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googleapis/google-cloud-python
|
firestore/google/cloud/firestore_v1beta1/collection.py
|
CollectionReference.document
|
def document(self, document_id=None):
"""Create a sub-document underneath the current collection.
Args:
document_id (Optional[str]): The document identifier
within the current collection. If not provided, will default
to a random 20 character string composed of digits,
uppercase and lowercase and letters.
Returns:
~.firestore_v1beta1.document.DocumentReference: The child
document.
"""
if document_id is None:
document_id = _auto_id()
child_path = self._path + (document_id,)
return self._client.document(*child_path)
|
python
|
def document(self, document_id=None):
"""Create a sub-document underneath the current collection.
Args:
document_id (Optional[str]): The document identifier
within the current collection. If not provided, will default
to a random 20 character string composed of digits,
uppercase and lowercase and letters.
Returns:
~.firestore_v1beta1.document.DocumentReference: The child
document.
"""
if document_id is None:
document_id = _auto_id()
child_path = self._path + (document_id,)
return self._client.document(*child_path)
|
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Create a sub-document underneath the current collection.
Args:
document_id (Optional[str]): The document identifier
within the current collection. If not provided, will default
to a random 20 character string composed of digits,
uppercase and lowercase and letters.
Returns:
~.firestore_v1beta1.document.DocumentReference: The child
document.
|
[
"Create",
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"sub",
"-",
"document",
"underneath",
"the",
"current",
"collection",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/firestore/google/cloud/firestore_v1beta1/collection.py#L94-L111
|
train
|
googleapis/google-cloud-python
|
firestore/google/cloud/firestore_v1beta1/collection.py
|
CollectionReference._parent_info
|
def _parent_info(self):
"""Get fully-qualified parent path and prefix for this collection.
Returns:
Tuple[str, str]: Pair of
* the fully-qualified (with database and project) path to the
parent of this collection (will either be the database path
or a document path).
* the prefix to a document in this collection.
"""
parent_doc = self.parent
if parent_doc is None:
parent_path = _helpers.DOCUMENT_PATH_DELIMITER.join(
(self._client._database_string, "documents")
)
else:
parent_path = parent_doc._document_path
expected_prefix = _helpers.DOCUMENT_PATH_DELIMITER.join((parent_path, self.id))
return parent_path, expected_prefix
|
python
|
def _parent_info(self):
"""Get fully-qualified parent path and prefix for this collection.
Returns:
Tuple[str, str]: Pair of
* the fully-qualified (with database and project) path to the
parent of this collection (will either be the database path
or a document path).
* the prefix to a document in this collection.
"""
parent_doc = self.parent
if parent_doc is None:
parent_path = _helpers.DOCUMENT_PATH_DELIMITER.join(
(self._client._database_string, "documents")
)
else:
parent_path = parent_doc._document_path
expected_prefix = _helpers.DOCUMENT_PATH_DELIMITER.join((parent_path, self.id))
return parent_path, expected_prefix
|
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Get fully-qualified parent path and prefix for this collection.
Returns:
Tuple[str, str]: Pair of
* the fully-qualified (with database and project) path to the
parent of this collection (will either be the database path
or a document path).
* the prefix to a document in this collection.
|
[
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"-",
"qualified",
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"path",
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"prefix",
"for",
"this",
"collection",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/firestore/google/cloud/firestore_v1beta1/collection.py#L113-L133
|
train
|
googleapis/google-cloud-python
|
firestore/google/cloud/firestore_v1beta1/collection.py
|
CollectionReference.add
|
def add(self, document_data, document_id=None):
"""Create a document in the Firestore database with the provided data.
Args:
document_data (dict): Property names and values to use for
creating the document.
document_id (Optional[str]): The document identifier within the
current collection. If not provided, an ID will be
automatically assigned by the server (the assigned ID will be
a random 20 character string composed of digits,
uppercase and lowercase letters).
Returns:
Tuple[google.protobuf.timestamp_pb2.Timestamp, \
~.firestore_v1beta1.document.DocumentReference]: Pair of
* The ``update_time`` when the document was created (or
overwritten).
* A document reference for the created document.
Raises:
~google.cloud.exceptions.Conflict: If ``document_id`` is provided
and the document already exists.
"""
if document_id is None:
parent_path, expected_prefix = self._parent_info()
document_pb = document_pb2.Document()
created_document_pb = self._client._firestore_api.create_document(
parent_path,
collection_id=self.id,
document_id=None,
document=document_pb,
mask=None,
metadata=self._client._rpc_metadata,
)
new_document_id = _helpers.get_doc_id(created_document_pb, expected_prefix)
document_ref = self.document(new_document_id)
set_result = document_ref.set(document_data)
return set_result.update_time, document_ref
else:
document_ref = self.document(document_id)
write_result = document_ref.create(document_data)
return write_result.update_time, document_ref
|
python
|
def add(self, document_data, document_id=None):
"""Create a document in the Firestore database with the provided data.
Args:
document_data (dict): Property names and values to use for
creating the document.
document_id (Optional[str]): The document identifier within the
current collection. If not provided, an ID will be
automatically assigned by the server (the assigned ID will be
a random 20 character string composed of digits,
uppercase and lowercase letters).
Returns:
Tuple[google.protobuf.timestamp_pb2.Timestamp, \
~.firestore_v1beta1.document.DocumentReference]: Pair of
* The ``update_time`` when the document was created (or
overwritten).
* A document reference for the created document.
Raises:
~google.cloud.exceptions.Conflict: If ``document_id`` is provided
and the document already exists.
"""
if document_id is None:
parent_path, expected_prefix = self._parent_info()
document_pb = document_pb2.Document()
created_document_pb = self._client._firestore_api.create_document(
parent_path,
collection_id=self.id,
document_id=None,
document=document_pb,
mask=None,
metadata=self._client._rpc_metadata,
)
new_document_id = _helpers.get_doc_id(created_document_pb, expected_prefix)
document_ref = self.document(new_document_id)
set_result = document_ref.set(document_data)
return set_result.update_time, document_ref
else:
document_ref = self.document(document_id)
write_result = document_ref.create(document_data)
return write_result.update_time, document_ref
|
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"(",
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"return",
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Create a document in the Firestore database with the provided data.
Args:
document_data (dict): Property names and values to use for
creating the document.
document_id (Optional[str]): The document identifier within the
current collection. If not provided, an ID will be
automatically assigned by the server (the assigned ID will be
a random 20 character string composed of digits,
uppercase and lowercase letters).
Returns:
Tuple[google.protobuf.timestamp_pb2.Timestamp, \
~.firestore_v1beta1.document.DocumentReference]: Pair of
* The ``update_time`` when the document was created (or
overwritten).
* A document reference for the created document.
Raises:
~google.cloud.exceptions.Conflict: If ``document_id`` is provided
and the document already exists.
|
[
"Create",
"a",
"document",
"in",
"the",
"Firestore",
"database",
"with",
"the",
"provided",
"data",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/firestore/google/cloud/firestore_v1beta1/collection.py#L135-L180
|
train
|
googleapis/google-cloud-python
|
firestore/google/cloud/firestore_v1beta1/collection.py
|
CollectionReference.list_documents
|
def list_documents(self, page_size=None):
"""List all subdocuments of the current collection.
Args:
page_size (Optional[int]]): The maximum number of documents
in each page of results from this request. Non-positive values
are ignored. Defaults to a sensible value set by the API.
Returns:
Sequence[~.firestore_v1beta1.collection.DocumentReference]:
iterator of subdocuments of the current collection. If the
collection does not exist at the time of `snapshot`, the
iterator will be empty
"""
parent, _ = self._parent_info()
iterator = self._client._firestore_api.list_documents(
parent,
self.id,
page_size=page_size,
show_missing=True,
metadata=self._client._rpc_metadata,
)
iterator.collection = self
iterator.item_to_value = _item_to_document_ref
return iterator
|
python
|
def list_documents(self, page_size=None):
"""List all subdocuments of the current collection.
Args:
page_size (Optional[int]]): The maximum number of documents
in each page of results from this request. Non-positive values
are ignored. Defaults to a sensible value set by the API.
Returns:
Sequence[~.firestore_v1beta1.collection.DocumentReference]:
iterator of subdocuments of the current collection. If the
collection does not exist at the time of `snapshot`, the
iterator will be empty
"""
parent, _ = self._parent_info()
iterator = self._client._firestore_api.list_documents(
parent,
self.id,
page_size=page_size,
show_missing=True,
metadata=self._client._rpc_metadata,
)
iterator.collection = self
iterator.item_to_value = _item_to_document_ref
return iterator
|
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List all subdocuments of the current collection.
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page_size (Optional[int]]): The maximum number of documents
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Returns:
Sequence[~.firestore_v1beta1.collection.DocumentReference]:
iterator of subdocuments of the current collection. If the
collection does not exist at the time of `snapshot`, the
iterator will be empty
|
[
"List",
"all",
"subdocuments",
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"the",
"current",
"collection",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/firestore/google/cloud/firestore_v1beta1/collection.py#L182-L207
|
train
|
googleapis/google-cloud-python
|
firestore/google/cloud/firestore_v1beta1/collection.py
|
CollectionReference.select
|
def select(self, field_paths):
"""Create a "select" query with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.select` for
more information on this method.
Args:
field_paths (Iterable[str, ...]): An iterable of field paths
(``.``-delimited list of field names) to use as a projection
of document fields in the query results.
Returns:
~.firestore_v1beta1.query.Query: A "projected" query.
"""
query = query_mod.Query(self)
return query.select(field_paths)
|
python
|
def select(self, field_paths):
"""Create a "select" query with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.select` for
more information on this method.
Args:
field_paths (Iterable[str, ...]): An iterable of field paths
(``.``-delimited list of field names) to use as a projection
of document fields in the query results.
Returns:
~.firestore_v1beta1.query.Query: A "projected" query.
"""
query = query_mod.Query(self)
return query.select(field_paths)
|
[
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Create a "select" query with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.select` for
more information on this method.
Args:
field_paths (Iterable[str, ...]): An iterable of field paths
(``.``-delimited list of field names) to use as a projection
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Returns:
~.firestore_v1beta1.query.Query: A "projected" query.
|
[
"Create",
"a",
"select",
"query",
"with",
"this",
"collection",
"as",
"parent",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/firestore/google/cloud/firestore_v1beta1/collection.py#L209-L225
|
train
|
googleapis/google-cloud-python
|
firestore/google/cloud/firestore_v1beta1/collection.py
|
CollectionReference.where
|
def where(self, field_path, op_string, value):
"""Create a "where" query with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.where` for
more information on this method.
Args:
field_path (str): A field path (``.``-delimited list of
field names) for the field to filter on.
op_string (str): A comparison operation in the form of a string.
Acceptable values are ``<``, ``<=``, ``==``, ``>=``
and ``>``.
value (Any): The value to compare the field against in the filter.
If ``value`` is :data:`None` or a NaN, then ``==`` is the only
allowed operation.
Returns:
~.firestore_v1beta1.query.Query: A filtered query.
"""
query = query_mod.Query(self)
return query.where(field_path, op_string, value)
|
python
|
def where(self, field_path, op_string, value):
"""Create a "where" query with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.where` for
more information on this method.
Args:
field_path (str): A field path (``.``-delimited list of
field names) for the field to filter on.
op_string (str): A comparison operation in the form of a string.
Acceptable values are ``<``, ``<=``, ``==``, ``>=``
and ``>``.
value (Any): The value to compare the field against in the filter.
If ``value`` is :data:`None` or a NaN, then ``==`` is the only
allowed operation.
Returns:
~.firestore_v1beta1.query.Query: A filtered query.
"""
query = query_mod.Query(self)
return query.where(field_path, op_string, value)
|
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Create a "where" query with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.where` for
more information on this method.
Args:
field_path (str): A field path (``.``-delimited list of
field names) for the field to filter on.
op_string (str): A comparison operation in the form of a string.
Acceptable values are ``<``, ``<=``, ``==``, ``>=``
and ``>``.
value (Any): The value to compare the field against in the filter.
If ``value`` is :data:`None` or a NaN, then ``==`` is the only
allowed operation.
Returns:
~.firestore_v1beta1.query.Query: A filtered query.
|
[
"Create",
"a",
"where",
"query",
"with",
"this",
"collection",
"as",
"parent",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/firestore/google/cloud/firestore_v1beta1/collection.py#L227-L248
|
train
|
googleapis/google-cloud-python
|
firestore/google/cloud/firestore_v1beta1/collection.py
|
CollectionReference.order_by
|
def order_by(self, field_path, **kwargs):
"""Create an "order by" query with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.order_by` for
more information on this method.
Args:
field_path (str): A field path (``.``-delimited list of
field names) on which to order the query results.
kwargs (Dict[str, Any]): The keyword arguments to pass along
to the query. The only supported keyword is ``direction``,
see :meth:`~.firestore_v1beta1.query.Query.order_by` for
more information.
Returns:
~.firestore_v1beta1.query.Query: An "order by" query.
"""
query = query_mod.Query(self)
return query.order_by(field_path, **kwargs)
|
python
|
def order_by(self, field_path, **kwargs):
"""Create an "order by" query with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.order_by` for
more information on this method.
Args:
field_path (str): A field path (``.``-delimited list of
field names) on which to order the query results.
kwargs (Dict[str, Any]): The keyword arguments to pass along
to the query. The only supported keyword is ``direction``,
see :meth:`~.firestore_v1beta1.query.Query.order_by` for
more information.
Returns:
~.firestore_v1beta1.query.Query: An "order by" query.
"""
query = query_mod.Query(self)
return query.order_by(field_path, **kwargs)
|
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Create an "order by" query with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.order_by` for
more information on this method.
Args:
field_path (str): A field path (``.``-delimited list of
field names) on which to order the query results.
kwargs (Dict[str, Any]): The keyword arguments to pass along
to the query. The only supported keyword is ``direction``,
see :meth:`~.firestore_v1beta1.query.Query.order_by` for
more information.
Returns:
~.firestore_v1beta1.query.Query: An "order by" query.
|
[
"Create",
"an",
"order",
"by",
"query",
"with",
"this",
"collection",
"as",
"parent",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/firestore/google/cloud/firestore_v1beta1/collection.py#L250-L269
|
train
|
googleapis/google-cloud-python
|
firestore/google/cloud/firestore_v1beta1/collection.py
|
CollectionReference.limit
|
def limit(self, count):
"""Create a limited query with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.limit` for
more information on this method.
Args:
count (int): Maximum number of documents to return that match
the query.
Returns:
~.firestore_v1beta1.query.Query: A limited query.
"""
query = query_mod.Query(self)
return query.limit(count)
|
python
|
def limit(self, count):
"""Create a limited query with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.limit` for
more information on this method.
Args:
count (int): Maximum number of documents to return that match
the query.
Returns:
~.firestore_v1beta1.query.Query: A limited query.
"""
query = query_mod.Query(self)
return query.limit(count)
|
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"limit",
"(",
"count",
")"
] |
Create a limited query with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.limit` for
more information on this method.
Args:
count (int): Maximum number of documents to return that match
the query.
Returns:
~.firestore_v1beta1.query.Query: A limited query.
|
[
"Create",
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"limited",
"query",
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"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/firestore/google/cloud/firestore_v1beta1/collection.py#L271-L286
|
train
|
googleapis/google-cloud-python
|
firestore/google/cloud/firestore_v1beta1/collection.py
|
CollectionReference.offset
|
def offset(self, num_to_skip):
"""Skip to an offset in a query with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.offset` for
more information on this method.
Args:
num_to_skip (int): The number of results to skip at the beginning
of query results. (Must be non-negative.)
Returns:
~.firestore_v1beta1.query.Query: An offset query.
"""
query = query_mod.Query(self)
return query.offset(num_to_skip)
|
python
|
def offset(self, num_to_skip):
"""Skip to an offset in a query with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.offset` for
more information on this method.
Args:
num_to_skip (int): The number of results to skip at the beginning
of query results. (Must be non-negative.)
Returns:
~.firestore_v1beta1.query.Query: An offset query.
"""
query = query_mod.Query(self)
return query.offset(num_to_skip)
|
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")",
"return",
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] |
Skip to an offset in a query with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.offset` for
more information on this method.
Args:
num_to_skip (int): The number of results to skip at the beginning
of query results. (Must be non-negative.)
Returns:
~.firestore_v1beta1.query.Query: An offset query.
|
[
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/firestore/google/cloud/firestore_v1beta1/collection.py#L288-L303
|
train
|
googleapis/google-cloud-python
|
firestore/google/cloud/firestore_v1beta1/collection.py
|
CollectionReference.start_at
|
def start_at(self, document_fields):
"""Start query at a cursor with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.start_at` for
more information on this method.
Args:
document_fields (Union[~.firestore_v1beta1.\
document.DocumentSnapshot, dict, list, tuple]): a document
snapshot or a dictionary/list/tuple of fields representing a
query results cursor. A cursor is a collection of values that
represent a position in a query result set.
Returns:
~.firestore_v1beta1.query.Query: A query with cursor.
"""
query = query_mod.Query(self)
return query.start_at(document_fields)
|
python
|
def start_at(self, document_fields):
"""Start query at a cursor with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.start_at` for
more information on this method.
Args:
document_fields (Union[~.firestore_v1beta1.\
document.DocumentSnapshot, dict, list, tuple]): a document
snapshot or a dictionary/list/tuple of fields representing a
query results cursor. A cursor is a collection of values that
represent a position in a query result set.
Returns:
~.firestore_v1beta1.query.Query: A query with cursor.
"""
query = query_mod.Query(self)
return query.start_at(document_fields)
|
[
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".",
"start_at",
"(",
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")"
] |
Start query at a cursor with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.start_at` for
more information on this method.
Args:
document_fields (Union[~.firestore_v1beta1.\
document.DocumentSnapshot, dict, list, tuple]): a document
snapshot or a dictionary/list/tuple of fields representing a
query results cursor. A cursor is a collection of values that
represent a position in a query result set.
Returns:
~.firestore_v1beta1.query.Query: A query with cursor.
|
[
"Start",
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"cursor",
"with",
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"as",
"parent",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/firestore/google/cloud/firestore_v1beta1/collection.py#L305-L323
|
train
|
googleapis/google-cloud-python
|
firestore/google/cloud/firestore_v1beta1/collection.py
|
CollectionReference.start_after
|
def start_after(self, document_fields):
"""Start query after a cursor with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.start_after` for
more information on this method.
Args:
document_fields (Union[~.firestore_v1beta1.\
document.DocumentSnapshot, dict, list, tuple]): a document
snapshot or a dictionary/list/tuple of fields representing a
query results cursor. A cursor is a collection of values that
represent a position in a query result set.
Returns:
~.firestore_v1beta1.query.Query: A query with cursor.
