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+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/csv.R
+\name{read_delim_arrow}
+\alias{read_delim_arrow}
+\alias{read_csv_arrow}
+\alias{read_tsv_arrow}
+\title{Read a CSV or other delimited file with Arrow}
+\usage{
+read_delim_arrow(
+  file,
+  delim = ",",
+  quote = "\\"",
+  escape_double = TRUE,
+  escape_backslash = FALSE,
+  schema = NULL,
+  col_names = TRUE,
+  col_types = NULL,
+  col_select = NULL,
+  na = c("", "NA"),
+  quoted_na = TRUE,
+  skip_empty_rows = TRUE,
+  skip = 0L,
+  parse_options = NULL,
+  convert_options = NULL,
+  read_options = NULL,
+  as_data_frame = TRUE,
+  timestamp_parsers = NULL
+)
+
+read_csv_arrow(
+  file,
+  quote = "\\"",
+  escape_double = TRUE,
+  escape_backslash = FALSE,
+  schema = NULL,
+  col_names = TRUE,
+  col_types = NULL,
+  col_select = NULL,
+  na = c("", "NA"),
+  quoted_na = TRUE,
+  skip_empty_rows = TRUE,
+  skip = 0L,
+  parse_options = NULL,
+  convert_options = NULL,
+  read_options = NULL,
+  as_data_frame = TRUE,
+  timestamp_parsers = NULL
+)
+
+read_tsv_arrow(
+  file,
+  quote = "\\"",
+  escape_double = TRUE,
+  escape_backslash = FALSE,
+  schema = NULL,
+  col_names = TRUE,
+  col_types = NULL,
+  col_select = NULL,
+  na = c("", "NA"),
+  quoted_na = TRUE,
+  skip_empty_rows = TRUE,
+  skip = 0L,
+  parse_options = NULL,
+  convert_options = NULL,
+  read_options = NULL,
+  as_data_frame = TRUE,
+  timestamp_parsers = NULL
+)
+}
+\arguments{
+\item{file}{A character file name or URI, \code{raw} vector, an Arrow input stream,
+or a \code{FileSystem} with path (\code{SubTreeFileSystem}).
+If a file name, a memory-mapped Arrow \link{InputStream} will be opened and
+closed when finished; compression will be detected from the file extension
+and handled automatically. If an input stream is provided, it will be left
+open.}
+
+\item{delim}{Single character used to separate fields within a record.}
+
+\item{quote}{Single character used to quote strings.}
+
+\item{escape_double}{Does the file escape quotes by doubling them?
+i.e. If this option is \code{TRUE}, the value \verb{""""} represents
+a single quote, \verb{\\"}.}
+
+\item{escape_backslash}{Does the file use backslashes to escape special
+characters? This is more general than \code{escape_double} as backslashes
+can be used to escape the delimiter character, the quote character, or
+to add special characters like \verb{\\\\n}.}
+
+\item{schema}{\link{Schema} that describes the table. If provided, it will be
+used to satisfy both \code{col_names} and \code{col_types}.}
+
+\item{col_names}{If \code{TRUE}, the first row of the input will be used as the
+column names and will not be included in the data frame. If \code{FALSE}, column
+names will be generated by Arrow, starting with "f0", "f1", ..., "fN".
+Alternatively, you can specify a character vector of column names.}
+
+\item{col_types}{A compact string representation of the column types, or
+\code{NULL} (the default) to infer types from the data.}
+
+\item{col_select}{A character vector of column names to keep, as in the
+"select" argument to \code{data.table::fread()}, or a
+\link[tidyselect:vars_select]{tidy selection specification}
+of columns, as used in \code{dplyr::select()}.}
+
+\item{na}{A character vector of strings to interpret as missing values.}
+
+\item{quoted_na}{Should missing values inside quotes be treated as missing
+values (the default) or strings. (Note that this is different from the
+the Arrow C++ default for the corresponding convert option,
+\code{strings_can_be_null}.)}
+
+\item{skip_empty_rows}{Should blank rows be ignored altogether? If
+\code{TRUE}, blank rows will not be represented at all. If \code{FALSE}, they will be
+filled with missings.}
+
+\item{skip}{Number of lines to skip before reading data.}
+
+\item{parse_options}{see \link[=CsvReadOptions]{file reader options}.
