).

  • vec_depth() computes the depth (i.e. the number of levels of indexing) or a vector (#243).

  • reduce2() and reduce2_right() make it possible to reduce with a 3 argument function where the first argument is the accumulated value, the second argument is .x, and the third argument is .y (#163).

  • list_modify() extends stats::modifyList() to replace by position if the list is not named.(#201). list_merge() operates similarly to list_modify() but combines instead of replacing (#322).

  • The legacy function update_list() is basically a version of list_modify that evaluates formulas within the list. It is likely to be deprecated in the future in favour of a tidyeval interface such as a list method for dplyr::mutate().

Minor improvements and bug fixes

  • Thanks to @dchiu911, the unit test coverage of purrr is now much greater.

  • All predicate functions are re-exported from rlang (#124).

  • compact() now works with standard mapper conventions (#282).

  • cross_n() has been renamed to cross(). The _n suffix was removed for consistency with pmap() (originally called map_n() at the start of the project) and transpose() (originally called zip_n()). Similarly, cross_d() has been renamed to cross_df() for consistency with map_df().

  • every() and some() now return NA if present in the input (#174).

  • invoke() uses a more robust approach to generate the argument list (#249) It no longer uses lazyeval to figure out which enviroment a character f comes from.

  • is_numeric() and is_scalar_numeric() are deprecated because they don't test for what you might expect at first sight.

  • reduce() now throws an error if .x is empty and .init is not supplied.

  • Deprecated functions flatmap(), map3(), map_n(), walk3(), walk_n(), zip2(), zip3(), zip_n() have been removed.

  • pmap() coerces data frames to lists to avoid the expensive [.data.frame which provides security that is unneeded here (#220).

  • rdunif() checks its inputs for validity (#211).

  • set_names() can now take a function to tranform the names programmatically (#276), and you can supply names in ... to reduce typing even more more (#316). set_names() is now powered by rlang::set_names().

  • safely() now actually uses the quiet argument (#296).

  • transpose() now matches by name if available (#164). You can override the default choice with the new .names argument.

  • The function argument of detect() and detect_index() have been renamed from .p to .f. This is because they have mapper semantics rather than predicate semantics.


This is a compatibility release with dplyr 0.6.0.

  • All data-frame based mappers have been removed in favour of new functions and idioms in the tidyverse. dmap(), dmap_at(), dmap_if(), invoke_rows(), slice_rows(), map_rows(), by_slice(), by_row(), and unslice() have been moved to purrrlyr. This is a bit of an aggresive change but it allows us to make the dependencies much lighter.

purrr 0.2.2

  • Fix for dev tibble support.

  • as_function() now supports list arguments which allow recursive indexing using either names or positions. They now always stop when encountering the first NULL (#173).

  • accumulate and reduce correctly pass extra arguments to the worker function.

purrr 0.2.1

  • as_function() gains a .null argument that for character and numeric values allows you to specify what to return for null/absent elements (#110). This can be used with any map function, e.g. map_int(x, 1, .null = NA)

  • as_function() is now generic.

  • New is_function() that returns TRUE only for regular functions.

  • Fix crash on GCC triggered by invoke_rows().

purrr 0.2.0

New functions

  • There are two handy infix functions:

    • x %||% y is shorthand for if (is.null(x)) y else x (#109).
    • x %@% "a" is shorthand for attr(x, "a", exact = TRUE) (#69).
  • accumulate() has been added to handle recursive folding. It is shortand for Reduce(f, .x, accumulate = TRUE) and follows a similar syntax to reduce() (#145). A right-hand version accumulate_right() was also added.

  • map_df() row-binds output together. It's the equivalent of plyr::ldply() (#127)

  • flatten() is now type-stable and always returns a list. To return a simpler vector, use flatten_lgl(), flatten_int(), flatten_dbl(), flatten_chr(), or flatten_df().

  • invoke() has been overhauled to be more useful: it now works similarly to map_call() when .x is NULL, and hence map_call() has been deprecated. invoke_map() is a vectorised complement to invoke() (#125), and comes with typed variants invoke_map_lgl(), invoke_map_int(), invoke_map_dbl(), invoke_map_chr(), and invoke_map_df().

