Interpolate strings with SQL escaping

SQL databases often have custom quotation syntax for identifiers and strings which make writing SQL queries error prone and cumbersome to do. glue_sql() and glue_data_sql() are analogs to glue() and glue_data() which handle the SQL quoting. glue_sql_collapse() can be used to collapse DBI::SQL() objects.

They automatically quote character results, quote identifiers if the glue expression is surrounded by backticks '`' and do not quote non-characters such as numbers. If numeric data is stored in a character column (which should be quoted) pass the data to glue_sql() as a character.

Returning the result with DBI::SQL() will suppress quoting if desired for a given value.

Note parameterized queries are generally the safest and most efficient way to pass user defined values in a query, however not every database driver supports them.

If you place a * at the end of a glue expression the values will be collapsed with commas, or if there are no values, produce NULL. This is useful for (e.g.) the SQL IN Operator.

Usage

glue_sql(
  ...,
  .con,
  .sep = "",
  .envir = parent.frame(),
  .open = "{",
  .close = "}",
  .na = DBI::SQL("NULL"),
  .null = character(),
  .comment = "#",
  .literal = FALSE,
  .trim = TRUE
)

glue_data_sql(
  .x,
  ...,
  .con,
  .sep = "",
  .envir = parent.frame(),
  .open = "{",
  .close = "}",
  .na = DBI::SQL("NULL"),
  .null = character(),
  .comment = "#",
  .literal = FALSE,
  .trim = TRUE
)

Arguments

...

[expressions]
Unnamed arguments are taken to be expression string(s) to format. Multiple inputs are concatenated together before formatting. Named arguments are taken to be temporary variables available for substitution.

For glue_data(), elements in ... override the values in .x.

.con

[DBIConnection]: A DBI connection object obtained from DBI::dbConnect().

.sep

[character(1): ‘""’]
Separator used to separate elements.

.envir

[environment: parent.frame()]
Environment to evaluate each expression in. Expressions are evaluated from left to right. If .x is an environment, the expressions are evaluated in that environment and .envir is ignored. If NULL is passed, it is equivalent to emptyenv().

.open

[character(1): ‘\{’]
The opening delimiter. Doubling the full delimiter escapes it.

.close

[character(1): ‘\}’]
The closing delimiter. Doubling the full delimiter escapes it.

.na

[character(1): DBI::SQL("NULL")]
Value to replace NA values with. If NULL missing values are propagated, that is an NA result will cause NA output. Otherwise the value is replaced by the value of .na.

.null

[character(1): ‘character()’]
Value to replace NULL values with. If character() whole output is character(). If NULL all NULL values are dropped (as in paste0()). Otherwise the value is replaced by the value of .null.

.comment

[character(1): ‘#’]
Value to use as the comment character.

.literal

[boolean(1): ‘FALSE’]
Whether to treat single or double quotes, backticks, and comments as regular characters (vs. as syntactic elements), when parsing the expression string. Setting .literal = TRUE probably only makes sense in combination with a custom .transformer, as is the case with glue_col(). Regard this argument (especially, its name) as experimental.

.trim

[logical(1): ‘TRUE’]
Whether to trim the input template with trim() or not.

.x

[listish]
An environment, list, or data frame used to lookup values.

Value

A DBI::SQL() object with the given query.

Examples

con <- DBI::dbConnect(RSQLite::SQLite(), ":memory:")
iris2 <- iris
colnames(iris2) <- gsub("[.]", "_", tolower(colnames(iris)))
DBI::dbWriteTable(con, "iris", iris2)
var <- "sepal_width"
tbl <- "iris"
num <- 2
val <- "setosa"
glue_sql("
  SELECT {`var`}
  FROM {`tbl`}
  WHERE {`tbl`}.sepal_length > {num}
    AND {`tbl`}.species = {val}
  ", .con = con)
#> <SQL> SELECT `sepal_width`
#> FROM `iris`
#> WHERE `iris`.sepal_length > 2
#>   AND `iris`.species = 'setosa'

# If sepal_length is store on the database as a character explicitly convert
# the data to character to quote appropriately.
glue_sql("
  SELECT {`var`}
  FROM {`tbl`}
  WHERE {`tbl`}.sepal_length > {as.character(num)}
    AND {`tbl`}.species = {val}
  ", .con = con)
#> <SQL> SELECT `sepal_width`
#> FROM `iris`
#> WHERE `iris`.sepal_length > '2'
#>   AND `iris`.species = 'setosa'


