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import copy
from collections import defaultdict
from collections.abc import Sequence
from typing import Any, Optional, Union
from moto.core.common_models import BaseModel, CloudFormationModel
from moto.core.utils import unix_time, unix_time_millis, utcnow
from moto.dynamodb.comparisons import get_expected, get_filter_expression
from moto.dynamodb.exceptions import (
ConditionalCheckFailed,
HashKeyTooLong,
InvalidAttributeTypeError,
InvalidConversion,
InvalidIndexNameError,
MockValidationException,
RangeKeyTooLong,
SerializationException,
)
from moto.dynamodb.limits import HASH_KEY_MAX_LENGTH, RANGE_KEY_MAX_LENGTH
from moto.dynamodb.models.dynamo_type import DynamoType, Item
from moto.dynamodb.models.utilities import dynamo_json_dump
from moto.moto_api._internal import mock_random
from moto.utilities.utils import get_partition
RESULT_SIZE_LIMIT = 1000000 # DynamoDB has a 1MB size limit
DEFAULT_WARM_THROUGHPUT_RCU = 12000
DEFAULT_WARM_THROUGHPUT_WCU = 4000
class SecondaryIndex(BaseModel):
def __init__(
self,
index_name: str,
schema: list[dict[str, str]],
projection: dict[str, Any],
table_key_attrs: list[str],
):
self.name = index_name
self.schema = schema
self.table_key_attrs = table_key_attrs
self.projection = projection
self.schema_key_attrs = [k["AttributeName"] for k in schema]
def project(self, item: Item) -> Item:
"""
Enforces the ProjectionType of this Index (LSI/GSI)
Removes any non-wanted attributes from the item
:param item:
:return:
"""
if self.projection:
projection_type = self.projection.get("ProjectionType", None)
key_attributes = self.table_key_attrs + [
key["AttributeName"] for key in self.schema
]
if projection_type == "KEYS_ONLY":
# 'project' expects lists of lists of strings
# project([["attr1"], ["nested", "attr2"]]
#
# In our case, we need to convert
# ["key1", "key2"]
# into
# [["key1"], ["key2"]]
item = item.project([[attr] for attr in key_attributes])
elif projection_type == "INCLUDE":
allowed_attributes = key_attributes
allowed_attributes.extend(self.projection.get("NonKeyAttributes", []))
item = item.project([[attr] for attr in allowed_attributes])
# ALL is handled implicitly by not filtering
return item
class LocalSecondaryIndex(SecondaryIndex):
def describe(self) -> dict[str, Any]:
return {
"IndexName": self.name,
"KeySchema": self.schema,
"Projection": self.projection,
}
@staticmethod
def create( # type: ignore[misc]
dct: dict[str, Any], table_key_attrs: list[str]
) -> "LocalSecondaryIndex":
return LocalSecondaryIndex(
index_name=dct["IndexName"],
schema=dct["KeySchema"],
projection=dct["Projection"],
table_key_attrs=table_key_attrs,
)
class GlobalSecondaryIndex(SecondaryIndex):
def __init__(
self,
index_name: str,
schema: list[dict[str, str]],
projection: dict[str, Any],
table_key_attrs: list[str],
status: str = "ACTIVE",
throughput: Optional[dict[str, Any]] = None,
warm_throughput: Optional[dict[str, Any]] = None,
):
super().__init__(index_name, schema, projection, table_key_attrs)
self.status = status
if throughput:
self.throughput = throughput
self.warm_throughput = warm_throughput or {
"ReadUnitsPerSecond": throughput["ReadCapacityUnits"],
"WriteUnitsPerSecond": throughput["WriteCapacityUnits"],
}
else:
self.throughput = {
"ReadCapacityUnits": 0,
"WriteCapacityUnits": 0,
}
self.warm_throughput = warm_throughput or {
"ReadUnitsPerSecond": DEFAULT_WARM_THROUGHPUT_RCU,
"WriteUnitsPerSecond": DEFAULT_WARM_THROUGHPUT_WCU,
}
self.warm_throughput["Status"] = "ACTIVE"
def describe(self) -> dict[str, Any]:
return {
"IndexName": self.name,
"KeySchema": self.schema,
"Projection": self.projection,
"IndexStatus": self.status,
"ProvisionedThroughput": self.throughput,
"WarmThroughput": self.warm_throughput,
}
@staticmethod
def create( # type: ignore[misc]
dct: dict[str, Any], table_key_attrs: list[str]
) -> "GlobalSecondaryIndex":
return GlobalSecondaryIndex(
index_name=dct["IndexName"],
schema=dct["KeySchema"],
projection=dct["Projection"],
table_key_attrs=table_key_attrs,
throughput=dct.get("ProvisionedThroughput", None),
warm_throughput=dct.get("WarmThroughput", None),
)
def update(self, u: dict[str, Any]) -> None:
self.name = u.get("IndexName", self.name)
self.schema = u.get("KeySchema", self.schema)
self.projection = u.get("Projection", self.projection)
self.throughput = u.get("ProvisionedThroughput", self.throughput)
self.warm_throughput = u.get("WarmThroughput", self.warm_throughput)
self.warm_throughput["Status"] = "ACTIVE"
class StreamRecord(BaseModel):
def __init__(
self,
table: "Table",
stream_type: str,
event_name: str,
old: Optional[Item],
new: Optional[Item],
