• Stars
    star
    310
  • Rank 124,354 (Top 3 %)
  • Language
    R
  • License
    Other
  • Created about 13 years ago
  • Updated 9 months ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

Easy memoisation for R

memoise

CRAN status R build status Codecov test coverage

The memoise package makes it easy to memoise R functions. Memoisation (https://en.wikipedia.org/wiki/Memoization) caches function calls so that if a previously seen set of inputs is seen, it can return the previously computed output.

Installation

Install from CRAN with

install.packages("memoise")

Usage

To memoise a function, use memoise():

library(memoise)
f <- function(x) {
  Sys.sleep(1)
  mean(x)
}
mf <- memoise(f)
system.time(mf(1:10))
#>    user  system elapsed
#>   0.002   0.000   1.003
system.time(mf(1:10))
#>    user  system elapsed
#>   0.000   0.000   0.001

You can clear mf’s cache with:

forget(mf)

And you can test whether a function is memoised with is.memoised().

Caches

By default, memoise uses an in-memory cache, using cache_mem() from the cachem package. cachem::cache_disk() allows caching using files on a local filesystem.

Both cachem::cache_mem() and cachem::cache_disk() support automatic pruning by default; this means that they will not keep growing past a certain size, and eventually older items will be removed from the cache. The default size cache_mem() is 512 MB, and the default size for a cache_disk() is 1 GB, but this can be customized by specifying max_size:

# 100 MB limit
cm <- cachem::cache_mem(max_size = 100 * 1024^2)

mf <- memoise(f, cache = cm)

You can also change the maximum age of items in the cache with max_age:

# Expire items in cache after 15 minutes
cm <- cachem::cache_mem(max_age = 15 * 60)

mf <- memoise(f, cache = cm)

By default, a cache_disk() uses a subdirectory the R process’s temp directory, but it is possible to specify the directory. This is useful for persisting a cache across R sessions, sharing a cache among different processes, or even for synchronizing across the network.

# Store in "R-myapp" directory inside of user-level cache directory
cd <- cachem::cache_disk(rappdirs::user_cache_dir("R-myapp"))

# Store in Dropbox
cdb <- cachem::cache_disk("~/Dropbox/.rcache")

A single cache object can be shared among multiple memoised functions. By default, the cache key includes not only the arguments to the function, but also the body of the function. This essentially eliminates the possibility of a cache collision, even if two memoised functions are called with the same arguments.

m <- cachem::cache_mem()

times2 <- memoise(function(x) { x * 2 }, cache = m)
times4 <- memoise(function(x) { x * 4 }, cache = m)

times2(10)
#> [1] 20
times4(10)
#> [1] 40

Cache API

It is possible to use other caching backends with memoise. These caching objects must be key-value stores which use the same API as those from the cachem package. The following methods are required for full compatibiltiy with memoise:

  • $set(key, value): Sets a key to value in the cache.
  • $get(key): Gets the value associated with key. If the key is not in the cache, this returns an object with class "key_missing".
  • $exists(key): Checks for the existence of key in the cache.
  • $remove(key): Removes the value for key from the cache.
  • $reset(): Resets the cache, clearing all key/value pairs.

Note that the sentinel value for missing keys can be created by calling cachem::key_missing(), or structure(list(), class = "key_missing").

Old-style cache objects

Before version 2.0, memoise used different caching objects, which did not have automatic pruning and had a slightly different API. These caching objects can still be used, but we recommend using the caching objects from cachem when possible.

With the old-style caching objects, memoise first checks for the existence of a key in the cache, and if present, it fetches the value. This results in a possible race condition (when using caches other than the memory cache): an object could be deleted from the cache after the existence check, but before the value is fetched. With the new cachem-style caching objects, the possibility of a a race condition is eliminated: memoise simply tries to fetch the key, and if it’s not present in the cache, the cache returns a sentinel value indicating that it’s missing. (Note that the caching objects must also be designed to avoid a similar race condition internally.)

