Mappings and Conversions Between R and JS Types
QuickJSR uses the respective C APIs of
R and QuickJS in order to pass values between
the two. This allows for increased efficiency in passing and returning
values (as no serialisation or de-serialisation is required) and also
allows for greater flexibility in working with R closures, functions,
and environments in JS code.
QuickJSR aims to broadly follow the conventions of
jsonlite in terms of how R types are converted to JS types
and vice-versa.
Primitive & Scalar Types
The following table outlines the basic mappings of primitive types between R and JS types:
| R Type | JS Type |
|---|---|
| NULL | null |
| logical | boolean |
| integer | number |
| double | number |
| character | string |
| date | date |
| POSIXct | date |
| factor | string |
Note that the handling of Date/POSIXct
types differs from jsonlite, where they are converted to
strings. In QuickJSR, they are treated directly as
Date objects in JS.
Container Types
The following table outlines the basic mappings of container types between R and JS types:
| R Type | JS Type |
|---|---|
| named list | object |
| unnamed list | array |
| vector | array |
| array | array |
| matrix | 2D number array |
| data.frame | array of objects |
Examples of the matrix and data.frame
conversions are shown below:
df <- data.frame(a = 1:3, b = c("x", "y", "z"))
cat(to_json(df))
#> [{"a":1,"b":"x"},{"a":2,"b":"y"},{"a":3,"b":"z"}]Typed Arrays
Use js_typed_array() when a raw, integer, or double
vector should cross the boundary as contiguous typed storage rather than
as an ordinary JavaScript array.
ctx <- JSContext$new()
ctx$source(code = paste(
"function typeName(x) { return x.constructor.name; }",
"function total(x) { return x.reduce((a, b) => a + b, 0); }"
))
values <- js_typed_array(as.double(1:1000))
ctx$call("typeName", values)
#> [1] "Float64Array"
ctx$call("total", values)
#> [1] 500500Raw vectors become Uint8Array, integer vectors become
Int32Array, and double vectors become
Float64Array. Integer vectors containing NA
are rejected because Int32Array has no missing-value
representation. Double NA and NaN values are
both treated as JavaScript NaN. On return, the
Int32Array value -2147483648 becomes R’s
NA_integer_ sentinel. JavaScript 64-bit BigInt arrays
return as doubles and can lose precision outside the exact integer range
of an R double.
JavaScript typed arrays are copied directly into matching R vector storage on return. Use a persistent reference when the value should remain in JavaScript across several operations, and materialise it only when R needs the result.
Missing Typed Values
Use js_masked_typed_array() when logical, integer, or
double values need contiguous typed storage without losing R missing
values. JavaScript receives a branded object containing
values, validity, and length.
ctx$source(code = paste(
"function fillMissing(x) {",
" x.values[1] = 20;",
" x.validity[1] = 1;",
" return x;",
"}"
))
masked <- js_masked_typed_array(c(10L, NA_integer_, 30L))
ctx$call("fillMissing", masked)
#> [1] 10 20 30Logical values use a Uint8Array, integers use an
Int32Array, and doubles use a Float64Array.
The validity mask is a Uint8Array with zero for missing and
one for valid. A double NA is masked, while an ordinary
NaN remains a valid Float64 value.
JavaScript may modify both buffers. Returning the branded object
reconstructs the corresponding R vector using their current contents.
The mask costs one byte per element, so js_typed_array()
remains preferable when missing-value metadata is unnecessary. Factors
and dates are excluded because their class semantics require more than
numeric storage and a validity mask.
Read-only R Vector Views
Use js_readonly_view() when JavaScript only needs to
read an R vector. View creation wraps and retains the R vector but does
not copy or convert its elements. Conversion happens one element at a
time as JavaScript reads indexed values.
ctx$source(code = paste(
"function endpoints(x) { return [x[0], x[x.length - 1]]; }",
"function viewTotal(x) { return x.reduce((a, b) => a + b, 0); }"
))
view <- js_readonly_view(as.double(1:1000))
ctx$call("endpoints", view)
#> [1] 1 1000
ctx$call("viewTotal", view)
#> [1] 500500Views are array-like rather than typed arrays. They have
length, indexed access, iteration, and inherited
Array methods. view.toArray(), spread syntax,
and Array.from(view) create an ordinary mutable JavaScript
array. Direct writes and deletes throw an error.
The JavaScript object retains the wrapper and vector for its full lifetime. Normal assignment in R still follows copy-on-write rules: changing an R binding can create a new vector while an existing JavaScript view continues to see the retained vector. Passing the view back to R returns that retained object directly.
Use a view when JavaScript reads a small part of a large vector or
when avoiding the initial transfer is important. Use
js_typed_array() when JavaScript will scan the vector
repeatedly, needs typed-array APIs, or needs a mutable independent
copy.
