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  • deepcopying variable raises `TypeError: h5py objects cannot be pickled` (Dataset.sortby) · 5 ✖

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693112371 https://github.com/pydata/xarray/issues/4425#issuecomment-693112371 https://api.github.com/repos/pydata/xarray/issues/4425 MDEyOklzc3VlQ29tbWVudDY5MzExMjM3MQ== shoyer 1217238 2020-09-16T01:16:31Z 2020-09-16T01:16:31Z MEMBER

Hmm. It appears that one advantage of the old implementation for is that it meant that calling copy with deep=True would always succeed.

See https://github.com/pydata/xarray/pull/4426 for a potential fix.

 
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   deepcopying variable raises `TypeError: h5py objects cannot be pickled` (Dataset.sortby) 701764313
692906011 https://github.com/pydata/xarray/issues/4425#issuecomment-692906011 https://api.github.com/repos/pydata/xarray/issues/4425 MDEyOklzc3VlQ29tbWVudDY5MjkwNjAxMQ== rabernat 1197350 2020-09-15T18:49:58Z 2020-09-15T18:49:58Z MEMBER

Thanks for digging on this. I don't have an answer, but I wanted to tag as related to #4242.

 
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   deepcopying variable raises `TypeError: h5py objects cannot be pickled` (Dataset.sortby) 701764313
692728529 https://github.com/pydata/xarray/issues/4425#issuecomment-692728529 https://api.github.com/repos/pydata/xarray/issues/4425 MDEyOklzc3VlQ29tbWVudDY5MjcyODUyOQ== kmuehlbauer 5821660 2020-09-15T13:51:13Z 2020-09-15T13:51:13Z MEMBER

OK, seems that the above code uses DummyFileManager instead of CachingFileManager for both backends...

 
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   deepcopying variable raises `TypeError: h5py objects cannot be pickled` (Dataset.sortby) 701764313
692698627 https://github.com/pydata/xarray/issues/4425#issuecomment-692698627 https://api.github.com/repos/pydata/xarray/issues/4425 MDEyOklzc3VlQ29tbWVudDY5MjY5ODYyNw== kmuehlbauer 5821660 2020-09-15T13:01:37Z 2020-09-15T13:01:37Z MEMBER

I've tried to dig a bit deeper, this happens if I apply this for the NetCDF4DataStore:

python import netCDF4 as nc f = nc.Dataset("myfile.h5", mode="r") s0 = xr.backends.NetCDF4DataStore(f) ds = xr.open_dataset(s0, engine="netcdf4", chunks=None) ds = ds.assign_coords({"phony_dim_0": np.arange(ds.dims['phony_dim_0'], 0, -1)}) ds.sortby('phony_dim_0') ds.close() ``` netCDF4/_netCDF4.pyx in netCDF4._netCDF4.Dataset.reduce()

NotImplementedError: Dataset is not picklable `` I think there must be something wrong with using the open file handles compared to the normalxr.open_dataset`. Any thoughts?

