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.. _table_io:
.. _io-unified:
High-level Unified File I/O
***************************
``astropy`` uses the :ref:`I/O Registry <io_registry>` to provide a unified interface
for reading and writing data in different formats. For many common cases this will
streamline the process of file I/O and reduce the need to learn the separate details of
all of the low-level I/O packages within ``astropy``.
.. toctree::
:maxdepth: 2
unified_image
unified_table
**Overview**
The fundamental idea for the unified interface is that each data container class such as
`~astropy.table.Table` or `~astropy.nddata.CCDData` has class methods ``read()``
and ``write()`` that can be used to read and write data.
The first positional argument to these methods specifies the input or output. In
general the input can be a file name, a file-like object or a URL. For some formats,
most notably the :ref:`table_io_ascii` formats, the input can also be a string or
list of strings representing the data. The output can be a file name or a file-like
object.
The file format is specified using the ``format`` keyword argument. This is required
unless the format can be uniquely determined from the file name or file content.
**Example**
The example below shows how to read a table in the specialized DAOphot format and write
it back to FITS format. Notice that FITS is a format where the interface recognizes the
format automatically from the file name, so the ``format`` argument is not needed.
.. doctest-skip::
>>> from astropy.table import Table
>>> t = Table.read('photometry.dat', format='ascii.daophot')
>>> t.write('photometry.fits')
Each file format is handled by a specific reader or writer, and each of those
functions will have its own set of arguments.
**Getting Help**
To get help on the available arguments for each format, use the ``help()`` method of the
appropriate ``read()`` or ``write()`` class method, e.g., `astropy.table.Table.read`.
In the examples below we do not show the long output:
.. doctest-skip::
>>> from astropy.table import Table
>>> from astropy.nddata import CCDData
>>> CCDData.read.help('fits')
>>> Table.read.help('ascii')
>>> Table.read.help('ascii.latex')
>>> Table.write.help('hdf5')
>>> Table.write.help('csv')
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