  • transpose() replaces zip2(), zip3(), and zip_n() (#128). The name more clearly reflects the intent (transposing the first and second levels of list). It no longer has fields argument or the .simplify argument; instead use the new simplify_all() function.

  • safely(), quietly(), and possibly() are experimental functions for working with functions with side-effects (e.g. printed output, messages, warnings, and errors) (#120). safely() is a version of try() that modifies a function (rather than an expression), and always returns a list with two components, result and error.

  • list_along() and rep_along() generalise the idea of seq_along(). (#122).

  • is_null() is the snake-case version of is.null().

  • pmap() (parallel map) replaces map_n() (#132), and has typed-variants suffixed pmap_lgl(), pmap_int(), pmap_dbl(), pmap_chr(), and pmap_df().

  • set_names() is a snake-case alternative to setNames() with stricter equality checking, and more convenient defaults for pipes: x %>% set_names() is equivalent to setNames(x, x) (#119).

Row based functionals

We are still figuring out what belongs in dplyr and what belongs in purrr. Expect much experimentation and many changes with these functions.

  • map() now always returns a list. Data frame support has been moved to map_df() and dmap(). The latter supports sliced data frames as a shortcut for the combination of by_slice() and dmap(): x %>% by_slice(dmap, fun, .collate = "rows"). The conditional variants dmap_at() and dmap_if() also support sliced data frames and will recycle scalar results to the slice size.

  • map_rows() has been renamed to invoke_rows(). As other rows-based functionals, it collates results inside lists by default, but with column collation this function is equivalent to plyr::mdply().

  • The rows-based functionals gain a .to option to name the output column as well as a .collate argument. The latter allows to collate the output in lists (by default), on columns or on rows. This makes these functions more flexible and more predictable.

Bug fixes and minor changes

  • as_function(), which converts formulas etc to functions, is now exported (#123).

  • rerun() is correctly scoped (#95)

  • update_list() can now modify an element called x (#98).

  • map*() now use custom C code, rather than relying on lapply(), mapply() etc. The performance characteristcs are very similar, but it allows us greater control over the output (#118).

  • map_lgl() now has second argument .f, not .p (#134).

Deprecated functions

  • flatmap() -> use map() followed by the appropriate flatten().

  • map_call() -> invoke().

  • map_n() -> pmap(); walk_n() -> pwalk().

  • map3(x, y, z) -> map_n(list(x, y, z)); walk3(x, y, z) ->pwalk(list(x, y, z))`

Reference manual

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0.2.5 by Lionel Henry, 8 months ago,

Report a bug at

Browse source code at

Authors: Lionel Henry [aut, cre] , Hadley Wickham [aut] , RStudio [cph, fnd]

