Unified file read/write interface¶
Astropy provides a unified interface for reading and writing data in different formats. For many common cases this will simplify the process of file I/O and reduce the need to master the separate details of all the I/O packages within Astropy. This functionality is still in active development and the number of supported formats will be increasing. For details on the implementation see I/O Registry (astropy.io.registry).
Getting started with Table I/O¶
The Table
class includes two methods,
read()
and
write()
, that make it possible to read from
and write to files. A number of formats are automatically supported (see
Built-in table readers/writers) and new file formats and extensions can be
registered with the Table
class (see
I/O Registry (astropy.io.registry)).
To use this interface, first import the Table
class, then
simply call the Table
read()
method with the name of the file and
the file format, for instance 'ascii.daophot'
:
>>> from astropy.table import Table
>>> t = Table.read('photometry.dat', format='ascii.daophot')
It is possible to load tables directly from the Internet using URLs. For example,
download tables from Vizier catalogues in CDS format ('ascii.cds'
):
>>> t = Table.read("ftp://cdsarc.u-strasbg.fr/pub/cats/VII/253/snrs.dat",
... readme="ftp://cdsarc.u-strasbg.fr/pub/cats/VII/253/ReadMe",
... format="ascii.cds")
For certain file formats, the format can be automatically detected, for example from the filename extension:
>>> t = Table.read('table.tex')
Similarly, for writing, the format can be explicitly specified:
>>> t.write(filename, format='latex')
As for the read()
method, the format may
be automatically identified in some cases.
The underlying file handler will also automatically detect various
compressed data formats and transparently uncompress them as far as
supported by the Python installation (see
get_readable_fileobj()
).
Any additional arguments specified will depend on the format. For examples of this see the
section Built-in table readers/writers. This section also provides the full list of
choices for the format
argument.
Built-in table readers/writers¶
The full list of built-in readers and writers is shown in the table below:
Format | Read | Write | Auto-identify | Deprecated |
---|---|---|---|---|
aastex | Yes | Yes | No | Yes |
ascii | Yes | Yes | No | |
ascii.aastex | Yes | Yes | No | |
ascii.basic | Yes | Yes | No | |
ascii.cds | Yes | No | No | |
ascii.commented_header | Yes | Yes | No | |
ascii.daophot | Yes | No | No | |
ascii.ecsv | Yes | Yes | No | |
ascii.fixed_width | Yes | Yes | No | |
ascii.fixed_width_no_header | Yes | Yes | No | |
ascii.fixed_width_two_line | Yes | Yes | No | |
ascii.html | Yes | Yes | Yes | |
ascii.ipac | Yes | Yes | No | |
ascii.latex | Yes | Yes | Yes | |
ascii.no_header | Yes | Yes | No | |
ascii.rdb | Yes | Yes | Yes | |
ascii.sextractor | Yes | No | No | |
ascii.tab | Yes | Yes | No | |
ascii.csv | Yes | Yes | Yes | |
cds | Yes | No | No | Yes |
daophot | Yes | No | No | Yes |
fits | Yes | Yes | Yes | |
hdf5 | Yes | Yes | Yes | |
html | Yes | Yes | No | Yes |
ipac | Yes | Yes | No | Yes |
latex | Yes | Yes | No | Yes |
rdb | Yes | Yes | No | Yes |
votable | Yes | Yes | Yes |
Deprecated format names like aastex
will be removed in a future version.
Use the full name (e.g. ascii.aastex
) instead.
ASCII formats¶
The read()
and
write()
methods can be used to read and write formats
supported by astropy.io.ascii
.
Use format='ascii'
in order to interface to the generic
read()
and write()
functions from astropy.io.ascii
. When reading a table this means
that all supported ASCII table formats will be tried in order to successfully
parse the input. For example:
>>> t = Table.read('astropy/io/ascii/tests/t/latex1.tex', format='ascii')
>>> print(t)
cola colb colc
---- ---- ----
a 1 2
b 3 4
When writing a table with format='ascii'
the output is a basic
character-delimited file with a single header line containing the
column names.
All additional arguments are passed to the astropy.io.ascii
read()
and write()
functions. Further details are available in the sections on
Parameters for read() and Parameters for write(). For example, to change
column delimiter and the output format for the colc
column use:
>>> t.write(sys.stdout, format='ascii', delimiter='|', formats={'colc': '%0.2f'})
cola|colb|colc
a|1|2.00
b|3|4.00
A full list of the supported format
values and corresponding format types
for ASCII tables is given below. The Suffix
column indicates the filename
suffix where the format will be auto-detected, while the Write
column
indicates which support write functionality.
Format | Suffix | Write | Description |
---|---|---|---|
ascii |
Yes | ASCII table in any supported format (uses guessing) | |
ascii.aastex |
Yes | AASTex : AASTeX deluxetable used for AAS journals |
|
ascii.basic |
Yes | Basic : Basic table with custom delimiters |
|
ascii.cds |
Cds : CDS format table |
||
ascii.commented_header |
Yes | CommentedHeader : Column names in a commented line |
|
ascii.daophot |
Daophot : IRAF DAOphot format table |
||
ascii.fixed_width |
Yes | FixedWidth : Fixed width |
|
ascii.fixed_width_no_header |
Yes | FixedWidthNoHeader : Fixed width with no header |
|
ascii.fixed_width_two_line |
Yes | FixedWidthTwoLine : Fixed width with second header line |
|
ascii.ipac |
Yes | Ipac : IPAC format table |
|
ascii.html |
.html | Yes | HTML : HTML table |
ascii.latex |
.tex | Yes | Latex : LaTeX table |
ascii.no_header |
Yes | NoHeader : Basic table with no headers |
|
ascii.rdb |
.rdb | Yes | Rdb : Tab-separated with a type definition header line |
ascii.sextractor |
SExtractor : SExtractor format table |
||
ascii.tab |
Yes | Tab : Basic table with tab-separated values |
|
ascii.csv |
.csv | Yes | Csv : Basic table with comma-separated values |
ascii.ecsv |
.ecsv | Yes | Ecsv : Basic table with Enhanced CSV (supporting metadata) |
Note
When specifying a specific ASCII table format using the unified interface, the format name is
prefixed with ascii.