"""
query = query_mod.Query(self)
return query.start_after(document_fields)
|
python
|
def start_after(self, document_fields):
"""Start query after a cursor with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.start_after` for
more information on this method.
Args:
document_fields (Union[~.firestore_v1beta1.\
document.DocumentSnapshot, dict, list, tuple]): a document
snapshot or a dictionary/list/tuple of fields representing a
query results cursor. A cursor is a collection of values that
represent a position in a query result set.
Returns:
~.firestore_v1beta1.query.Query: A query with cursor.
"""
query = query_mod.Query(self)
return query.start_after(document_fields)
|
[
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"return",
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"start_after",
"(",
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")"
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Start query after a cursor with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.start_after` for
more information on this method.
Args:
document_fields (Union[~.firestore_v1beta1.\
document.DocumentSnapshot, dict, list, tuple]): a document
snapshot or a dictionary/list/tuple of fields representing a
query results cursor. A cursor is a collection of values that
represent a position in a query result set.
Returns:
~.firestore_v1beta1.query.Query: A query with cursor.
|
[
"Start",
"query",
"after",
"a",
"cursor",
"with",
"this",
"collection",
"as",
"parent",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/firestore/google/cloud/firestore_v1beta1/collection.py#L325-L343
|
train
|
googleapis/google-cloud-python
|
firestore/google/cloud/firestore_v1beta1/collection.py
|
CollectionReference.end_before
|
def end_before(self, document_fields):
"""End query before a cursor with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.end_before` for
more information on this method.
Args:
document_fields (Union[~.firestore_v1beta1.\
document.DocumentSnapshot, dict, list, tuple]): a document
snapshot or a dictionary/list/tuple of fields representing a
query results cursor. A cursor is a collection of values that
represent a position in a query result set.
Returns:
~.firestore_v1beta1.query.Query: A query with cursor.
"""
query = query_mod.Query(self)
return query.end_before(document_fields)
|
python
|
def end_before(self, document_fields):
"""End query before a cursor with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.end_before` for
more information on this method.
Args:
document_fields (Union[~.firestore_v1beta1.\
document.DocumentSnapshot, dict, list, tuple]): a document
snapshot or a dictionary/list/tuple of fields representing a
query results cursor. A cursor is a collection of values that
represent a position in a query result set.
Returns:
~.firestore_v1beta1.query.Query: A query with cursor.
"""
query = query_mod.Query(self)
return query.end_before(document_fields)
|
[
"def",
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"self",
")",
"return",
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".",
"end_before",
"(",
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")"
] |
End query before a cursor with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.end_before` for
more information on this method.
Args:
document_fields (Union[~.firestore_v1beta1.\
document.DocumentSnapshot, dict, list, tuple]): a document
snapshot or a dictionary/list/tuple of fields representing a
query results cursor. A cursor is a collection of values that
represent a position in a query result set.
Returns:
~.firestore_v1beta1.query.Query: A query with cursor.
|
[
"End",
"query",
"before",
"a",
"cursor",
"with",
"this",
"collection",
"as",
"parent",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/firestore/google/cloud/firestore_v1beta1/collection.py#L345-L363
|
train
|
googleapis/google-cloud-python
|
firestore/google/cloud/firestore_v1beta1/collection.py
|
CollectionReference.end_at
|
def end_at(self, document_fields):
"""End query at a cursor with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.end_at` for
more information on this method.
Args:
document_fields (Union[~.firestore_v1beta1.\
document.DocumentSnapshot, dict, list, tuple]): a document
snapshot or a dictionary/list/tuple of fields representing a
query results cursor. A cursor is a collection of values that
represent a position in a query result set.
Returns:
~.firestore_v1beta1.query.Query: A query with cursor.
"""
query = query_mod.Query(self)
return query.end_at(document_fields)
|
python
|
def end_at(self, document_fields):
"""End query at a cursor with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.end_at` for
more information on this method.
Args:
document_fields (Union[~.firestore_v1beta1.\
document.DocumentSnapshot, dict, list, tuple]): a document
snapshot or a dictionary/list/tuple of fields representing a
query results cursor. A cursor is a collection of values that
represent a position in a query result set.
Returns:
~.firestore_v1beta1.query.Query: A query with cursor.
"""
query = query_mod.Query(self)
return query.end_at(document_fields)
|
[
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"return",
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".",
"end_at",
"(",
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")"
] |
End query at a cursor with this collection as parent.
See
:meth:`~.firestore_v1beta1.query.Query.end_at` for
more information on this method.
Args:
document_fields (Union[~.firestore_v1beta1.\
document.DocumentSnapshot, dict, list, tuple]): a document
snapshot or a dictionary/list/tuple of fields representing a
query results cursor. A cursor is a collection of values that
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Returns:
~.firestore_v1beta1.query.Query: A query with cursor.
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[
"End",
"query",
"at",
"a",
"cursor",
"with",
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"collection",
"as",
"parent",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/firestore/google/cloud/firestore_v1beta1/collection.py#L365-L383
|
train
|
googleapis/google-cloud-python
|
firestore/google/cloud/firestore_v1beta1/collection.py
|
CollectionReference.stream
|
def stream(self, transaction=None):
"""Read the documents in this collection.
This sends a ``RunQuery`` RPC and then returns an iterator which
consumes each document returned in the stream of ``RunQueryResponse``
messages.
.. note::
The underlying stream of responses will time out after
the ``max_rpc_timeout_millis`` value set in the GAPIC
client configuration for the ``RunQuery`` API. Snapshots
not consumed from the iterator before that point will be lost.
If a ``transaction`` is used and it already has write operations
added, this method cannot be used (i.e. read-after-write is not
allowed).
Args:
transaction (Optional[~.firestore_v1beta1.transaction.\
Transaction]): An existing transaction that the query will
run in.
Yields:
~.firestore_v1beta1.document.DocumentSnapshot: The next
document that fulfills the query.
"""
query = query_mod.Query(self)
return query.stream(transaction=transaction)
|
python
|
def stream(self, transaction=None):
"""Read the documents in this collection.
This sends a ``RunQuery`` RPC and then returns an iterator which
consumes each document returned in the stream of ``RunQueryResponse``
messages.
.. note::
The underlying stream of responses will time out after
the ``max_rpc_timeout_millis`` value set in the GAPIC
client configuration for the ``RunQuery`` API. Snapshots
not consumed from the iterator before that point will be lost.
If a ``transaction`` is used and it already has write operations
added, this method cannot be used (i.e. read-after-write is not
allowed).
Args:
transaction (Optional[~.firestore_v1beta1.transaction.\
Transaction]): An existing transaction that the query will
run in.
Yields:
~.firestore_v1beta1.document.DocumentSnapshot: The next
document that fulfills the query.
"""
query = query_mod.Query(self)
return query.stream(transaction=transaction)
|
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Read the documents in this collection.
This sends a ``RunQuery`` RPC and then returns an iterator which
consumes each document returned in the stream of ``RunQueryResponse``
messages.
.. note::
The underlying stream of responses will time out after
the ``max_rpc_timeout_millis`` value set in the GAPIC
client configuration for the ``RunQuery`` API. Snapshots
not consumed from the iterator before that point will be lost.
If a ``transaction`` is used and it already has write operations
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Args:
transaction (Optional[~.firestore_v1beta1.transaction.\
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Yields:
~.firestore_v1beta1.document.DocumentSnapshot: The next
document that fulfills the query.
|
[
"Read",
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/firestore/google/cloud/firestore_v1beta1/collection.py#L394-L422
|
train
|
googleapis/google-cloud-python
|
translate/google/cloud/translate_v2/client.py
|
Client.get_languages
|
def get_languages(self, target_language=None):
"""Get list of supported languages for translation.
Response
See
https://cloud.google.com/translate/docs/discovering-supported-languages
:type target_language: str
:param target_language: (Optional) The language used to localize
returned language names. Defaults to the
target language on the current client.
:rtype: list
:returns: List of dictionaries. Each dictionary contains a supported
ISO 639-1 language code (using the dictionary key
``language``). If ``target_language`` is passed, each
dictionary will also contain the name of each supported
language (localized to the target language).
"""
query_params = {}
if target_language is None:
target_language = self.target_language
if target_language is not None:
query_params["target"] = target_language
response = self._connection.api_request(
method="GET", path="/languages", query_params=query_params
)
return response.get("data", {}).get("languages", ())
|
python
|
def get_languages(self, target_language=None):
"""Get list of supported languages for translation.
Response
See
https://cloud.google.com/translate/docs/discovering-supported-languages
:type target_language: str
:param target_language: (Optional) The language used to localize
returned language names. Defaults to the
target language on the current client.
:rtype: list
:returns: List of dictionaries. Each dictionary contains a supported
ISO 639-1 language code (using the dictionary key
``language``). If ``target_language`` is passed, each
dictionary will also contain the name of each supported
language (localized to the target language).
"""
query_params = {}
if target_language is None:
target_language = self.target_language
if target_language is not None:
query_params["target"] = target_language
response = self._connection.api_request(
method="GET", path="/languages", query_params=query_params
)
return response.get("data", {}).get("languages", ())
|
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Get list of supported languages for translation.
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See
https://cloud.google.com/translate/docs/discovering-supported-languages
:type target_language: str
:param target_language: (Optional) The language used to localize
returned language names. Defaults to the
target language on the current client.
:rtype: list
:returns: List of dictionaries. Each dictionary contains a supported
ISO 639-1 language code (using the dictionary key
``language``). If ``target_language`` is passed, each
dictionary will also contain the name of each supported
language (localized to the target language).
|
[
"Get",
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"languages",
"for",
"translation",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/translate/google/cloud/translate_v2/client.py#L67-L95
|
train
|
googleapis/google-cloud-python
|
translate/google/cloud/translate_v2/client.py
|
Client.detect_language
|
def detect_language(self, values):
"""Detect the language of a string or list of strings.
See https://cloud.google.com/translate/docs/detecting-language
:type values: str or list
:param values: String or list of strings that will have
language detected.
:rtype: dict or list
:returns: A list of dictionaries for each queried value. Each
dictionary typically contains three keys
* ``confidence``: The confidence in language detection, a
float between 0 and 1.
* ``input``: The corresponding input value.
* ``language``: The detected language (as an ISO 639-1
language code).
though the key ``confidence`` may not always be present.
If only a single value is passed, then only a single
dictionary will be returned.
:raises: :class:`ValueError <exceptions.ValueError>` if the number of
detections is not equal to the number of values.
:class:`ValueError <exceptions.ValueError>` if a value
produces a list of detections with 0 or multiple results
in it.
"""
single_value = False
if isinstance(values, six.string_types):
single_value = True
values = [values]
data = {"q": values}
response = self._connection.api_request(
method="POST", path="/detect", data=data
)
detections = response.get("data", {}).get("detections", ())
if len(values) != len(detections):
raise ValueError(
"Expected same number of values and detections", values, detections
)
for index, value in enumerate(values):
# Empirically, even clearly ambiguous text like "no" only returns
# a single detection, so we replace the list of detections with
# the single detection contained.
if len(detections[index]) == 1:
detections[index] = detections[index][0]
else:
message = (
"Expected a single detection per value, API " "returned %d"
) % (len(detections[index]),)
raise ValueError(message, value, detections[index])
detections[index]["input"] = value
# The ``isReliable`` field is deprecated.
detections[index].pop("isReliable", None)
if single_value:
return detections[0]
else:
return detections
|
python
|
def detect_language(self, values):
"""Detect the language of a string or list of strings.
See https://cloud.google.com/translate/docs/detecting-language
:type values: str or list
:param values: String or list of strings that will have
language detected.
:rtype: dict or list
:returns: A list of dictionaries for each queried value. Each
dictionary typically contains three keys
* ``confidence``: The confidence in language detection, a
float between 0 and 1.
* ``input``: The corresponding input value.
* ``language``: The detected language (as an ISO 639-1
language code).
though the key ``confidence`` may not always be present.
If only a single value is passed, then only a single
dictionary will be returned.
:raises: :class:`ValueError <exceptions.ValueError>` if the number of
detections is not equal to the number of values.
:class:`ValueError <exceptions.ValueError>` if a value
produces a list of detections with 0 or multiple results
in it.
"""
single_value = False
if isinstance(values, six.string_types):
single_value = True
values = [values]
data = {"q": values}
response = self._connection.api_request(
method="POST", path="/detect", data=data
)
detections = response.get("data", {}).get("detections", ())
if len(values) != len(detections):
raise ValueError(
"Expected same number of values and detections", values, detections
)
for index, value in enumerate(values):
# Empirically, even clearly ambiguous text like "no" only returns
# a single detection, so we replace the list of detections with
# the single detection contained.
if len(detections[index]) == 1:
detections[index] = detections[index][0]
else:
message = (
"Expected a single detection per value, API " "returned %d"
) % (len(detections[index]),)
raise ValueError(message, value, detections[index])
detections[index]["input"] = value
# The ``isReliable`` field is deprecated.
detections[index].pop("isReliable", None)
if single_value:
return detections[0]
else:
return detections
|
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Detect the language of a string or list of strings.
See https://cloud.google.com/translate/docs/detecting-language
:type values: str or list
:param values: String or list of strings that will have
language detected.
:rtype: dict or list
:returns: A list of dictionaries for each queried value. Each
dictionary typically contains three keys
* ``confidence``: The confidence in language detection, a
float between 0 and 1.
* ``input``: The corresponding input value.
* ``language``: The detected language (as an ISO 639-1
language code).
though the key ``confidence`` may not always be present.
If only a single value is passed, then only a single
dictionary will be returned.
:raises: :class:`ValueError <exceptions.ValueError>` if the number of
detections is not equal to the number of values.
:class:`ValueError <exceptions.ValueError>` if a value
produces a list of detections with 0 or multiple results
in it.
|
[
"Detect",
"the",
"language",
"of",
"a",
"string",
"or",
"list",
"of",
"strings",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/translate/google/cloud/translate_v2/client.py#L97-L163
|
train
|
googleapis/google-cloud-python
|
translate/google/cloud/translate_v2/client.py
|
Client.translate
|
def translate(
self,
values,
target_language=None,
format_=None,
source_language=None,
customization_ids=(),
model=None,
):
"""Translate a string or list of strings.
See https://cloud.google.com/translate/docs/translating-text
:type values: str or list
:param values: String or list of strings to translate.
:type target_language: str
:param target_language: The language to translate results into. This
is required by the API and defaults to
the target language of the current instance.
:type format_: str
:param format_: (Optional) One of ``text`` or ``html``, to specify
if the input text is plain text or HTML.
:type source_language: str
:param source_language: (Optional) The language of the text to
be translated.
:type customization_ids: str or list
:param customization_ids: (Optional) ID or list of customization IDs
for translation. Sets the ``cid`` parameter
in the query.
:type model: str
:param model: (Optional) The model used to translate the text, such
as ``'base'`` or ``'nmt'``.
:rtype: str or list
:returns: A list of dictionaries for each queried value. Each
dictionary typically contains three keys (though not
all will be present in all cases)
* ``detectedSourceLanguage``: The detected language (as an
ISO 639-1 language code) of the text.
* ``translatedText``: The translation of the text into the
target language.
* ``input``: The corresponding input value.
* ``model``: The model used to translate the text.
If only a single value is passed, then only a single
dictionary will be returned.
:raises: :class:`~exceptions.ValueError` if the number of
values and translations differ.
"""
single_value = False
if isinstance(values, six.string_types):
single_value = True
values = [values]
if target_language is None:
target_language = self.target_language
if isinstance(customization_ids, six.string_types):
customization_ids = [customization_ids]
data = {
"target": target_language,
"q": values,
"cid": customization_ids,
"format": format_,
"source": source_language,
"model": model,
}
response = self._connection.api_request(method="POST", path="", data=data)
translations = response.get("data", {}).get("translations", ())
if len(values) != len(translations):
raise ValueError(
"Expected iterations to have same length", values, translations
)
for value, translation in six.moves.zip(values, translations):
translation["input"] = value
if single_value:
return translations[0]
else:
return translations
|
python
|
def translate(
self,
values,
target_language=None,
format_=None,
source_language=None,
customization_ids=(),
model=None,
):
"""Translate a string or list of strings.
See https://cloud.google.com/translate/docs/translating-text
:type values: str or list
:param values: String or list of strings to translate.
:type target_language: str
:param target_language: The language to translate results into. This
is required by the API and defaults to
the target language of the current instance.
:type format_: str
:param format_: (Optional) One of ``text`` or ``html``, to specify
if the input text is plain text or HTML.
:type source_language: str
:param source_language: (Optional) The language of the text to
be translated.
:type customization_ids: str or list
:param customization_ids: (Optional) ID or list of customization IDs
for translation. Sets the ``cid`` parameter
in the query.
:type model: str
:param model: (Optional) The model used to translate the text, such
as ``'base'`` or ``'nmt'``.
:rtype: str or list
:returns: A list of dictionaries for each queried value. Each
dictionary typically contains three keys (though not
all will be present in all cases)
* ``detectedSourceLanguage``: The detected language (as an
ISO 639-1 language code) of the text.
* ``translatedText``: The translation of the text into the
target language.
* ``input``: The corresponding input value.
* ``model``: The model used to translate the text.
If only a single value is passed, then only a single
dictionary will be returned.
:raises: :class:`~exceptions.ValueError` if the number of
values and translations differ.
"""
single_value = False
if isinstance(values, six.string_types):
single_value = True
values = [values]
if target_language is None:
target_language = self.target_language
if isinstance(customization_ids, six.string_types):
customization_ids = [customization_ids]
data = {
"target": target_language,
"q": values,
"cid": customization_ids,
"format": format_,
"source": source_language,
"model": model,
}
response = self._connection.api_request(method="POST", path="", data=data)
translations = response.get("data", {}).get("translations", ())
if len(values) != len(translations):
raise ValueError(
"Expected iterations to have same length", values, translations
)
for value, translation in six.moves.zip(values, translations):
translation["input"] = value
if single_value:
return translations[0]
else:
return translations
|
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] |
Translate a string or list of strings.
See https://cloud.google.com/translate/docs/translating-text
:type values: str or list
:param values: String or list of strings to translate.
:type target_language: str
:param target_language: The language to translate results into. This
is required by the API and defaults to
the target language of the current instance.
:type format_: str
:param format_: (Optional) One of ``text`` or ``html``, to specify
if the input text is plain text or HTML.
:type source_language: str
:param source_language: (Optional) The language of the text to
be translated.
:type customization_ids: str or list
:param customization_ids: (Optional) ID or list of customization IDs
for translation. Sets the ``cid`` parameter
in the query.
:type model: str
:param model: (Optional) The model used to translate the text, such
as ``'base'`` or ``'nmt'``.