seq: int,
):
old_a = old.to_json()["Attributes"] if old is not None else {}
new_a = new.to_json()["Attributes"] if new is not None else {}
rec = old if old is not None else new
keys = {table.hash_key_attr: rec.hash_key.to_json()} # type: ignore[union-attr]
if table.range_key_attr is not None and rec is not None:
keys[table.range_key_attr] = rec.range_key.to_json() # type: ignore
self.record: dict[str, Any] = {
"eventID": mock_random.uuid4().hex,
"eventName": event_name,
"eventSource": "aws:dynamodb",
"eventVersion": "1.0",
"awsRegion": "us-east-1",
"dynamodb": {
"StreamViewType": stream_type,
"ApproximateCreationDateTime": utcnow().isoformat(),
"SequenceNumber": str(seq),
"SizeBytes": 1,
"Keys": keys,
},
}
if stream_type in ("NEW_IMAGE", "NEW_AND_OLD_IMAGES"):
self.record["dynamodb"]["NewImage"] = new_a
if stream_type in ("OLD_IMAGE", "NEW_AND_OLD_IMAGES"):
self.record["dynamodb"]["OldImage"] = old_a
# This is a substantial overestimate but it's the easiest to do now
self.record["dynamodb"]["SizeBytes"] = len(
dynamo_json_dump(self.record["dynamodb"])
)
def to_json(self) -> dict[str, Any]:
return self.record
class StreamShard(BaseModel):
def __init__(self, account_id: str, table: "Table"):
self.account_id = account_id
self.table = table
self.id = "shardId-00000001541626099285-f35f62ef"
self.starting_sequence_number = 1100000000017454423009
self.items: list[StreamRecord] = []
self.created_on = utcnow()
def to_json(self) -> dict[str, Any]:
return {
"ShardId": self.id,
"SequenceNumberRange": {
"StartingSequenceNumber": str(self.starting_sequence_number)
},
}
def add(self, old: Optional[Item], new: Optional[Item]) -> None:
t = self.table.stream_specification["StreamViewType"] # type: ignore
if old is None:
event_name = "INSERT"
elif new is None:
event_name = "REMOVE"
else:
event_name = "MODIFY"
seq = len(self.items) + self.starting_sequence_number
self.items.append(StreamRecord(self.table, t, event_name, old, new, seq))
result = None
from moto.awslambda.utils import get_backend
for arn, esm in self.table.lambda_event_source_mappings.items():
region = arn.split(":")[3]
result = get_backend(self.account_id, region).send_dynamodb_items(
arn, self.items, esm.event_source_arn
)
if result:
self.items = []
def get(self, start: int, quantity: int) -> list[dict[str, Any]]:
start -= self.starting_sequence_number
assert start >= 0
end = start + quantity
return [i.to_json() for i in self.items[start:end]]
class Table(CloudFormationModel):
def __init__(
self,
table_name: str,
account_id: str,
region: str,
schema: list[dict[str, Any]],
attr: list[dict[str, str]],
throughput: Optional[dict[str, int]] = None,
billing_mode: Optional[str] = None,
indexes: Optional[list[dict[str, Any]]] = None,
global_indexes: Optional[list[dict[str, Any]]] = None,
streams: Optional[dict[str, Any]] = None,
sse_specification: Optional[dict[str, Any]] = None,
tags: Optional[list[dict[str, str]]] = None,
deletion_protection_enabled: Optional[bool] = False,
warm_throughput: Optional[dict[str, Any]] = None,
):
self.name = table_name
self.account_id = account_id
self.region_name = region
self.attr = attr
self.schema = schema
self.range_key_attr: Optional[str] = None
self.hash_key_attr: str = ""
self.range_key_type: Optional[str] = None
self.hash_key_type: str = ""
for elem in schema:
attr_type = [
a["AttributeType"]
for a in attr
if a["AttributeName"] == elem["AttributeName"]
][0]
if elem["KeyType"] == "HASH":
self.hash_key_attr = elem["AttributeName"]
self.hash_key_type = attr_type
elif elem["KeyType"] == "RANGE":
self.range_key_attr = elem["AttributeName"]
self.range_key_type = attr_type
self.table_key_attrs = [
key for key in (self.hash_key_attr, self.range_key_attr) if key is not None
]
self.billing_mode = billing_mode
if throughput:
self.throughput = throughput
self.warm_throughput = warm_throughput or {
"ReadUnitsPerSecond": throughput["ReadCapacityUnits"],
"WriteUnitsPerSecond": throughput["WriteCapacityUnits"],
}
else:
self.throughput = {
"ReadCapacityUnits": 0,
"WriteCapacityUnits": 0,
}
self.warm_throughput = warm_throughput or {
"ReadUnitsPerSecond": DEFAULT_WARM_THROUGHPUT_RCU,
"WriteUnitsPerSecond": DEFAULT_WARM_THROUGHPUT_WCU,
}
self.throughput["NumberOfDecreasesToday"] = 0
self.warm_throughput["Status"] = "ACTIVE"
self.indexes = [
LocalSecondaryIndex.create(i, self.table_key_attrs)
for i in (indexes if indexes else [])
]
self.global_indexes = [
GlobalSecondaryIndex.create(i, self.table_key_attrs)
for i in (global_indexes if global_indexes else [])
]
self.created_at = utcnow()
self.items = defaultdict(dict) # type: ignore # [hash: DynamoType] or [hash: [range: DynamoType]]