+If given, this overrides any
+parsing options provided in other arguments (e.g. \code{delim}, \code{quote}, etc.).}
+
+\item{convert_options}{see \link[=CsvReadOptions]{file reader options}}
+
+\item{read_options}{see \link[=CsvReadOptions]{file reader options}}
+
+\item{as_data_frame}{Should the function return a \code{data.frame} (default) or
+an Arrow \link{Table}?}
+
+\item{timestamp_parsers}{User-defined timestamp parsers. If more than one
+parser is specified, the CSV conversion logic will try parsing values
+starting from the beginning of this vector. Possible values are:
+\itemize{
+\item \code{NULL}: the default, which uses the ISO-8601 parser
+\item a character vector of \link[base:strptime]{strptime} parse strings
+\item a list of \link{TimestampParser} objects
+}}
+}
+\value{
+A \code{data.frame}, or a Table if \code{as_data_frame = FALSE}.
+}
+\description{
+These functions uses the Arrow C++ CSV reader to read into a \code{data.frame}.
+Arrow C++ options have been mapped to argument names that follow those of
+\code{readr::read_delim()}, and \code{col_select} was inspired by \code{vroom::vroom()}.
+}
+\details{
+\code{read_csv_arrow()} and \code{read_tsv_arrow()} are wrappers around
+\code{read_delim_arrow()} that specify a delimiter.
+
+Note that not all \code{readr} options are currently implemented here. Please file
+an issue if you encounter one that \code{arrow} should support.
+
+If you need to control Arrow-specific reader parameters that don't have an
+equivalent in \code{readr::read_csv()}, you can either provide them in the
+\code{parse_options}, \code{convert_options}, or \code{read_options} arguments, or you can
+use \link{CsvTableReader} directly for lower-level access.
+}
+\section{Specifying column types and names}{
+
+
+By default, the CSV reader will infer the column names and data types from the file, but there
+are a few ways you can specify them directly.
+
+One way is to provide an Arrow \link{Schema} in the \code{schema} argument,
+which is an ordered map of column name to type.
+When provided, it satisfies both the \code{col_names} and \code{col_types} arguments.
+This is good if you know all of this information up front.
+
+You can also pass a \code{Schema} to the \code{col_types} argument. If you do this,
+column names will still be inferred from the file unless you also specify
+\code{col_names}. In either case, the column names in the \code{Schema} must match the
+data's column names, whether they are explicitly provided or inferred. That
+said, this \code{Schema} does not have to reference all columns: those omitted
+will have their types inferred.
+
+Alternatively, you can declare column types by providing the compact string representation
+that \code{readr} uses to the \code{col_types} argument. This means you provide a
+single string, one character per column, where the characters map to Arrow
+types analogously to the \code{readr} type mapping:
+\itemize{
+\item "c": \code{utf8()}
+\item "i": \code{int32()}
+\item "n": \code{float64()}
+\item "d": \code{float64()}
+\item "l": \code{bool()}
+\item "f": \code{dictionary()}
+\item "D": \code{date32()}
+\item "T": \code{timestamp()}
+\item "t": \code{time32()}
+\item "_": \code{null()}
+\item "-": \code{null()}
+\item "?": infer the type from the data
+}
+
+If you use the compact string representation for \code{col_types}, you must also
+specify \code{col_names}.
+
+Regardless of how types are specified, all columns with a \code{null()} type will
+be dropped.
+
+Note that if you are specifying column names, whether by \code{schema} or
+\code{col_names}, and the CSV file has a header row that would otherwise be used
+to idenfity column names, you'll need to add \code{skip = 1} to skip that row.
+}
+
+\examples{
+\dontshow{if (arrow_available()) (if (getRversion() >= "3.4") withAutoprint else force)(\{ # examplesIf}
+tf <- tempfile()
+on.exit(unlink(tf))
+write.csv(mtcars, file = tf)
+df <- read_csv_arrow(tf)
+dim(df)
+# Can select columns
+df <- read_csv_arrow(tf, col_select = starts_with("d"))
+\dontshow{\}) # examplesIf}
+}