The following cache objects do not currently have an equivalent in cachem.

  • cache_s3() allows caching on Amazon S3 Requires you to specify a bucket using cache_name. When creating buckets, they must be unique among all s3 users when created.

    Sys.setenv(
      "AWS_ACCESS_KEY_ID" = "<access key>",
      "AWS_SECRET_ACCESS_KEY" = "<access secret>"
    )
    cache <- cache_s3("<unique bucket name>")
  • cache_gcs() saves the cache to Google Cloud Storage. It requires you to authenticate by downloading a JSON authentication file, and specifying a pre-made bucket:

    Sys.setenv(
      "GCS_AUTH_FILE" = "<google-service-json>",
      "GCS_DEFAULT_BUCKET" = "unique-bucket-name"
    )
    gcs <- cache_gcs()

More Repositories

1

devtools

Tools to make an R developer's life easier
R
2,312
star
2

lintr

Static Code Analysis for R
R
1,119
star
3

httr

httr: a friendly http package for R
R
977
star
4

actions

GitHub Actions for the R community
JavaScript
868
star
5

testthat

An R πŸ“¦ to make testing πŸ˜€
R
838
star
6

usethis

Set up commonly used πŸ“¦ components
R
798
star
7

pkgdown

Generate static html documentation for an R package
R
686
star
8

styler

Non-invasive pretty printing of R code
R
657
star
9

roxygen2

Generate R package documentation from inline R comments
R
553
star
10

cli

Tools for making beautiful & useful command line interfaces
R
537
star
11

pak

A fresh approach to package installation
R
521
star
12

rlang

Low-level API for programming with R
R
454
star
13

progress

Progress bar in your R terminal
R
443
star
14

rig

The R Installation Manager
Rust
391
star
15

R6

Encapsulated object-oriented programming for R
R
389
star
16

here

A simpler way to find your files
R
387
star
17

scales

Tools for ggplot2 scales
R
370
star
18

fs

Provide cross platform file operations based on libuv.
C
348
star
19

covr

Test coverage reports for R
R
328
star
20

rex

Friendly regular expressions for R.
R
325
star
21

crayon

πŸ–οΈ R package for colored terminal output β€” now superseded by cli
R
319
star
22

remotes

Install R packages from GitHub, GitLab, Bitbucket, git, svn repositories, URLs
R
309
star
23

lobstr

Understanding complex R objects with tools similar to str()
R
289
star
24

callr

Call R from R
R
276
star
25

vctrs

Generic programming with typed R vectors
C
272
star
26

waldo

Find differences between R objects
R
265
star
27

slider

Sliding Window Functions
R
259
star
28

conflicted

An alternative conflict resolution strategy for R
R
242
star
29

zeallot

Variable assignment with zeal! (or multiple, unpacking, and destructuring assignment in R)
R
242
star
30

gmailr

Access the Gmail RESTful API from R.
R
234
star
31

bench

High Precision Timing of R Expressions
R
231
star
32

processx

Execute and Control Subprocesses from R
R
225
star
33

xml2

Bindings to libxml2
R
213
star
34

asciicast

Turn R scripts into terminal screencasts
R
211
star
35

gh

Minimalistic GitHub API client in R
R
211
star
36

httr2

Make HTTP requests and process their responses. A modern reimagining of httr.
R
203
star
37