Error Traceback ```python --------------------------------------------------------------------------- NotImplementedError Traceback (most recent call last) <ipython-input-4-b0e55062ef80> in <module> 1 #ds.load() ----> 2 ds.sortby('phony_dim_0') 3 ds.close() /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/site-packages/xarray-0.16.1.dev86+g264fdb29-py3.8.egg/xarray/core/dataset.py in sortby(self, variables, ascending) 5293 variables = variables 5294 variables = [v if isinstance(v, DataArray) else self[v] for v in variables] -> 5295 aligned_vars = align(self, *variables, join="left") 5296 aligned_self = aligned_vars[0] 5297 aligned_other_vars = aligned_vars[1:] /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/site-packages/xarray-0.16.1.dev86+g264fdb29-py3.8.egg/xarray/core/alignment.py in align(join, copy, indexes, exclude, fill_value, *objects) 336 if not valid_indexers: 337 # fast path for no reindexing necessary --> 338 new_obj = obj.copy(deep=copy) 339 else: 340 new_obj = obj.reindex(copy=copy, fill_value=fill_value, **valid_indexers) /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/site-packages/xarray-0.16.1.dev86+g264fdb29-py3.8.egg/xarray/core/dataset.py in copy(self, deep, data) 1076 """ 1077 if data is None: -> 1078 variables = {k: v.copy(deep=deep) for k, v in self._variables.items()} 1079 elif not utils.is_dict_like(data): 1080 raise ValueError("Data must be dict-like") /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/site-packages/xarray-0.16.1.dev86+g264fdb29-py3.8.egg/xarray/core/dataset.py in <dictcomp>(.0) 1076 """ 1077 if data is None: -> 1078 variables = {k: v.copy(deep=deep) for k, v in self._variables.items()} 1079 elif not utils.is_dict_like(data): 1080 raise ValueError("Data must be dict-like") /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/site-packages/xarray-0.16.1.dev86+g264fdb29-py3.8.egg/xarray/core/variable.py in copy(self, deep, data) 938 939 if deep: --> 940 data = copy.deepcopy(data) 941 942 else: /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 170 y = x 171 else: --> 172 y = _reconstruct(x, memo, *rv) 173 174 # If is its own copy, don't memoize. /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in _reconstruct(x, memo, func, args, state, listiter, dictiter, deepcopy) 268 if state is not None: 269 if deep: --> 270 state = deepcopy(state, memo) 271 if hasattr(y, '__setstate__'): 272 y.__setstate__(state) /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 144 copier = _deepcopy_dispatch.get(cls) 145 if copier is not None: --> 146 y = copier(x, memo) 147 else: 148 if issubclass(cls, type): /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in _deepcopy_tuple(x, memo, deepcopy) 208 209 def _deepcopy_tuple(x, memo, deepcopy=deepcopy): --> 210 y = [deepcopy(a, memo) for a in x] 211 # We're not going to put the tuple in the memo, but it's still important we 212 # check for it, in case the tuple contains recursive mutable structures. /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in <listcomp>(.0) 208 209 def _deepcopy_tuple(x, memo, deepcopy=deepcopy): --> 210 y = [deepcopy(a, memo) for a in x] 211 # We're not going to put the tuple in the memo, but it's still important we 212 # check for it, in case the tuple contains recursive mutable structures. /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 144 copier = _deepcopy_dispatch.get(cls) 145 if copier is not None: --> 146 y = copier(x, memo) 147 else: 148 if issubclass(cls, type): /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in _deepcopy_dict(x, memo, deepcopy) 228 memo[id(x)] = y 229 for key, value in x.items(): --> 230 y[deepcopy(key, memo)] = deepcopy(value, memo) 231 return y 232 d[dict] = _deepcopy_dict /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 170 y = x 171 else: --> 172 y = _reconstruct(x, memo, *rv) 173 174 # If is its own copy, don't memoize. /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in _reconstruct(x, memo, func, args, state, listiter, dictiter, deepcopy) 268 if state is not None: 269 if deep: --> 270 state = deepcopy(state, memo) 271 if hasattr(y, '__setstate__'): 272 y.__setstate__(state) /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 144 copier = _deepcopy_dispatch.get(cls) 145 if copier is not None: --> 146 y = copier(x, memo) 147 else: 148 if issubclass(cls, type): /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in _deepcopy_tuple(x, memo, deepcopy) 208 209 def _deepcopy_tuple(x, memo, deepcopy=deepcopy): --> 210 y = [deepcopy(a, memo) for a in x] 211 # We're not going to put the tuple in the memo, but it's still important we 212 # check for it, in case the tuple contains recursive mutable structures. /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in <listcomp>(.0) 208 209 def _deepcopy_tuple(x, memo, deepcopy=deepcopy): --> 210 y = [deepcopy(a, memo) for a in x] 211 # We're not going to put the tuple in the memo, but it's still important we 212 # check for it, in case the tuple contains recursive mutable structures. /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 144 copier = _deepcopy_dispatch.get(cls) 145 if copier is not None: --> 146 y = copier(x, memo) 147 else: 148 if issubclass(cls, type): /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in _deepcopy_dict(x, memo, deepcopy) 228 memo[id(x)] = y 229 for key, value in x.items(): --> 230 y[deepcopy(key, memo)] = deepcopy(value, memo) 231 return y 232 d[dict] = _deepcopy_dict /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 170 y = x 171 else: --> 172 y = _reconstruct(x, memo, *rv) 173 174 # If is its own copy, don't memoize. /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in _reconstruct(x, memo, func, args, state, listiter, dictiter, deepcopy) 268 if state is not None: 269 if deep: --> 270 state = deepcopy(state, memo) 271 if hasattr(y, '__setstate__'): 272 y.