self.table_arn = self._generate_arn(table_name)
self.tags = tags or []
self.ttl = {
"TimeToLiveStatus": "DISABLED" # One of 'ENABLING'|'DISABLING'|'ENABLED'|'DISABLED',
# 'AttributeName': 'string' # Can contain this
}
self.stream_specification: Optional[dict[str, Any]] = {"StreamEnabled": False}
self.latest_stream_label: Optional[str] = None
self.stream_shard: Optional[StreamShard] = None
self.set_stream_specification(streams)
self.lambda_event_source_mappings: dict[str, Any] = {}
self.continuous_backups: dict[str, Any] = {
"ContinuousBackupsStatus": "ENABLED", # One of 'ENABLED'|'DISABLED', it's enabled by default
"PointInTimeRecoveryDescription": {
"PointInTimeRecoveryStatus": "DISABLED" # One of 'ENABLED'|'DISABLED'
},
}
self.sse_specification = sse_specification
if self.sse_specification and "KMSMasterKeyId" not in self.sse_specification:
self.sse_specification["KMSMasterKeyId"] = self._get_default_encryption_key(
account_id, region
)
self.deletion_protection_enabled = deletion_protection_enabled
def _get_default_encryption_key(self, account_id: str, region: str) -> str:
from moto.kms import kms_backends
# https://aws.amazon.com/kms/features/#AWS_Service_Integration
# An AWS managed CMK is created automatically when you first create
# an encrypted resource using an AWS service integrated with KMS.
kms = kms_backends[account_id][region]
ddb_alias = "alias/aws/dynamodb"
if not kms.alias_exists(ddb_alias):
key = kms.create_key(
policy="",
key_usage="ENCRYPT_DECRYPT",
key_spec="SYMMETRIC_DEFAULT",
description="Default master key that protects my DynamoDB table storage",
tags=None,
)
kms.create_alias(key.id, ddb_alias)
ebs_key = kms.describe_key(ddb_alias)
return ebs_key.arn
@classmethod
def has_cfn_attr(cls, attr: str) -> bool:
return attr in ["Arn", "StreamArn"]
def get_cfn_attribute(self, attribute_name: str) -> Any:
from moto.cloudformation.exceptions import UnformattedGetAttTemplateException
if attribute_name == "Arn":
return self.table_arn
elif attribute_name == "StreamArn" and self.stream_specification:
return self.describe()["TableDescription"]["LatestStreamArn"]
raise UnformattedGetAttTemplateException()
@property
def physical_resource_id(self) -> str:
return self.name
@property
def attribute_keys(self) -> list[str]:
# A set of all the hash or range attributes for all indexes
def keys_from_index(idx: SecondaryIndex) -> list[str]:
schema = idx.schema
return [attr["AttributeName"] for attr in schema]
fieldnames = copy.copy(self.table_key_attrs)
for idx in self.indexes + self.global_indexes:
fieldnames += keys_from_index(idx)
return fieldnames
@staticmethod
def cloudformation_name_type() -> str:
return "TableName"
@staticmethod
def cloudformation_type() -> str:
# https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-dynamodb-table.html
return "AWS::DynamoDB::Table"
@classmethod
def create_from_cloudformation_json( # type: ignore[misc]
cls,
resource_name: str,
cloudformation_json: dict[str, Any],
account_id: str,
region_name: str,
**kwargs: Any,
) -> "Table":
from moto.dynamodb.models import dynamodb_backends
properties = cloudformation_json["Properties"]
params = {}
if "KeySchema" in properties:
params["schema"] = properties["KeySchema"]
if "AttributeDefinitions" in properties:
params["attr"] = properties["AttributeDefinitions"]
params["global_indexes"] = properties.get("GlobalSecondaryIndexes", [])
params["throughput"] = properties.get("ProvisionedThroughput")
params["indexes"] = properties.get("LocalSecondaryIndexes", [])
params["streams"] = properties.get("StreamSpecification")
params["tags"] = properties.get("Tags")
params["deletion_protection_enabled"] = properties.get(
"DeletionProtectionEnabled", False
)
params["sse_specification"] = properties.get("SSESpecification")
params["warm_throughput"] = properties.get("WarmThroughput")
billing_mode = (
"PAY_PER_REQUEST"
if properties.get("BillingMode") == "PAY_PER_REQUEST"
else "PROVISIONED"
)
params["billing_mode"] = billing_mode
table = dynamodb_backends[account_id][region_name].create_table(
name=resource_name, **params
)
return table
@classmethod
def delete_from_cloudformation_json( # type: ignore[misc]
cls,
resource_name: str,
cloudformation_json: dict[str, Any],
account_id: str,
region_name: str,
) -> None:
from moto.dynamodb.models import dynamodb_backends
dynamodb_backends[account_id][region_name].delete_table(name=resource_name)
def _generate_arn(self, name: str) -> str:
return f"arn:{get_partition(self.region_name)}:dynamodb:{self.region_name}:{self.account_id}:table/{name}"
def set_stream_specification(self, streams: Optional[dict[str, Any]]) -> None:
self.stream_specification = streams
if (
self.stream_specification
and streams
and (streams.get("StreamEnabled") or streams.get("StreamViewType"))
):
self.stream_specification["StreamEnabled"] = True
self.latest_stream_label = utcnow().isoformat()
self.stream_shard = StreamShard(self.account_id, self)
else:
self.stream_specification = {"StreamEnabled": False}
def describe(self, base_key: str = "TableDescription") -> dict[str, Any]:
results: dict[str, Any] = {
base_key: {
"AttributeDefinitions": self.attr,
"ProvisionedThroughput": self.throughput,
"BillingModeSummary": {"BillingMode": self.billing_mode},
"TableSizeBytes": 0,
"TableName": self.name,
"TableStatus": "ACTIVE",
"TableArn": self.table_arn,
"KeySchema": self.schema,
"ItemCount": len(self),
"CreationDateTime": unix_time(self.created_at),
"GlobalSecondaryIndexes": [
index.describe() for index in self.global_indexes
],
"LocalSecondaryIndexes": [index.describe() for index in self.indexes],
"DeletionProtectionEnabled": self.deletion_protection_enabled,
"WarmThroughput": self.warm_throughput,
}
}
if self.latest_stream_label:
results[base_key]["LatestStreamLabel"] = self.latest_stream_label
results[base_key]["LatestStreamArn"] = (
f"{self.table_arn}/stream/{self.latest_stream_label}"
)
if self.stream_specification and self.stream_specification["StreamEnabled"]:
results[base_key]["StreamSpecification"] = self.stream_specification
if self.sse_specification and self.sse_specification.get("Enabled") is True:
results[base_key]["SSEDescription"] = {
"Status": "ENABLED",
"SSEType": "KMS",
"KMSMasterKeyArn": self.sse_specification.get("KMSMasterKeyId"),
}
return results
def __len__(self) -> int:
return sum(
[(len(value) if self.has_range_key else 1) for value in self.items.values()]
)
@property
def hash_key_names(self) -> list[str]:
keys = [self.hash_key_attr]
for index in self.global_indexes:
for key in index.schema:
if key["KeyType"] == "HASH":
keys.append(key["AttributeName"])
return keys
@property
def range_key_names(self) -> list[str]:
keys = [self.range_key_attr] if self.has_range_key else []
for index in self.global_indexes:
for key in index.schema:
if key["KeyType"] == "RANGE":
keys.append(key["AttributeName"])
return keys # type: ignore[return-value]
def _validate_key_sizes(self, item_attrs: dict[str, Any]) -> None:
for hash_name in self.hash_key_names:
hash_value = item_attrs.get(hash_name)
if hash_value:
if DynamoType(hash_value).size() > HASH_KEY_MAX_LENGTH:
raise HashKeyTooLong
for range_name in self.range_key_names:
range_value = item_attrs.get(range_name)
if range_value:
if DynamoType(range_value).size() > RANGE_KEY_MAX_LENGTH:
raise RangeKeyTooLong
def _validate_item_types(
self, item_attrs: dict[str, Any], attr: Optional[str] = None
) -> None:
for key, value in item_attrs.items():
if isinstance(value, dict):
self._validate_item_types(value, attr=key if attr is None else key)
elif isinstance(value, int) and key == "N":
raise InvalidConversion
if key == "S":
# This scenario is usually caught by boto3, but the user can disable parameter validation
# Which is why we need to catch it 'server-side' as well
if isinstance(value, int):
raise SerializationException(
"NUMBER_VALUE cannot be converted to String"
)
if attr and attr in self.table_key_attrs and isinstance(value, dict):
raise SerializationException(
"Start of structure or map found where not expected"
)
def put_item(
self,
item_attrs: dict[str, Any],
expected: Optional[dict[str, Any]] = None,
condition_expression: Optional[str] = None,
expression_attribute_names: Optional[dict[str, str]] = None,
expression_attribute_values: Optional[dict[str, Any]] = None,
overwrite: bool = False,
return_values_on_condition_check_failure: Optional[str] = None,
) -> Item:
if self.hash_key_attr not in item_attrs.keys():
raise MockValidationException(
"One or more parameter values were invalid: Missing the key "
+ self.hash_key_attr
+ " in the item"
)
hash_value = DynamoType(item_attrs[self.hash_key_attr])
if self.range_key_attr is not None:
if self.range_key_attr not in item_attrs.keys():
raise MockValidationException(
f"One or more parameter values were invalid: Missing the key {self.range_key_attr} in the item"
)
range_value = DynamoType(item_attrs[self.range_key_attr])
else:
range_value = None
if hash_value.type != self.hash_key_type:
raise InvalidAttributeTypeError(
self.hash_key_attr,
expected_type=self.hash_key_type,
actual_type=hash_value.type,
)
if range_value and range_value.type != self.range_key_type:
raise InvalidAttributeTypeError(
self.range_key_attr,
expected_type=self.range_key_type,
actual_type=range_value.type,
)