:rtype: str or list
:returns: A list of dictionaries for each queried value. Each
dictionary typically contains three keys (though not
all will be present in all cases)
* ``detectedSourceLanguage``: The detected language (as an
ISO 639-1 language code) of the text.
* ``translatedText``: The translation of the text into the
target language.
* ``input``: The corresponding input value.
* ``model``: The model used to translate the text.
If only a single value is passed, then only a single
dictionary will be returned.
:raises: :class:`~exceptions.ValueError` if the number of
values and translations differ.
|
[
"Translate",
"a",
"string",
"or",
"list",
"of",
"strings",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/translate/google/cloud/translate_v2/client.py#L165-L252
|
train
|
googleapis/google-cloud-python
|
pubsub/google/cloud/pubsub_v1/subscriber/_protocol/leaser.py
|
Leaser.add
|
def add(self, items):
"""Add messages to be managed by the leaser."""
for item in items:
# Add the ack ID to the set of managed ack IDs, and increment
# the size counter.
if item.ack_id not in self._leased_messages:
self._leased_messages[item.ack_id] = _LeasedMessage(
added_time=time.time(), size=item.byte_size
)
self._bytes += item.byte_size
else:
_LOGGER.debug("Message %s is already lease managed", item.ack_id)
|
python
|
def add(self, items):
"""Add messages to be managed by the leaser."""
for item in items:
# Add the ack ID to the set of managed ack IDs, and increment
# the size counter.
if item.ack_id not in self._leased_messages:
self._leased_messages[item.ack_id] = _LeasedMessage(
added_time=time.time(), size=item.byte_size
)
self._bytes += item.byte_size
else:
_LOGGER.debug("Message %s is already lease managed", item.ack_id)
|
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Add messages to be managed by the leaser.
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[
"Add",
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"to",
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"by",
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"leaser",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/pubsub/google/cloud/pubsub_v1/subscriber/_protocol/leaser.py#L65-L76
|
train
|
googleapis/google-cloud-python
|
pubsub/google/cloud/pubsub_v1/subscriber/_protocol/leaser.py
|
Leaser.remove
|
def remove(self, items):
"""Remove messages from lease management."""
# Remove the ack ID from lease management, and decrement the
# byte counter.
for item in items:
if self._leased_messages.pop(item.ack_id, None) is not None:
self._bytes -= item.byte_size
else:
_LOGGER.debug("Item %s was not managed.", item.ack_id)
if self._bytes < 0:
_LOGGER.debug("Bytes was unexpectedly negative: %d", self._bytes)
self._bytes = 0
|
python
|
def remove(self, items):
"""Remove messages from lease management."""
# Remove the ack ID from lease management, and decrement the
# byte counter.
for item in items:
if self._leased_messages.pop(item.ack_id, None) is not None:
self._bytes -= item.byte_size
else:
_LOGGER.debug("Item %s was not managed.", item.ack_id)
if self._bytes < 0:
_LOGGER.debug("Bytes was unexpectedly negative: %d", self._bytes)
self._bytes = 0
|
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Remove messages from lease management.
|
[
"Remove",
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"from",
"lease",
"management",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/pubsub/google/cloud/pubsub_v1/subscriber/_protocol/leaser.py#L78-L90
|
train
|
googleapis/google-cloud-python
|
pubsub/google/cloud/pubsub_v1/subscriber/_protocol/leaser.py
|
Leaser.maintain_leases
|
def maintain_leases(self):
"""Maintain all of the leases being managed.
This method modifies the ack deadline for all of the managed
ack IDs, then waits for most of that time (but with jitter), and
repeats.
"""
while self._manager.is_active and not self._stop_event.is_set():
# Determine the appropriate duration for the lease. This is
# based off of how long previous messages have taken to ack, with
# a sensible default and within the ranges allowed by Pub/Sub.
p99 = self._manager.ack_histogram.percentile(99)
_LOGGER.debug("The current p99 value is %d seconds.", p99)
# Make a copy of the leased messages. This is needed because it's
# possible for another thread to modify the dictionary while
# we're iterating over it.
leased_messages = copy.copy(self._leased_messages)
# Drop any leases that are well beyond max lease time. This
# ensures that in the event of a badly behaving actor, we can
# drop messages and allow Pub/Sub to resend them.
cutoff = time.time() - self._manager.flow_control.max_lease_duration
to_drop = [
requests.DropRequest(ack_id, item.size)
for ack_id, item in six.iteritems(leased_messages)
if item.added_time < cutoff
]
if to_drop:
_LOGGER.warning(
"Dropping %s items because they were leased too long.", len(to_drop)
)
self._manager.dispatcher.drop(to_drop)
# Remove dropped items from our copy of the leased messages (they
# have already been removed from the real one by
# self._manager.drop(), which calls self.remove()).
for item in to_drop:
leased_messages.pop(item.ack_id)
# Create a streaming pull request.
# We do not actually call `modify_ack_deadline` over and over
# because it is more efficient to make a single request.
ack_ids = leased_messages.keys()
if ack_ids:
_LOGGER.debug("Renewing lease for %d ack IDs.", len(ack_ids))
# NOTE: This may not work as expected if ``consumer.active``
# has changed since we checked it. An implementation
# without any sort of race condition would require a
# way for ``send_request`` to fail when the consumer
# is inactive.
self._manager.dispatcher.modify_ack_deadline(
[requests.ModAckRequest(ack_id, p99) for ack_id in ack_ids]
)
# Now wait an appropriate period of time and do this again.
#
# We determine the appropriate period of time based on a random
# period between 0 seconds and 90% of the lease. This use of
# jitter (http://bit.ly/2s2ekL7) helps decrease contention in cases
# where there are many clients.
snooze = random.uniform(0.0, p99 * 0.9)
_LOGGER.debug("Snoozing lease management for %f seconds.", snooze)
self._stop_event.wait(timeout=snooze)
_LOGGER.info("%s exiting.", _LEASE_WORKER_NAME)
|
python
|
def maintain_leases(self):
"""Maintain all of the leases being managed.
This method modifies the ack deadline for all of the managed
ack IDs, then waits for most of that time (but with jitter), and
repeats.
"""
while self._manager.is_active and not self._stop_event.is_set():
# Determine the appropriate duration for the lease. This is
# based off of how long previous messages have taken to ack, with
# a sensible default and within the ranges allowed by Pub/Sub.
p99 = self._manager.ack_histogram.percentile(99)
_LOGGER.debug("The current p99 value is %d seconds.", p99)
# Make a copy of the leased messages. This is needed because it's
# possible for another thread to modify the dictionary while
# we're iterating over it.
leased_messages = copy.copy(self._leased_messages)
# Drop any leases that are well beyond max lease time. This
# ensures that in the event of a badly behaving actor, we can
# drop messages and allow Pub/Sub to resend them.
cutoff = time.time() - self._manager.flow_control.max_lease_duration
to_drop = [
requests.DropRequest(ack_id, item.size)
for ack_id, item in six.iteritems(leased_messages)
if item.added_time < cutoff
]
if to_drop:
_LOGGER.warning(
"Dropping %s items because they were leased too long.", len(to_drop)
)
self._manager.dispatcher.drop(to_drop)
# Remove dropped items from our copy of the leased messages (they
# have already been removed from the real one by
# self._manager.drop(), which calls self.remove()).
for item in to_drop:
leased_messages.pop(item.ack_id)
# Create a streaming pull request.
# We do not actually call `modify_ack_deadline` over and over
# because it is more efficient to make a single request.
ack_ids = leased_messages.keys()
if ack_ids:
_LOGGER.debug("Renewing lease for %d ack IDs.", len(ack_ids))
# NOTE: This may not work as expected if ``consumer.active``
# has changed since we checked it. An implementation
# without any sort of race condition would require a
# way for ``send_request`` to fail when the consumer
# is inactive.
self._manager.dispatcher.modify_ack_deadline(
[requests.ModAckRequest(ack_id, p99) for ack_id in ack_ids]
)
# Now wait an appropriate period of time and do this again.
#
# We determine the appropriate period of time based on a random
# period between 0 seconds and 90% of the lease. This use of
# jitter (http://bit.ly/2s2ekL7) helps decrease contention in cases
# where there are many clients.
snooze = random.uniform(0.0, p99 * 0.9)
_LOGGER.debug("Snoozing lease management for %f seconds.", snooze)
self._stop_event.wait(timeout=snooze)
_LOGGER.info("%s exiting.", _LEASE_WORKER_NAME)
|
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Maintain all of the leases being managed.
This method modifies the ack deadline for all of the managed
ack IDs, then waits for most of that time (but with jitter), and
repeats.
|
[
"Maintain",
"all",
"of",
"the",
"leases",
"being",
"managed",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/pubsub/google/cloud/pubsub_v1/subscriber/_protocol/leaser.py#L92-L159
|
train
|
googleapis/google-cloud-python
|
error_reporting/google/cloud/error_reporting/_gapic.py
|
make_report_error_api
|
def make_report_error_api(client):
"""Create an instance of the gapic Logging API.
:type client::class:`google.cloud.error_reporting.Client`
:param client: Error Reporting client.
:rtype: :class:_ErrorReportingGapicApi
:returns: An Error Reporting API instance.
"""
gax_client = report_errors_service_client.ReportErrorsServiceClient(
credentials=client._credentials, client_info=_CLIENT_INFO
)
return _ErrorReportingGapicApi(gax_client, client.project)
|
python
|
def make_report_error_api(client):
"""Create an instance of the gapic Logging API.
:type client::class:`google.cloud.error_reporting.Client`
:param client: Error Reporting client.
:rtype: :class:_ErrorReportingGapicApi
:returns: An Error Reporting API instance.
"""
gax_client = report_errors_service_client.ReportErrorsServiceClient(
credentials=client._credentials, client_info=_CLIENT_INFO
)
return _ErrorReportingGapicApi(gax_client, client.project)
|
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Create an instance of the gapic Logging API.
:type client::class:`google.cloud.error_reporting.Client`
:param client: Error Reporting client.
:rtype: :class:_ErrorReportingGapicApi
:returns: An Error Reporting API instance.
|
[
"Create",
"an",
"instance",
"of",
"the",
"gapic",
"Logging",
"API",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/error_reporting/google/cloud/error_reporting/_gapic.py#L27-L39
|
train
|
googleapis/google-cloud-python
|
error_reporting/google/cloud/error_reporting/_gapic.py
|
_ErrorReportingGapicApi.report_error_event
|
def report_error_event(self, error_report):
"""Uses the gapic client to report the error.
:type error_report: dict
:param error_report:
payload of the error report formatted according to
https://cloud.google.com/error-reporting/docs/formatting-error-messages
This object should be built using
Use
:meth:~`google.cloud.error_reporting.client._build_error_report`
"""
project_name = self._gapic_api.project_path(self._project)
error_report_payload = report_errors_service_pb2.ReportedErrorEvent()
ParseDict(error_report, error_report_payload)
self._gapic_api.report_error_event(project_name, error_report_payload)
|
python
|
def report_error_event(self, error_report):
"""Uses the gapic client to report the error.
:type error_report: dict
:param error_report:
payload of the error report formatted according to
https://cloud.google.com/error-reporting/docs/formatting-error-messages
This object should be built using
Use
:meth:~`google.cloud.error_reporting.client._build_error_report`
"""
project_name = self._gapic_api.project_path(self._project)
error_report_payload = report_errors_service_pb2.ReportedErrorEvent()
ParseDict(error_report, error_report_payload)
self._gapic_api.report_error_event(project_name, error_report_payload)
|
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",",
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":",
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"=",
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".",
"_gapic_api",
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"project_path",
"(",
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")",
"self",
".",
"_gapic_api",
".",
"report_error_event",
"(",
"project_name",
",",
"error_report_payload",
")"
] |
Uses the gapic client to report the error.
:type error_report: dict
:param error_report:
payload of the error report formatted according to
https://cloud.google.com/error-reporting/docs/formatting-error-messages
This object should be built using
Use
:meth:~`google.cloud.error_reporting.client._build_error_report`
|
[
"Uses",
"the",
"gapic",
"client",
"to",
"report",
"the",
"error",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/error_reporting/google/cloud/error_reporting/_gapic.py#L57-L71
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable_v2/gapic/bigtable_client.py
|
BigtableClient.table_path
|
def table_path(cls, project, instance, table):
"""Return a fully-qualified table string."""
return google.api_core.path_template.expand(
"projects/{project}/instances/{instance}/tables/{table}",
project=project,
instance=instance,
table=table,
)
|
python
|
def table_path(cls, project, instance, table):
"""Return a fully-qualified table string."""
return google.api_core.path_template.expand(
"projects/{project}/instances/{instance}/tables/{table}",
project=project,
instance=instance,
table=table,
)
|
[
"def",
"table_path",
"(",
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",",
"project",
",",
"instance",
",",
"table",
")",
":",
"return",
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".",
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".",
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"\"projects/{project}/instances/{instance}/tables/{table}\"",
",",
"project",
"=",
"project",
",",
"instance",
"=",
"instance",
",",
"table",
"=",
"table",
",",
")"
] |
Return a fully-qualified table string.
|
[
"Return",
"a",
"fully",
"-",
"qualified",
"table",
"string",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable_v2/gapic/bigtable_client.py#L70-L77
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable_v2/gapic/bigtable_client.py
|
BigtableClient.read_rows
|
def read_rows(
self,
table_name,
app_profile_id=None,
rows=None,
filter_=None,
rows_limit=None,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None,
):
"""
Streams back the contents of all requested rows in key order, optionally
applying the same Reader filter to each. Depending on their size,
rows and cells may be broken up across multiple responses, but
atomicity of each row will still be preserved. See the
ReadRowsResponse documentation for details.
Example:
>>> from google.cloud import bigtable_v2
>>>
>>> client = bigtable_v2.BigtableClient()
>>>
>>> table_name = client.table_path('[PROJECT]', '[INSTANCE]', '[TABLE]')
>>>
>>> for element in client.read_rows(table_name):
... # process element
... pass
Args:
table_name (str): The unique name of the table from which to read. Values are of the form
``projects/<project>/instances/<instance>/tables/<table>``.
app_profile_id (str): This value specifies routing for replication. If not specified, the
"default" application profile will be used.
rows (Union[dict, ~google.cloud.bigtable_v2.types.RowSet]): The row keys and/or ranges to read. If not specified, reads from all rows.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.RowSet`
filter_ (Union[dict, ~google.cloud.bigtable_v2.types.RowFilter]): The filter to apply to the contents of the specified row(s). If unset,
reads the entirety of each row.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.RowFilter`
rows_limit (long): The read will terminate after committing to N rows' worth of results. The
default (zero) is to return all results.
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will not
be retried.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
Iterable[~google.cloud.bigtable_v2.types.ReadRowsResponse].
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid.
"""
# Wrap the transport method to add retry and timeout logic.
if "read_rows" not in self._inner_api_calls:
self._inner_api_calls[
"read_rows"
] = google.api_core.gapic_v1.method.wrap_method(
self.transport.read_rows,
default_retry=self._method_configs["ReadRows"].retry,
default_timeout=self._method_configs["ReadRows"].timeout,
client_info=self._client_info,
)
request = bigtable_pb2.ReadRowsRequest(
table_name=table_name,
app_profile_id=app_profile_id,
rows=rows,
filter=filter_,
rows_limit=rows_limit,
)
if metadata is None:
metadata = []
metadata = list(metadata)
try:
routing_header = [("table_name", table_name)]
except AttributeError:
pass
else:
routing_metadata = google.api_core.gapic_v1.routing_header.to_grpc_metadata(
routing_header
)
metadata.append(routing_metadata)
return self._inner_api_calls["read_rows"](
request, retry=retry, timeout=timeout, metadata=metadata
)
|
python
|
def read_rows(
self,
table_name,
app_profile_id=None,
rows=None,
filter_=None,
rows_limit=None,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None,
):
"""
Streams back the contents of all requested rows in key order, optionally
applying the same Reader filter to each. Depending on their size,
rows and cells may be broken up across multiple responses, but
atomicity of each row will still be preserved. See the
ReadRowsResponse documentation for details.
Example:
>>> from google.cloud import bigtable_v2
>>>
>>> client = bigtable_v2.BigtableClient()
>>>
>>> table_name = client.table_path('[PROJECT]', '[INSTANCE]', '[TABLE]')
>>>
>>> for element in client.read_rows(table_name):
... # process element
... pass
Args:
table_name (str): The unique name of the table from which to read. Values are of the form
``projects/<project>/instances/<instance>/tables/<table>``.
app_profile_id (str): This value specifies routing for replication. If not specified, the
"default" application profile will be used.
rows (Union[dict, ~google.cloud.bigtable_v2.types.RowSet]): The row keys and/or ranges to read. If not specified, reads from all rows.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.RowSet`
filter_ (Union[dict, ~google.cloud.bigtable_v2.types.RowFilter]): The filter to apply to the contents of the specified row(s). If unset,
reads the entirety of each row.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.RowFilter`
rows_limit (long): The read will terminate after committing to N rows' worth of results. The
default (zero) is to return all results.
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will not
be retried.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
Iterable[~google.cloud.bigtable_v2.types.ReadRowsResponse].
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid.
"""
# Wrap the transport method to add retry and timeout logic.
if "read_rows" not in self._inner_api_calls:
self._inner_api_calls[
"read_rows"
] = google.api_core.gapic_v1.method.wrap_method(
self.transport.read_rows,
default_retry=self._method_configs["ReadRows"].retry,
default_timeout=self._method_configs["ReadRows"].timeout,
client_info=self._client_info,
)
request = bigtable_pb2.ReadRowsRequest(
table_name=table_name,
app_profile_id=app_profile_id,
rows=rows,
filter=filter_,
rows_limit=rows_limit,
)
if metadata is None:
metadata = []
metadata = list(metadata)
try:
routing_header = [("table_name", table_name)]
except AttributeError:
pass
else:
routing_metadata = google.api_core.gapic_v1.routing_header.to_grpc_metadata(
routing_header
)
metadata.append(routing_metadata)
return self._inner_api_calls["read_rows"](
request, retry=retry, timeout=timeout, metadata=metadata
)
|
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Streams back the contents of all requested rows in key order, optionally
applying the same Reader filter to each. Depending on their size,
rows and cells may be broken up across multiple responses, but
atomicity of each row will still be preserved. See the
ReadRowsResponse documentation for details.