in order to identify the format as ASCII-based. Compare the
table above to the astropy.io.ascii
list of Supported formats. Therefore the following
are equivalent:
>>> dat = ascii.read('file.dat', format='daophot')
>>> dat = Table.read('file.dat', format='ascii.daophot')
For compatibility with astropy version 0.2 and earlier, the following format
values are also allowed in Table.read()
: daophot
, ipac
, html
, latex
, and rdb
.
FITS¶
Reading and writing tables in FITS format is
supported with format='fits'
. In most cases, existing FITS files should be
automatically identified as such based on the header of the file, but if not,
or if writing to disk, then the format should be explicitly specified.
Reading¶
If a FITS table file contains only a single table, then it can be read in with:
>>> from astropy.table import Table
>>> t = Table.read('data.fits')
If more than one table is present in the file, you can select the HDU as follows:
>>> t = Table.read('data.fits', hdu=3)
In this case if the hdu
argument is omitted then the first table found will be
read in and a warning will be emitted:
>>> t = Table.read('data.fits')
WARNING: hdu= was not specified but multiple tables are present, reading in first available table (hdu=1) [astropy.io.fits.connect]
Writing¶
To write a table t
to a new file:
>>> t.write('new_table.fits')
If the file already exists and you want to overwrite it, then set the
overwrite
keyword:
>>> t.write('existing_table.fits', overwrite=True)
At this time there is no support for appending an HDU to an existing file or writing multi-HDU files using the Table interface. Instead one can use the lower-level astropy.io.fits interface.
Keywords¶
The FITS keywords associated with an HDU table are represented in the meta
ordered dictionary attribute of a Table. After reading
a table one can view the available keywords in a readable format using:
>>> for key, value in t.meta.items():
... print('{0} = {1}'.format(key, value))
This does not include the “internal” FITS keywords that are required to specify
the FITS table properties (e.g. NAXIS
, TTYPE1
). HISTORY
and
COMMENT
keywords are treated specially and are returned as a list of
values.
Conversely, the following shows examples of setting user keyword values for a
table t
:
>>> t.meta['MY_KEYWD'] = 'my value'
>>> t.meta['COMMENT'] = ['First comment', 'Second comment', 'etc']
>>> t.write('my_table.fits', overwrite=True)
The keyword names (e.g. MY_KEYWD
) will be automatically capitalized prior
to writing.
At this time, the meta
attribute of the Table
class
is simply an ordered dictionary and does not fully represent the structure of a
FITS header (for example, keyword comments are dropped).
HDF5¶
Reading/writing from/to HDF5 files is
supported with format='hdf5'
(this requires h5py to be installed). However, the .hdf5
file extension is automatically recognized when writing files, and HDF5 files
are automatically identified (even with a different extension) when reading
in (using the first few bytes of the file to identify the format), so in most
cases you will not need to explicitly specify format='hdf5'
.
Since HDF5 files can contain multiple tables, the full path to the table
should be specified via the path=
argument when reading and writing.
For example, to read a table called data
from an HDF5 file named
observations.hdf5
, you can do:
>>> t = Table.read('observations.hdf5', path='data')
To read a table nested in a group in the HDF5 file, you can do:
>>> t = Table.read('observations.hdf5', path='group/data')
To write a table to a new file, the path should also be specified:
>>> t.write('new_file.hdf5', path='updated_data')
It is also possible to write a table to an existing file using append=True
:
>>> t.write('observations.hdf5', path='updated_data', append=True)
As with other formats, the overwrite=True
argument is supported for
overwriting existing files. To overwrite only a single table within an HDF5
file that has multiple datasets, use both the overwrite=True
and
append=True
arguments.
If the metadata of the table cannot be written directly to the HDF5 file
(e.g. dictionaries), or if you want to preserve the units and description
of tables and columns, use using serialize_meta=True
:
>>> t.write('observations.hdf5', path='updated_data', serialize_meta=True)
Finally, when writing to HDF5 files, the compression=
argument can be
used to ensure that the data is compressed on disk:
>>> t.write('new_file.hdf5', path='updated_data', compression=True)
VO Tables¶
Reading/writing from/to VO table
files is supported with format='votable'
. In most cases, existing VO
tables should be automatically identified as such based on the header of the
file, but if not, or if writing to disk, then the format should be explicitly
specified.
If a VO table file contains only a single table, then it can be read in with:
>>> t = Table.read('aj285677t3_votable.xml')
If more than one table is present in the file, an error will be raised,
unless the table ID is specified via the table_id=
argument:
>>> t = Table.read('catalog.xml')
Traceback (most recent call last):
...
ValueError: Multiple tables found: table id should be set via the table_id= argument. The available tables are twomass, spitzer
>>> t = Table.read('catalog.xml', table_id='twomass')
To write to a new file, the ID of the table should also be specified (unless
t.meta['ID']
is defined):
>>> t.write('new_catalog.xml', table_id='updated_table', format='votable')
When writing, the compression=True
argument can be used to force
compression of the data on disk, and the overwrite=True
argument can be
used to overwrite an existing file.