Note
The I/O registry is only meant to be used directly by users who want to define their own custom readers/writers. Users who want to find out more about what built-in formats are supported by Table by default should see Unified file read/write interface. No built-in formats are currently defined for NDData, but this will be added in future).
The I/O registry is a sub-module used to define the readers/writers available for the Table and NDData classes.
The following example demonstrates how to create a reader for the Table class. First, we can create a highly simplistic FITS reader which just reads the data as a structured array:
from astropy.table import Table
def fits_table_reader(filename, hdu=1):
from astropy.io import fits
data = fits.open(filename)[hdu].data
return Table(data)
and then register it:
from astropy.io import registry
registry.register_reader('fits', Table, fits_table_reader)
Reader functions can take any arguments except format (since this is reserved for read()) and should return an instance of the class specified as the second argument of register_reader (Table in the above case.)
We can then read in a FITS table with:
t = Table.read('catalog.fits', format='fits')
In practice, it would be nice to have the read method automatically identify that this file was a FITS file, so we can construct a function that can recognize FITS files, which we refer to here as an identifier function. An identifier function should take a first argument that should be a string which indicates whether the identifier is being called from read or write, and should then accept arbitrary number of positional and keyword arguments via *args and **kwargs, which are the arguments passed to Table.read. We can write a simplistic function that only looks at filenames (but in practice, this function could even look at the first few bytes of the file for example). The only requirement is that it return a boolean indicating whether the input matches that expected for the format:
def fits_identify(origin, *args, **kwargs):
return isinstance(args[0], basestring) and \
args[0].lower().split('.')[-1] in ['fits', 'fit']
Note
Identifier functions should be prepared for arbitrary input - in particular, the first argument may not be a filename or file object, so it should not assume that this is the case.
We then register this identifier function:
registry.register_identifier('fits', Table, fits_identify)
And we can then do:
t = Table.read('catalog.fits')
If multiple formats match the current input, then an exception is raised, and similarly if no format matches the current input. In that case, the format should be explicitly given with the format= keyword argument.
Similarly, it is possible to create custom writers. To go with our simplistic FITS reader above, we can write a simplistic FITS writer:
def fits_table_writer(table, filename, clobber=False):
import numpy as np
from astropy.io import fits
fits.writeto(filename, np.array(table), clobber=clobber)
We then register the writer:
io_registry.register_writer('fits', Table, fits_table_writer)
And we can then write the file out to a FITS file:
t.write('catalog_new.fits', format='fits')
If we have registered the identifier as above, we can simply do:
t.write('catalog_new.fits')
| register_reader(data_format, data_class, ...) | Register a reader function. |
| register_writer(data_format, data_class, ...) | Register a table writer function. |
| register_identifier(data_format, data_class, ...) | Associate an identifier function with a specific data type. |
| identify_format(origin, data_class_required, ...) | |
| get_reader(data_format, data_class) | |
| get_writer(data_format, data_class) | |
| read(cls, *args, **kwargs) | Read in data |
| write(data, *args, **kwargs) | Write out data |
| get_formats([data_class]) | Get the list of registered I/O formats as a Table. |