Example:
>>> from google.cloud import bigtable_v2
>>>
>>> client = bigtable_v2.BigtableClient()
>>>
>>> table_name = client.table_path('[PROJECT]', '[INSTANCE]', '[TABLE]')
>>>
>>> for element in client.read_rows(table_name):
... # process element
... pass
Args:
table_name (str): The unique name of the table from which to read. Values are of the form
``projects/<project>/instances/<instance>/tables/<table>``.
app_profile_id (str): This value specifies routing for replication. If not specified, the
"default" application profile will be used.
rows (Union[dict, ~google.cloud.bigtable_v2.types.RowSet]): The row keys and/or ranges to read. If not specified, reads from all rows.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.RowSet`
filter_ (Union[dict, ~google.cloud.bigtable_v2.types.RowFilter]): The filter to apply to the contents of the specified row(s). If unset,
reads the entirety of each row.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.RowFilter`
rows_limit (long): The read will terminate after committing to N rows' worth of results. The
default (zero) is to return all results.
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will not
be retried.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
Iterable[~google.cloud.bigtable_v2.types.ReadRowsResponse].
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid.
|
[
"Streams",
"back",
"the",
"contents",
"of",
"all",
"requested",
"rows",
"in",
"key",
"order",
"optionally",
"applying",
"the",
"same",
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"filter",
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"Depending",
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"will",
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"See",
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"ReadRowsResponse",
"documentation",
"for",
"details",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable_v2/gapic/bigtable_client.py#L178-L275
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable_v2/gapic/bigtable_client.py
|
BigtableClient.mutate_rows
|
def mutate_rows(
self,
table_name,
entries,
app_profile_id=None,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None,
):
"""
Mutates multiple rows in a batch. Each individual row is mutated
atomically as in MutateRow, but the entire batch is not executed
atomically.
Example:
>>> from google.cloud import bigtable_v2
>>>
>>> client = bigtable_v2.BigtableClient()
>>>
>>> table_name = client.table_path('[PROJECT]', '[INSTANCE]', '[TABLE]')
>>>
>>> # TODO: Initialize `entries`:
>>> entries = []
>>>
>>> for element in client.mutate_rows(table_name, entries):
... # process element
... pass
Args:
table_name (str): The unique name of the table to which the mutations should be applied.
entries (list[Union[dict, ~google.cloud.bigtable_v2.types.Entry]]): The row keys and corresponding mutations to be applied in bulk.
Each entry is applied as an atomic mutation, but the entries may be
applied in arbitrary order (even between entries for the same row).
At least one entry must be specified, and in total the entries can
contain at most 100000 mutations.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.Entry`
app_profile_id (str): This value specifies routing for replication. If not specified, the
"default" application profile will be used.
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will not
be retried.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
Iterable[~google.cloud.bigtable_v2.types.MutateRowsResponse].
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid.
"""
# Wrap the transport method to add retry and timeout logic.
if "mutate_rows" not in self._inner_api_calls:
self._inner_api_calls[
"mutate_rows"
] = google.api_core.gapic_v1.method.wrap_method(
self.transport.mutate_rows,
default_retry=self._method_configs["MutateRows"].retry,
default_timeout=self._method_configs["MutateRows"].timeout,
client_info=self._client_info,
)
request = bigtable_pb2.MutateRowsRequest(
table_name=table_name, entries=entries, app_profile_id=app_profile_id
)
if metadata is None:
metadata = []
metadata = list(metadata)
try:
routing_header = [("table_name", table_name)]
except AttributeError:
pass
else:
routing_metadata = google.api_core.gapic_v1.routing_header.to_grpc_metadata(
routing_header
)
metadata.append(routing_metadata)
return self._inner_api_calls["mutate_rows"](
request, retry=retry, timeout=timeout, metadata=metadata
)
|
python
|
def mutate_rows(
self,
table_name,
entries,
app_profile_id=None,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None,
):
"""
Mutates multiple rows in a batch. Each individual row is mutated
atomically as in MutateRow, but the entire batch is not executed
atomically.
Example:
>>> from google.cloud import bigtable_v2
>>>
>>> client = bigtable_v2.BigtableClient()
>>>
>>> table_name = client.table_path('[PROJECT]', '[INSTANCE]', '[TABLE]')
>>>
>>> # TODO: Initialize `entries`:
>>> entries = []
>>>
>>> for element in client.mutate_rows(table_name, entries):
... # process element
... pass
Args:
table_name (str): The unique name of the table to which the mutations should be applied.
entries (list[Union[dict, ~google.cloud.bigtable_v2.types.Entry]]): The row keys and corresponding mutations to be applied in bulk.
Each entry is applied as an atomic mutation, but the entries may be
applied in arbitrary order (even between entries for the same row).
At least one entry must be specified, and in total the entries can
contain at most 100000 mutations.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.Entry`
app_profile_id (str): This value specifies routing for replication. If not specified, the
"default" application profile will be used.
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will not
be retried.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
Iterable[~google.cloud.bigtable_v2.types.MutateRowsResponse].
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid.
"""
# Wrap the transport method to add retry and timeout logic.
if "mutate_rows" not in self._inner_api_calls:
self._inner_api_calls[
"mutate_rows"
] = google.api_core.gapic_v1.method.wrap_method(
self.transport.mutate_rows,
default_retry=self._method_configs["MutateRows"].retry,
default_timeout=self._method_configs["MutateRows"].timeout,
client_info=self._client_info,
)
request = bigtable_pb2.MutateRowsRequest(
table_name=table_name, entries=entries, app_profile_id=app_profile_id
)
if metadata is None:
metadata = []
metadata = list(metadata)
try:
routing_header = [("table_name", table_name)]
except AttributeError:
pass
else:
routing_metadata = google.api_core.gapic_v1.routing_header.to_grpc_metadata(
routing_header
)
metadata.append(routing_metadata)
return self._inner_api_calls["mutate_rows"](
request, retry=retry, timeout=timeout, metadata=metadata
)
|
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Mutates multiple rows in a batch. Each individual row is mutated
atomically as in MutateRow, but the entire batch is not executed
atomically.
Example:
>>> from google.cloud import bigtable_v2
>>>
>>> client = bigtable_v2.BigtableClient()
>>>
>>> table_name = client.table_path('[PROJECT]', '[INSTANCE]', '[TABLE]')
>>>
>>> # TODO: Initialize `entries`:
>>> entries = []
>>>
>>> for element in client.mutate_rows(table_name, entries):
... # process element
... pass
Args:
table_name (str): The unique name of the table to which the mutations should be applied.
entries (list[Union[dict, ~google.cloud.bigtable_v2.types.Entry]]): The row keys and corresponding mutations to be applied in bulk.
Each entry is applied as an atomic mutation, but the entries may be
applied in arbitrary order (even between entries for the same row).
At least one entry must be specified, and in total the entries can
contain at most 100000 mutations.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.Entry`
app_profile_id (str): This value specifies routing for replication. If not specified, the
"default" application profile will be used.
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will not
be retried.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
Iterable[~google.cloud.bigtable_v2.types.MutateRowsResponse].
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid.
|
[
"Mutates",
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"in",
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"batch",
".",
"Each",
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"row",
"is",
"mutated",
"atomically",
"as",
"in",
"MutateRow",
"but",
"the",
"entire",
"batch",
"is",
"not",
"executed",
"atomically",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable_v2/gapic/bigtable_client.py#L452-L540
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable_v2/gapic/bigtable_client.py
|
BigtableClient.check_and_mutate_row
|
def check_and_mutate_row(
self,
table_name,
row_key,
app_profile_id=None,
predicate_filter=None,
true_mutations=None,
false_mutations=None,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None,
):
"""
Mutates a row atomically based on the output of a predicate Reader filter.
Example:
>>> from google.cloud import bigtable_v2
>>>
>>> client = bigtable_v2.BigtableClient()
>>>
>>> table_name = client.table_path('[PROJECT]', '[INSTANCE]', '[TABLE]')
>>>
>>> # TODO: Initialize `row_key`:
>>> row_key = b''
>>>
>>> response = client.check_and_mutate_row(table_name, row_key)
Args:
table_name (str): The unique name of the table to which the conditional mutation should be
applied. Values are of the form
``projects/<project>/instances/<instance>/tables/<table>``.
row_key (bytes): The key of the row to which the conditional mutation should be applied.
app_profile_id (str): This value specifies routing for replication. If not specified, the
"default" application profile will be used.
predicate_filter (Union[dict, ~google.cloud.bigtable_v2.types.RowFilter]): The filter to be applied to the contents of the specified row. Depending
on whether or not any results are yielded, either ``true_mutations`` or
``false_mutations`` will be executed. If unset, checks that the row
contains any values at all.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.RowFilter`
true_mutations (list[Union[dict, ~google.cloud.bigtable_v2.types.Mutation]]): Changes to be atomically applied to the specified row if
``predicate_filter`` yields at least one cell when applied to
``row_key``. Entries are applied in order, meaning that earlier
mutations can be masked by later ones. Must contain at least one entry
if ``false_mutations`` is empty, and at most 100000.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.Mutation`
false_mutations (list[Union[dict, ~google.cloud.bigtable_v2.types.Mutation]]): Changes to be atomically applied to the specified row if
``predicate_filter`` does not yield any cells when applied to
``row_key``. Entries are applied in order, meaning that earlier
mutations can be masked by later ones. Must contain at least one entry
if ``true_mutations`` is empty, and at most 100000.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.Mutation`
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will not
be retried.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
A :class:`~google.cloud.bigtable_v2.types.CheckAndMutateRowResponse` instance.
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid.
"""
# Wrap the transport method to add retry and timeout logic.
if "check_and_mutate_row" not in self._inner_api_calls:
self._inner_api_calls[
"check_and_mutate_row"
] = google.api_core.gapic_v1.method.wrap_method(
self.transport.check_and_mutate_row,
default_retry=self._method_configs["CheckAndMutateRow"].retry,
default_timeout=self._method_configs["CheckAndMutateRow"].timeout,
client_info=self._client_info,
)
request = bigtable_pb2.CheckAndMutateRowRequest(
table_name=table_name,
row_key=row_key,
app_profile_id=app_profile_id,
predicate_filter=predicate_filter,
true_mutations=true_mutations,
false_mutations=false_mutations,
)
if metadata is None:
metadata = []
metadata = list(metadata)
try:
routing_header = [("table_name", table_name)]
except AttributeError:
pass
else:
routing_metadata = google.api_core.gapic_v1.routing_header.to_grpc_metadata(
routing_header
)
metadata.append(routing_metadata)
return self._inner_api_calls["check_and_mutate_row"](
request, retry=retry, timeout=timeout, metadata=metadata
)
|
python
|
def check_and_mutate_row(
self,
table_name,
row_key,
app_profile_id=None,
predicate_filter=None,
true_mutations=None,
false_mutations=None,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None,
):
"""
Mutates a row atomically based on the output of a predicate Reader filter.
Example:
>>> from google.cloud import bigtable_v2
>>>
>>> client = bigtable_v2.BigtableClient()
>>>
>>> table_name = client.table_path('[PROJECT]', '[INSTANCE]', '[TABLE]')
>>>
>>> # TODO: Initialize `row_key`:
>>> row_key = b''
>>>
>>> response = client.check_and_mutate_row(table_name, row_key)
Args:
table_name (str): The unique name of the table to which the conditional mutation should be
applied. Values are of the form
``projects/<project>/instances/<instance>/tables/<table>``.
row_key (bytes): The key of the row to which the conditional mutation should be applied.
app_profile_id (str): This value specifies routing for replication. If not specified, the
"default" application profile will be used.
predicate_filter (Union[dict, ~google.cloud.bigtable_v2.types.RowFilter]): The filter to be applied to the contents of the specified row. Depending
on whether or not any results are yielded, either ``true_mutations`` or
``false_mutations`` will be executed. If unset, checks that the row
contains any values at all.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.RowFilter`
true_mutations (list[Union[dict, ~google.cloud.bigtable_v2.types.Mutation]]): Changes to be atomically applied to the specified row if
``predicate_filter`` yields at least one cell when applied to
``row_key``. Entries are applied in order, meaning that earlier
mutations can be masked by later ones. Must contain at least one entry
if ``false_mutations`` is empty, and at most 100000.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.Mutation`
false_mutations (list[Union[dict, ~google.cloud.bigtable_v2.types.Mutation]]): Changes to be atomically applied to the specified row if
``predicate_filter`` does not yield any cells when applied to
``row_key``. Entries are applied in order, meaning that earlier
mutations can be masked by later ones. Must contain at least one entry
if ``true_mutations`` is empty, and at most 100000.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.Mutation`
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will not
be retried.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
A :class:`~google.cloud.bigtable_v2.types.CheckAndMutateRowResponse` instance.
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid.
"""
# Wrap the transport method to add retry and timeout logic.
if "check_and_mutate_row" not in self._inner_api_calls:
self._inner_api_calls[
"check_and_mutate_row"
] = google.api_core.gapic_v1.method.wrap_method(
self.transport.check_and_mutate_row,
default_retry=self._method_configs["CheckAndMutateRow"].retry,
default_timeout=self._method_configs["CheckAndMutateRow"].timeout,
client_info=self._client_info,
)
request = bigtable_pb2.CheckAndMutateRowRequest(
table_name=table_name,
row_key=row_key,
app_profile_id=app_profile_id,
predicate_filter=predicate_filter,
true_mutations=true_mutations,
false_mutations=false_mutations,
)
if metadata is None:
metadata = []
metadata = list(metadata)
try:
routing_header = [("table_name", table_name)]
except AttributeError:
pass
else:
routing_metadata = google.api_core.gapic_v1.routing_header.to_grpc_metadata(
routing_header
)
metadata.append(routing_metadata)
return self._inner_api_calls["check_and_mutate_row"](
request, retry=retry, timeout=timeout, metadata=metadata
)
|
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Mutates a row atomically based on the output of a predicate Reader filter.
Example:
>>> from google.cloud import bigtable_v2
>>>
>>> client = bigtable_v2.BigtableClient()
>>>
>>> table_name = client.table_path('[PROJECT]', '[INSTANCE]', '[TABLE]')
>>>
>>> # TODO: Initialize `row_key`:
>>> row_key = b''
>>>
>>> response = client.check_and_mutate_row(table_name, row_key)
Args:
table_name (str): The unique name of the table to which the conditional mutation should be
applied. Values are of the form
``projects/<project>/instances/<instance>/tables/<table>``.
row_key (bytes): The key of the row to which the conditional mutation should be applied.
app_profile_id (str): This value specifies routing for replication. If not specified, the
"default" application profile will be used.
predicate_filter (Union[dict, ~google.cloud.bigtable_v2.types.RowFilter]): The filter to be applied to the contents of the specified row. Depending
on whether or not any results are yielded, either ``true_mutations`` or
``false_mutations`` will be executed. If unset, checks that the row
contains any values at all.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.RowFilter`
true_mutations (list[Union[dict, ~google.cloud.bigtable_v2.types.Mutation]]): Changes to be atomically applied to the specified row if
``predicate_filter`` yields at least one cell when applied to
``row_key``. Entries are applied in order, meaning that earlier
mutations can be masked by later ones. Must contain at least one entry
if ``false_mutations`` is empty, and at most 100000.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.Mutation`
false_mutations (list[Union[dict, ~google.cloud.bigtable_v2.types.Mutation]]): Changes to be atomically applied to the specified row if
``predicate_filter`` does not yield any cells when applied to
``row_key``. Entries are applied in order, meaning that earlier
mutations can be masked by later ones. Must contain at least one entry
if ``true_mutations`` is empty, and at most 100000.
If a dict is provided, it must be of the same form as the protobuf
message :class:`~google.cloud.bigtable_v2.types.Mutation`
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will not
be retried.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
A :class:`~google.cloud.bigtable_v2.types.CheckAndMutateRowResponse` instance.
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid.
|
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"atomically",
"based",
"on",
"the",
"output",
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"a",
"predicate",
"Reader",
"filter",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable_v2/gapic/bigtable_client.py#L542-L652
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable/instance.py
|
Instance._update_from_pb
|
def _update_from_pb(self, instance_pb):
"""Refresh self from the server-provided protobuf.
Helper for :meth:`from_pb` and :meth:`reload`.
"""
if not instance_pb.display_name: # Simple field (string)
raise ValueError("Instance protobuf does not contain display_name")
self.display_name = instance_pb.display_name
self.type_ = instance_pb.type
self.labels = dict(instance_pb.labels)
self._state = instance_pb.state
|
python
|
def _update_from_pb(self, instance_pb):
"""Refresh self from the server-provided protobuf.
Helper for :meth:`from_pb` and :meth:`reload`.
"""
if not instance_pb.display_name: # Simple field (string)
raise ValueError("Instance protobuf does not contain display_name")
self.display_name = instance_pb.display_name
self.type_ = instance_pb.type
self.labels = dict(instance_pb.labels)
self._state = instance_pb.state
|
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Refresh self from the server-provided protobuf.
Helper for :meth:`from_pb` and :meth:`reload`.
|
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"meth",
":",
"reload",
"."
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable/instance.py#L118-L127
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable/instance.py
|
Instance.name
|
def name(self):
"""Instance name used in requests.
.. note::
This property will not change if ``instance_id`` does not,
but the return value is not cached.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_instance_name]
:end-before: [END bigtable_instance_name]
The instance name is of the form
``"projects/{project}/instances/{instance_id}"``
:rtype: str
:returns: Return a fully-qualified instance string.
"""
return self._client.instance_admin_client.instance_path(
project=self._client.project, instance=self.instance_id
)
|
python
|
def name(self):
"""Instance name used in requests.
.. note::
This property will not change if ``instance_id`` does not,
but the return value is not cached.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_instance_name]
:end-before: [END bigtable_instance_name]
The instance name is of the form
``"projects/{project}/instances/{instance_id}"``
:rtype: str
:returns: Return a fully-qualified instance string.
"""
return self._client.instance_admin_client.instance_path(
project=self._client.project, instance=self.instance_id
)
|
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"_client",
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"project",
",",
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"=",
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"instance_id",
")"
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Instance name used in requests.
.. note::
This property will not change if ``instance_id`` does not,
but the return value is not cached.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_instance_name]
:end-before: [END bigtable_instance_name]
The instance name is of the form
``"projects/{project}/instances/{instance_id}"``
:rtype: str
:returns: Return a fully-qualified instance string.
|
[
"Instance",
"name",
"used",
"in",
"requests",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable/instance.py#L170-L192
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable/instance.py
|
Instance.create
|
def create(
self,
location_id=None,
serve_nodes=None,
default_storage_type=None,
clusters=None,
):
"""Create this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_prod_instance]
:end-before: [END bigtable_create_prod_instance]
.. note::
Uses the ``project`` and ``instance_id`` on the current
:class:`Instance` in addition to the ``display_name``.
To change them before creating, reset the values via
.. code:: python
instance.display_name = 'New display name'
instance.instance_id = 'i-changed-my-mind'
before calling :meth:`create`.
:type location_id: str
:param location_id: (Creation Only) The location where nodes and
storage of the cluster owned by this instance
reside. For best performance, clients should be
located as close as possible to cluster's location.
