def _encode_mixins(tbl):
"""Encode a Table ``tbl`` that may have mixin columns to a Table with only
astropy Columns + appropriate meta-data to allow subsequent decoding.
"""
from astropy.table import serialize
from astropy.table.table import has_info_class
from astropy import units as u
from astropy.utils.data_info import MixinInfo, serialize_context_as
# If PyYAML is not available then check to see if there are any mixin cols
# that *require* YAML serialization. HDF5 already has support for
# Quantity, so if those are the only mixins the proceed without doing the
# YAML bit, for backward compatibility (i.e. not requiring YAML to write
# Quantity).
try:
import yaml
except ImportError:
for col in tbl.itercols():
if (has_info_class(col, MixinInfo)
and col.__class__ is not u.Quantity):
raise TypeError("cannot write type {} column '{}' "
"to HDF5 without PyYAML installed.".format(
col.__class__.__name__, col.info.name))
# Convert the table to one with no mixins, only Column objects. This adds
# meta data which is extracted with meta.get_yaml_from_table.
with serialize_context_as('hdf5'):
encode_tbl = serialize.represent_mixins_as_columns(tbl)
return encode_tbl
def _encode_mixins(tbl):
"""Encode a Table ``tbl`` that may have mixin columns to a Table with only
astropy Columns + appropriate meta-data to allow subsequent decoding.
"""
from astropy.table import serialize
from astropy.table.table import has_info_class
from astropy import units as u
from astropy.utils.data_info import MixinInfo, serialize_context_as
# If PyYAML is not available then check to see if there are any mixin cols
# that *require* YAML serialization. HDF5 already has support for
# Quantity, so if those are the only mixins the proceed without doing the
# YAML bit, for backward compatibility (i.e. not requiring YAML to write
# Quantity).
try:
import yaml
except ImportError:
for col in tbl.itercols():
if (has_info_class(col, MixinInfo) and
col.__class__ is not u.Quantity):
raise TypeError("cannot write type {} column '{}' "
"to HDF5 without PyYAML installed."
.format(col.__class__.__name__, col.info.name))
# Convert the table to one with no mixins, only Column objects. This adds
# meta data which is extracted with meta.get_yaml_from_table.
with serialize_context_as('hdf5'):
encode_tbl = serialize.represent_mixins_as_columns(tbl)
return encode_tbl
def _encode_mixins(tbl):
from astropy.table import serialize
from astropy.table.table import has_info_class
from astropy import units as u
from astropy.utils.data_info import MixinInfo, serialize_context_as
try:
import yaml
except ImportError:
for col in tbl.itercols():
if (has_info_class(col, MixinInfo)
and col.__class__ is not u.Quantity):
raise TypeError("cannot write type {} column '{}' "
"to HDF5 without PyYAML installed.".format(
col.__class__.__name__, col.info.name))
with serialize_context_as('hdf5'):
encode_tbl = serialize.represent_mixins_as_columns(tbl)
return encode_tbl
def _encode_mixins(tbl):
"""Encode a Table ``tbl`` that may have mixin columns to a Table with only
astropy Columns + appropriate meta-data to allow subsequent decoding.
"""
# Determine if information will be lost without serializing meta. This is hardcoded
# to the set difference between column info attributes and what FITS can store
# natively (name, dtype, unit). See _get_col_attributes() in table/meta.py for where
# this comes from.
info_lost = any(
any(
getattr(col.info, attr, None) not in (None, {})
for attr in ('description', 'meta')) for col in tbl.itercols())
# If PyYAML is not available then check to see if there are any mixin cols
# that *require* YAML serialization. FITS already has support for Time,
# Quantity, so if those are the only mixins the proceed without doing the
# YAML bit, for backward compatibility (i.e. not requiring YAML to write
# Time or Quantity). In this case other mixin column meta (e.g.
# description or meta) will be silently dropped, consistent with astropy <=
# 2.0 behavior.
try:
import yaml # noqa
except ImportError:
for col in tbl.itercols():
if (has_info_class(col, MixinInfo)
and col.__class__ not in (u.Quantity, Time)):
raise TypeError("cannot write type {} column '{}' "
"to FITS without PyYAML installed.".format(
col.__class__.__name__, col.info.name))
else:
if info_lost:
warnings.warn(
"table contains column(s) with defined 'format',"
" 'description', or 'meta' info attributes. These"
" will be dropped unless you install PyYAML.",
AstropyUserWarning)
return tbl
# Convert the table to one with no mixins, only Column objects. This adds
# meta data which is extracted with meta.get_yaml_from_table. This ignores
# Time-subclass columns and leave them in the table so that the downstream
# FITS Time handling does the right thing.
with serialize_context_as('fits'):
encode_tbl = serialize._represent_mixins_as_columns(
tbl, exclude_classes=(Time, ))
# If the encoded table is unchanged then there were no mixins. But if there
# is column metadata (format, description, meta) that would be lost, then
# still go through the serialized columns machinery.
if encode_tbl is tbl and not info_lost:
return tbl
# Get the YAML serialization of information describing the table columns.
# This is re-using ECSV code that combined existing table.meta with with
# the extra __serialized_columns__ key. For FITS the table.meta is handled
# by the native FITS connect code, so don't include that in the YAML
# output.
ser_col = '__serialized_columns__'
# encode_tbl might not have a __serialized_columns__ key if there were no mixins,
# but machinery below expects it to be available, so just make an empty dict.
encode_tbl.meta.setdefault(ser_col, {})
tbl_meta_copy = encode_tbl.meta.copy()
try:
encode_tbl.meta = {ser_col: encode_tbl.meta[ser_col]}
meta_yaml_lines = meta.get_yaml_from_table(encode_tbl)
finally:
encode_tbl.meta = tbl_meta_copy
del encode_tbl.meta[ser_col]
if 'comments' not in encode_tbl.meta:
encode_tbl.meta['comments'] = []
encode_tbl.meta['comments'].append('--BEGIN-ASTROPY-SERIALIZED-COLUMNS--')
for line in meta_yaml_lines:
if len(line) == 0:
lines = ['']
else:
# Split line into 70 character chunks for COMMENT cards
idxs = list(range(0, len(line) + 70, 70))
lines = [line[i0:i1] + '\\' for i0, i1 in zip(idxs[:-1], idxs[1:])]
lines[-1] = lines[-1][:-1]
encode_tbl.meta['comments'].extend(lines)
encode_tbl.meta['comments'].append('--END-ASTROPY-SERIALIZED-COLUMNS--')
return encode_tbl
def _encode_mixins(tbl):
"""Encode a Table ``tbl`` that may have mixin columns to a Table with only
astropy Columns + appropriate meta-data to allow subsequent decoding.
"""
# Determine if information will be lost without serializing meta. This is hardcoded
# to the set difference between column info attributes and what FITS can store
# natively (name, dtype, unit). See _get_col_attributes() in table/meta.py for where
# this comes from.
info_lost = any(any(getattr(col.info, attr, None) not in (None, {})
for attr in ('description', 'meta'))
for col in tbl.itercols())
# If PyYAML is not available then check to see if there are any mixin cols
# that *require* YAML serialization. FITS already has support for Time,
# Quantity, so if those are the only mixins the proceed without doing the
# YAML bit, for backward compatibility (i.e. not requiring YAML to write
# Time or Quantity). In this case other mixin column meta (e.g.
# description or meta) will be silently dropped, consistent with astropy <=
# 2.0 behavior.
try:
import yaml # noqa
except ImportError:
for col in tbl.itercols():
if (has_info_class(col, MixinInfo) and
col.__class__ not in (u.Quantity, Time)):
raise TypeError("cannot write type {} column '{}' "
"to FITS without PyYAML installed."
.format(col.__class__.__name__, col.info.name))
else:
if info_lost:
warnings.warn("table contains column(s) with defined 'format',"
" 'description', or 'meta' info attributes. These"
" will be dropped unless you install PyYAML.",
AstropyUserWarning)
return tbl
# Convert the table to one with no mixins, only Column objects. This adds
# meta data which is extracted with meta.get_yaml_from_table. This ignores
# Time-subclass columns and leave them in the table so that the downstream
# FITS Time handling does the right thing.
with serialize_context_as('fits'):
encode_tbl = serialize._represent_mixins_as_columns(
tbl, exclude_classes=(Time,))
# If the encoded table is unchanged then there were no mixins. But if there
# is column metadata (format, description, meta) that would be lost, then
# still go through the serialized columns machinery.
if encode_tbl is tbl and not info_lost:
return tbl
# Get the YAML serialization of information describing the table columns.
# This is re-using ECSV code that combined existing table.meta with with
# the extra __serialized_columns__ key. For FITS the table.meta is handled
# by the native FITS connect code, so don't include that in the YAML
# output.
ser_col = '__serialized_columns__'
# encode_tbl might not have a __serialized_columns__ key if there were no mixins,
# but machinery below expects it to be available, so just make an empty dict.
encode_tbl.meta.setdefault(ser_col, {})
tbl_meta_copy = encode_tbl.meta.copy()
try:
encode_tbl.meta = {ser_col: encode_tbl.meta[ser_col]}
meta_yaml_lines = meta.get_yaml_from_table(encode_tbl)
finally:
encode_tbl.meta = tbl_meta_copy
del encode_tbl.meta[ser_col]
if 'comments' not in encode_tbl.meta:
encode_tbl.meta['comments'] = []
encode_tbl.meta['comments'].append('--BEGIN-ASTROPY-SERIALIZED-COLUMNS--')
for line in meta_yaml_lines:
if len(line) == 0:
lines = ['']
else:
# Split line into 70 character chunks for COMMENT cards
idxs = list(range(0, len(line) + 70, 70))
lines = [line[i0:i1] + '\\' for i0, i1 in zip(idxs[:-1], idxs[1:])]
lines[-1] = lines[-1][:-1]
encode_tbl.meta['comments'].extend(lines)
encode_tbl.meta['comments'].append('--END-ASTROPY-SERIALIZED-COLUMNS--')
return encode_tbl