self._validate_item_types(item_attrs)
self._validate_key_sizes(item_attrs)
if expected is None:
expected = {}
lookup_range_value = range_value
else:
expected_range_value = expected.get(self.range_key_attr, {}).get("Value") # type: ignore
if expected_range_value is None:
lookup_range_value = range_value
else:
lookup_range_value = DynamoType(expected_range_value)
current = self.get_item(hash_value, lookup_range_value)
item = Item(hash_value, range_value, item_attrs)
if not overwrite:
if not get_expected(expected).expr(current):
raise ConditionalCheckFailed
condition_op = get_filter_expression(
condition_expression,
expression_attribute_names,
expression_attribute_values,
)
if not condition_op.expr(current):
if (
return_values_on_condition_check_failure == "ALL_OLD"
and current is not None
):
raise ConditionalCheckFailed(item=current.to_json()["Attributes"])
else:
raise ConditionalCheckFailed
if range_value:
self.items[hash_value][range_value] = item
else:
self.items[hash_value] = item # type: ignore[assignment]
if self.stream_shard is not None:
self.stream_shard.add(current, item)
return item
def __nonzero__(self) -> bool:
return True
def __bool__(self) -> bool:
return self.__nonzero__()
@property
def has_range_key(self) -> bool:
return self.range_key_attr is not None
def get_item(
self,
hash_key: DynamoType,
range_key: Optional[DynamoType] = None,
projection_expression: Optional[list[list[str]]] = None,
) -> Optional[Item]:
if self.has_range_key and not range_key:
raise MockValidationException(
"Table has a range key, but no range key was passed into get_item"
)
try:
result = None
if range_key:
result = self.items[hash_key][range_key]
elif hash_key in self.items:
result = self.items[hash_key]
if projection_expression and result:
result = result.project(projection_expression)
return result
except KeyError:
return None
def delete_item(
self, hash_key: DynamoType, range_key: Optional[DynamoType]
) -> Optional[Item]:
try:
if range_key:
item = self.items[hash_key].pop(range_key)
else:
item = self.items.pop(hash_key)
if self.stream_shard is not None:
self.stream_shard.add(item, None)
return item
except KeyError:
return None
def query(
self,
hash_key: DynamoType,
range_comparison: Optional[str],
range_objs: list[DynamoType],
limit: int,
exclusive_start_key: dict[str, Any],
scan_index_forward: bool,
projection_expressions: Optional[list[list[str]]],
index_name: Optional[str] = None,
consistent_read: bool = False,
filter_expression: Any = None,
**filter_kwargs: Any,
) -> tuple[list[Item], int, Optional[dict[str, Any]]]:
# FIND POSSIBLE RESULTS
if index_name:
all_indexes = self.all_indexes()
indexes_by_name = {i.name: i for i in all_indexes}
if index_name not in indexes_by_name:
all_names = ", ".join(indexes_by_name.keys())
raise MockValidationException(
f"Invalid index: {index_name} for table: {self.name}. Available indexes are: {all_names}"
)
index = indexes_by_name[index_name]
if consistent_read and index in self.global_indexes:
raise MockValidationException(
"Consistent reads are not supported on global secondary indexes"
)
try:
index_hash_key = [
key for key in index.schema if key["KeyType"] == "HASH"
][0]
except IndexError:
raise MockValidationException(
f"Missing Hash Key. KeySchema: {index.name}"
)
try:
index_range_key = [
key for key in index.schema if key["KeyType"] == "RANGE"
][0]
except IndexError:
if isinstance(index, GlobalSecondaryIndex) and self.range_key_attr:
# If we're querying a GSI that does not have a range key, the main range key acts as a range key
index_range_key = {"AttributeName": self.range_key_attr}
else:
# If we don't have a range key on the main table either, the hash key acts as a range key
index_range_key = {"AttributeName": self.hash_key_attr}
if range_comparison:
raise ValueError(
f"Range Key comparison but no range key found for index: {index_name}"
)
hash_attrs = [index_hash_key["AttributeName"], self.hash_key_attr]
if index_range_key:
range_attrs = [
index_range_key["AttributeName"],
self.range_key_attr,
]
else:
range_attrs = [self.range_key_attr]
possible_results = []
for item in self.all_items():
if not isinstance(item, Item):
continue
item_hash_key = item.attrs.get(hash_attrs[0])
if len(range_attrs) == 1:
if item_hash_key and item_hash_key == hash_key:
possible_results.append(item)
else:
item_range_key = item.attrs.get(range_attrs[0]) # type: ignore
if item_hash_key and item_hash_key == hash_key and item_range_key:
possible_results.append(item)
else:
hash_attrs = [self.hash_key_attr]
range_attrs = [self.range_key_attr]
possible_results = [
item
for item in self.all_items()
if isinstance(item, Item) and item.hash_key == hash_key