For list of supported locations refer to
https://cloud.google.com/bigtable/docs/locations
:type serve_nodes: int
:param serve_nodes: (Optional) The number of nodes in the instance's
cluster; used to set up the instance's cluster.
:type default_storage_type: int
:param default_storage_type: (Optional) The storage media type for
persisting Bigtable data.
Possible values are represented
by the following constants:
:data:`google.cloud.bigtable.enums.StorageType.SSD`.
:data:`google.cloud.bigtable.enums.StorageType.SHD`,
Defaults to
:data:`google.cloud.bigtable.enums.StorageType.UNSPECIFIED`.
:type clusters: class:`~[~google.cloud.bigtable.cluster.Cluster]`
:param clusters: List of clusters to be created.
:rtype: :class:`~google.api_core.operation.Operation`
:returns: The long-running operation corresponding to the create
operation.
:raises: :class:`ValueError <exceptions.ValueError>` if both
``clusters`` and one of ``location_id``, ``serve_nodes``
and ``default_storage_type`` are set.
"""
if clusters is None:
warnings.warn(
_INSTANCE_CREATE_WARNING.format(
"location_id", "serve_nodes", "default_storage_type"
),
DeprecationWarning,
stacklevel=2,
)
cluster_id = "{}-cluster".format(self.instance_id)
clusters = [
self.cluster(
cluster_id,
location_id=location_id,
serve_nodes=serve_nodes,
default_storage_type=default_storage_type,
)
]
elif (
location_id is not None
or serve_nodes is not None
or default_storage_type is not None
):
raise ValueError(
"clusters and one of location_id, serve_nodes, \
default_storage_type can not be set \
simultaneously."
)
instance_pb = instance_pb2.Instance(
display_name=self.display_name, type=self.type_, labels=self.labels
)
parent = self._client.project_path
return self._client.instance_admin_client.create_instance(
parent=parent,
instance_id=self.instance_id,
instance=instance_pb,
clusters={c.cluster_id: c._to_pb() for c in clusters},
)
|
python
|
def create(
self,
location_id=None,
serve_nodes=None,
default_storage_type=None,
clusters=None,
):
"""Create this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_prod_instance]
:end-before: [END bigtable_create_prod_instance]
.. note::
Uses the ``project`` and ``instance_id`` on the current
:class:`Instance` in addition to the ``display_name``.
To change them before creating, reset the values via
.. code:: python
instance.display_name = 'New display name'
instance.instance_id = 'i-changed-my-mind'
before calling :meth:`create`.
:type location_id: str
:param location_id: (Creation Only) The location where nodes and
storage of the cluster owned by this instance
reside. For best performance, clients should be
located as close as possible to cluster's location.
For list of supported locations refer to
https://cloud.google.com/bigtable/docs/locations
:type serve_nodes: int
:param serve_nodes: (Optional) The number of nodes in the instance's
cluster; used to set up the instance's cluster.
:type default_storage_type: int
:param default_storage_type: (Optional) The storage media type for
persisting Bigtable data.
Possible values are represented
by the following constants:
:data:`google.cloud.bigtable.enums.StorageType.SSD`.
:data:`google.cloud.bigtable.enums.StorageType.SHD`,
Defaults to
:data:`google.cloud.bigtable.enums.StorageType.UNSPECIFIED`.
:type clusters: class:`~[~google.cloud.bigtable.cluster.Cluster]`
:param clusters: List of clusters to be created.
:rtype: :class:`~google.api_core.operation.Operation`
:returns: The long-running operation corresponding to the create
operation.
:raises: :class:`ValueError <exceptions.ValueError>` if both
``clusters`` and one of ``location_id``, ``serve_nodes``
and ``default_storage_type`` are set.
"""
if clusters is None:
warnings.warn(
_INSTANCE_CREATE_WARNING.format(
"location_id", "serve_nodes", "default_storage_type"
),
DeprecationWarning,
stacklevel=2,
)
cluster_id = "{}-cluster".format(self.instance_id)
clusters = [
self.cluster(
cluster_id,
location_id=location_id,
serve_nodes=serve_nodes,
default_storage_type=default_storage_type,
)
]
elif (
location_id is not None
or serve_nodes is not None
or default_storage_type is not None
):
raise ValueError(
"clusters and one of location_id, serve_nodes, \
default_storage_type can not be set \
simultaneously."
)
instance_pb = instance_pb2.Instance(
display_name=self.display_name, type=self.type_, labels=self.labels
)
parent = self._client.project_path
return self._client.instance_admin_client.create_instance(
parent=parent,
instance_id=self.instance_id,
instance=instance_pb,
clusters={c.cluster_id: c._to_pb() for c in clusters},
)
|
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Create this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_prod_instance]
:end-before: [END bigtable_create_prod_instance]
.. note::
Uses the ``project`` and ``instance_id`` on the current
:class:`Instance` in addition to the ``display_name``.
To change them before creating, reset the values via
.. code:: python
instance.display_name = 'New display name'
instance.instance_id = 'i-changed-my-mind'
before calling :meth:`create`.
:type location_id: str
:param location_id: (Creation Only) The location where nodes and
storage of the cluster owned by this instance
reside. For best performance, clients should be
located as close as possible to cluster's location.
For list of supported locations refer to
https://cloud.google.com/bigtable/docs/locations
:type serve_nodes: int
:param serve_nodes: (Optional) The number of nodes in the instance's
cluster; used to set up the instance's cluster.
:type default_storage_type: int
:param default_storage_type: (Optional) The storage media type for
persisting Bigtable data.
Possible values are represented
by the following constants:
:data:`google.cloud.bigtable.enums.StorageType.SSD`.
:data:`google.cloud.bigtable.enums.StorageType.SHD`,
Defaults to
:data:`google.cloud.bigtable.enums.StorageType.UNSPECIFIED`.
:type clusters: class:`~[~google.cloud.bigtable.cluster.Cluster]`
:param clusters: List of clusters to be created.
:rtype: :class:`~google.api_core.operation.Operation`
:returns: The long-running operation corresponding to the create
operation.
:raises: :class:`ValueError <exceptions.ValueError>` if both
``clusters`` and one of ``location_id``, ``serve_nodes``
and ``default_storage_type`` are set.
|
[
"Create",
"this",
"instance",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable/instance.py#L221-L325
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable/instance.py
|
Instance.exists
|
def exists(self):
"""Check whether the instance already exists.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_check_instance_exists]
:end-before: [END bigtable_check_instance_exists]
:rtype: bool
:returns: True if the table exists, else False.
"""
try:
self._client.instance_admin_client.get_instance(name=self.name)
return True
# NOTE: There could be other exceptions that are returned to the user.
except NotFound:
return False
|
python
|
def exists(self):
"""Check whether the instance already exists.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_check_instance_exists]
:end-before: [END bigtable_check_instance_exists]
:rtype: bool
:returns: True if the table exists, else False.
"""
try:
self._client.instance_admin_client.get_instance(name=self.name)
return True
# NOTE: There could be other exceptions that are returned to the user.
except NotFound:
return False
|
[
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"return",
"True",
"# NOTE: There could be other exceptions that are returned to the user.",
"except",
"NotFound",
":",
"return",
"False"
] |
Check whether the instance already exists.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_check_instance_exists]
:end-before: [END bigtable_check_instance_exists]
:rtype: bool
:returns: True if the table exists, else False.
|
[
"Check",
"whether",
"the",
"instance",
"already",
"exists",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable/instance.py#L327-L344
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable/instance.py
|
Instance.reload
|
def reload(self):
"""Reload the metadata for this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_reload_instance]
:end-before: [END bigtable_reload_instance]
"""
instance_pb = self._client.instance_admin_client.get_instance(self.name)
# NOTE: _update_from_pb does not check that the project and
# instance ID on the response match the request.
self._update_from_pb(instance_pb)
|
python
|
def reload(self):
"""Reload the metadata for this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_reload_instance]
:end-before: [END bigtable_reload_instance]
"""
instance_pb = self._client.instance_admin_client.get_instance(self.name)
# NOTE: _update_from_pb does not check that the project and
# instance ID on the response match the request.
self._update_from_pb(instance_pb)
|
[
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"# instance ID on the response match the request.",
"self",
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"_update_from_pb",
"(",
"instance_pb",
")"
] |
Reload the metadata for this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_reload_instance]
:end-before: [END bigtable_reload_instance]
|
[
"Reload",
"the",
"metadata",
"for",
"this",
"instance",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable/instance.py#L346-L359
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable/instance.py
|
Instance.update
|
def update(self):
"""Updates an instance within a project.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_update_instance]
:end-before: [END bigtable_update_instance]
.. note::
Updates any or all of the following values:
``display_name``
``type``
``labels``
To change a value before
updating, assign that values via
.. code:: python
instance.display_name = 'New display name'
before calling :meth:`update`.
:rtype: :class:`~google.api_core.operation.Operation`
:returns: The long-running operation corresponding to the update
operation.
"""
update_mask_pb = field_mask_pb2.FieldMask()
if self.display_name is not None:
update_mask_pb.paths.append("display_name")
if self.type_ is not None:
update_mask_pb.paths.append("type")
if self.labels is not None:
update_mask_pb.paths.append("labels")
instance_pb = instance_pb2.Instance(
name=self.name,
display_name=self.display_name,
type=self.type_,
labels=self.labels,
)
return self._client.instance_admin_client.partial_update_instance(
instance=instance_pb, update_mask=update_mask_pb
)
|
python
|
def update(self):
"""Updates an instance within a project.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_update_instance]
:end-before: [END bigtable_update_instance]
.. note::
Updates any or all of the following values:
``display_name``
``type``
``labels``
To change a value before
updating, assign that values via
.. code:: python
instance.display_name = 'New display name'
before calling :meth:`update`.
:rtype: :class:`~google.api_core.operation.Operation`
:returns: The long-running operation corresponding to the update
operation.
"""
update_mask_pb = field_mask_pb2.FieldMask()
if self.display_name is not None:
update_mask_pb.paths.append("display_name")
if self.type_ is not None:
update_mask_pb.paths.append("type")
if self.labels is not None:
update_mask_pb.paths.append("labels")
instance_pb = instance_pb2.Instance(
name=self.name,
display_name=self.display_name,
type=self.type_,
labels=self.labels,
)
return self._client.instance_admin_client.partial_update_instance(
instance=instance_pb, update_mask=update_mask_pb
)
|
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Updates an instance within a project.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_update_instance]
:end-before: [END bigtable_update_instance]
.. note::
Updates any or all of the following values:
``display_name``
``type``
``labels``
To change a value before
updating, assign that values via
.. code:: python
instance.display_name = 'New display name'
before calling :meth:`update`.
:rtype: :class:`~google.api_core.operation.Operation`
:returns: The long-running operation corresponding to the update
operation.
|
[
"Updates",
"an",
"instance",
"within",
"a",
"project",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable/instance.py#L361-L405
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable/instance.py
|
Instance.get_iam_policy
|
def get_iam_policy(self):
"""Gets the access control policy for an instance resource.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_get_iam_policy]
:end-before: [END bigtable_get_iam_policy]
:rtype: :class:`google.cloud.bigtable.policy.Policy`
:returns: The current IAM policy of this instance
"""
instance_admin_client = self._client.instance_admin_client
resp = instance_admin_client.get_iam_policy(resource=self.name)
return Policy.from_pb(resp)
|
python
|
def get_iam_policy(self):
"""Gets the access control policy for an instance resource.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_get_iam_policy]
:end-before: [END bigtable_get_iam_policy]
:rtype: :class:`google.cloud.bigtable.policy.Policy`
:returns: The current IAM policy of this instance
"""
instance_admin_client = self._client.instance_admin_client
resp = instance_admin_client.get_iam_policy(resource=self.name)
return Policy.from_pb(resp)
|
[
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".",
"name",
")",
"return",
"Policy",
".",
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"(",
"resp",
")"
] |
Gets the access control policy for an instance resource.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_get_iam_policy]
:end-before: [END bigtable_get_iam_policy]
:rtype: :class:`google.cloud.bigtable.policy.Policy`
:returns: The current IAM policy of this instance
|
[
"Gets",
"the",
"access",
"control",
"policy",
"for",
"an",
"instance",
"resource",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable/instance.py#L437-L451
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable/instance.py
|
Instance.set_iam_policy
|
def set_iam_policy(self, policy):
"""Sets the access control policy on an instance resource. Replaces any
existing policy.
For more information about policy, please see documentation of
class `google.cloud.bigtable.policy.Policy`
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_set_iam_policy]
:end-before: [END bigtable_set_iam_policy]
:type policy: :class:`google.cloud.bigtable.policy.Policy`
:param policy: A new IAM policy to replace the current IAM policy
of this instance
:rtype: :class:`google.cloud.bigtable.policy.Policy`
:returns: The current IAM policy of this instance.
"""
instance_admin_client = self._client.instance_admin_client
resp = instance_admin_client.set_iam_policy(
resource=self.name, policy=policy.to_pb()
)
return Policy.from_pb(resp)
|
python
|
def set_iam_policy(self, policy):
"""Sets the access control policy on an instance resource. Replaces any
existing policy.
For more information about policy, please see documentation of
class `google.cloud.bigtable.policy.Policy`
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_set_iam_policy]
:end-before: [END bigtable_set_iam_policy]
:type policy: :class:`google.cloud.bigtable.policy.Policy`
:param policy: A new IAM policy to replace the current IAM policy
of this instance
:rtype: :class:`google.cloud.bigtable.policy.Policy`
:returns: The current IAM policy of this instance.
"""
instance_admin_client = self._client.instance_admin_client
resp = instance_admin_client.set_iam_policy(
resource=self.name, policy=policy.to_pb()
)
return Policy.from_pb(resp)
|
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] |
Sets the access control policy on an instance resource. Replaces any
existing policy.
For more information about policy, please see documentation of
class `google.cloud.bigtable.policy.Policy`
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_set_iam_policy]
:end-before: [END bigtable_set_iam_policy]
:type policy: :class:`google.cloud.bigtable.policy.Policy`
:param policy: A new IAM policy to replace the current IAM policy
of this instance
:rtype: :class:`google.cloud.bigtable.policy.Policy`
:returns: The current IAM policy of this instance.
|
[
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"policy",
"on",
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"instance",
"resource",
".",
"Replaces",
"any",
"existing",
"policy",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable/instance.py#L453-L477
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable/instance.py
|
Instance.cluster
|
def cluster(
self, cluster_id, location_id=None, serve_nodes=None, default_storage_type=None
):
"""Factory to create a cluster associated with this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_cluster]
:end-before: [END bigtable_create_cluster]
:type cluster_id: str
:param cluster_id: The ID of the cluster.
:type instance: :class:`~google.cloud.bigtable.instance.Instance`
:param instance: The instance where the cluster resides.
:type location_id: str
:param location_id: (Creation Only) The location where this cluster's
nodes and storage reside. For best performance,
clients should be located as close as possible to
this cluster.
For list of supported locations refer to
https://cloud.google.com/bigtable/docs/locations
:type serve_nodes: int
:param serve_nodes: (Optional) The number of nodes in the cluster.
:type default_storage_type: int
:param default_storage_type: (Optional) The type of storage
Possible values are represented by the
following constants:
:data:`google.cloud.bigtable.enums.StorageType.SSD`.
:data:`google.cloud.bigtable.enums.StorageType.SHD`,
Defaults to
:data:`google.cloud.bigtable.enums.StorageType.UNSPECIFIED`.
:rtype: :class:`~google.cloud.bigtable.instance.Cluster`
:returns: a cluster owned by this instance.
"""
return Cluster(
cluster_id,
self,
location_id=location_id,
serve_nodes=serve_nodes,
default_storage_type=default_storage_type,
)
|
python
|
def cluster(
self, cluster_id, location_id=None, serve_nodes=None, default_storage_type=None
):
"""Factory to create a cluster associated with this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_cluster]
:end-before: [END bigtable_create_cluster]
:type cluster_id: str
:param cluster_id: The ID of the cluster.
:type instance: :class:`~google.cloud.bigtable.instance.Instance`
:param instance: The instance where the cluster resides.
:type location_id: str
:param location_id: (Creation Only) The location where this cluster's
nodes and storage reside. For best performance,
clients should be located as close as possible to
this cluster.
For list of supported locations refer to
https://cloud.google.com/bigtable/docs/locations
:type serve_nodes: int
:param serve_nodes: (Optional) The number of nodes in the cluster.
:type default_storage_type: int
:param default_storage_type: (Optional) The type of storage
Possible values are represented by the
following constants:
:data:`google.cloud.bigtable.enums.StorageType.SSD`.
:data:`google.cloud.bigtable.enums.StorageType.SHD`,
Defaults to
:data:`google.cloud.bigtable.enums.StorageType.UNSPECIFIED`.
:rtype: :class:`~google.cloud.bigtable.instance.Cluster`
:returns: a cluster owned by this instance.
"""
return Cluster(
cluster_id,
self,
location_id=location_id,
serve_nodes=serve_nodes,
default_storage_type=default_storage_type,
)
|
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",",
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] |
Factory to create a cluster associated with this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_cluster]
:end-before: [END bigtable_create_cluster]
:type cluster_id: str
:param cluster_id: The ID of the cluster.
:type instance: :class:`~google.cloud.bigtable.instance.Instance`
:param instance: The instance where the cluster resides.
:type location_id: str
:param location_id: (Creation Only) The location where this cluster's
nodes and storage reside. For best performance,
clients should be located as close as possible to
this cluster.
For list of supported locations refer to
https://cloud.google.com/bigtable/docs/locations
:type serve_nodes: int
:param serve_nodes: (Optional) The number of nodes in the cluster.
:type default_storage_type: int
:param default_storage_type: (Optional) The type of storage
Possible values are represented by the
following constants:
:data:`google.cloud.bigtable.enums.StorageType.SSD`.
:data:`google.cloud.bigtable.enums.StorageType.SHD`,
Defaults to
:data:`google.cloud.bigtable.enums.StorageType.UNSPECIFIED`.
:rtype: :class:`~google.cloud.bigtable.instance.Cluster`
:returns: a cluster owned by this instance.
|
[
"Factory",
"to",
"create",
"a",
"cluster",
"associated",
"with",
"this",
"instance",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable/instance.py#L507-L553
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable/instance.py
|
Instance.list_clusters
|
def list_clusters(self):
"""List the clusters in this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_list_clusters_on_instance]
:end-before: [END bigtable_list_clusters_on_instance]
:rtype: tuple
:returns:
(clusters, failed_locations), where 'clusters' is list of
:class:`google.cloud.bigtable.instance.Cluster`, and
'failed_locations' is a list of locations which could not
be resolved.
