Upgrading dask 2022 to 2023
Unknown2022.12.1 → 2023.12.1
UnknownUpgrade verdict
None of the 26 releases in this range publish notes, so breaking changes can't be ruled out.
In plain terms
- Some releases in this range publish no notes, so DepDelta can't rule out breaking changes.
- Their commits are listed with this comparison.
Must act Unknown for releases without notes
Releases without notes may still need changes. Check their commits before upgrading.
Python requirement changed in 2023.5.1: >=3.8 → >=3.9.
Adds importlib-metadata >=4.13.0.
Installs 10 packages in all (was 8).
API changes
Generated by DepDelta from published Python source. Not mixed with prose notes.
- added:
export get_annotations
- added:
function to_numpy_dispatch_from_numpy(data, **kwargs) - added:
property ArrayBackendEntrypoint.default_bit_generator - added:
property NumpyBackendEntrypoint.default_bit_generator - added:
static method NumpyBackendEntrypoint.to_backend(data: Array, **kwargs) - added:
static method NumpyBackendEntrypoint.to_backend_dispatch()
- changed:
function retrieve_from_ooc(keys: Collection[Hashable], dsk_pre: Mapping, dsk_post: Mapping) -> dict[tuple, Any] → function retrieve_from_ooc(keys: Collection[Key], dsk_pre: Graph, dsk_post: Graph) -> dict[tuple, Any] - changed:
method Array.rechunk(chunks=…, threshold=…, block_size_limit=…, balance=…) → method Array.rechunk(chunks=…, threshold=…, block_size_limit=…, balance=…, method=…) - added:
method Array.to_backend(backend: str | None=…, **kwargs)
- added:
function to_backend(x: Array, backend: str | None=…, **kwargs)
- added:
property CupyBackendEntrypoint.default_bit_generator - added:
static method CupyBackendEntrypoint.to_backend(data: Array, **kwargs) - added:
static method CupyBackendEntrypoint.to_backend_dispatch()
- added:
variable to_cupy_dispatch - added:
variable to_numpy_dispatch
- added:
function nonzero(a) - added:
function where(condition, x=…, y=…)
- removed:
function sliding_window_view(x, window_shape, axis=…, *, subok=…, writeable=…) - removed:
variable ArrayLike - removed:
variable DTypeLike - removed:
variable sliding_window_view - added:
variable AxisError - added:
variable ComplexWarning
- added:
class Generator - added:
constructor Generator(bit_generator) - added:
function default_rng(seed=…) - added:
method Generator.beta(a, b, size=…, chunks=…, **kwargs) - added:
method Generator.binomial(n, p, size=…, chunks=…, **kwargs) - added:
method Generator.chisquare(df, size=…, chunks=…, **kwargs) - added:
method Generator.choice(a, size=…, replace=…, p=…, axis=…, shuffle=…, chunks=…) - added:
method Generator.exponential(scale=…, size=…, chunks=…, **kwargs) - added:
method Generator.f(dfnum, dfden, size=…, chunks=…, **kwargs) - added:
method Generator.gamma(shape, scale=…, size=…, chunks=…, **kwargs) - added:
method Generator.geometric(p, size=…, chunks=…, **kwargs) - added:
method Generator.gumbel(loc=…, scale=…, size=…, chunks=…, **kwargs) - added:
method Generator.hypergeometric(ngood, nbad, nsample, size=…, chunks=…, **kwargs) - added:
method Generator.integers(low, high=…, size=…, dtype=…, endpoint=…, chunks=…, **kwargs) - added:
method Generator.laplace(loc=…, scale=…, size=…, chunks=…, **kwargs) - added:
method Generator.logistic(loc=…, scale=…, size=…, chunks=…, **kwargs) - added:
method Generator.lognormal(mean=…, sigma=…, size=…, chunks=…, **kwargs) - added:
method Generator.logseries(p, size=…, chunks=…, **kwargs) - added:
method Generator.multinomial(n, pvals, size=…, chunks=…, **kwargs) - added:
method Generator.multivariate_hypergeometric(colors, nsample, size=…, method=…, chunks=…, **kwargs) - added:
method Generator.negative_binomial(n, p, size=…, chunks=…, **kwargs) - added:
method Generator.noncentral_chisquare(df, nonc, size=…, chunks=…, **kwargs) - added:
method Generator.noncentral_f(dfnum, dfden, nonc, size=…, chunks=…, **kwargs) - added:
method Generator.normal(loc=…, scale=…, size=…, chunks=…, **kwargs) - added:
method Generator.pareto(a, size=…, chunks=…, **kwargs) - added:
method Generator.permutation(x) - added:
method Generator.poisson(lam=…, size=…, chunks=…, **kwargs) - added:
method Generator.power(a, size=…, chunks=…, **kwargs) - added:
method Generator.random(size=…, dtype=…, out=…, chunks=…, **kwargs) - added:
method Generator.rayleigh(scale=…, size=…, chunks=…, **kwargs) - added:
method Generator.standard_cauchy(size=…, chunks=…, **kwargs) - added:
method Generator.standard_exponential(size=…, chunks=…, **kwargs) - added:
method Generator.standard_gamma(shape, size=…, chunks=…, **kwargs) - added:
method Generator.standard_normal(size=…, chunks=…, **kwargs) - added:
method Generator.standard_t(df, size=…, chunks=…, **kwargs) - added:
method Generator.triangular(left, mode, right, size=…, chunks=…, **kwargs) - added:
method Generator.uniform(low=…, high=…, size=…, chunks=…, **kwargs) - added:
method Generator.vonmises(mu, kappa, size=…, chunks=…, **kwargs) - added:
method Generator.wald(mean, scale, size=…, chunks=…, **kwargs) - added:
method Generator.weibull(a, size=…, chunks=…, **kwargs) - added:
method Generator.zipf(a, size=…, chunks=…, **kwargs)
- changed:
function rechunk(x, chunks=…, threshold=…, block_size_limit=…, balance=…) → function rechunk(x, chunks=…, threshold=…, block_size_limit=…, balance=…, method=…) - added:
function old_to_new(old_chunks, new_chunks)
- changed:
function moment_chunk(A, order=…, sum=…, numel=…, dtype=…, computing_meta=…, **kwargs) → function moment_chunk(A, order=…, sum=…, numel=…, dtype=…, computing_meta=…, implicit_complex_dtype=…, **kwargs)
- added:
static method DaskBackendEntrypoint.to_backend(data) - added:
static method DaskBackendEntrypoint.to_backend_dispatch()
- removed:
variable no_default - changed:
constructor Bag(dsk: Mapping, name: str, npartitions: int) → constructor Bag(dsk: Graph, name: str, npartitions: int) - changed:
function random_state_data_python(n, random_state=…) → function random_state_data_python(n: int, random_state: int | Random | None=…) -> list[tuple[int, tuple[int, ...], None]]
- changed:
function annotate(**annotations) → function annotate(**annotations: Any) -> Iterator[None] - changed:
function clone_key(key, seed) → function clone_key(key: KeyOrStrT, seed: Hashable) -> KeyOrStrT - changed:
function get_name_from_key(key) -> str → function get_name_from_key(key: Key) -> str - changed:
function replace_name_in_key(key, rename: Mapping[str, str]) → function replace_name_in_key(key: KeyOrStrT, rename: Mapping[str, str]) -> KeyOrStrT - added:
function get_annotations() -> dict[str, Any]
- changed:
constructor Blockwise(output: str, output_indices: Iterable[str], dsk: Mapping[str, tuple], indices: Iterable[tuple[str | BlockwiseDep, Iterable[str] | None]], numblocks: Mapping[str, Sequence[int]], concatenate: bool | None=…, new_axes: Mapping[str, int] | None=…, output_blocks: set[tuple[int, ...]] | None=…, annotations: Mapping[str, Any] | None=…, io_deps: Mapping[str, BlockwiseDep] | None=…) → constructor Blockwise(output: str, output_indices: Iterable[str], dsk: Graph, indices: Iterable[tuple[str | BlockwiseDep, Iterable[str] | None]], numblocks: Mapping[str, Sequence[int]], concatenate: bool | None=…, new_axes: Mapping[str, int] | None=…, output_blocks: set[tuple[int, ...]] | None=…, annotations: Mapping[str, Any] | None=…, io_deps: Mapping[str, BlockwiseDep] | None=…) - changed:
field Blockwise.dsk: Mapping[str, tuple] → field Blockwise.dsk: Graph - changed:
function make_blockwise_graph(func, output, out_indices, *arrind_pairs, numblocks=…, concatenate=…, new_axes=…, output_blocks=…, dims=…, deserializing=…, func_future_args=…, return_key_deps=…, io_deps=…, **kwargs) → function make_blockwise_graph(func, output, out_indices, *arrind_pairs, numblocks=…, concatenate=…, new_axes=…, output_blocks=…, dims=…, deserializing=…, func_future_args=…, return_key_deps=…, io_deps=…) - changed:
method Blockwise.clone(keys: set, seed: Hashable, bind_to: Hashable=…) -> tuple[Layer, bool] → method Blockwise.clone(keys: set[Key], seed: Hashable, bind_to: Key | None=…) -> tuple[Layer, bool] - changed:
method Blockwise.cull(keys: set, all_hlg_keys: Iterable) -> tuple[Layer, Mapping[Hashable, set]] → method Blockwise.cull(keys: set, all_hlg_keys: Iterable) -> tuple[Layer, Mapping[Key, set[Key]]]
- added:
function config() - added:
function config_get(key=…) - added:
function config_list()
- removed:
function entry_points(group=…)
- removed:
variable no_default - changed:
function check_deprecations(key: str, deprecations: dict=…) -> str → function check_deprecations(key: str, deprecations: Mapping[str, str | None]=…) -> str - changed:
function get(key: str, default: Any=…, config: dict=…, override_with: Any | None=…) -> Any → function get(key: str, default: Any=…, config: dict=…, override_with: Any=…) -> Any - changed:
function rename(aliases: Mapping, config: dict=…) -> None → function rename(deprecations: Mapping[str, str | None]=…, config: dict=…) -> None - changed:
function update(old: dict, new: Mapping, priority: Literal['old', 'new']=…) -> dict → function update(old: dict, new: Mapping, priority: Literal['old', 'new', 'new-defaults']=…, defaults: Mapping | None=…) -> dict - changed:
variable deprecations → variable deprecations: dict[str, str | None] - added:
function pop(key: str, default: Any=…, config: dict=…) -> Any
- removed:
function find_all_possible_keys(tasks) -> set - removed:
variable no_default - changed:
function get_dependencies(dsk, key=…, task=…, as_list=…) → function get_dependencies(dsk: Graph, key: Key | None=…, task: Key | NoDefault=…, as_list: Literal[False]=…) -> set[Key] | (dsk: Graph, key: Key | None, task: Key | NoDefault, as_list: Literal[True]) -> list[Key] - changed:
function get_deps(dsk) → function get_deps(dsk: Graph) -> tuple[dict[Key, set[Key]], dict[Key, set[Key]]] - changed:
function keys_in_tasks(keys, tasks, as_list=…) → function keys_in_tasks(keys: Collection[Key], tasks: Iterable[Any], as_list: bool=…) - changed:
function reverse_dict(d) → function reverse_dict(d: Mapping[T_, Iterable[T_]]) -> dict[T_, set[T_]] - added:
function iskey(key: object) -> bool - added:
function validate_key(key: object) -> None - added:
variable T_
- added:
function raise_not_implemented_error(attr_name) - added:
variable Aggregation - added:
variable from_array - added:
variable from_dask_array - added:
variable from_delayed - added:
variable from_dict - added:
variable get_dummies - added:
variable isna - added:
variable map_partitions - added:
variable melt - added:
variable merge_asof - added:
variable read_fwf - added:
variable read_hdf - added:
variable read_json - added:
variable read_orc - added:
variable read_sql - added:
variable read_sql_query - added:
variable read_sql_table - added:
variable read_table - added:
variable to_bag - added:
variable to_csv - added:
variable to_hdf - added:
variable to_json - added:
variable to_orc - added:
variable to_records - added:
variable to_sql
- removed:
function tolist_pandas(obj) - changed:
function get_pyarrow_schema_pandas(obj) → function get_pyarrow_schema_pandas(obj, preserve_index=…) - added:
function get_pandas_dataframe_from_pyarrow(meta, table, **kwargs) - added:
function get_pyarrow_table_from_pandas(obj, **kwargs) - added:
function partd_pandas_blocks(_) - added:
function to_pandas_dispatch_from_pandas(data, **kwargs) - added:
function tolist_numpy_or_pandas(obj) - added:
static method PandasBackendEntrypoint.to_backend(data: _Frame, **kwargs) - added:
static method PandasBackendEntrypoint.to_backend_dispatch()
- removed:
function cov_corr(df, min_periods=…, corr=…, scalar=…, split_every=…) - removed:
function cov_corr_agg(data, cols, min_periods=…, corr=…, scalar=…, like_df=…) - removed:
function cov_corr_chunk(df, corr=…) - removed:
function cov_corr_combine(data_in, corr=…) - removed:
method DataFrame.clip_lower(threshold) - removed:
method DataFrame.clip_upper(threshold) - removed:
method DataFrame.get_dtype_counts() - removed:
method DataFrame.get_ftype_counts() - removed:
method Series.clip_lower(threshold) - removed:
method Series.clip_upper(threshold) - removed:
variable no_default - changed:
function idxmaxmin_agg(x, fn=…, skipna=…, scalar=…) → function idxmaxmin_agg(x, fn=…, skipna=…, scalar=…, numeric_only=…) - changed:
function idxmaxmin_chunk(x, fn=…, skipna=…) → function idxmaxmin_chunk(x, fn=…, skipna=…, numeric_only=…) - changed:
method DataFrame.clip(lower=…, upper=…, out=…) → method DataFrame.clip(lower=…, upper=…, out=…, axis=…) - changed:
method DataFrame.corr(method=…, min_periods=…, split_every=…) → method DataFrame.corr(method=…, min_periods=…, numeric_only=…, split_every=…) - changed:
method DataFrame.cov(min_periods=…, split_every=…) → method DataFrame.cov(min_periods=…, numeric_only=…, split_every=…) - changed:
method DataFrame.mode(dropna=…, split_every=…) → method DataFrame.mode(dropna=…, split_every=…, numeric_only=…) - changed:
method DataFrame.set_index(other: str | Series, drop: bool=…, sorted: bool=…, npartitions: int | Literal['auto'] | None=…, divisions: Sequence | None=…, inplace: bool=…, **kwargs) → method DataFrame.set_index(other: str | Series, drop: bool=…, sorted: bool=…, npartitions: int | Literal['auto'] | None=…, divisions: Sequence | None=…, inplace: bool=…, sort: bool=…, **kwargs) - changed:
method DataFrame.sort_values(by: str, npartitions: int | Literal['auto'] | None=…, ascending: bool=…, na_position: Literal['first'] | Literal['last']=…, sort_function: Callable[[pd.DataFrame], pd.DataFrame] | None=…, sort_function_kwargs: Mapping[str, Any] | None=…, **kwargs) -> DataFrame → method DataFrame.sort_values(by: str | list[str], npartitions: int | Literal['auto'] | None=…, ascending: bool=…, na_position: Literal['first'] | Literal['last']=…, sort_function: Callable[[pd.DataFrame], pd.DataFrame] | None=…, sort_function_kwargs: Mapping[str, Any] | None=…, **kwargs) -> DataFrame - changed:
method Series.clip(lower=…, upper=…, out=…) → method Series.clip(lower=…, upper=…, out=…, axis=…) - added:
method DataFrame.map(func, meta=…, na_action=…) - added:
method Index.drop_duplicates(split_every=…, split_out=…, shuffle=…, **kwargs) - added:
variable GROUP_KEYS_DEFAULT: bool | None
- added:
variable from_pyarrow_table_dispatch - added:
variable partd_encode_dispatch - added:
variable to_pandas_dispatch - added:
variable to_pyarrow_table_dispatch
- added:
function numeric_only_deprecate_default(func) - added:
function numeric_only_not_implemented(func) - added:
variable NUMERIC_ONLY_NOT_IMPLEMENTED
- added:
export to_backend
- added:
class ColumnSpec - added:
class DatasetSpec - added:
class DatetimeIndexSpec - added:
class RangeIndexSpec - added:
field ColumnSpec.args: tuple[Any, ...] - added:
field ColumnSpec.choices: list - added:
field ColumnSpec.dtype: str | type | None - added:
field ColumnSpec.high: int | None - added:
field ColumnSpec.kwargs: dict[str, Any] - added:
field ColumnSpec.length: int | None - added:
field ColumnSpec.low: int | None - added:
field ColumnSpec.method: str | None - added:
field ColumnSpec.number: int - added:
field ColumnSpec.nunique: int | None - added:
field ColumnSpec.prefix: str | None - added:
field ColumnSpec.random: bool - added:
field DatasetSpec.column_specs: list[ColumnSpec] - added:
field DatasetSpec.index_spec: RangeIndexSpec | DatetimeIndexSpec - added:
field DatasetSpec.npartitions: int - added:
field DatasetSpec.nrecords: int - added:
field DatetimeIndexSpec.dtype: str | type - added:
field DatetimeIndexSpec.freq: str - added:
field DatetimeIndexSpec.partition_freq: str | None - added:
field DatetimeIndexSpec.start: str | None - added:
field RangeIndexSpec.dtype: str | type - added:
field RangeIndexSpec.step: int - added:
function with_spec(spec: DatasetSpec, seed: int | None=…)
- added:
function to_backend(ddf: _Frame, backend: str | None=…, **kwargs)
- removed:
variable partitioning_supported - removed:
variable pre_buffer_supported - removed:
variable subset_stats_supported - changed:
static method ArrowDatasetEngine.read_metadata(fs, paths, categories=…, index=…, use_nullable_dtypes=…, gather_statistics=…, filters=…, split_row_groups=…, chunksize=…, aggregate_files=…, ignore_metadata_file=…, metadata_task_size=…, parquet_file_extension=…, **kwargs) → static method ArrowDatasetEngine.read_metadata(fs, paths, categories=…, index=…, use_nullable_dtypes=…, dtype_backend=…, gather_statistics=…, filters=…, split_row_groups=…, blocksize=…, aggregate_files=…, ignore_metadata_file=…, metadata_task_size=…, parquet_file_extension=…, **kwargs) - changed:
static method ArrowDatasetEngine.read_partition(fs, pieces, columns, index, use_nullable_dtypes=…, categories=…, partitions=…, filters=…, schema=…, **kwargs) → static method ArrowDatasetEngine.read_partition(fs, pieces, columns, index, dtype_backend=…, categories=…, partitions=…, filters=…, schema=…, **kwargs)
- changed:
function read_parquet(path, columns=…, filters=…, categories=…, index=…, storage_options=…, engine=…, use_nullable_dtypes: bool=…, calculate_divisions=…, ignore_metadata_file=…, metadata_task_size=…, split_row_groups=…, chunksize=…, aggregate_files=…, parquet_file_extension=…, filesystem=…, **kwargs) → function read_parquet(path, columns=…, filters=…, categories=…, index=…, storage_options=…, engine=…, use_nullable_dtypes: bool | None=…, dtype_backend=…, calculate_divisions=…, ignore_metadata_file=…, metadata_task_size=…, split_row_groups=…, blocksize=…, aggregate_files=…, parquet_file_extension=…, filesystem=…, **kwargs) - changed:
function to_parquet(df, path, engine=…, compression=…, write_index=…, append=…, overwrite=…, ignore_divisions=…, partition_on=…, storage_options=…, custom_metadata=…, write_metadata_file=…, compute=…, compute_kwargs=…, schema=…, name_function=…, **kwargs) → function to_parquet(df, path, engine=…, compression=…, write_index=…, append=…, overwrite=…, ignore_divisions=…, partition_on=…, storage_options=…, custom_metadata=…, write_metadata_file=…, compute=…, compute_kwargs=…, schema=…, name_function=…, filesystem=…, **kwargs)