Documentation:   PDF Manual  

GPL-3 | file LICENSE license

Imports magrittr, rlang, tibble

Suggests covr, dplyr, knitr, rmarkdown, testthat

Imported by BAwiR, BayesMallows, BradleyTerryScalable, CDECRetrieve, CPAT, CPBayes, CrossClustering, DLMtool, DataPackageR, DiagrammeR, ERSA, EventStudy, GSODR, HURDAT, INDperform, ImputeRobust, LAGOSNE, MPTmultiverse, MRFcov, MarginalMediation, MetamapsDB, Nmisc, PKPDmisc, PopED, REddyProc, RPyGeo, RSDA, Rd, Rdrools, RevEcoR, SCORPIUS, STRMPS, SanzCircos, ShinyTester, SingleCaseES, WRTDStidal, abjutils, adaptalint, ahnr, alphavantager, amt, analysisPipelines, anomalize, anomalyDetection, apa, areal, arena2r, ari, atlantistools, automagic, autothresholdr, banR, beadplexr, binneR, biomartr, bipartiteD3, blorr, blscrapeR, breathtestcore, breathteststan, broom, broom.mixed, bsplus, bupaR, cansim, casino, cdcfluview, censys, cepR, childesr, childsds, chinese.misc, chorrrds, cimir, circumplex, civis, clustermq, coalitions, codebook, codemetar, coefplot, collateral, colorednoise, colorfindr, comtradr, congressbr, cosinor2, countyweather, covTestR, crawl, crimedata, crplyr, crsra, customsteps, cutpointr, cytominer, datadogr, datastructures, dbparser, dbplot, dbplyr, deeplr, descriptr, desctable, detrendr, dials, diceR, dkanr, dlookr, docxtools, docxtractr, dotwhisker, dynutils, easyalluvial, echarts4r, echor, edeaR, eesim, egor, embed, emuR, epidata, ergm, ergm.ego, esc, estatapi, europepmc, evaluator, exampletestr, exuber, eyetrackingR, fbar, fcuk, fedregs, filesstrings, finalfit, fingertipsR, fingertipscharts, forecastHybrid, forestControl, forestmangr, frite, ftDK, furrr, fuzzr, fuzzyjoin, geniusr, genogeographer, geoparser, germanpolls, getTBinR, ggbuildr, ggdag, ggedit, ggeffects, gghighlight, ggiraphExtra, gglogo, ggmosaic, ggpage, ggpubr, ggstatsplot, ggthemes, giphyr, gitlabr, googleAnalyticsR, googleLanguageR, googledrive, googlenlp, googlesheets, graphTweets, gravity, groupedstats, gutenbergr, healthcareai, highcharter, hpiR, hurricaneexposure, icpsrdata, ijtiff, imager, incgraph, inferr, influxdbr, interplot, iotables, ipumsr, janitor, jpmesh, jpndistrict, jstor, kntnr, kokudosuuchi, konfound, landscapetools, livechatR, longurl, mathpix, mboxr, meetupapi, memery, metaDigitise, mleap, mlflow, modeldb, modelgrid, modelr, monkeylearn, moonBook, muHVT, multicolor, namer, nandb, naniar, ncappc, nesRdata, nls.multstart, nonet, normalr, nullabor, oak, obliqueRSF, oec, olsrr, openVA, openair, optiSel, pammtools, parsnip, patrick, patternize, pcr, perccalc, petrinetR, pewdata, phylopath, pinnacle.API, pivot, pkgdown, plotly, pointblank, pollen, pollstR, postal, postlightmercury, prcr, prism, processmapR, projects, proustr, psychmeta, psycho, purrrlyr, qccrs, qiitr, qqplotr, qsort, qsub, qualmap, quokar, r4lineups, rbin, rclimateca, rdfp, rdrop2, reReg, readOffice, recipes, reinforcelearn, rfbCNPJ, rfishbase, rfm, rhierbaps, riingo, rmapzen, rmd, rmsfuns, rmweather, rnr, roadoi, roxygen2, rrtable, rsample, rtrek, rtypeform, ruta, salesforcer, salty, sampler, scanstatistics, scriptName, sergeant, shiny.semantic, sigmajs, simTool, simglm, simstandard, sjPlot, sjlabelled, sjmisc, sjstats, skimr, sloop, spAddins, sparklyr, sparklyr.nested, sperrorest, splashr, spotifyr, spup, starmie, steemr, stminsights, strex, styler, suropt, surveydata, survivalAnalysis, survminer, survutils, swmmr, syllabifyr, tableschema.r, tabr, tatoo, tauturri, tbrf, tensorr, testextra, textfeatures, textrecipes, tfestimators, tibbletime, tidyLPA, tidyRSS, tidybayes, tidyboot, tidycensus, tidygenomics, tidymodels, tidyposterior, tidypredict, tidyquant, tidyr, tidyselect, tidystats, tidytext, tidytidbits, tidyverse, timetk, tipr, togglr, totalcensus, trelliscopejs, tsibble, tuber, twilio, uaparserjs, ukbtools, understandBPMN, unpivotr, uptasticsearch, useful, valaddin, vdiffr, veccompare, visdat, voxel, vqtl, walkalytics, walmartAPI, wand, weathercan, webTRISr, widgetframe, widyr, wikisourcer, wordbankr, xesreadR, xpose, xspliner, zeligverse.

Depended on by LipidMS, ggraptR.

Suggested by RBesT, VarBundle, bigQueryR, c3, classyfireR, countytimezones, d3r, diffdf, dodgr, edgarWebR, facerec, fc, fourierin, fpp2, fredr, ganalytics, ggformula, ggparliament, humanize, knitrProgressBar, leaflet, listarrays, lognorm, mixdir, mlr, nomisr, quanteda, rAltmetric, rcongresso, rdflib, repurrrsive, rnoaa, rtdists, ssdtools, sweep, taipan, tidyxl, valr, vinereg, yardstick, zeallot.

See at CRAN