"""
resp = self._client.instance_admin_client.list_clusters(self.name)
clusters = [Cluster.from_pb(cluster, self) for cluster in resp.clusters]
return clusters, resp.failed_locations
|
python
|
def list_clusters(self):
"""List the clusters in this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_list_clusters_on_instance]
:end-before: [END bigtable_list_clusters_on_instance]
:rtype: tuple
:returns:
(clusters, failed_locations), where 'clusters' is list of
:class:`google.cloud.bigtable.instance.Cluster`, and
'failed_locations' is a list of locations which could not
be resolved.
"""
resp = self._client.instance_admin_client.list_clusters(self.name)
clusters = [Cluster.from_pb(cluster, self) for cluster in resp.clusters]
return clusters, resp.failed_locations
|
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List the clusters in this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_list_clusters_on_instance]
:end-before: [END bigtable_list_clusters_on_instance]
:rtype: tuple
:returns:
(clusters, failed_locations), where 'clusters' is list of
:class:`google.cloud.bigtable.instance.Cluster`, and
'failed_locations' is a list of locations which could not
be resolved.
|
[
"List",
"the",
"clusters",
"in",
"this",
"instance",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable/instance.py#L555-L573
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable/instance.py
|
Instance.table
|
def table(self, table_id, mutation_timeout=None, app_profile_id=None):
"""Factory to create a table associated with this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_table]
:end-before: [END bigtable_create_table]
:type table_id: str
:param table_id: The ID of the table.
:type app_profile_id: str
:param app_profile_id: (Optional) The unique name of the AppProfile.
:rtype: :class:`Table <google.cloud.bigtable.table.Table>`
:returns: The table owned by this instance.
"""
return Table(
table_id,
self,
app_profile_id=app_profile_id,
mutation_timeout=mutation_timeout,
)
|
python
|
def table(self, table_id, mutation_timeout=None, app_profile_id=None):
"""Factory to create a table associated with this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_table]
:end-before: [END bigtable_create_table]
:type table_id: str
:param table_id: The ID of the table.
:type app_profile_id: str
:param app_profile_id: (Optional) The unique name of the AppProfile.
:rtype: :class:`Table <google.cloud.bigtable.table.Table>`
:returns: The table owned by this instance.
"""
return Table(
table_id,
self,
app_profile_id=app_profile_id,
mutation_timeout=mutation_timeout,
)
|
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",",
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"=",
"mutation_timeout",
",",
")"
] |
Factory to create a table associated with this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_table]
:end-before: [END bigtable_create_table]
:type table_id: str
:param table_id: The ID of the table.
:type app_profile_id: str
:param app_profile_id: (Optional) The unique name of the AppProfile.
:rtype: :class:`Table <google.cloud.bigtable.table.Table>`
:returns: The table owned by this instance.
|
[
"Factory",
"to",
"create",
"a",
"table",
"associated",
"with",
"this",
"instance",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable/instance.py#L575-L598
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable/instance.py
|
Instance.list_tables
|
def list_tables(self):
"""List the tables in this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_list_tables]
:end-before: [END bigtable_list_tables]
:rtype: list of :class:`Table <google.cloud.bigtable.table.Table>`
:returns: The list of tables owned by the instance.
:raises: :class:`ValueError <exceptions.ValueError>` if one of the
returned tables has a name that is not of the expected format.
"""
table_list_pb = self._client.table_admin_client.list_tables(self.name)
result = []
for table_pb in table_list_pb:
table_prefix = self.name + "/tables/"
if not table_pb.name.startswith(table_prefix):
raise ValueError(
"Table name {} not of expected format".format(table_pb.name)
)
table_id = table_pb.name[len(table_prefix) :]
result.append(self.table(table_id))
return result
|
python
|
def list_tables(self):
"""List the tables in this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_list_tables]
:end-before: [END bigtable_list_tables]
:rtype: list of :class:`Table <google.cloud.bigtable.table.Table>`
:returns: The list of tables owned by the instance.
:raises: :class:`ValueError <exceptions.ValueError>` if one of the
returned tables has a name that is not of the expected format.
"""
table_list_pb = self._client.table_admin_client.list_tables(self.name)
result = []
for table_pb in table_list_pb:
table_prefix = self.name + "/tables/"
if not table_pb.name.startswith(table_prefix):
raise ValueError(
"Table name {} not of expected format".format(table_pb.name)
)
table_id = table_pb.name[len(table_prefix) :]
result.append(self.table(table_id))
return result
|
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"(",
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")",
"return",
"result"
] |
List the tables in this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_list_tables]
:end-before: [END bigtable_list_tables]
:rtype: list of :class:`Table <google.cloud.bigtable.table.Table>`
:returns: The list of tables owned by the instance.
:raises: :class:`ValueError <exceptions.ValueError>` if one of the
returned tables has a name that is not of the expected format.
|
[
"List",
"the",
"tables",
"in",
"this",
"instance",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable/instance.py#L600-L626
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable/instance.py
|
Instance.app_profile
|
def app_profile(
self,
app_profile_id,
routing_policy_type=None,
description=None,
cluster_id=None,
allow_transactional_writes=None,
):
"""Factory to create AppProfile associated with this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_app_profile]
:end-before: [END bigtable_create_app_profile]
:type app_profile_id: str
:param app_profile_id: The ID of the AppProfile. Must be of the form
``[_a-zA-Z0-9][-_.a-zA-Z0-9]*``.
:type: routing_policy_type: int
:param: routing_policy_type: The type of the routing policy.
Possible values are represented
by the following constants:
:data:`google.cloud.bigtable.enums.RoutingPolicyType.ANY`
:data:`google.cloud.bigtable.enums.RoutingPolicyType.SINGLE`
:type: description: str
:param: description: (Optional) Long form description of the use
case for this AppProfile.
:type: cluster_id: str
:param: cluster_id: (Optional) Unique cluster_id which is only required
when routing_policy_type is
ROUTING_POLICY_TYPE_SINGLE.
:type: allow_transactional_writes: bool
:param: allow_transactional_writes: (Optional) If true, allow
transactional writes for
ROUTING_POLICY_TYPE_SINGLE.
:rtype: :class:`~google.cloud.bigtable.app_profile.AppProfile>`
:returns: AppProfile for this instance.
"""
return AppProfile(
app_profile_id,
self,
routing_policy_type=routing_policy_type,
description=description,
cluster_id=cluster_id,
allow_transactional_writes=allow_transactional_writes,
)
|
python
|
def app_profile(
self,
app_profile_id,
routing_policy_type=None,
description=None,
cluster_id=None,
allow_transactional_writes=None,
):
"""Factory to create AppProfile associated with this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_app_profile]
:end-before: [END bigtable_create_app_profile]
:type app_profile_id: str
:param app_profile_id: The ID of the AppProfile. Must be of the form
``[_a-zA-Z0-9][-_.a-zA-Z0-9]*``.
:type: routing_policy_type: int
:param: routing_policy_type: The type of the routing policy.
Possible values are represented
by the following constants:
:data:`google.cloud.bigtable.enums.RoutingPolicyType.ANY`
:data:`google.cloud.bigtable.enums.RoutingPolicyType.SINGLE`
:type: description: str
:param: description: (Optional) Long form description of the use
case for this AppProfile.
:type: cluster_id: str
:param: cluster_id: (Optional) Unique cluster_id which is only required
when routing_policy_type is
ROUTING_POLICY_TYPE_SINGLE.
:type: allow_transactional_writes: bool
:param: allow_transactional_writes: (Optional) If true, allow
transactional writes for
ROUTING_POLICY_TYPE_SINGLE.
:rtype: :class:`~google.cloud.bigtable.app_profile.AppProfile>`
:returns: AppProfile for this instance.
"""
return AppProfile(
app_profile_id,
self,
routing_policy_type=routing_policy_type,
description=description,
cluster_id=cluster_id,
allow_transactional_writes=allow_transactional_writes,
)
|
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Factory to create AppProfile associated with this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_app_profile]
:end-before: [END bigtable_create_app_profile]
:type app_profile_id: str
:param app_profile_id: The ID of the AppProfile. Must be of the form
``[_a-zA-Z0-9][-_.a-zA-Z0-9]*``.
:type: routing_policy_type: int
:param: routing_policy_type: The type of the routing policy.
Possible values are represented
by the following constants:
:data:`google.cloud.bigtable.enums.RoutingPolicyType.ANY`
:data:`google.cloud.bigtable.enums.RoutingPolicyType.SINGLE`
:type: description: str
:param: description: (Optional) Long form description of the use
case for this AppProfile.
:type: cluster_id: str
:param: cluster_id: (Optional) Unique cluster_id which is only required
when routing_policy_type is
ROUTING_POLICY_TYPE_SINGLE.
:type: allow_transactional_writes: bool
:param: allow_transactional_writes: (Optional) If true, allow
transactional writes for
ROUTING_POLICY_TYPE_SINGLE.
:rtype: :class:`~google.cloud.bigtable.app_profile.AppProfile>`
:returns: AppProfile for this instance.
|
[
"Factory",
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"create",
"AppProfile",
"associated",
"with",
"this",
"instance",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable/instance.py#L628-L679
|
train
|
googleapis/google-cloud-python
|
bigtable/google/cloud/bigtable/instance.py
|
Instance.list_app_profiles
|
def list_app_profiles(self):
"""Lists information about AppProfiles in an instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_list_app_profiles]
:end-before: [END bigtable_list_app_profiles]
:rtype: :list:[`~google.cloud.bigtable.app_profile.AppProfile`]
:returns: A :list:[`~google.cloud.bigtable.app_profile.AppProfile`].
By default, this is a list of
:class:`~google.cloud.bigtable.app_profile.AppProfile`
instances.
"""
resp = self._client.instance_admin_client.list_app_profiles(self.name)
return [AppProfile.from_pb(app_profile, self) for app_profile in resp]
|
python
|
def list_app_profiles(self):
"""Lists information about AppProfiles in an instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_list_app_profiles]
:end-before: [END bigtable_list_app_profiles]
:rtype: :list:[`~google.cloud.bigtable.app_profile.AppProfile`]
:returns: A :list:[`~google.cloud.bigtable.app_profile.AppProfile`].
By default, this is a list of
:class:`~google.cloud.bigtable.app_profile.AppProfile`
instances.
"""
resp = self._client.instance_admin_client.list_app_profiles(self.name)
return [AppProfile.from_pb(app_profile, self) for app_profile in resp]
|
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Lists information about AppProfiles in an instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_list_app_profiles]
:end-before: [END bigtable_list_app_profiles]
:rtype: :list:[`~google.cloud.bigtable.app_profile.AppProfile`]
:returns: A :list:[`~google.cloud.bigtable.app_profile.AppProfile`].
By default, this is a list of
:class:`~google.cloud.bigtable.app_profile.AppProfile`
instances.
|
[
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"in",
"an",
"instance",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/google/cloud/bigtable/instance.py#L681-L697
|
train
|
googleapis/google-cloud-python
|
bigtable/noxfile.py
|
system
|
def system(session):
"""Run the system test suite."""
system_test_path = os.path.join("tests", "system.py")
system_test_folder_path = os.path.join("tests", "system")
# Sanity check: Only run tests if the environment variable is set.
if not os.environ.get("GOOGLE_APPLICATION_CREDENTIALS", ""):
session.skip("Credentials must be set via environment variable")
system_test_exists = os.path.exists(system_test_path)
system_test_folder_exists = os.path.exists(system_test_folder_path)
# Sanity check: only run tests if found.
if not system_test_exists and not system_test_folder_exists:
session.skip("System tests were not found")
# Use pre-release gRPC for system tests.
session.install("--pre", "grpcio")
# Install all test dependencies, then install this package into the
# virtualenv's dist-packages.
session.install("mock", "pytest")
for local_dep in LOCAL_DEPS:
session.install("-e", local_dep)
session.install("-e", "../test_utils/")
session.install("-e", ".")
# Run py.test against the system tests.
if system_test_exists:
session.run("py.test", "--quiet", system_test_path, *session.posargs)
if system_test_folder_exists:
session.run("py.test", "--quiet", system_test_folder_path, *session.posargs)
|
python
|
def system(session):
"""Run the system test suite."""
system_test_path = os.path.join("tests", "system.py")
system_test_folder_path = os.path.join("tests", "system")
# Sanity check: Only run tests if the environment variable is set.
if not os.environ.get("GOOGLE_APPLICATION_CREDENTIALS", ""):
session.skip("Credentials must be set via environment variable")
system_test_exists = os.path.exists(system_test_path)
system_test_folder_exists = os.path.exists(system_test_folder_path)
# Sanity check: only run tests if found.
if not system_test_exists and not system_test_folder_exists:
session.skip("System tests were not found")
# Use pre-release gRPC for system tests.
session.install("--pre", "grpcio")
# Install all test dependencies, then install this package into the
# virtualenv's dist-packages.
session.install("mock", "pytest")
for local_dep in LOCAL_DEPS:
session.install("-e", local_dep)
session.install("-e", "../test_utils/")
session.install("-e", ".")
# Run py.test against the system tests.
if system_test_exists:
session.run("py.test", "--quiet", system_test_path, *session.posargs)
if system_test_folder_exists:
session.run("py.test", "--quiet", system_test_folder_path, *session.posargs)
|
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Run the system test suite.
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[
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] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigtable/noxfile.py#L94-L123
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
_reference_getter
|
def _reference_getter(table):
"""A :class:`~google.cloud.bigquery.table.TableReference` pointing to
this table.
Returns:
google.cloud.bigquery.table.TableReference: pointer to this table.
"""
from google.cloud.bigquery import dataset
dataset_ref = dataset.DatasetReference(table.project, table.dataset_id)
return TableReference(dataset_ref, table.table_id)
|
python
|
def _reference_getter(table):
"""A :class:`~google.cloud.bigquery.table.TableReference` pointing to
this table.
Returns:
google.cloud.bigquery.table.TableReference: pointer to this table.
"""
from google.cloud.bigquery import dataset
dataset_ref = dataset.DatasetReference(table.project, table.dataset_id)
return TableReference(dataset_ref, table.table_id)
|
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A :class:`~google.cloud.bigquery.table.TableReference` pointing to
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L80-L90
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
_view_use_legacy_sql_getter
|
def _view_use_legacy_sql_getter(table):
"""bool: Specifies whether to execute the view with Legacy or Standard SQL.
This boolean specifies whether to execute the view with Legacy SQL
(:data:`True`) or Standard SQL (:data:`False`). The client side default is
:data:`False`. The server-side default is :data:`True`. If this table is
not a view, :data:`None` is returned.
Raises:
ValueError: For invalid value types.
"""
view = table._properties.get("view")
if view is not None:
# The server-side default for useLegacySql is True.
return view.get("useLegacySql", True)
# In some cases, such as in a table list no view object is present, but the
# resource still represents a view. Use the type as a fallback.
if table.table_type == "VIEW":
# The server-side default for useLegacySql is True.
return True
|
python
|
def _view_use_legacy_sql_getter(table):
"""bool: Specifies whether to execute the view with Legacy or Standard SQL.
This boolean specifies whether to execute the view with Legacy SQL
(:data:`True`) or Standard SQL (:data:`False`). The client side default is
:data:`False`. The server-side default is :data:`True`. If this table is
not a view, :data:`None` is returned.
Raises:
ValueError: For invalid value types.
"""
view = table._properties.get("view")
if view is not None:
# The server-side default for useLegacySql is True.
return view.get("useLegacySql", True)
# In some cases, such as in a table list no view object is present, but the
# resource still represents a view. Use the type as a fallback.
if table.table_type == "VIEW":
# The server-side default for useLegacySql is True.
return True
|
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bool: Specifies whether to execute the view with Legacy or Standard SQL.
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L93-L112
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
_row_from_mapping
|
def _row_from_mapping(mapping, schema):
"""Convert a mapping to a row tuple using the schema.
Args:
mapping (Dict[str, object])
Mapping of row data: must contain keys for all required fields in
the schema. Keys which do not correspond to a field in the schema
are ignored.
schema (List[google.cloud.bigquery.schema.SchemaField]):
The schema of the table destination for the rows
Returns:
Tuple[object]:
Tuple whose elements are ordered according to the schema.
Raises:
ValueError: If schema is empty.
"""
if len(schema) == 0:
raise ValueError(_TABLE_HAS_NO_SCHEMA)
row = []
for field in schema:
if field.mode == "REQUIRED":
row.append(mapping[field.name])
elif field.mode == "REPEATED":
row.append(mapping.get(field.name, ()))
elif field.mode == "NULLABLE":
row.append(mapping.get(field.name))
else:
raise ValueError("Unknown field mode: {}".format(field.mode))
return tuple(row)
|
python
|
def _row_from_mapping(mapping, schema):
"""Convert a mapping to a row tuple using the schema.
Args:
mapping (Dict[str, object])
Mapping of row data: must contain keys for all required fields in
the schema. Keys which do not correspond to a field in the schema
are ignored.
schema (List[google.cloud.bigquery.schema.SchemaField]):
The schema of the table destination for the rows
Returns:
Tuple[object]:
Tuple whose elements are ordered according to the schema.
Raises:
ValueError: If schema is empty.
"""
if len(schema) == 0:
raise ValueError(_TABLE_HAS_NO_SCHEMA)
row = []
for field in schema:
if field.mode == "REQUIRED":
row.append(mapping[field.name])
elif field.mode == "REPEATED":
row.append(mapping.get(field.name, ()))
elif field.mode == "NULLABLE":
row.append(mapping.get(field.name))
else:
raise ValueError("Unknown field mode: {}".format(field.mode))
return tuple(row)
|
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Convert a mapping to a row tuple using the schema.
Args:
mapping (Dict[str, object])
Mapping of row data: must contain keys for all required fields in
the schema. Keys which do not correspond to a field in the schema
are ignored.
schema (List[google.cloud.bigquery.schema.SchemaField]):
The schema of the table destination for the rows
Returns:
Tuple[object]:
Tuple whose elements are ordered according to the schema.
Raises:
ValueError: If schema is empty.
|
[
"Convert",
"a",
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"using",
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] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L1105-L1136
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
_item_to_row
|
def _item_to_row(iterator, resource):
"""Convert a JSON row to the native object.
.. note::
This assumes that the ``schema`` attribute has been
added to the iterator after being created, which
should be done by the caller.
:type iterator: :class:`~google.api_core.page_iterator.Iterator`
:param iterator: The iterator that is currently in use.
:type resource: dict
:param resource: An item to be converted to a row.
:rtype: :class:`~google.cloud.bigquery.table.Row`
:returns: The next row in the page.
"""
return Row(
_helpers._row_tuple_from_json(resource, iterator.schema),
iterator._field_to_index,
)
|
python
|
def _item_to_row(iterator, resource):
"""Convert a JSON row to the native object.
