zarr.testing.stateful

Attributes

MAX_BINARY_SIZE

Classes

SyncStoreWrapper
ZarrHierarchyStateMachine	This state machine models operations that modify a zarr store's
ZarrStoreStateMachine

Functions

split_prefix_name(→ tuple[str, str])

Module Contents

class zarr.testing.stateful.SyncStoreWrapper(store: zarr.abc.store.Store)

Bases: zarr.core.sync.SyncMixin

clear() → None

delete(path: str) → None

exists(key: str) → bool

get(

key: str,

prototype: zarr.core.buffer.BufferPrototype,

) → zarr.core.buffer.Buffer | None

get_partial_values(

key_ranges: list[Any],

prototype: zarr.core.buffer.BufferPrototype,

) → list[zarr.core.buffer.Buffer | None]

is_empty(prefix: str) → bool

list() → list[str]

abstract list_dir(prefix: str) → None

abstract list_prefix(prefix: str) → None

set(key: str, data_buffer: zarr.core.buffer.Buffer) → None

abstract set_partial_values(key_start_values: Any) → None

property read_only: bool

store

property supports_deletes: bool

property supports_listing: bool

property supports_partial_writes: bool

property supports_writes: bool

class zarr.testing.stateful.ZarrHierarchyStateMachine(store: zarr.abc.store.Store)

Bases: zarr.core.sync.SyncMixin, hypothesis.stateful.RuleBasedStateMachine

This state machine models operations that modify a zarr store’s hierarchy. That is, user actions that modify arrays/groups as well as list operations. It is intended to be used by external stores, and compares their results to a MemoryStore that is assumed to be perfect.

add_array(

data: hypothesis.strategies.DataObject,

name: str,

array_and_chunks: tuple[numpy.ndarray[Any, Any], tuple[int, Ellipsis]],

) → None

add_group(name: str, data: hypothesis.strategies.DataObject) → None

can_add(path: str) → bool

check_list_prefix_from_root() → None

delete_array_using_del(data: hypothesis.strategies.DataObject) → None

delete_group_using_del(data: hypothesis.strategies.DataObject) → None

init_store() → None

all_arrays: set[str]

all_groups: set[str]

model

store

class zarr.testing.stateful.ZarrStoreStateMachine(store: zarr.abc.store.Store)

Bases: hypothesis.stateful.RuleBasedStateMachine

” Zarr store state machine

This is a subclass of a Hypothesis RuleBasedStateMachine. It is testing a framework to ensure that the state of a Zarr store matches an expected state after a set of random operations. It contains a store (currently, a Zarr MemoryStore) and a model, a simplified version of a zarr store (in this case, a dict). It also contains rules which represent actions that can be applied to a zarr store. Rules apply an action to both the store and the model, and invariants assert that the state of the model is equal to the state of the store. Hypothesis then generates sequences of rules, running invariants after each rule. It raises an error if a sequence produces discontinuity between state of the model and state of the store (ie. an invariant is violated). https://hypothesis.readthedocs.io/en/latest/stateful.html

check_num_zarr_keys_equal() → None

check_paths_equal() → None

check_vals_equal() → None

check_zarr_keys() → None

clear() → None

delete(data: hypothesis.strategies.DataObject) → None

exists(key: str) → None

get(key: str, data: hypothesis.strategies.DataObject) → None

get_invalid_zarr_keys(key: str, data: hypothesis.strategies.DataObject) → None

get_partial_values(data: hypothesis.strategies.DataObject) → None

init_store() → None

is_empty() → None

set(key: str, data: hypothesis.strategies.DataObject) → None

model: dict[str, zarr.core.buffer.Buffer]

prototype

store

zarr.testing.stateful.split_prefix_name(path: str) → tuple[str, str]

zarr.testing.stateful.MAX_BINARY_SIZE = 100