Mutable R Vector Views
Use js_mutable_view() when JavaScript needs repeated,
sparse mutation of a vector and R needs to observe those changes without
a full return conversion. The wrapper owns an independent R copy, so the
input binding is never changed.
ctx$source(code = paste(
"function updateEndpoints(x) {",
" x[0] += 1;",
" x[x.length - 1] += 1;",
" return x;",
"}"
))
original <- as.double(1:1000)
view <- js_mutable_view(original)
ctx$call("updateEndpoints", view)
#> $value
#> [1] 2 2 3 4 5 6 7 8 9 10 11 12 13 14
#> [15] 15 16 17 18 19 20 21 22 23 24 25 26 27 28
#> [29] 29 30 31 32 33 34 35 36 37 38 39 40 41 42
#> [43] 43 44 45 46 47 48 49 50 51 52 53 54 55 56
#> [57] 57 58 59 60 61 62 63 64 65 66 67 68 69 70
#> [71] 71 72 73 74 75 76 77 78 79 80 81 82 83 84
#> [85] 85 86 87 88 89 90 91 92 93 94 95 96 97 98
#> [99] 99 100 101 102 103 104 105 106 107 108 109 110 111 112
#> [113] 113 114 115 116 117 118 119 120 121 122 123 124 125 126
#> [127] 127 128 129 130 131 132 133 134 135 136 137 138 139 140
#> [141] 141 142 143 144 145 146 147 148 149 150 151 152 153 154
#> [155] 155 156 157 158 159 160 161 162 163 164 165 166 167 168
#> [169] 169 170 171 172 173 174 175 176 177 178 179 180 181 182
#> [183] 183 184 185 186 187 188 189 190 191 192 193 194 195 196
#> [197] 197 198 199 200 201 202 203 204 205 206 207 208 209 210
#> [211] 211 212 213 214 215 216 217 218 219 220 221 222 223 224
#> [225] 225 226 227 228 229 230 231 232 233 234 235 236 237 238
#> [239] 239 240 241 242 243 244 245 246 247 248 249 250 251 252
#> [253] 253 254 255 256 257 258 259 260 261 262 263 264 265 266
#> [267] 267 268 269 270 271 272 273 274 275 276 277 278 279 280
#> [281] 281 282 283 284 285 286 287 288 289 290 291 292 293 294
#> [295] 295 296 297 298 299 300 301 302 303 304 305 306 307 308
#> [309] 309 310 311 312 313 314 315 316 317 318 319 320 321 322
#> [323] 323 324 325 326 327 328 329 330 331 332 333 334 335 336
#> [337] 337 338 339 340 341 342 343 344 345 346 347 348 349 350
#> [351] 351 352 353 354 355 356 357 358 359 360 361 362 363 364
#> [365] 365 366 367 368 369 370 371 372 373 374 375 376 377 378
#> [379] 379 380 381 382 383 384 385 386 387 388 389 390 391 392
#> [393] 393 394 395 396 397 398 399 400 401 402 403 404 405 406
#> [407] 407 408 409 410 411 412 413 414 415 416 417 418 419 420
#> [421] 421 422 423 424 425 426 427 428 429 430 431 432 433 434
#> [435] 435 436 437 438 439 440 441 442 443 444 445 446 447 448
#> [449] 449 450 451 452 453 454 455 456 457 458 459 460 461 462
#> [463] 463 464 465 466 467 468 469 470 471 472 473 474 475 476
#> [477] 477 478 479 480 481 482 483 484 485 486 487 488 489 490
#> [491] 491 492 493 494 495 496 497 498 499 500 501 502 503 504
#> [505] 505 506 507 508 509 510 511 512 513 514 515 516 517 518
#> [519] 519 520 521 522 523 524 525 526 527 528 529 530 531 532
#> [533] 533 534 535 536 537 538 539 540 541 542 543 544 545 546
#> [547] 547 548 549 550 551 552 553 554 555 556 557 558 559 560
#> [561] 561 562 563 564 565 566 567 568 569 570 571 572 573 574
#> [575] 575 576 577 578 579 580 581 582 583 584 585 586 587 588
#> [589] 589 590 591 592 593 594 595 596 597 598 599 600 601 602
#> [603] 603 604 605 606 607 608 609 610 611 612 613 614 615 616
#> [617] 617 618 619 620 621 622 623 624 625 626 627 628 629 630
#> [631] 631 632 633 634 635 636 637 638 639 640 641 642 643 644
#> [645] 645 646 647 648 649 650 651 652 653 654 655 656 657 658
#> [659] 659 660 661 662 663 664 665 666 667 668 669 670 671 672
#> [673] 673 674 675 676 677 678 679 680 681 682 683 684 685 686
#> [687] 687 688 689 690 691 692 693 694 695 696 697 698 699 700
#> [701] 701 702 703 704 705 706 707 708 709 710 711 712 713 714
#> [715] 715 716 717 718 719 720 721 722 723 724 725 726 727 728
#> [729] 729 730 731 732 733 734 735 736 737 738 739 740 741 742
#> [743] 743 744 745 746 747 748 749 750 751 752 753 754 755 756
#> [757] 757 758 759 760 761 762 763 764 765 766 767 768 769 770
#> [771] 771 772 773 774 775 776 777 778 779 780 781 782 783 784
#> [785] 785 786 787 788 789 790 791 792 793 794 795 796 797 798
#> [799] 799 800 801 802 803 804 805 806 807 808 809 810 811 812