.. note::
This assumes that the ``schema`` attribute has been
added to the iterator after being created, which
should be done by the caller.
:type iterator: :class:`~google.api_core.page_iterator.Iterator`
:param iterator: The iterator that is currently in use.
:type resource: dict
:param resource: An item to be converted to a row.
:rtype: :class:`~google.cloud.bigquery.table.Row`
:returns: The next row in the page.
"""
return Row(
_helpers._row_tuple_from_json(resource, iterator.schema),
iterator._field_to_index,
)
|
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Convert a JSON row to the native object.
.. note::
This assumes that the ``schema`` attribute has been
added to the iterator after being created, which
should be done by the caller.
:type iterator: :class:`~google.api_core.page_iterator.Iterator`
:param iterator: The iterator that is currently in use.
:type resource: dict
:param resource: An item to be converted to a row.
:rtype: :class:`~google.cloud.bigquery.table.Row`
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[
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L1882-L1903
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
_rows_page_start
|
def _rows_page_start(iterator, page, response):
"""Grab total rows when :class:`~google.cloud.iterator.Page` starts.
:type iterator: :class:`~google.api_core.page_iterator.Iterator`
:param iterator: The iterator that is currently in use.
:type page: :class:`~google.api_core.page_iterator.Page`
:param page: The page that was just created.
:type response: dict
:param response: The JSON API response for a page of rows in a table.
"""
total_rows = response.get("totalRows")
if total_rows is not None:
total_rows = int(total_rows)
iterator._total_rows = total_rows
|
python
|
def _rows_page_start(iterator, page, response):
"""Grab total rows when :class:`~google.cloud.iterator.Page` starts.
:type iterator: :class:`~google.api_core.page_iterator.Iterator`
:param iterator: The iterator that is currently in use.
:type page: :class:`~google.api_core.page_iterator.Page`
:param page: The page that was just created.
:type response: dict
:param response: The JSON API response for a page of rows in a table.
"""
total_rows = response.get("totalRows")
if total_rows is not None:
total_rows = int(total_rows)
iterator._total_rows = total_rows
|
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Grab total rows when :class:`~google.cloud.iterator.Page` starts.
:type iterator: :class:`~google.api_core.page_iterator.Iterator`
:param iterator: The iterator that is currently in use.
:type page: :class:`~google.api_core.page_iterator.Page`
:param page: The page that was just created.
:type response: dict
:param response: The JSON API response for a page of rows in a table.
|
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":",
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":",
"~google",
".",
"cloud",
".",
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".",
"Page",
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L1907-L1922
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
_table_arg_to_table_ref
|
def _table_arg_to_table_ref(value, default_project=None):
"""Helper to convert a string or Table to TableReference.
This function keeps TableReference and other kinds of objects unchanged.
"""
if isinstance(value, six.string_types):
value = TableReference.from_string(value, default_project=default_project)
if isinstance(value, (Table, TableListItem)):
value = value.reference
return value
|
python
|
def _table_arg_to_table_ref(value, default_project=None):
"""Helper to convert a string or Table to TableReference.
This function keeps TableReference and other kinds of objects unchanged.
"""
if isinstance(value, six.string_types):
value = TableReference.from_string(value, default_project=default_project)
if isinstance(value, (Table, TableListItem)):
value = value.reference
return value
|
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Helper to convert a string or Table to TableReference.
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|
[
"Helper",
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"a",
"string",
"or",
"Table",
"to",
"TableReference",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L1928-L1937
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
_table_arg_to_table
|
def _table_arg_to_table(value, default_project=None):
"""Helper to convert a string or TableReference to a Table.
This function keeps Table and other kinds of objects unchanged.
"""
if isinstance(value, six.string_types):
value = TableReference.from_string(value, default_project=default_project)
if isinstance(value, TableReference):
value = Table(value)
if isinstance(value, TableListItem):
newvalue = Table(value.reference)
newvalue._properties = value._properties
value = newvalue
return value
|
python
|
def _table_arg_to_table(value, default_project=None):
"""Helper to convert a string or TableReference to a Table.
This function keeps Table and other kinds of objects unchanged.
"""
if isinstance(value, six.string_types):
value = TableReference.from_string(value, default_project=default_project)
if isinstance(value, TableReference):
value = Table(value)
if isinstance(value, TableListItem):
newvalue = Table(value.reference)
newvalue._properties = value._properties
value = newvalue
return value
|
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Helper to convert a string or TableReference to a Table.
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[
"Helper",
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"string",
"or",
"TableReference",
"to",
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"Table",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L1940-L1954
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
TableReference.from_string
|
def from_string(cls, table_id, default_project=None):
"""Construct a table reference from table ID string.
Args:
table_id (str):
A table ID in standard SQL format. If ``default_project``
is not specified, this must included a project ID, dataset
ID, and table ID, each separated by ``.``.
default_project (str):
Optional. The project ID to use when ``table_id`` does not
include a project ID.
Returns:
TableReference: Table reference parsed from ``table_id``.
Examples:
>>> TableReference.from_string('my-project.mydataset.mytable')
TableRef...(DatasetRef...('my-project', 'mydataset'), 'mytable')
Raises:
ValueError:
If ``table_id`` is not a fully-qualified table ID in
standard SQL format.
"""
from google.cloud.bigquery.dataset import DatasetReference
(
output_project_id,
output_dataset_id,
output_table_id,
) = _helpers._parse_3_part_id(
table_id, default_project=default_project, property_name="table_id"
)
return cls(
DatasetReference(output_project_id, output_dataset_id), output_table_id
)
|
python
|
def from_string(cls, table_id, default_project=None):
"""Construct a table reference from table ID string.
Args:
table_id (str):
A table ID in standard SQL format. If ``default_project``
is not specified, this must included a project ID, dataset
ID, and table ID, each separated by ``.``.
default_project (str):
Optional. The project ID to use when ``table_id`` does not
include a project ID.
Returns:
TableReference: Table reference parsed from ``table_id``.
Examples:
>>> TableReference.from_string('my-project.mydataset.mytable')
TableRef...(DatasetRef...('my-project', 'mydataset'), 'mytable')
Raises:
ValueError:
If ``table_id`` is not a fully-qualified table ID in
standard SQL format.
"""
from google.cloud.bigquery.dataset import DatasetReference
(
output_project_id,
output_dataset_id,
output_table_id,
) = _helpers._parse_3_part_id(
table_id, default_project=default_project, property_name="table_id"
)
return cls(
DatasetReference(output_project_id, output_dataset_id), output_table_id
)
|
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"(",
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",",
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Construct a table reference from table ID string.
Args:
table_id (str):
A table ID in standard SQL format. If ``default_project``
is not specified, this must included a project ID, dataset
ID, and table ID, each separated by ``.``.
default_project (str):
Optional. The project ID to use when ``table_id`` does not
include a project ID.
Returns:
TableReference: Table reference parsed from ``table_id``.
Examples:
>>> TableReference.from_string('my-project.mydataset.mytable')
TableRef...(DatasetRef...('my-project', 'mydataset'), 'mytable')
Raises:
ValueError:
If ``table_id`` is not a fully-qualified table ID in
standard SQL format.
|
[
"Construct",
"a",
"table",
"reference",
"from",
"table",
"ID",
"string",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L224-L260
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
TableReference.from_api_repr
|
def from_api_repr(cls, resource):
"""Factory: construct a table reference given its API representation
Args:
resource (Dict[str, object]):
Table reference representation returned from the API
Returns:
google.cloud.bigquery.table.TableReference:
Table reference parsed from ``resource``.
"""
from google.cloud.bigquery.dataset import DatasetReference
project = resource["projectId"]
dataset_id = resource["datasetId"]
table_id = resource["tableId"]
return cls(DatasetReference(project, dataset_id), table_id)
|
python
|
def from_api_repr(cls, resource):
"""Factory: construct a table reference given its API representation
Args:
resource (Dict[str, object]):
Table reference representation returned from the API
Returns:
google.cloud.bigquery.table.TableReference:
Table reference parsed from ``resource``.
"""
from google.cloud.bigquery.dataset import DatasetReference
project = resource["projectId"]
dataset_id = resource["datasetId"]
table_id = resource["tableId"]
return cls(DatasetReference(project, dataset_id), table_id)
|
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Factory: construct a table reference given its API representation
Args:
resource (Dict[str, object]):
Table reference representation returned from the API
Returns:
google.cloud.bigquery.table.TableReference:
Table reference parsed from ``resource``.
|
[
"Factory",
":",
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"table",
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"given",
"its",
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L263-L279
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
TableReference.to_bqstorage
|
def to_bqstorage(self):
"""Construct a BigQuery Storage API representation of this table.
Install the ``google-cloud-bigquery-storage`` package to use this
feature.
If the ``table_id`` contains a partition identifier (e.g.
``my_table$201812``) or a snapshot identifier (e.g.
``mytable@1234567890``), it is ignored. Use
:class:`google.cloud.bigquery_storage_v1beta1.types.TableReadOptions`
to filter rows by partition. Use
:class:`google.cloud.bigquery_storage_v1beta1.types.TableModifiers`
to select a specific snapshot to read from.
Returns:
google.cloud.bigquery_storage_v1beta1.types.TableReference:
A reference to this table in the BigQuery Storage API.
Raises:
ValueError:
If the :mod:`google.cloud.bigquery_storage_v1beta1` module
cannot be imported.
"""
if bigquery_storage_v1beta1 is None:
raise ValueError(_NO_BQSTORAGE_ERROR)
table_ref = bigquery_storage_v1beta1.types.TableReference()
table_ref.project_id = self._project
table_ref.dataset_id = self._dataset_id
table_id = self._table_id
if "@" in table_id:
table_id = table_id.split("@")[0]
if "$" in table_id:
table_id = table_id.split("$")[0]
table_ref.table_id = table_id
return table_ref
|
python
|
def to_bqstorage(self):
"""Construct a BigQuery Storage API representation of this table.
Install the ``google-cloud-bigquery-storage`` package to use this
feature.
If the ``table_id`` contains a partition identifier (e.g.
``my_table$201812``) or a snapshot identifier (e.g.
``mytable@1234567890``), it is ignored. Use
:class:`google.cloud.bigquery_storage_v1beta1.types.TableReadOptions`
to filter rows by partition. Use
:class:`google.cloud.bigquery_storage_v1beta1.types.TableModifiers`
to select a specific snapshot to read from.
Returns:
google.cloud.bigquery_storage_v1beta1.types.TableReference:
A reference to this table in the BigQuery Storage API.
Raises:
ValueError:
If the :mod:`google.cloud.bigquery_storage_v1beta1` module
cannot be imported.
"""
if bigquery_storage_v1beta1 is None:
raise ValueError(_NO_BQSTORAGE_ERROR)
table_ref = bigquery_storage_v1beta1.types.TableReference()
table_ref.project_id = self._project
table_ref.dataset_id = self._dataset_id
table_id = self._table_id
if "@" in table_id:
table_id = table_id.split("@")[0]
if "$" in table_id:
table_id = table_id.split("$")[0]
table_ref.table_id = table_id
return table_ref
|
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Construct a BigQuery Storage API representation of this table.
Install the ``google-cloud-bigquery-storage`` package to use this
feature.
If the ``table_id`` contains a partition identifier (e.g.
``my_table$201812``) or a snapshot identifier (e.g.
``mytable@1234567890``), it is ignored. Use
:class:`google.cloud.bigquery_storage_v1beta1.types.TableReadOptions`
to filter rows by partition. Use
:class:`google.cloud.bigquery_storage_v1beta1.types.TableModifiers`
to select a specific snapshot to read from.
Returns:
google.cloud.bigquery_storage_v1beta1.types.TableReference:
A reference to this table in the BigQuery Storage API.
Raises:
ValueError:
If the :mod:`google.cloud.bigquery_storage_v1beta1` module
cannot be imported.
|
[
"Construct",
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"API",
"representation",
"of",
"this",
"table",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L293-L332
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
Table.encryption_configuration
|
def encryption_configuration(self):
"""google.cloud.bigquery.table.EncryptionConfiguration: Custom
encryption configuration for the table.
Custom encryption configuration (e.g., Cloud KMS keys) or :data:`None`
if using default encryption.
See `protecting data with Cloud KMS keys
<https://cloud.google.com/bigquery/docs/customer-managed-encryption>`_
in the BigQuery documentation.
"""
prop = self._properties.get("encryptionConfiguration")
if prop is not None:
prop = EncryptionConfiguration.from_api_repr(prop)
return prop
|
python
|
def encryption_configuration(self):
"""google.cloud.bigquery.table.EncryptionConfiguration: Custom
encryption configuration for the table.
Custom encryption configuration (e.g., Cloud KMS keys) or :data:`None`
if using default encryption.
See `protecting data with Cloud KMS keys
<https://cloud.google.com/bigquery/docs/customer-managed-encryption>`_
in the BigQuery documentation.
"""
prop = self._properties.get("encryptionConfiguration")
if prop is not None:
prop = EncryptionConfiguration.from_api_repr(prop)
return prop
|
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google.cloud.bigquery.table.EncryptionConfiguration: Custom
encryption configuration for the table.
Custom encryption configuration (e.g., Cloud KMS keys) or :data:`None`
if using default encryption.
See `protecting data with Cloud KMS keys
<https://cloud.google.com/bigquery/docs/customer-managed-encryption>`_
in the BigQuery documentation.
|
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L471-L485
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
Table.time_partitioning
|
def time_partitioning(self):
"""google.cloud.bigquery.table.TimePartitioning: Configures time-based
partitioning for a table.
Raises:
ValueError:
If the value is not :class:`TimePartitioning` or :data:`None`.
"""
prop = self._properties.get("timePartitioning")
if prop is not None:
return TimePartitioning.from_api_repr(prop)
|
python
|
def time_partitioning(self):
"""google.cloud.bigquery.table.TimePartitioning: Configures time-based
partitioning for a table.
Raises:
ValueError:
If the value is not :class:`TimePartitioning` or :data:`None`.
"""
prop = self._properties.get("timePartitioning")
if prop is not None:
return TimePartitioning.from_api_repr(prop)
|
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google.cloud.bigquery.table.TimePartitioning: Configures time-based
partitioning for a table.
Raises:
ValueError:
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|
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L565-L575
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
Table.partition_expiration
|
def partition_expiration(self):
"""Union[int, None]: Expiration time in milliseconds for a partition.
If :attr:`partition_expiration` is set and :attr:`type_` is
not set, :attr:`type_` will default to
:attr:`~google.cloud.bigquery.table.TimePartitioningType.DAY`.
"""
warnings.warn(
"This method will be deprecated in future versions. Please use "
"Table.time_partitioning.expiration_ms instead.",
PendingDeprecationWarning,
stacklevel=2,
)
if self.time_partitioning is not None:
return self.time_partitioning.expiration_ms
|
python
|
def partition_expiration(self):
"""Union[int, None]: Expiration time in milliseconds for a partition.
If :attr:`partition_expiration` is set and :attr:`type_` is
not set, :attr:`type_` will default to
:attr:`~google.cloud.bigquery.table.TimePartitioningType.DAY`.
"""
warnings.warn(
"This method will be deprecated in future versions. Please use "
"Table.time_partitioning.expiration_ms instead.",
PendingDeprecationWarning,
stacklevel=2,
)
if self.time_partitioning is not None:
return self.time_partitioning.expiration_ms
|
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Union[int, None]: Expiration time in milliseconds for a partition.
If :attr:`partition_expiration` is set and :attr:`type_` is
not set, :attr:`type_` will default to
:attr:`~google.cloud.bigquery.table.TimePartitioningType.DAY`.
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L618-L632
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
Table.clustering_fields
|
def clustering_fields(self):
"""Union[List[str], None]: Fields defining clustering for the table
(Defaults to :data:`None`).
Clustering fields are immutable after table creation.
.. note::
As of 2018-06-29, clustering fields cannot be set on a table
which does not also have time partioning defined.
"""
prop = self._properties.get("clustering")
if prop is not None:
return list(prop.get("fields", ()))
|
python
|
def clustering_fields(self):
"""Union[List[str], None]: Fields defining clustering for the table
(Defaults to :data:`None`).
Clustering fields are immutable after table creation.
.. note::
As of 2018-06-29, clustering fields cannot be set on a table
which does not also have time partioning defined.
"""
prop = self._properties.get("clustering")
if prop is not None:
return list(prop.get("fields", ()))
|
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Union[List[str], None]: Fields defining clustering for the table
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Clustering fields are immutable after table creation.
.. note::
As of 2018-06-29, clustering fields cannot be set on a table
which does not also have time partioning defined.
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L647-L661
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
Table.clustering_fields
|
def clustering_fields(self, value):
"""Union[List[str], None]: Fields defining clustering for the table
(Defaults to :data:`None`).
"""
if value is not None:
prop = self._properties.setdefault("clustering", {})
prop["fields"] = value
else:
if "clustering" in self._properties:
del self._properties["clustering"]
|
python
|
def clustering_fields(self, value):
"""Union[List[str], None]: Fields defining clustering for the table
(Defaults to :data:`None`).
"""
if value is not None:
prop = self._properties.setdefault("clustering", {})
prop["fields"] = value
else:
if "clustering" in self._properties:
del self._properties["clustering"]
|
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L664-L674
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
Table.expires
|
def expires(self):
"""Union[datetime.datetime, None]: Datetime at which the table will be
deleted.
Raises:
ValueError: For invalid value types.
"""
expiration_time = self._properties.get("expirationTime")
if expiration_time is not None:
# expiration_time will be in milliseconds.
return google.cloud._helpers._datetime_from_microseconds(
1000.0 * float(expiration_time)
)
|
python
|
def expires(self):
"""Union[datetime.datetime, None]: Datetime at which the table will be
deleted.
Raises:
ValueError: For invalid value types.
"""
expiration_time = self._properties.get("expirationTime")
if expiration_time is not None:
# expiration_time will be in milliseconds.
return google.cloud._helpers._datetime_from_microseconds(
1000.0 * float(expiration_time)
)
|
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Union[datetime.datetime, None]: Datetime at which the table will be
deleted.
Raises:
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L693-L705
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
Table.external_data_configuration
|
def external_data_configuration(self):
"""Union[google.cloud.bigquery.ExternalConfig, None]: Configuration for
an external data source (defaults to :data:`None`).
Raises:
ValueError: For invalid value types.
"""
prop = self._properties.get("externalDataConfiguration")
if prop is not None:
prop = ExternalConfig.from_api_repr(prop)
return prop
|
python
|
def external_data_configuration(self):
"""Union[google.cloud.bigquery.ExternalConfig, None]: Configuration for
an external data source (defaults to :data:`None`).
Raises:
ValueError: For invalid value types.