__setstate__(state) /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 144 copier = _deepcopy_dispatch.get(cls) 145 if copier is not None: --> 146 y = copier(x, memo) 147 else: 148 if issubclass(cls, type): /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in _deepcopy_tuple(x, memo, deepcopy) 208 209 def _deepcopy_tuple(x, memo, deepcopy=deepcopy): --> 210 y = [deepcopy(a, memo) for a in x] 211 # We're not going to put the tuple in the memo, but it's still important we 212 # check for it, in case the tuple contains recursive mutable structures. /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in <listcomp>(.0) 208 209 def _deepcopy_tuple(x, memo, deepcopy=deepcopy): --> 210 y = [deepcopy(a, memo) for a in x] 211 # We're not going to put the tuple in the memo, but it's still important we 212 # check for it, in case the tuple contains recursive mutable structures. /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 144 copier = _deepcopy_dispatch.get(cls) 145 if copier is not None: --> 146 y = copier(x, memo) 147 else: 148 if issubclass(cls, type): /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in _deepcopy_dict(x, memo, deepcopy) 228 memo[id(x)] = y 229 for key, value in x.items(): --> 230 y[deepcopy(key, memo)] = deepcopy(value, memo) 231 return y 232 d[dict] = _deepcopy_dict /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 170 y = x 171 else: --> 172 y = _reconstruct(x, memo, *rv) 173 174 # If is its own copy, don't memoize. /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in _reconstruct(x, memo, func, args, state, listiter, dictiter, deepcopy) 268 if state is not None: 269 if deep: --> 270 state = deepcopy(state, memo) 271 if hasattr(y, '__setstate__'): 272 y.__setstate__(state) /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 144 copier = _deepcopy_dispatch.get(cls) 145 if copier is not None: --> 146 y = copier(x, memo) 147 else: 148 if issubclass(cls, type): /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in _deepcopy_tuple(x, memo, deepcopy) 208 209 def _deepcopy_tuple(x, memo, deepcopy=deepcopy): --> 210 y = [deepcopy(a, memo) for a in x] 211 # We're not going to put the tuple in the memo, but it's still important we 212 # check for it, in case the tuple contains recursive mutable structures. /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in <listcomp>(.0) 208 209 def _deepcopy_tuple(x, memo, deepcopy=deepcopy): --> 210 y = [deepcopy(a, memo) for a in x] 211 # We're not going to put the tuple in the memo, but it's still important we 212 # check for it, in case the tuple contains recursive mutable structures. /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 144 copier = _deepcopy_dispatch.get(cls) 145 if copier is not None: --> 146 y = copier(x, memo) 147 else: 148 if issubclass(cls, type): /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in _deepcopy_dict(x, memo, deepcopy) 228 memo[id(x)] = y 229 for key, value in x.items(): --> 230 y[deepcopy(key, memo)] = deepcopy(value, memo) 231 return y 232 d[dict] = _deepcopy_dict /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 170 y = x 171 else: --> 172 y = _reconstruct(x, memo, *rv) 173 174 # If is its own copy, don't memoize. /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in _reconstruct(x, memo, func, args, state, listiter, dictiter, deepcopy) 268 if state is not None: 269 if deep: --> 270 state = deepcopy(state, memo) 271 if hasattr(y, '__setstate__'): 272 y.__setstate__(state) /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 144 copier = _deepcopy_dispatch.get(cls) 145 if copier is not None: --> 146 y = copier(x, memo) 147 else: 148 if issubclass(cls, type): /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in _deepcopy_tuple(x, memo, deepcopy) 208 209 def _deepcopy_tuple(x, memo, deepcopy=deepcopy): --> 210 y = [deepcopy(a, memo) for a in x] 211 # We're not going to put the tuple in the memo, but it's still important we 212 # check for it, in case the tuple contains recursive mutable structures. /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in <listcomp>(.0) 208 209 def _deepcopy_tuple(x, memo, deepcopy=deepcopy): --> 210 y = [deepcopy(a, memo) for a in x] 211 # We're not going to put the tuple in the memo, but it's still important we 212 # check for it, in case the tuple contains recursive mutable structures. /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 144 copier = _deepcopy_dispatch.get(cls) 145 if copier is not None: --> 146 y = copier(x, memo) 147 else: 148 if issubclass(cls, type): /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in _deepcopy_dict(x, memo, deepcopy) 228 memo[id(x)] = y 229 for key, value in x.items(): --> 230 y[deepcopy(key, memo)] = deepcopy(value, memo) 231 return y 232 d[dict] = _deepcopy_dict /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 170 y = x 171 else: --> 172 y = _reconstruct(x, memo, *rv) 173 174 # If is its own copy, don't memoize. /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in _reconstruct(x, memo, func, args, state, listiter, dictiter, deepcopy) 268 if state is not None: 269 if deep: --> 270 state = deepcopy(state, memo) 271 if hasattr(y, '__setstate__'): 272 y.__setstate__(state) /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 144 copier = _deepcopy_dispatch.get(cls) 145 if copier is not None: --> 146 y = copier(x, memo) 147 else: 148 if issubclass(cls, type): /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in _deepcopy_dict(x, memo, deepcopy) 228 memo[id(x)] = y 229 for key, value in x.items(): --> 230 y[deepcopy(key, memo)] = deepcopy(value, memo) 231 return y 232 d[dict] = _deepcopy_dict /home/kai/miniconda/envs/wradlib_devel/lib/python3.8/copy.py in deepcopy(x, memo, _nil) 159 reductor = getattr(x, "__reduce_ex__", None) 160 if reductor is not None: --> 161 rv = reductor(4) 162 else: 163 reductor = getattr(x, "__reduce__", None) netCDF4/_netCDF4.pyx in netCDF4._netCDF4.Dataset.__reduce__() NotImplementedError: Dataset is not picklable ``` 
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   deepcopying variable raises `TypeError: h5py objects cannot be pickled` (Dataset.sortby) 701764313
692615988 https://github.com/pydata/xarray/issues/4425#issuecomment-692615988 https://api.github.com/repos/pydata/xarray/issues/4425 MDEyOklzc3VlQ29tbWVudDY5MjYxNTk4OA== kmuehlbauer 5821660 2020-09-15T10:08:31Z 2020-09-15T10:08:31Z MEMBER

Please also see these comments and those comments in #4221 by @keewis and @shoyer, which led to the current state of that deepcopy.

Any idea how to fix this for the above use case?

 
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   deepcopying variable raises `TypeError: h5py objects cannot be pickled` (Dataset.sortby) 701764313

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