]
# SORT
if index_name:
possible_results = self.sorted_items(
hash_attrs, range_attrs, possible_results
)
else:
possible_results.sort(key=lambda item: item.range_key) # type: ignore
if scan_index_forward is False:
possible_results.reverse()
# FILTER
results: list[Item] = []
result_size = 0
scanned_count = 0
last_evaluated_key = None
processing_previous_page = exclusive_start_key is not None
for result in possible_results:
# Cycle through the previous page of results
# When we encounter our start key, we know we've reached the end of the previous page
if processing_previous_page:
if self._item_comes_before_dct(
result,
exclusive_start_key,
hash_attrs,
range_attrs,
scan_index_forward,
):
continue
else:
processing_previous_page = False
# Check wether we've reached the limit of our result set
# That can be either in number, or in size
reached_length_limit = len(results) == limit
reached_size_limit = (result_size + result.size()) > RESULT_SIZE_LIMIT
if reached_length_limit or reached_size_limit:
last_evaluated_key = self._get_last_evaluated_key(
results[-1], index_name
)
break
if not range_comparison and not filter_kwargs:
# If we're not filtering on range key or on an index
results.append(result)
result_size += result.size()
scanned_count += 1
if range_comparison:
if (
index_name
and index_range_key
and result.attrs.get(index_range_key["AttributeName"])
):
if result.attrs.get(index_range_key["AttributeName"]).compare( # type: ignore
range_comparison, range_objs
):
results.append(result)
result_size += result.size()
scanned_count += 1
else:
if result.range_key.compare(range_comparison, range_objs): # type: ignore[union-attr]
results.append(result)
result_size += result.size()
scanned_count += 1
if filter_kwargs:
for field, value in filter_kwargs.items():
dynamo_types = [
DynamoType(ele) for ele in value["AttributeValueList"]
]
if result.attrs.get(field).compare( # type: ignore[union-attr]
value["ComparisonOperator"], dynamo_types
):
results.append(result)
result_size += result.size()
scanned_count += 1
results = copy.deepcopy(results)
if index_name:
index = self.get_index(index_name)
results = [index.project(r) for r in results]
if filter_expression is not None:
results = [item for item in results if filter_expression.expr(item)]
if projection_expressions:
results = [r.project(projection_expressions) for r in results]
return results, scanned_count, last_evaluated_key
def all_items(self) -> list[Item]:
items: list[Item] = []
for hash_set in self.items.values():
if self.range_key_attr:
for item in hash_set.values():
items.append(item)
else:
items.append(hash_set) # type: ignore
return sorted(
items,
key=lambda x: (x.hash_key, x.range_key) if x.range_key else x.hash_key,
)
def all_indexes(self) -> Sequence[SecondaryIndex]:
return (self.global_indexes or []) + (self.indexes or []) # type: ignore
def get_index(self, index_name: str, error_if_not: bool = False) -> SecondaryIndex:
all_indexes = self.all_indexes()
indexes_by_name = {i.name: i for i in all_indexes}
if error_if_not and index_name not in indexes_by_name:
raise InvalidIndexNameError(
f"The table does not have the specified index: {index_name}"
)
return indexes_by_name[index_name]
def has_idx_items(self, index_name: str) -> list[Item]:
idx = self.get_index(index_name)
idx_col_set = {i["AttributeName"] for i in idx.schema}
items: list[Item] = []
for hash_set in self.items.values():
if self.range_key_attr:
for item in hash_set.values():
if idx_col_set.issubset(set(item.attrs)):
items.append(item)
else:
if idx_col_set.issubset(set(hash_set.attrs)): # type: ignore
items.append(hash_set) # type: ignore
return items
def scan(
self,
filters: dict[str, Any],
limit: int,
exclusive_start_key: dict[str, Any],
filter_expression: Any = None,
index_name: Optional[str] = None,
consistent_read: bool = False,
projection_expression: Optional[list[list[str]]] = None,
segments: Union[tuple[None, None], tuple[int, int]] = (None, None),
) -> tuple[list[Item], int, Optional[dict[str, Any]]]:
results: list[Item] = []
result_size = 0
scanned_count = 0
if index_name:
index = self.get_index(index_name, error_if_not=True)
if consistent_read and index in self.global_indexes:
raise MockValidationException(
"Consistent reads are not supported on global secondary indexes"
)
try:
index_hash_key = [
key for key in index.schema if key["KeyType"] == "HASH"
][0]
except IndexError:
raise MockValidationException(
f"Missing Hash Key. KeySchema: {index.name}"
)
try:
index_range_key = [
key for key in index.schema if key["KeyType"] == "RANGE"
][0]
except IndexError:
index_range_key = None
