I/O Registry (astropy.io.registry)#
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.
Likewise Cosmology I/O & Convert for built-in formats supported by
Cosmology.
No built-in formats are currently defined for
NDData, but this will be added in future.
Introduction#
The I/O registry is a submodule used to define the readers/writers available
for the Table, NDData,
and Cosmology classes.
Custom Read/Write Functions#
This section demonstrates how to create a custom reader/writer. A reader is
written as a function that can take any arguments except format (which is
needed when manually specifying the format — see below) and returns an
instance of the Table or
NDData classes (or subclasses).
Examples#
Here we assume that we are trying to write a reader/writer for the
Table class:
>>> from astropy.table import Table
>>> def my_table_reader(filename, some_option=1):
... # Read in the table by any means necessary
... return table # should be an instance of Table
Such a function can then be registered with the I/O registry:
from astropy.io import registry
registry.register_reader('my-table-format', Table, my_table_reader)
where the first argument is the name of the format, the second argument is the class that the function returns an instance for, and the third argument is the reader itself.
We can then read in a table with:
d = Table.read('my_table_file.mtf', format='my-table-format')
In practice, it would be nice to have the read method automatically
identify that this file is in the my-table-format format, so we can
construct a function that can recognize these files, which we refer to here as
an identifier function.
An identifier function should take a first argument that is a string
which indicates whether the identifier is being called from read or
write, and should then accept an arbitrary number of positional and keyword
arguments via *args and **kwargs, which are the arguments passed to
the read method.
In the above case, we can write a 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 for the identifier
function is that it return a boolean indicating whether the input matches that
expected for the format. In our example, we want to automatically recognize
files with filenames ending in .mtf as being in the my-table-format
format:
import os
def identify_mtf(origin, *args, **kwargs):
return (isinstance(args[0], str) and
os.path.splitext(args[0].lower())[1] == '.mtf')
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, similarly to the reader function:
registry.register_identifier('my-table-format', Table, identify_mtf)
Having registered this function, we can then do:
t = Table.read('catalog.mtf')
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.
It is also possible to create custom writers. To go with our custom reader above, we can write a custom writer:
def my_table_writer(table, filename, overwrite=False):
... # Write the table out to a file
return ... # generally None, but other values are not forbidden.
Writer functions should take a dataset object (either an instance of the
Table or NDData
classes or subclasses), and any number of subsequent positional and keyword
arguments — although as for the reader, the format keyword argument cannot
be used.
We then register the writer:
registry.register_writer('my-custom-format', Table, my_table_writer)
We can write the table out to a file:
t.write('catalog_new.mtf', format='my-table-format')
Since we have already registered the identifier function, we can also do:
t.write('catalog_new.mtf')
Registries, local and default#
Changed in version 5.0.
As of Astropy 5.0 the I/O registry submodule has switched to a class-based
architecture, allowing for the creation of custom registries.
The three supported registry types are read-only –
UnifiedInputRegistry –
write-only – UnifiedOutputRegistry –
and read/write – UnifiedIORegistry.
>>> from astropy.io.registry import UnifiedIORegistry
>>> example_reg = UnifiedIORegistry()
>>> print([m for m in dir(example_reg) if not m.startswith("_")])
['available_registries', 'delay_doc_updates', 'get_formats', 'get_reader',
'get_writer', 'identify_format', 'read', 'register_identifier',
'register_reader', 'register_writer', 'unregister_identifier',
'unregister_reader', 'unregister_writer', 'write']
For backward compatibility all the methods on this registry have corresponding module-level functions, which work with the default global read/write registry. These functions were used in the previous examples. This new registry is empty.
>>> example_reg.get_formats()
<Table length=0>
Data class Format Read Write Auto-identify
float64 float64 float64 float64 float64
---------- ------- ------- ------- -------------
We can register read / write / identify methods with this registry object:
>>> example_reg.register_reader('my-table-format', Table, my_table_reader)
>>> example_reg.get_formats()
<Table length=1>
Data class Format Read Write Auto-identify
str5 str15 str3 str2 str2
---------- --------------- ---- ----- -------------
Table my-table-format Yes No No
What is the use of a custom registries?
To make read-only or write-only registries.
To allow for different readers for the same format.
To allow for an object to have different kinds of readers and writers. E.g.
Cosmologywhich supports both file I/O and object conversion.