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typetracer is an R package to trace function parameter
types. The R language includes a
set of defined types, but the language itself is “absurdly
dynamic”[1], and lacks any way to specify which types are expected
by any expression. The typetracer package enables code to
be traced to extract detailed information on the properties of
parameters passed to R functions. typetracer can trace
individual functions or entire packages, as demonstrated below.
The stable version of the package can be installed with one of the following commands:
# Stable version from CRAN:
install.packages ("typetrace")
# Current development version from r-universe:
install.packages (
"typetracer",
repos = c ("https://mpadge.r-universe.dev", "https://cloud.r-project.org")
)Alternatively, for those who prefer to use other source code platforms, the package can also be installed by running any one of the following lines:
remotes::install_git ("https://git.sr.ht/~mpadge/dodgr")
remotes::install_git ("https://codeberg.org/UrbanAnalyst/dodgr")
remotes::install_bitbucket ("UrbanAnalyst/dodgr")
remotes::install_gitlab ("UrbanAnalyst/dodgr")The package can then loaded for use by calling
library:
library (typetracer)typetracer works by “injecting” tracing code into the
body of a function using the
inject_tracer() function. Locally-defined functions can
be traced by simply passing the functions directly to
inject_tracer(). The following example includes four
parameters, including ... to allow passing of additional
and entirely arbitrary parameter types and values.
f <- function (x, y, z, ...) {
x * x + y * y
}
inject_tracer (f)After injecting the typetracer code, calls to the
function, f, will “trace” each parameter of the function,
by capturing both unevaluated and evaluated representations at the point
at which the function is first called. These values can be accessed with
the
load_traces function, which returns a
data.frame object (in tibble format) with
one row for each parameter from each function call.
val <- f (
x = 1:2,
y = 3:4 + 0.,
a = "blah",
b = list (a = 1, b = "b"),
f = a ~ b
)
x <- load_traces ()
x
## # A tibble: 7 × 12
## trace_number fn_name fn_call_hash par_name class typeof mode storage_mode
## <int> <chr> <chr> <chr> <I<list>> <chr> <chr> <chr>
## 1 0 f uDgEbied x <chr [1]> integ… nume… integer
## 2 0 f uDgEbied y <chr [1]> double nume… double
## 3 0 f uDgEbied z <chr [1]> NULL NULL NULL
## 4 0 f uDgEbied ... <chr [1]> NULL NULL NULL
## 5 0 f uDgEbied a <chr [1]> chara… char… character
## 6 0 f uDgEbied b <chr [1]> list list list
## 7 0 f uDgEbied f <chr [1]> langu… call language
## # ℹ 4 more variables: length <int>, formal <named list>, uneval <I<list>>,
## # eval <I<list>>Each row of the result returned by load_traces()
represents one parameter passed to one function call. Each function call
itself represents a single “trace” as enumerated by the
trace_number column, and also uniquely identified by an
arbitrary function call hash (fn_call_hash). The remaining
columns of the trace data define the properties of each parameter,
p, as:
par_name: Name of parameter.class: List of classes of parameter.typeof: Result of typeof(p).mode: Result of mode(p).storage_mode: Result of
storage.mode(p).length: Result of length(p).formal: Result of formals(f)[["p"]], as
named list item with default value where specified.uneval: Parameters as passed to the function call prior
to evaluation within function environment.eval: Evaluated version of parameter.The results above show that all parameters of the function,
f(), were successfully traced, including the additional
parameters, a, b, and f, passed
as part of the ... argument. Such additional parameters can
be identified through having a "formal" entry of
NULL, indicating that they are not part of the formal
arguments to the function.
That result can also be used to demonstrate the difference between the unevaluated and evaluated forms of parameters:
x$uneval [x$par_name %in% c ("b", "f")]
## $b
## [1] "list(a = 1, b = \"b\")"
##
## $f
## [1] "a ~ b"
x$eval [x$par_name %in% c ("b", "f")]
## $b
## $b$a
## [1] 1
##
## $b$b
## [1] "b"
##
##
## $f
## a ~ b
## <environment: 0x560b15656ca8>Unevaluated parameters are generally converted to equivalent character expressions.
The typeof, mode, and
storage_mode columns are similar, yet may hold distinct
information for certain types of parameters. The conditions under which
these values differ are complex, and depend among other things on the
version of R itself. typeof alone should generally provide
sufficient information, although this list of differences
may provide further insight into whether the other columns may provide
useful additional information.
Traces themselves are saved in the temporary directory of the current
R session, and the
load_traces() function simply loads all traces created
in that session. The
function clear_traces() removes all traces, so that load_traces()
will only load new traces produced after that time.
It is important after applying the
inject_tracer() function to restore the functions back
to their original form through calling the
obverse uninject_tracer() function. For the function,
r, above, this simply requires,
uninject_tracer (f)
## [1] TRUEAll traces can also be removed with this functions:
clear_traces ()Because typetracer modifies the internal code of
functions as defined within a current R session, we strongly recommend
restarting your R session after using typetracer, to ensure
expected function behaviour is restored.
R has extensive support for list structures, notably including all
data.frame-like objects in which each column is actually a
list item. typetracer also offers the ability to recurse
into the list structures of individual parameters, to recursively trace
the properties of each list item. To do this, the traces themselves have
to be injected with the additional parameter,
trace_lists = TRUE.