# `glue_sql()` can be used in conjuction with parameterized queries using
# `DBI::dbBind()` to provide protection for SQL Injection attacks
 sql <- glue_sql("
    SELECT {`var`}
    FROM {`tbl`}
    WHERE {`tbl`}.sepal_length > ?
  ", .con = con)
query <- DBI::dbSendQuery(con, sql)
DBI::dbBind(query, list(num))
DBI::dbFetch(query, n = 4)
#>   sepal_width
#> 1         3.5
#> 2         3.0
#> 3         3.2
#> 4         3.1
DBI::dbClearResult(query)

# `glue_sql()` can be used to build up more complex queries with
# interchangeable sub queries. It returns `DBI::SQL()` objects which are
# properly protected from quoting.
sub_query <- glue_sql("
  SELECT *
  FROM {`tbl`}
  ", .con = con)

glue_sql("
  SELECT s.{`var`}
  FROM ({sub_query}) AS s
  ", .con = con)
#> <SQL> SELECT s.`sepal_width`
#> FROM (SELECT *
#> FROM `iris`) AS s

# If you want to input multiple values for use in SQL IN statements put `*`
# at the end of the value and the values will be collapsed and quoted appropriately.
glue_sql("SELECT * FROM {`tbl`} WHERE sepal_length IN ({vals*})",
  vals = 1, .con = con)
#> <SQL> SELECT * FROM `iris` WHERE sepal_length IN (1)

glue_sql("SELECT * FROM {`tbl`} WHERE sepal_length IN ({vals*})",
  vals = 1:5, .con = con)
#> <SQL> SELECT * FROM `iris` WHERE sepal_length IN (1, 2, 3, 4, 5)

glue_sql("SELECT * FROM {`tbl`} WHERE species IN ({vals*})",
  vals = "setosa", .con = con)
#> <SQL> SELECT * FROM `iris` WHERE species IN ('setosa')

glue_sql("SELECT * FROM {`tbl`} WHERE species IN ({vals*})",
  vals = c("setosa", "versicolor"), .con = con)
#> <SQL> SELECT * FROM `iris` WHERE species IN ('setosa', 'versicolor')

# If you need to reference variables from multiple tables use `DBI::Id()`.
# Here we create a new table of nicknames, join the two tables together and
# select columns from both tables. Using `DBI::Id()` and the special
# `glue_sql()` syntax ensures all the table and column identifiers are quoted
# appropriately.

iris_db <- "iris"
nicknames_db <- "nicknames"

nicknames <- data.frame(
  species = c("setosa", "versicolor", "virginica"),
  nickname = c("Beachhead Iris", "Harlequin Blueflag", "Virginia Iris"),
  stringsAsFactors = FALSE
)

DBI::dbWriteTable(con, nicknames_db, nicknames)

cols <- list(
  DBI::Id(iris_db, "sepal_length"),
  DBI::Id(iris_db, "sepal_width"),
  DBI::Id(nicknames_db, "nickname")
)

iris_species <- DBI::Id(iris_db, "species")
nicknames_species <- DBI::Id(nicknames_db, "species")

query <- glue_sql("
  SELECT {`cols`*}
  FROM {`iris_db`}
  JOIN {`nicknames_db`}
  ON {`iris_species`}={`nicknames_species`}",
  .con = con
)
query
#> <SQL> SELECT `iris`.`sepal_length`, `iris`.`sepal_width`, `nicknames`.`nickname`
#> FROM `iris`
#> JOIN `nicknames`
#> ON `iris`.`species`=`nicknames`.`species`

DBI::dbGetQuery(con, query, n = 5)
#>   sepal_length sepal_width       nickname
#> 1          5.1         3.5 Beachhead Iris
#> 2          4.9         3.0 Beachhead Iris
#> 3          4.7         3.2 Beachhead Iris
#> 4          4.6         3.1 Beachhead Iris
#> 5          5.0         3.6 Beachhead Iris

DBI::dbDisconnect(con)

Interpolate strings with SQL escaping

Usage

Arguments

Value

See also

Examples