hash_attrs = [index_hash_key["AttributeName"], self.hash_key_attr]
if index_range_key:
range_attrs = [index_range_key["AttributeName"], self.range_key_attr]
else:
range_attrs = [self.range_key_attr]
items = self.has_idx_items(index_name)
items = self.sorted_items(hash_attrs, range_attrs, items)
else:
hash_attrs = [self.hash_key_attr]
range_attrs = [self.range_key_attr]
items = self.all_items()
last_evaluated_key = None
processing_previous_page = exclusive_start_key is not None
for item in items:
if not item.is_within_segment(segments):
continue
# Cycle through the previous page of results
# When we encounter our start key, we know we've reached the end of the previous page
if processing_previous_page:
if self._item_comes_before_dct(
item,
exclusive_start_key,
hash_attrs,
range_attrs,
True,
):
continue
else:
processing_previous_page = False
# Check whether we've reached the limit of our result set
# That can be either in number, or in size
reached_length_limit = len(results) == limit
reached_size_limit = (result_size + item.size()) > RESULT_SIZE_LIMIT
if reached_length_limit or reached_size_limit:
last_evaluated_key = self._get_last_evaluated_key(
results[-1], index_name
)
break
passes_all_conditions = True
for attribute_name in filters:
attribute = item.attrs.get(attribute_name)
(comparison_operator, comparison_objs) = filters[attribute_name]
if attribute:
# Attribute found
if not attribute.compare(comparison_operator, comparison_objs):
passes_all_conditions = False
break
elif comparison_operator == "NULL":
# Comparison is NULL and we don't have the attribute
continue
else:
# No attribute found and comparison is no NULL. This item
# fails
passes_all_conditions = False
break
if passes_all_conditions:
if index_name:
index = self.get_index(index_name)
results.append(index.project(copy.deepcopy(item)))
else:
results.append(copy.deepcopy(item))
result_size += item.size()
scanned_count += 1
# https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Query.html#Query.FilterExpression
# the filter expression should be evaluated after the query.
if filter_expression is not None:
results = [item for item in results if filter_expression.expr(item)]
if projection_expression:
results = [r.project(projection_expression) for r in results]
return results, scanned_count, last_evaluated_key
def _item_comes_before_dct(
self,
item: Item,
dct: dict[str, Any],
hash_key_attrs: list[str],
range_key_attrs: list[Optional[str]],
scan_index_forward: bool,
) -> bool:
"""
Does item appear before or at dct relative to sort options?
hash_key_attrs: The list of hash keys.
Includes the key of the GSI (first, if it exists) and the key of the main table.
range_key_attrs: A list of range keys (RK).
Includes the RK-name of the GSI (first, if it exists) and the RK-name of the main table (second - can be None).
When sorting a GSI, we'll try to sort by the GSI RK first.
However, because GSI RK's are not unique (by design), item and dct can have the same RK-value
If that is the case, we compare by the RK of the main table instead
Related: https://github.com/getmoto/moto/issues/7761
"""
attrs_to_sort_by = self._generate_attr_to_sort_by(
hash_key_attrs, range_key_attrs
)
for attr in attrs_to_sort_by:
if attr in item.attrs and item.attrs[attr] != DynamoType(dct.get(attr)): # type: ignore
return (
(item.attrs[attr] < DynamoType(dct.get(attr))) # type: ignore
== scan_index_forward
)
# Keys were equal, items are identical
return True
def sorted_items(
self,
hash_key_attrs: list[str],
range_key_attrs: list[Optional[str]],
items: list[Item],
) -> list[Item]:
attrs_to_sort_by = self._generate_attr_to_sort_by(
hash_key_attrs, range_key_attrs
)
items.sort(
key=lambda x: tuple([x.attrs[key] for key in attrs_to_sort_by]),
)
return items
def _generate_attr_to_sort_by(
self, hash_key_attrs: list[str], range_key_attrs: list[Optional[str]]
) -> list[str]:
gsi_hash_key = hash_key_attrs[0] if len(hash_key_attrs) == 2 else None
table_hash_key = str(
hash_key_attrs[0] if gsi_hash_key is None else hash_key_attrs[1]
)
gsi_range_key = range_key_attrs[0] if len(range_key_attrs) == 2 else None
table_range_key = str(
range_key_attrs[0] if gsi_range_key is None else range_key_attrs[1]
)
# Gets the GSI and table hash and range keys in the order to try sorting by
attrs_to_sort_by = [
gsi_hash_key,
gsi_range_key,
table_hash_key,
table_range_key,
]
return [
attr for attr in attrs_to_sort_by if attr is not None and attr != "None"
]
def _get_last_evaluated_key(
self, last_result: Item, index_name: Optional[str]
) -> dict[str, Any]:
last_evaluated_key = {self.hash_key_attr: last_result.hash_key}
if self.range_key_attr is not None and last_result.range_key is not None:
last_evaluated_key[self.range_key_attr] = last_result.range_key
if index_name:
index = self.get_index(index_name)
idx_col_list = [i["AttributeName"] for i in index.schema]
for col in idx_col_list:
last_evaluated_key[col] = last_result.attrs[col]
return last_evaluated_key
def delete(self, account_id: str, region_name: str) -> None:
from moto.dynamodb.models import dynamodb_backends
dynamodb_backends[account_id][region_name].delete_table(self.name)
class Backup:
def __init__(
self,
account_id: str,
region_name: str,
name: str,
table: Table,
status: Optional[str] = None,
type_: Optional[str] = None,
):
self.region_name = region_name
self.account_id = account_id
self.name = name
self.table = copy.deepcopy(table)
self.status = status or "AVAILABLE"
self.type = type_ or "USER"
self.creation_date_time = utcnow()
self.identifier = self._make_identifier()
def _make_identifier(self) -> str:
timestamp = int(unix_time_millis(self.creation_date_time))
timestamp_padded = str("0" + str(timestamp))[-16:16]
guid = str(mock_random.uuid4())
guid_shortened = guid[:8]
return f"{timestamp_padded}-{guid_shortened}"
@property
def arn(self) -> str:
return f"arn:{get_partition(self.region_name)}:dynamodb:{self.region_name}:{self.account_id}:table/{self.table.name}/backup/{self.identifier}"
@property
def details(self) -> dict[str, Any]: # type: ignore[misc]
return {
"BackupArn": self.arn,
"BackupName": self.name,
"BackupSizeBytes": 123,
"BackupStatus": self.status,
"BackupType": self.type,
"BackupCreationDateTime": unix_time(self.creation_date_time),
}
@property
def summary(self) -> dict[str, Any]: # type: ignore[misc]
return {
"TableName": self.table.name,
# 'TableId': 'string',
"TableArn": self.table.table_arn,
"BackupArn": self.arn,
"BackupName": self.name,
"BackupCreationDateTime": unix_time(self.creation_date_time),
# 'BackupExpiryDateTime': datetime(2015, 1, 1),
"BackupStatus": self.status,
"BackupType": self.type,
"BackupSizeBytes": 123,
}
@property
def description(self) -> dict[str, Any]: # type: ignore[misc]
source_table_details = self.table.describe()["TableDescription"]
source_table_details["TableCreationDateTime"] = source_table_details[
"CreationDateTime"
]
description = {
"BackupDetails": self.details,
"SourceTableDetails": source_table_details,
}
return description
class RestoredTable(Table):
def __init__(self, name: str, account_id: str, region: str, backup: "Backup"):
params = self._parse_params_from_backup(backup)
super().__init__(name, account_id=account_id, region=region, **params)
self.indexes = copy.deepcopy(backup.table.indexes)
self.global_indexes = copy.deepcopy(backup.table.global_indexes)
self.items = copy.deepcopy(backup.table.items)
# Restore Attrs
self.source_backup_arn = backup.arn
self.source_table_arn = backup.table.table_arn
self.restore_date_time = self.created_at
def _parse_params_from_backup(self, backup: "Backup") -> dict[str, Any]:
return {
"schema": copy.deepcopy(backup.table.schema),
"attr": copy.deepcopy(backup.table.attr),
"throughput": copy.deepcopy(backup.table.throughput),
}
def describe(self, base_key: str = "TableDescription") -> dict[str, Any]:
result = super().describe(base_key=base_key)
result[base_key]["RestoreSummary"] = {
"SourceBackupArn": self.source_backup_arn,
"SourceTableArn": self.source_table_arn,
"RestoreDateTime": unix_time(self.restore_date_time),
"RestoreInProgress": False,
}
return result
class RestoredPITTable(Table):
def __init__(self, name: str, account_id: str, region: str, source: Table):
params = self._parse_params_from_table(source)
super().__init__(name, account_id=account_id, region=region, **params)
self.indexes = copy.deepcopy(source.indexes)
self.global_indexes = copy.deepcopy(source.global_indexes)
self.items = copy.deepcopy(source.items)
# Restore Attrs
self.source_table_arn = source.table_arn
self.restore_date_time = self.created_at
def _parse_params_from_table(self, table: Table) -> dict[str, Any]:
return {
"schema": copy.deepcopy(table.schema),
"attr": copy.deepcopy(table.attr),
"throughput": copy.deepcopy(table.throughput),
}
def describe(self, base_key: str = "TableDescription") -> dict[str, Any]:
result = super().describe(base_key=base_key)
result[base_key]["RestoreSummary"] = {
"SourceTableArn": self.source_table_arn,
"RestoreDateTime": unix_time(self.restore_date_time),
"RestoreInProgress": False,
}
return result
class ResourcePolicy:
def __init__(self, resource_arn: str, policy_doc: str):
self.resource_arn = resource_arn
self.policy_doc = policy_doc
self.revision_id = str(int(unix_time_millis()))
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