The final call above included an additional parameter passed as a list. The following code re-injects a tracer with the ability to traverse into list structures:
inject_tracer (f, trace_lists = TRUE)
val <- f (
x = 1:2,
y = 3:4 + 0.,
a = "blah",
b = list (a = 1, b = "b"),
f = a ~ b
)
x_lists <- load_traces ()
print (x_lists)
## # A tibble: 9 × 12
## trace_number fn_name fn_call_hash par_name class typeof mode storage_mode
## <int> <chr> <chr> <chr> <I<list>> <chr> <chr> <chr>
## 1 0 f LzZIbYvx x <chr [1]> integ… nume… integer
## 2 0 f LzZIbYvx y <chr [1]> double nume… double
## 3 0 f LzZIbYvx z <chr [1]> NULL NULL NULL
## 4 0 f LzZIbYvx ... <chr [1]> NULL NULL NULL
## 5 0 f LzZIbYvx a <chr [1]> chara… char… character
## 6 0 f LzZIbYvx b <chr [1]> list list list
## 7 0 f LzZIbYvx f <chr [1]> langu… call language
## 8 0 f LzZIbYvx b$a <chr [1]> double nume… double
## 9 0 f LzZIbYvx b$b <chr [1]> chara… char… character
## # ℹ 4 more variables: length <int>, formal <named list>, uneval <I<list>>,
## # eval <I<list>>And that result now has 9 rows, or 2 more than the previous example,
reflecting the two items passed as a list to the parameter,
b. List-parameter items are identifiable in typetracer
output through the “dollar-notation” in the par_name field.
The final two values in the above table are b$a and
b$b, representing the two elements of the list passed as
the parameter, b.
This section presents a more complex example tracing all function
calls from the
rematch package, chosen because it has less code than
almost any other package on CRAN. The following single line traces
function calls in all examples for the nominated package. The
trace_package() function automatically injects tracing
code into every function within the package, so there is no need to
explicitly call the
inject_tracer() function.
(This function also includes a trace_lists parameter, as
demonstrated above, with a default of FALSE to not recurse
into tracing list structures.)
res <- trace_package ("rematch")
res
## # A tibble: 8 × 14
## trace_number source_file_name fn_name fn_call_hash call_env par_name class
## <int> <chr> <chr> <chr> <chr> <chr> <I<list>
## 1 0 man/re_match.Rd re_match UJfHAIRp <NA> pattern <chr>
## 2 0 man/re_match.Rd re_match UJfHAIRp <NA> text <chr>
## 3 0 man/re_match.Rd re_match UJfHAIRp <NA> perl <chr>
## 4 0 man/re_match.Rd re_match UJfHAIRp <NA> ... <chr>
## 5 1 man/re_match.Rd re_match Anyflkea <NA> pattern <chr>
## 6 1 man/re_match.Rd re_match Anyflkea <NA> text <chr>
## 7 1 man/re_match.Rd re_match Anyflkea <NA> perl <chr>
## 8 1 man/re_match.Rd re_match Anyflkea <NA> ... <chr>
## # ℹ 7 more variables: typeof <chr>, mode <chr>, storage_mode <chr>,
## # length <int>, formal <named list>, uneval <I<list>>, eval <I<list>>The data.frame returned by the
trace_package() function includes three more columns than
the result directly returned by load_traces(). These
columns identify the sources and calling environments of each function
call being traces. The “call_env” column identifies the calling
environment which generated each trace, while “source_file_name”
identifies the file.
unique (res$call_env)
## [1] NA
unique (res$source_file_name)
## [1] "man/re_match.Rd"Although the “call_env” columns contains no useful information for
that package, it includes information on the full environment in which
each function was called. These “environments” include such things as
tryCatch calls expected to generate errors, or the various
expect_ functions of the “testthat” package. The above
case of racing an installed package generally only extracts traces from
example code, as documented in help, or .Rd, files. These
are identified by the “rd_” prefix on the “source_file_name”, with the
rematch package including only one .Rd
file.
The
trace_package() function also includes an additional
parameter, types, which defaults to
c ("examples", "tests"), so that traces are also by default
generated for all tests included with local source packages (or for
packages installed to include test files). The “source” column for test
files identifies the names of each test, prefixed with “test_”.
The other two additional columns of “trace_file” and “call_env” respectively specify the source file and calling environment of each trace. These will generally only retain information from test files, in which case the source file will generally be the file name identified in the “source” column, and “call_env” will specify the environment from which that function call originated. Environments may, for example, include various types of expectation from the “testthat” package. These calling environments are useful to discern whether, for example, a call was made with an expectation that it should error.
The
trace_package() function also accepts an argument,
functions, specifying which functions from a package should
be traced. For example,
x <- trace_package ("stats", functions = "sd")
## # A tibble: 2 × 16
## trace_number trace_source fn_name fn_call_hash trace_file call_env par_name
## <int> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 0 examples sd EzasZOKV <NA> <NA> x
## 2 0 examples sd EzasZOKV <NA> <NA> na.rm
## # ℹ 9 more variables: class <I<list>>, typeof <chr>, mode <chr>,
## # storage_mode <chr>, length <int>, formal <I<list>>, uneval <I<list>>,
## # eval <I<list>>, source <chr>This package extends on concepts previously developed in other R packages, notably including:
typed
package by @moodymudskippercontractr
package by @aviralg & @fikovnikPlus work explained in detail in this footnote:
[1] Alexi Turcotte & Jan Vitek (2019), Towards a Type System for R, ICOOOLPS ’19: Proceedings of the 14th Workshop on Implementation, Compilation, Optimization of Object-Oriented Languages, Programs and Systems. Article No. 4, Pages 1–5, https://doi.org/10.1145/3340670.3342426
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.