#> [813] 813 814 815 816 817 818 819 820 821 822 823 824 825 826
#> [827] 827 828 829 830 831 832 833 834 835 836 837 838 839 840
#> [841] 841 842 843 844 845 846 847 848 849 850 851 852 853 854
#> [855] 855 856 857 858 859 860 861 862 863 864 865 866 867 868
#> [869] 869 870 871 872 873 874 875 876 877 878 879 880 881 882
#> [883] 883 884 885 886 887 888 889 890 891 892 893 894 895 896
#> [897] 897 898 899 900 901 902 903 904 905 906 907 908 909 910
#> [911] 911 912 913 914 915 916 917 918 919 920 921 922 923 924
#> [925] 925 926 927 928 929 930 931 932 933 934 935 936 937 938
#> [939] 939 940 941 942 943 944 945 946 947 948 949 950 951 952
#> [953] 953 954 955 956 957 958 959 960 961 962 963 964 965 966
#> [967] 967 968 969 970 971 972 973 974 975 976 977 978 979 980
#> [981] 981 982 983 984 985 986 987 988 989 990 991 992 993 994
#> [995] 995 996 997 998 999 1001
#>
#> attr(,"class")
#> [1] "quickjs_mutable_view"
view$value[c(1, length(view$value))]
#> [1] 2 1001
original[c(1, length(original))]
#> [1] 1 1000Creating the wrapper copies the vector once. Passing it to JavaScript is then constant time, and indexed reads and writes operate directly on its retained R storage. Returning the JavaScript view recovers the same wrapper without materialising an array.
Mutable views are fixed-length array-like objects rather than typed
arrays. Existing elements can be replaced directly or through methods
such as reverse(), sort(),
fill(), and copyWithin(). Adding properties,
growing the view, or deleting elements throws an error. Writes are type
checked, with null and undefined representing
R missing values except for raw vectors. Only unclassed raw, logical,
integer, double, and character vectors are accepted.
If R modifies view$value after JavaScript retains the
view, normal R copy-on-write can detach the R binding from the retained
storage. Complete R updates before retaining a mutable view, then treat
JavaScript as its writer.
Use a mutable view for sparse or repeated mutation shared with R. Use
js_typed_array() when JavaScript needs typed-array APIs or
will perform dense numeric work entirely inside JavaScript.
Column-oriented Data Frames
The compatibility conversion represents a data frame as an array of
row objects. Use js_columnar_data_frame() when JavaScript
can operate on whole columns instead.
df <- data.frame(
value = as.double(1:1000),
group = rep(c("a", "b"), 500)
)
ctx$source(code = paste(
"function columnTypes(x) {",
" return [x.value.constructor.name, x.group.constructor.name];",
"}"
))
ctx$call("columnTypes", js_columnar_data_frame(df))
#> [1] "Float64Array" "Array"Eligible numeric columns become typed arrays by default. Integer
columns with missing values, factors, and date-time columns remain
ordinary arrays so their missing-value and class semantics are
preserved. Set typed = FALSE to use ordinary arrays for
every column.
Note that the to_json() function operates by converting
R objects to their JS equivalents, and then calling
JSON.stringify() on the result. This allows you to explore
how different types are being converted to JS.
Working with R Environments
R environments are represented in JS as a custom class:
REnv. The REnv class simply wraps the pointer
to the R environment, and provides methods for getting and setting
values - this means that there is only a ‘cost’ for conversion when
values or accessed or updated.
Environment values can be accessed using either
env.value or env["value"] syntax:
ctx$source(code = 'function env_test(env) { return env.a + env["b"]; }')
env <- new.env()
env$a <- 1
env$b <- 2
ctx$call("env_test", env)
#> [1] 3Values in the environment can also be updated from JS code:
ctx$source(code = "function env_update(env) { env.a = 10; env.b = 20; }")
ctx$call("env_update", env)
#> NULL
env$a
#> [1] 10
env$b
#> [1] 20Accessing Package Namespaces & Functions
QuickJSR automatically adds a global object
R to each context, which can be used to access the
namespaces of installed packages - and subsequently extract and use
functions and objects from them.
qjs_eval('R.package("base").getwd()')
#> [1] "/home/runner/work/QuickJSR/QuickJSR/vignettes"