How to use the zarr.Group function in zarr

zarr.codecs.codec_registry[numcodecs.Pickle.codec_id] = numcodecs.Pickle
zarr.codecs.codec_registry[numcodecs.MsgPack.codec_id] = numcodecs.MsgPack

from progressivis.core.config import get_option
from .base import StorageEngine, Group, Attribute, Dataset


# For now (April 21st 2017), zarr misses two important features: fancy indexing and Boolean indexing.
# These two features are scheduled for inclusion in future releases of zarr.


Group.register(zarr.Group)
Attribute.register(Attributes)
Dataset.register(zarr.Array)

class ZARRGroup(zarr.Group):
    def __init__(self, store, **kwds):
        super(ZARRGroup, self).__init__(store, **kwds)

    def create_dataset(self, name, shape=None, dtype=None, data=None, maxshape=None, **kwds):
        _ = maxshape
        if kwds.get('compression') is None:
            kwds.update(get_option('storage.zarr.filter', {}))
        filters = kwds.get('filters', [])
        filters.append(numcodecs.MsgPack())
        kwds['filters'] = filters
        if dtype == np.dtype('O') and kwds.get('object_codec') is None:
            kwds.update({'object_codec': numcodecs.VLenUTF8()})
        return super(ZARRGroup, self).create_dataset(name, shape=shape, dtype=dtype, data=data, **kwds)

    def require_dataset(self, name, shape, dtype=None, exact=False, **kwds):
        if kwds.get('compression') is None:

import zarr
from zarr.attrs import Attributes
from zarr.storage import init_group, contains_group
import numcodecs
zarr.codecs.codec_registry[numcodecs.Pickle.codec_id] = numcodecs.Pickle
zarr.codecs.codec_registry[numcodecs.MsgPack.codec_id] = numcodecs.MsgPack

from progressivis.core.config import get_option
from .base import StorageEngine, Group, Attribute, Dataset


# For now (April 21st 2017), zarr misses two important features: fancy indexing and Boolean indexing.
# These two features are scheduled for inclusion in future releases of zarr.


Group.register(zarr.Group)
Attribute.register(Attributes)
Dataset.register(zarr.Array)

class ZARRGroup(zarr.Group):
    def __init__(self, store, **kwds):
        super(ZARRGroup, self).__init__(store, **kwds)

    def create_dataset(self, name, shape=None, dtype=None, data=None, maxshape=None, **kwds):
        _ = maxshape
        if kwds.get('compression') is None:
            kwds.update(get_option('storage.zarr.filter', {}))
        filters = kwds.get('filters', [])
        filters.append(numcodecs.MsgPack())
        kwds['filters'] = filters
        if dtype == np.dtype('O') and kwds.get('object_codec') is None:
            kwds.update({'object_codec': numcodecs.VLenUTF8()})

def __init__(
        self,
        dataset: xr.Dataset,
        model: Model,
        zobject: Optional[Union[zarr.Group, MutableMapping, str]] = None,
        encoding: Optional[EncodingDict] = None,
        batch_dim: Optional[str] = None,
        lock: Optional[Any] = None,
    ):
        self.dataset = dataset
        self.model = model

        self.in_memory = False
        self.consolidated = False

        if isinstance(zobject, zarr.Group):
            self.zgroup = zobject
        elif zobject is None:
            self.zgroup = zarr.group(store=zarr.MemoryStore())
            self.in_memory = True
        else:
            self.zgroup = zarr.group(store=zobject)

        self.output_vars = dataset.xsimlab.output_vars_by_clock
        self.output_save_steps = dataset.xsimlab.get_output_save_steps()

        if encoding is None:
            encoding = {}

        self.var_info = _get_var_info(dataset, model, encoding)

        self.batch_dim = batch_dim

def set_default(self, f):
        assert isinstance(f, zarr.Group)
        if self._zarr is not None:
            self.close()
        self._zarr = f