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stringr

repository·main·Indexed 20 days ago

https://github.com/tidyverse/stringr

A tidyverse package providing a cohesive and consistent set of functions for string manipulation in R. Built on top of the high-performance stringi package and the ICU C library, stringr uses a consistent str_ prefix for its functions and takes a vector of strings as the first argument to ensure compatibility with the R pipe operator.

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What's inside stringr

  1. Overview of stringr

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    stringr provides a cohesive set of functions for string manipulation in R. It is built on top of the stringi package, which uses the ICU C library for high-performance and correct string operations. While stringr focuses on the most commonly used functions, stringi provides a more comprehensive, exhaustive set of tools. Because they share similar conventions, skills learned in stringr are easily transferable to stringi.

  2. Basic string manipulation with stringr

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    All stringr functions follow a consistent pattern: they start with the str_ prefix and take a vector of strings as the first argument. This makes them highly compatible with the R pipe operator (%>%).

    x <- c("why", "video", "cross", "extra", "deal", "authority")
str_length(x) 
#> [1] 3 5 5 5 4 9

str_c(x, collapse = ", ")
#> [1] "why, video, cross, extra, deal, authority"

str_sub(x, 1, 2)
#> [1] "wh" "vi" "cr" "ex" "de" "au"

  3. Pattern matching engines in stringr

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    While regular expressions are the default, stringr supports three other pattern matching engines to control how patterns are interpreted:

    • fixed(): Matches exact bytes.
    • coll(): Matches human letters (collation).
    • boundary(): Matches boundaries.

  4. Advantages of stringr over base R

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    Compared to base R string operations, stringr offers several improvements:

    • Consistency: Functions use consistent names and argument orders. The first argument is always the vector of strings, which facilitates piping.
    • Simplicity: It eliminates many complex options that are rarely used, focusing on the 95% use case.
    • Predictability: Outputs are designed to be easily used as inputs (e.g., missing inputs result in missing outputs, and zero-length inputs result in zero-length outputs).
    # Example of piping with stringr
letters %>%
  .[1:10] %>%
  str_pad(3, "right") %>%
  str_c(letters[2:11])
#>  [1] "a  b" "b  c" "c  d" "d  e" "e  f" "f  g" "g  h" "h  i" "i  j" "j  k"

  5. Install the RegExplain RStudio Addin

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    The RegExplain RStudio addin provides an interactive interface for building regular expressions and testing stringr functions. You can install it using devtools from GitHub.

    # install.packages("devtools")
devtools::install_github("gadenbuie/regexplain")

  6. Install stringr

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    You can install stringr either as part of the full tidyverse suite or as a standalone package.

    # The easiest way to get stringr is to install the whole tidyverse:
install.packages("tidyverse")

# Alternatively, install just stringr:
install.packages("stringr")

  7. Resolve `stringr::str_replace_all` length validation errors in latex2exp

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    In the package latex2exp (0.9.6), tests are failing during str_replace_all calls. The backtrace indicates issues within stringr:::check_lengths during pattern replacement operations involving LaTeX escape sequences.

    Error context:

    stringr::str_replace_all(., "([^\\\\\\]?)\\\\s", "\\1\\@SPACE2{}")
# ... followed by internal check_lengths calls

    Review the patterns and replacement strings used in latex2exp to ensure they comply with stringr length and type requirements.

  8. Fix `stringr::str_replace_all` replacement function return type in NMsim

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    In the package NMsim (v0.2.5), a test failure occurs because the replacement function passed to stringr::str_replace_all returns a double vector instead of a character vector. To fix this, ensure the function used as the replacement argument returns character strings.

    Error context:

    Error in `stringr::str_replace_all(mod$THETA, "\\d+\\.\\d+", function(x) round(as.numeric(x), 
    digits = 3))`: `replacement` function must return a character vector, not a double
vector.
    # Incorrect usage causing error:
stringr::str_replace_all(mod$THETA, "\\d+\\.\\d+", function(x) round(as.numeric(x), digits = 3))

# Correct usage (ensure character return):
stringr::str_replace_all(mod$THETA, "\\d+\\.\\d+", function(x) as.character(round(as.numeric(x), digits = 3)))

  9. Troubleshoot `str_replace_all()` replacement function errors

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    When using stringr::str_replace_all() with a function as the replacement argument, the function must be able to handle a character vector of any length and return a vector of the same length as the input.

    Common errors include:

    • Length Mismatch: The replacement function returns a vector of length 1 when the input vector has a different length (e.g., length 47).
    • Non-vectorized logic: The replacement function uses conditional logic (like if (condition)) that fails when the input is a vector of length > 1.
    • NA patterns: The pattern argument passed to str_replace() cannot contain NA values.
    # Example of a failing pattern: replacement function returning wrong length
salt_replace(x, replacement_shaker$capitalization, p = 0.5, rep_p = 0.2)
# Error: `replacement` function must return a vector the same length as the input (47), not length 1.

# Example of a failing pattern: non-vectorized replacement function
stringr::str_replace_all(eqn, pattern = pattern, replacement = reformat_scientific)
# Error: Failed to apply `replacement` function. It must accept a character vector of any length.

  10. Fix `stringr::str_replace` pattern NA error in nrlR

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    In the package nrlR (v0.1.1), an error occurs during fetch_lineups because the pattern argument passed to stringr::str_replace contains NA values.

    Error context:

    Error in `stringr::str_replace()`:
! `pattern` can not contain NAs.

    Ensure that the pattern being passed to str_replace is a valid character string and does not contain NA.

    # The error occurs here:
stringr::str_replace(rvest::html_text2(home_node), home_role_full, "")
# Ensure 'home_role_full' is not NA

  11. Ensure `str_replace()` patterns do not contain NAs

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    When calling stringr::str_replace() or stringr::str_remove(), ensure that the pattern argument does not contain NA values. Passing an NA as a pattern will cause a runtime error during test execution or data processing.

    # Error context from zipangu:
# Caused by error in `str_replace()`:
# ! `pattern` can not contain NAs.

  12. Pattern matching verbs in stringr

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    Most string functions in stringr work with regular expressions. There are seven primary 'verbs' used to interact with patterns:

    • str_detect(x, pattern): Returns a logical vector indicating if a match exists.
    • str_count(x, pattern): Counts the number of pattern matches in each string.
    • str_subset(x, pattern): Extracts the elements of the vector that match the pattern.
    • str_locate(x, pattern): Returns the start and end positions of the matches.
    • str_extract(x, pattern): Extracts the actual text of the match.
    • str_match(x, pattern): Extracts parts of the match defined by capture groups (parentheses).
    • str_replace(x, pattern, replacement): Replaces matches with new text.
    • str_split(x, pattern): Splits a string into multiple pieces based on the pattern.
    x <- c("why", "video", "cross", "extra", "deal", "authority")

# Example: Extracting characters on either side of a vowel using capture groups
str_match(x, "(.)[aeiou](.)")
#>      [,1]  [,2] [,3] 
#> [1,] NA    NA   NA  
#> [2,] "vid" "v"  "d" 
#> [3,] "ros" "r"  "s" 
#> [4,] NA    NA   NA  
#> [5,] "dea" "d"  "a" 
#> [6,] "aut" "a"  "t"