- changed:
static method FastParquetEngine.read_metadata(fs, paths, categories=…, index=…, use_nullable_dtypes=…, gather_statistics=…, filters=…, split_row_groups=…, chunksize=…, aggregate_files=…, ignore_metadata_file=…, metadata_task_size=…, parquet_file_extension=…, **kwargs) → static method FastParquetEngine.read_metadata(fs, paths, categories=…, index=…, use_nullable_dtypes=…, dtype_backend=…, gather_statistics=…, filters=…, split_row_groups=…, blocksize=…, aggregate_files=…, ignore_metadata_file=…, metadata_task_size=…, parquet_file_extension=…, **kwargs) - changed:
static method FastParquetEngine.read_partition(fs, pieces, columns, index, use_nullable_dtypes=…, categories=…, root_cats=…, root_file_scheme=…, base_path=…, **kwargs) → static method FastParquetEngine.read_partition(fs, pieces, columns, index, dtype_backend=…, categories=…, root_cats=…, root_file_scheme=…, base_path=…, **kwargs)
- changed:
static method Engine.read_metadata(fs, paths, categories=…, index=…, use_nullable_dtypes=…, gather_statistics=…, filters=…, **kwargs) → static method Engine.read_metadata(fs, paths, categories=…, index=…, use_nullable_dtypes=…, dtype_backend=…, gather_statistics=…, filters=…, **kwargs) - added:
static method Engine.default_blocksize()
- added:
class SupportsLock(Protocol) - added:
method SupportsLock.acquire() -> object - added:
method SupportsLock.release() -> object
- added:
function apply(df, *args, **kwargs) - added:
function applymap(df, *args, **kwargs)
- changed:
function create_merge_tree(func, keys, token) → function create_merge_tree(func, keys, token, level=…)
- changed:
method Rolling.aggregate(func, args=…, kwargs=…, **kwds) → method Rolling.aggregate(func, *args, **kwargs)
- removed:
function remove_nans(divisions: Sequence) -> List - changed:
constructor maybe_buffered_partd(buffer=…, tempdir=…) → constructor maybe_buffered_partd(encode_cls=…, buffer=…, tempdir=…) - changed:
function compute_divisions(df: DataFrame, col: Optional[Any]=…, **kwargs) -> Tuple → function compute_divisions(df: DataFrame, col: Any | None=…, **kwargs) -> tuple - changed:
function partitioning_index(df, npartitions) → function partitioning_index(df, npartitions, cast_dtype=…) - changed:
function set_index(df: DataFrame, index: Union[str, Series], npartitions: Optional[Union[int, Literal['auto']]]=…, shuffle: Optional[str]=…, compute: bool=…, drop: bool=…, upsample: float=…, divisions: Optional[Sequence]=…, partition_size: float=…, **kwargs) -> DataFrame → function set_index(df: DataFrame, index: str | Series, npartitions: int | Literal['auto'] | None=…, shuffle: str | None=…, compute: bool=…, drop: bool=…, upsample: float=…, divisions: Sequence | None=…, partition_size: float=…, sort: bool=…, **kwargs) -> DataFrame - changed:
function set_partition(df: DataFrame, index: Union[str, Series], divisions: Sequence, max_branch: int=…, drop: bool=…, shuffle: Optional[str]=…, compute: Optional[bool]=…) -> DataFrame → function set_partition(df: DataFrame, index: str | Series, divisions: Sequence, max_branch: int=…, drop: bool=…, shuffle: str | None=…, compute: bool | None=…) -> DataFrame - changed:
function set_sorted_index(df: DataFrame, index: Union[str, Series], drop: bool=…, divisions: Optional[Sequence]=…, **kwargs) -> DataFrame → function set_sorted_index(df: DataFrame, index: str | Series, drop: bool=…, divisions: Sequence | None=…, **kwargs) -> DataFrame - changed:
