docs/source/cpp/csv.rst

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.. to you under the Apache License, Version 2.0 (the
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..   http://www.apache.org/licenses/LICENSE-2.0

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.. default-domain:: cpp
.. highlight:: cpp

.. cpp:namespace:: arrow::csv

=================
Reading CSV files
=================

Arrow provides a fast CSV reader allowing ingestion of external data
as Arrow tables.

.. seealso::
   :ref:`CSV reader API reference <cpp-api-csv>`.

Basic usage
===========

A CSV file is read from a :class:`~arrow::io::InputStream`.

.. code-block:: cpp

   #include "arrow/csv/api.h"

   {
      // ...
      arrow::io::IOContext io_context = arrow::io::default_io_context();
      std::shared_ptr<arrow::io::InputStream> input = ...;

      auto read_options = arrow::csv::ReadOptions::Defaults();
      auto parse_options = arrow::csv::ParseOptions::Defaults();
      auto convert_options = arrow::csv::ConvertOptions::Defaults();

      // Instantiate TableReader from input stream and options
      auto maybe_reader =
        arrow::csv::TableReader::Make(io_context,
                                      input,
                                      read_options,
                                      parse_options,
                                      convert_options);
      if (!maybe_reader.ok()) {
         // Handle TableReader instantiation error...
      }
      std::shared_ptr<arrow::csv::TableReader> reader = *maybe_reader;

      // Read table from CSV file
      auto maybe_table = reader->Read();
      if (!maybe_table.ok()) {
         // Handle CSV read error
         // (for example a CSV syntax error or failed type conversion)
      }
      std::shared_ptr<arrow::Table> table = *maybe_table;
   }

Column names
============

There are three possible ways to infer column names from the CSV file:

* By default, the column names are read from the first row in the CSV file
* If :member:`ReadOptions::column_names` is set, it forces the column
  names in the table to these values (the first row in the CSV file is
  read as data)
* If :member:`ReadOptions::autogenerate_column_names` is true, column names
  will be autogenerated with the pattern "f0", "f1"... (the first row in the
  CSV file is read as data)

Column selection
================

By default, Arrow reads all columns in the CSV file.  You can narrow the
selection of columns with the :member:`ConvertOptions::include_columns`
option.  If some columns in :member:`ConvertOptions::include_columns`
are missing from the CSV file, an error will be emitted unless
:member:`ConvertOptions::include_missing_columns` is true, in which case
the missing columns are assumed to contain all-null values.

Interaction with column names
-----------------------------

If both :member:`ReadOptions::column_names` and
:member:`ConvertOptions::include_columns` are specified,
the :member:`ReadOptions::column_names` are assumed to map to CSV columns,
and :member:`ConvertOptions::include_columns` is a subset of those column
names that will part of the Arrow Table.

Data types
==========

By default, the CSV reader infers the most appropriate data type for each
column.  Type inference considers the following data types, in order:

* Null
* Int64
* Boolean
* Date32
* Timestamp (with seconds unit)
* Float64
* Dictionary<String> (if :member:`ConvertOptions::auto_dict_encode` is true)
* Dictionary<Binary> (if :member:`ConvertOptions::auto_dict_encode` is true)
* String
* Binary

It is possible to override type inference for select columns by setting
the :member:`ConvertOptions::column_types` option.  Explicit data types
can be chosen from the following list:

* Null
* All Integer types
* Float32 and Float64
* Decimal128
* Boolean
* Date32 and Date64
* Timestamp
* Binary and Large Binary
* String and Large String (with optional UTF8 input validation)
* Fixed-Size Binary
* Dictionary with index type Int32 and value type one of the following:
  Binary, String, LargeBinary, LargeString,  Int32, UInt32, Int64, UInt64,
  Float32, Float64, Decimal128

Other data types do not support conversion from CSV values and will error out.

Dictionary inference
--------------------

If type inference is enabled and :member:`ConvertOptions::auto_dict_encode`
is true, the CSV reader first tries to convert string-like columns to a
dictionary-encoded string-like array.  It switches to a plain string-like
array when the threshold in :member:`ConvertOptions::auto_dict_max_cardinality`
is reached.

Nulls
-----

Null values are recognized from the spellings stored in
:member:`ConvertOptions::null_values`.  The :func:`ConvertOptions::Defaults`
factory method will initialize a number of conventional null spellings such
as ``N/A``.

Character encoding
------------------

CSV files are expected to be encoded in UTF8.  However, non-UTF8 data
is accepted for Binary columns.

Performance
===========

By default, the CSV reader will parallelize reads in order to exploit all
CPU cores on your machine.  You can change this setting in
:member:`ReadOptions::use_threads`.  A reasonable expectation is at least
100 MB/s per core on a performant desktop or laptop computer (measured in
source CSV bytes, not target Arrow data bytes).