cpp11

cpp11 helps you to interact with R objects using C++ code.
C++
185
star
38

vdiffr

Visual regression testing and graphical diffing with testthat
C++
177
star
39

keyring

πŸ” Access the system credential store from R
R
177
star
40

svglite

A lightweight svg graphics device for R
C++
177
star
41

pillar

Format columns with colour
R
173
star
42

ragg

Graphic Devices Based on AGG
C++
169
star
43

ymlthis

write YAML for R Markdown, bookdown, blogdown, and more
R
163
star
44

hugodown

Make websites with hugo and RMarkdown
R
162
star
45

withr

Methods For Temporarily Modifying Global State
R
153
star
46

rprojroot

Finding files in project subdirectories
R
146
star
47

coro

Coroutines for R
R
146
star
48

debugme

Easy and efficient debugging for R packages
R
144
star
49

available

Check if a package name is available to use
R
139
star
50

ellipsis

Tools for Working with ...
R
138
star
51

archive

R bindings to libarchive, supporting a large variety of archive formats
C++
137
star
52

gert

Simple git client for R
C
135
star
53

later

Schedule an R function or formula to run after a specified period of time.
C++
132
star
54

itdepends

R
130
star
55

rray

Simple Arrays
R
130
star
56

isoband

isoband: An R package to generate contour lines and polygons.
C++
128
star
57

fastmap

Fast map implementation for R
C++
124
star
58

prettyunits

Pretty, human readable formatting of quantities
JavaScript
122
star
59

desc

Manipulate DESCRIPTION files
R
119
star
60

tidyselect

A backend for functions taking tidyverse selections
R
119
star
61

gargle

Infrastructure for calling Google APIs from R, including auth
R
111
star
62

rcmdcheck

Run R CMD check from R and collect the results
R
110
star
63

evaluate

A version of eval for R that returns more information about what happened
R
107
star
64

mockery

A mocking library for R.
R
99
star
65

prettycode

Syntax highlight R code in the terminal
R
99
star
66

sloop

S language OOP ⛡️
R
98
star
67

clock

A Date-Time Library for R
R
91
star
68

revdepcheck

R package reverse dependency checking
R
90
star
69

systemfonts

System Native Font Handling in R
C++
90
star
70

lifecycle

Manage the life cycle of your exported functions and arguments
R
87
star
71

gtable

The layout packages that powers ggplot2
R
85
star
72

pkgdepends

R Package Dependency Resolution
R
84
star
73

askpass

Password Entry for R, Git, and SSH
R
83
star
74

rappdirs

Find OS-specific directories to store data, caches, and logs. A port of python's AppDirs
R
81
star
75

commonmark

High Performance CommonMark and Github Markdown Rendering in R
C
81
star
76

zip

Platform independent zip compression via miniz
C
81
star
77

downlit

Syntax Highlighting and Automatic Linking
R
79
star
78

clisymbols

Unicode symbols for CLI applications, with fallbacks
R
74
star
79

sessioninfo

Print Session Information
R
72
star
80

ps

R package to query, list, manipulate system processes
C
71
star
81

pkgapi

Create a map of functions for an R package - WORK IN PROGRESS!
R
69
star
82

credentials

Tools for Managing SSH and Git Credentials
R
69
star
83

roxygen2md

Convert elements of roxygen documentation to markdown
R
69
star
84

sodium

R bindings to libsodium
R
68
star
85

backports

Reimplementations of Functions Introduced Since R-3.0.0
R
66
star
86

tree-sitter-r

C
66
star
87

cliapp

Rich Command Line Applications
R
62
star
88

pkgbuild

Find tools needed to build R packages
R
61
star
89

generics

Common generic methods
R
60
star
90

webfakes

Fake web apps for HTTP testing R packages
C
60
star
91

diffviewer

HTML widget to visually compare files
JavaScript
55
star
92

pkgload

Simulate installing and loading a package
R
55
star
93

liteq

Serverless R message queue using SQLite
R
55
star
94

cachem

Key-value caches for R
R
54
star
95

carrier

Create standalone functions for remote execution
R
49
star
96

brio

Basic R Input Output
R
49
star
97

jose

Javascript Object Signing and Encryption for R
R
47
star
98

urlchecker

Run CRAN URL checks from older versions of R
R
46
star
99

pkgconfig

Private configuration for R packages
R
40
star
100

filelock

Cross platform file locking in R
R
39
star