function sort_values(df: DataFrame, by: Union[str, List[str]], npartitions: Optional[Union[int, Literal['auto']]]=…, ascending: Union[bool, List[bool]]=…, na_position: Union[Literal['first'], Literal['last']]=…, upsample: float=…, partition_size: float=…, sort_function: Optional[Callable[[pd.DataFrame], pd.DataFrame]]=…, sort_function_kwargs: Optional[Mapping[str, Any]]=…, **kwargs) -> DataFrame → function sort_values(df: DataFrame, by: str | list[str], npartitions: int | Literal['auto'] | None=…, shuffle: str | None=…, ascending: bool | list[bool]=…, na_position: Literal['first'] | Literal['last']=…, upsample: float=…, partition_size: float=…, sort_function: Callable[[pd.DataFrame], pd.DataFrame] | None=…, sort_function_kwargs: Mapping[str, Any] | None=…) -> DataFrame
- changed:
function clear_known_categories(x, cols=…, index=…) → function clear_known_categories(x, cols=…, index=…, dtype_backend=…) - added:
function assert_eq_dtypes(a, b) - added:
function check_numeric_only_valid(numeric_only: bool | NoDefault, name: str) -> dict - added:
function get_numeric_only_kwargs(numeric_only: bool | NoDefault) -> dict - added:
function get_string_dtype() - added:
function pyarrow_strings_enabled() -> bool
- changed:
function plot_cache(results, dsk, start_time, metric_name, palette=…, label_size=…, **kwargs) → function plot_cache(results, dsk, start_time, end_time, metric_name, palette=…, label_size=…, **kwargs) - changed:
function plot_resources(results, palette=…, **kwargs) → function plot_resources(results, start_time, end_time, palette=…, **kwargs) - changed:
function plot_tasks(results, dsk, palette=…, label_size=…, **kwargs) → function plot_tasks(results, dsk, start_time, end_time, palette=…, label_size=…, **kwargs)
- removed:
property HighLevelGraph.dependents - changed:
class HighLevelGraph(Mapping) → class HighLevelGraph(Graph) - changed:
class Layer(Mapping) → class Layer(Graph) - changed:
constructor HighLevelGraph(layers: Mapping[str, Mapping], dependencies: Mapping[str, Set], key_dependencies: dict[Hashable, Set] | None=…) → constructor HighLevelGraph(layers: Mapping[str, Graph], dependencies: Mapping[str, set[str]], key_dependencies: dict[Key, set[Key]] | None=…) - changed:
constructor MaterializedLayer(mapping: Mapping, annotations=…) → constructor MaterializedLayer(mapping: Mapping, annotations=…, collection_annotations=…) - changed:
field HighLevelGraph.dependencies: Mapping[str, Set] → field HighLevelGraph.dependencies: Mapping[str, set[str]] - changed:
field HighLevelGraph.key_dependencies: dict[Hashable, Set] → field HighLevelGraph.key_dependencies: dict[Key, set[Key]] - changed:
method HighLevelGraph.copy() → method HighLevelGraph.copy() -> HighLevelGraph - changed:
method HighLevelGraph.cull(keys: Iterable) -> HighLevelGraph → method HighLevelGraph.cull(keys: Iterable[Key]) -> HighLevelGraph - changed:
method HighLevelGraph.get_all_dependencies() -> dict[Hashable, Set] → method HighLevelGraph.get_all_dependencies() -> dict[Key, set[Key]] - changed:
method HighLevelGraph.get_all_external_keys() -> set → method HighLevelGraph.get_all_external_keys() -> set[Key] - changed:
method HighLevelGraph.items() → method HighLevelGraph.items() -> ItemsView[Key, Any] - changed:
method HighLevelGraph.to_dict() -> dict → method HighLevelGraph.to_dict() -> dict[Key, Any] - changed:
method HighLevelGraph.validate() → method HighLevelGraph.validate() -> None - changed:
method HighLevelGraph.values() → method HighLevelGraph.values() -> ValuesView[Any] - changed:
method Layer.clone(keys: set, seed: Hashable, bind_to: Hashable=…) -> tuple[Layer, bool] → method Layer.clone(keys: set, seed: Hashable, bind_to: Key | None=…) -> tuple[Layer, bool] - changed:
method Layer.cull(keys: set, all_hlg_keys: Iterable) -> tuple[Layer, Mapping[Hashable, set]] → method Layer.cull(keys: set[Key], all_hlg_keys: Collection[Key]) -> tuple[Layer, Mapping[Key, set[Key]]] - changed:
method Layer.get_dependencies(key: Hashable, all_hlg_keys: Iterable) -> set → method Layer.get_dependencies(key: Key, all_hlg_keys: Collection[Key]) -> set - changed:
method Layer.get_output_keys() -> Set → method Layer.get_output_keys() -> Set[Key] - changed:
static method HighLevelGraph.from_collections(name, layer, dependencies=…) → static method HighLevelGraph.from_collections(name: str, layer: Graph, dependencies: Sequence[DaskCollection]=…) -> HighLevelGraph - changed:
static method HighLevelGraph.merge(*graphs) → static method HighLevelGraph.merge(*graphs: Graph) -> HighLevelGraph - added:
property HighLevelGraph.dependents -> dict[str, set[str]]
- removed:
method ShuffleLayer.get_split_keys() - removed:
method SimpleShuffleLayer.get_split_keys() - changed:
constructor BroadcastJoinLayer(name, npartitions, lhs_name, lhs_npartitions, rhs_name, rhs_npartitions, parts_out=…, annotations=…, **merge_kwargs) → constructor BroadcastJoinLayer(name, npartitions, lhs_name, lhs_npartitions, rhs_name, rhs_npartitions, parts_out=…, annotations=…, left_on=…, right_on=…, **merge_kwargs)
- changed:
function get_sync(dsk: Mapping, keys: Sequence[Hashable] | Hashable, **kwargs) → function get_sync(dsk: Mapping, keys: Sequence[Key] | Key, **kwargs)
- changed:
function get(dsk: Mapping, keys: Sequence[Hashable] | Hashable, num_workers=…, func_loads=…, func_dumps=…, optimize_graph=…, pool=…, initializer=…, chunksize=…, **kwargs) → function get(dsk: Mapping, keys: Sequence[Key] | Key, num_workers=…, func_loads=…, func_dumps=…, optimize_graph=…, pool=…, initializer=…, chunksize=…, **kwargs)
- removed:
class StrComparable - removed:
constructor StrComparable(obj) - removed:
function graph_metrics(dependencies, dependents, total_dependencies) - changed:
function diagnostics(dsk, o=…, dependencies=…) → function diagnostics(dsk: MutableMapping[Key, Any], o: Mapping[Key, int] | None=…, dependencies: MutableMapping[Key, set[Key]] | None=…) -> tuple[dict[Key, OrderInfo], list[int]] - changed:
function ndependencies(dependencies, dependents) → function ndependencies(dependencies: Mapping[Key, set[Key]], dependents: Mapping[Key, set[Key]]) -> tuple[dict[Key, int], dict[Key, int]] - changed:
function order(dsk, dependencies=…) → function order(dsk: Mapping[Key, Any], dependencies: Mapping[Key, set[Key]] | None=…, *, return_stats: Literal[True]) -> dict[Key, Order] | (dsk: Mapping[Key, Any], dependencies: Mapping[Key, set[Key]] | None=…, *, return_stats: Literal[False]=…) -> dict[Key, int] - added:
class Order(NamedTuple) - added:
field Order.critical_path: float | int - added:
field Order.priority: int - added:
function sanitize_dsk(dsk: MutableMapping[Key, Any]) -> dict
- changed:
function get(dsk: Mapping, keys: Sequence[Hashable] | Hashable, cache=…, num_workers=…, pool=…, **kwargs) → function get(dsk: Mapping, keys: Sequence[Key] | Key, cache=…, num_workers=…, pool=…, **kwargs)
- added:
variable Graph: TypeAlias - added:
variable Key: TypeAlias - added:
variable NestedKeys: TypeAlias - added:
variable NoDefault - added:
variable no_default
- added:
class shorten_traceback - added:
function get_default_shuffle_method() -> str - added:
function get_meta_library(like) - added:
static method shorten_traceback.shorten(exc_tb: types.TracebackType) -> types.TracebackType