"""
prop = self._properties.get("externalDataConfiguration")
if prop is not None:
prop = ExternalConfig.from_api_repr(prop)
return prop
|
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Union[google.cloud.bigquery.ExternalConfig, None]: Configuration for
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Raises:
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L790-L800
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
Table.from_api_repr
|
def from_api_repr(cls, resource):
"""Factory: construct a table given its API representation
Args:
resource (Dict[str, object]):
Table resource representation from the API
Returns:
google.cloud.bigquery.table.Table: Table parsed from ``resource``.
Raises:
KeyError:
If the ``resource`` lacks the key ``'tableReference'``, or if
the ``dict`` stored within the key ``'tableReference'`` lacks
the keys ``'tableId'``, ``'projectId'``, or ``'datasetId'``.
"""
from google.cloud.bigquery import dataset
if (
"tableReference" not in resource
or "tableId" not in resource["tableReference"]
):
raise KeyError(
"Resource lacks required identity information:"
'["tableReference"]["tableId"]'
)
project_id = resource["tableReference"]["projectId"]
table_id = resource["tableReference"]["tableId"]
dataset_id = resource["tableReference"]["datasetId"]
dataset_ref = dataset.DatasetReference(project_id, dataset_id)
table = cls(dataset_ref.table(table_id))
table._properties = resource
return table
|
python
|
def from_api_repr(cls, resource):
"""Factory: construct a table given its API representation
Args:
resource (Dict[str, object]):
Table resource representation from the API
Returns:
google.cloud.bigquery.table.Table: Table parsed from ``resource``.
Raises:
KeyError:
If the ``resource`` lacks the key ``'tableReference'``, or if
the ``dict`` stored within the key ``'tableReference'`` lacks
the keys ``'tableId'``, ``'projectId'``, or ``'datasetId'``.
"""
from google.cloud.bigquery import dataset
if (
"tableReference" not in resource
or "tableId" not in resource["tableReference"]
):
raise KeyError(
"Resource lacks required identity information:"
'["tableReference"]["tableId"]'
)
project_id = resource["tableReference"]["projectId"]
table_id = resource["tableReference"]["tableId"]
dataset_id = resource["tableReference"]["datasetId"]
dataset_ref = dataset.DatasetReference(project_id, dataset_id)
table = cls(dataset_ref.table(table_id))
table._properties = resource
return table
|
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google.cloud.bigquery.table.Table: Table parsed from ``resource``.
Raises:
KeyError:
If the ``resource`` lacks the key ``'tableReference'``, or if
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L836-L870
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
TableListItem.partitioning_type
|
def partitioning_type(self):
"""Union[str, None]: Time partitioning of the table if it is
partitioned (Defaults to :data:`None`).
"""
warnings.warn(
"This method will be deprecated in future versions. Please use "
"TableListItem.time_partitioning.type_ instead.",
PendingDeprecationWarning,
stacklevel=2,
)
if self.time_partitioning is not None:
return self.time_partitioning.type_
|
python
|
def partitioning_type(self):
"""Union[str, None]: Time partitioning of the table if it is
partitioned (Defaults to :data:`None`).
"""
warnings.warn(
"This method will be deprecated in future versions. Please use "
"TableListItem.time_partitioning.type_ instead.",
PendingDeprecationWarning,
stacklevel=2,
)
if self.time_partitioning is not None:
return self.time_partitioning.type_
|
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Union[str, None]: Time partitioning of the table if it is
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L1016-L1027
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
Row.items
|
def items(self):
"""Return items as ``(key, value)`` pairs.
Returns:
Iterable[Tuple[str, object]]:
The ``(key, value)`` pairs representing this row.
Examples:
>>> list(Row(('a', 'b'), {'x': 0, 'y': 1}).items())
[('x', 'a'), ('y', 'b')]
"""
for key, index in six.iteritems(self._xxx_field_to_index):
yield (key, copy.deepcopy(self._xxx_values[index]))
|
python
|
def items(self):
"""Return items as ``(key, value)`` pairs.
Returns:
Iterable[Tuple[str, object]]:
The ``(key, value)`` pairs representing this row.
Examples:
>>> list(Row(('a', 'b'), {'x': 0, 'y': 1}).items())
[('x', 'a'), ('y', 'b')]
"""
for key, index in six.iteritems(self._xxx_field_to_index):
yield (key, copy.deepcopy(self._xxx_values[index]))
|
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Return items as ``(key, value)`` pairs.
Returns:
Iterable[Tuple[str, object]]:
The ``(key, value)`` pairs representing this row.
Examples:
>>> list(Row(('a', 'b'), {'x': 0, 'y': 1}).items())
[('x', 'a'), ('y', 'b')]
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[
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"pairs",
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L1198-L1211
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
Row.get
|
def get(self, key, default=None):
"""Return a value for key, with a default value if it does not exist.
Args:
key (str): The key of the column to access
default (object):
The default value to use if the key does not exist. (Defaults
to :data:`None`.)
Returns:
object:
The value associated with the provided key, or a default value.
Examples:
When the key exists, the value associated with it is returned.
>>> Row(('a', 'b'), {'x': 0, 'y': 1}).get('x')
'a'
The default value is :data:`None` when the key does not exist.
>>> Row(('a', 'b'), {'x': 0, 'y': 1}).get('z')
None
The default value can be overrided with the ``default`` parameter.
>>> Row(('a', 'b'), {'x': 0, 'y': 1}).get('z', '')
''
>>> Row(('a', 'b'), {'x': 0, 'y': 1}).get('z', default = '')
''
"""
index = self._xxx_field_to_index.get(key)
if index is None:
return default
return self._xxx_values[index]
|
python
|
def get(self, key, default=None):
"""Return a value for key, with a default value if it does not exist.
Args:
key (str): The key of the column to access
default (object):
The default value to use if the key does not exist. (Defaults
to :data:`None`.)
Returns:
object:
The value associated with the provided key, or a default value.
Examples:
When the key exists, the value associated with it is returned.
>>> Row(('a', 'b'), {'x': 0, 'y': 1}).get('x')
'a'
The default value is :data:`None` when the key does not exist.
>>> Row(('a', 'b'), {'x': 0, 'y': 1}).get('z')
None
The default value can be overrided with the ``default`` parameter.
>>> Row(('a', 'b'), {'x': 0, 'y': 1}).get('z', '')
''
>>> Row(('a', 'b'), {'x': 0, 'y': 1}).get('z', default = '')
''
"""
index = self._xxx_field_to_index.get(key)
if index is None:
return default
return self._xxx_values[index]
|
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to :data:`None`.)
Returns:
object:
The value associated with the provided key, or a default value.
Examples:
When the key exists, the value associated with it is returned.
>>> Row(('a', 'b'), {'x': 0, 'y': 1}).get('x')
'a'
The default value is :data:`None` when the key does not exist.
>>> Row(('a', 'b'), {'x': 0, 'y': 1}).get('z')
None
The default value can be overrided with the ``default`` parameter.
>>> Row(('a', 'b'), {'x': 0, 'y': 1}).get('z', '')
''
>>> Row(('a', 'b'), {'x': 0, 'y': 1}).get('z', default = '')
''
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] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L1213-L1248
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
RowIterator._get_next_page_response
|
def _get_next_page_response(self):
"""Requests the next page from the path provided.
Returns:
Dict[str, object]:
The parsed JSON response of the next page's contents.
"""
params = self._get_query_params()
if self._page_size is not None:
params["maxResults"] = self._page_size
return self.api_request(
method=self._HTTP_METHOD, path=self.path, query_params=params
)
|
python
|
def _get_next_page_response(self):
"""Requests the next page from the path provided.
Returns:
Dict[str, object]:
The parsed JSON response of the next page's contents.
"""
params = self._get_query_params()
if self._page_size is not None:
params["maxResults"] = self._page_size
return self.api_request(
method=self._HTTP_METHOD, path=self.path, query_params=params
)
|
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L1357-L1369
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
RowIterator._to_dataframe_tabledata_list
|
def _to_dataframe_tabledata_list(self, dtypes, progress_bar=None):
"""Use (slower, but free) tabledata.list to construct a DataFrame."""
column_names = [field.name for field in self.schema]
frames = []
for page in iter(self.pages):
current_frame = self._to_dataframe_dtypes(page, column_names, dtypes)
frames.append(current_frame)
if progress_bar is not None:
# In some cases, the number of total rows is not populated
# until the first page of rows is fetched. Update the
# progress bar's total to keep an accurate count.
progress_bar.total = progress_bar.total or self.total_rows
progress_bar.update(len(current_frame))
if progress_bar is not None:
# Indicate that the download has finished.
progress_bar.close()
return pandas.concat(frames)
|
python
|
def _to_dataframe_tabledata_list(self, dtypes, progress_bar=None):
"""Use (slower, but free) tabledata.list to construct a DataFrame."""
column_names = [field.name for field in self.schema]
frames = []
for page in iter(self.pages):
current_frame = self._to_dataframe_dtypes(page, column_names, dtypes)
frames.append(current_frame)
if progress_bar is not None:
# In some cases, the number of total rows is not populated
# until the first page of rows is fetched. Update the
# progress bar's total to keep an accurate count.
progress_bar.total = progress_bar.total or self.total_rows
progress_bar.update(len(current_frame))
if progress_bar is not None:
# Indicate that the download has finished.
progress_bar.close()
return pandas.concat(frames)
|
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Use (slower, but free) tabledata.list to construct a DataFrame.
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[
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"construct",
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] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L1390-L1410
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
RowIterator._to_dataframe_bqstorage
|
def _to_dataframe_bqstorage(self, bqstorage_client, dtypes, progress_bar=None):
"""Use (faster, but billable) BQ Storage API to construct DataFrame."""
if bigquery_storage_v1beta1 is None:
raise ValueError(_NO_BQSTORAGE_ERROR)
if "$" in self._table.table_id:
raise ValueError(
"Reading from a specific partition is not currently supported."
)
if "@" in self._table.table_id:
raise ValueError(
"Reading from a specific snapshot is not currently supported."
)
read_options = bigquery_storage_v1beta1.types.TableReadOptions()
if self._selected_fields is not None:
for field in self._selected_fields:
read_options.selected_fields.append(field.name)
session = bqstorage_client.create_read_session(
self._table.to_bqstorage(),
"projects/{}".format(self._project),
read_options=read_options,
)
# We need to parse the schema manually so that we can rearrange the
# columns.
schema = json.loads(session.avro_schema.schema)
columns = [field["name"] for field in schema["fields"]]
# Avoid reading rows from an empty table. pandas.concat will fail on an
# empty list.
if not session.streams:
return pandas.DataFrame(columns=columns)
# Use _to_dataframe_finished to notify worker threads when to quit.
# See: https://stackoverflow.com/a/29237343/101923
self._to_dataframe_finished = False
# Create a queue to track progress updates across threads.
worker_queue = _NoopProgressBarQueue()
progress_queue = None
progress_thread = None
if progress_bar is not None:
worker_queue = queue.Queue()
progress_queue = queue.Queue()
progress_thread = threading.Thread(
target=self._process_worker_updates, args=(worker_queue, progress_queue)
)
progress_thread.start()
def get_frames(pool):
frames = []
# Manually submit jobs and wait for download to complete rather
# than using pool.map because pool.map continues running in the
# background even if there is an exception on the main thread.
# See: https://github.com/googleapis/google-cloud-python/pull/7698
not_done = [
pool.submit(
self._to_dataframe_bqstorage_stream,
bqstorage_client,
dtypes,
columns,
session,
stream,
worker_queue,
)
for stream in session.streams
]
while not_done:
done, not_done = concurrent.futures.wait(
not_done, timeout=_PROGRESS_INTERVAL
)
frames.extend([future.result() for future in done])
# The progress bar needs to update on the main thread to avoid
# contention over stdout / stderr.
self._process_progress_updates(progress_queue, progress_bar)
return frames
with concurrent.futures.ThreadPoolExecutor() as pool:
try:
frames = get_frames(pool)
finally:
# No need for a lock because reading/replacing a variable is
# defined to be an atomic operation in the Python language
# definition (enforced by the global interpreter lock).
self._to_dataframe_finished = True
# Shutdown all background threads, now that they should know to
# exit early.
pool.shutdown(wait=True)
if progress_thread is not None:
progress_thread.join()
# Update the progress bar one last time to close it.
self._process_progress_updates(progress_queue, progress_bar)
return pandas.concat(frames)
|
python
|
def _to_dataframe_bqstorage(self, bqstorage_client, dtypes, progress_bar=None):
"""Use (faster, but billable) BQ Storage API to construct DataFrame."""
if bigquery_storage_v1beta1 is None:
raise ValueError(_NO_BQSTORAGE_ERROR)
if "$" in self._table.table_id:
raise ValueError(
"Reading from a specific partition is not currently supported."
)
if "@" in self._table.table_id:
raise ValueError(
"Reading from a specific snapshot is not currently supported."
)
read_options = bigquery_storage_v1beta1.types.TableReadOptions()
if self._selected_fields is not None:
for field in self._selected_fields:
read_options.selected_fields.append(field.name)
session = bqstorage_client.create_read_session(
self._table.to_bqstorage(),
"projects/{}".format(self._project),
read_options=read_options,
)
# We need to parse the schema manually so that we can rearrange the
# columns.
schema = json.loads(session.avro_schema.schema)
columns = [field["name"] for field in schema["fields"]]
# Avoid reading rows from an empty table. pandas.concat will fail on an
# empty list.
if not session.streams:
return pandas.DataFrame(columns=columns)
# Use _to_dataframe_finished to notify worker threads when to quit.
# See: https://stackoverflow.com/a/29237343/101923
self._to_dataframe_finished = False
# Create a queue to track progress updates across threads.
worker_queue = _NoopProgressBarQueue()
progress_queue = None
progress_thread = None
if progress_bar is not None:
worker_queue = queue.Queue()
progress_queue = queue.Queue()
progress_thread = threading.Thread(
target=self._process_worker_updates, args=(worker_queue, progress_queue)
)
progress_thread.start()
def get_frames(pool):
frames = []
# Manually submit jobs and wait for download to complete rather
# than using pool.map because pool.map continues running in the
# background even if there is an exception on the main thread.
# See: https://github.com/googleapis/google-cloud-python/pull/7698
not_done = [
pool.submit(
self._to_dataframe_bqstorage_stream,
bqstorage_client,
dtypes,
columns,
session,
stream,
worker_queue,
)
for stream in session.streams
]
while not_done:
done, not_done = concurrent.futures.wait(
not_done, timeout=_PROGRESS_INTERVAL
)
frames.extend([future.result() for future in done])
# The progress bar needs to update on the main thread to avoid
# contention over stdout / stderr.
self._process_progress_updates(progress_queue, progress_bar)
return frames
with concurrent.futures.ThreadPoolExecutor() as pool:
try:
frames = get_frames(pool)
finally:
# No need for a lock because reading/replacing a variable is
# defined to be an atomic operation in the Python language
# definition (enforced by the global interpreter lock).
self._to_dataframe_finished = True
# Shutdown all background threads, now that they should know to
# exit early.
pool.shutdown(wait=True)
if progress_thread is not None:
progress_thread.join()
# Update the progress bar one last time to close it.
self._process_progress_updates(progress_queue, progress_bar)
return pandas.concat(frames)
|
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Use (faster, but billable) BQ Storage API to construct DataFrame.
|
[
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"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L1480-L1580
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
RowIterator._get_progress_bar
|
def _get_progress_bar(self, progress_bar_type):
"""Construct a tqdm progress bar object, if tqdm is installed."""
if tqdm is None:
if progress_bar_type is not None:
warnings.warn(_NO_TQDM_ERROR, UserWarning, stacklevel=3)
return None
description = "Downloading"
unit = "rows"
try:
if progress_bar_type == "tqdm":
return tqdm.tqdm(desc=description, total=self.total_rows, unit=unit)
elif progress_bar_type == "tqdm_notebook":
return tqdm.tqdm_notebook(
desc=description, total=self.total_rows, unit=unit
)
elif progress_bar_type == "tqdm_gui":
return tqdm.tqdm_gui(desc=description, total=self.total_rows, unit=unit)
except (KeyError, TypeError):
# Protect ourselves from any tqdm errors. In case of
# unexpected tqdm behavior, just fall back to showing
# no progress bar.
warnings.warn(_NO_TQDM_ERROR, UserWarning, stacklevel=3)
return None
|
python
|
def _get_progress_bar(self, progress_bar_type):
"""Construct a tqdm progress bar object, if tqdm is installed."""
if tqdm is None:
if progress_bar_type is not None:
warnings.warn(_NO_TQDM_ERROR, UserWarning, stacklevel=3)
return None
description = "Downloading"
unit = "rows"
try:
if progress_bar_type == "tqdm":
return tqdm.tqdm(desc=description, total=self.total_rows, unit=unit)
elif progress_bar_type == "tqdm_notebook":
return tqdm.tqdm_notebook(
desc=description, total=self.total_rows, unit=unit
)
elif progress_bar_type == "tqdm_gui":
return tqdm.tqdm_gui(desc=description, total=self.total_rows, unit=unit)
except (KeyError, TypeError):
# Protect ourselves from any tqdm errors. In case of
# unexpected tqdm behavior, just fall back to showing
# no progress bar.
warnings.warn(_NO_TQDM_ERROR, UserWarning, stacklevel=3)
return None
|
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L1582-L1606
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
RowIterator.to_dataframe
|
def to_dataframe(self, bqstorage_client=None, dtypes=None, progress_bar_type=None):
"""Create a pandas DataFrame by loading all pages of a query.
Args:
bqstorage_client ( \
google.cloud.bigquery_storage_v1beta1.BigQueryStorageClient \
):
**Beta Feature** Optional. A BigQuery Storage API client. If
supplied, use the faster BigQuery Storage API to fetch rows
from BigQuery. This API is a billable API.
This method requires the ``fastavro`` and
``google-cloud-bigquery-storage`` libraries.
Reading from a specific partition or snapshot is not
currently supported by this method.
**Caution**: There is a known issue reading small anonymous
query result tables with the BQ Storage API. When a problem
is encountered reading a table, the tabledata.list method
from the BigQuery API is used, instead.
dtypes ( \
Map[str, Union[str, pandas.Series.dtype]] \
):
Optional. A dictionary of column names pandas ``dtype``s. The
provided ``dtype`` is used when constructing the series for
the column specified. Otherwise, the default pandas behavior
is used.
progress_bar_type (Optional[str]):
If set, use the `tqdm <https://tqdm.github.io/>`_ library to
display a progress bar while the data downloads. Install the
``tqdm`` package to use this feature.
Possible values of ``progress_bar_type`` include:
``None``
No progress bar.
``'tqdm'``
Use the :func:`tqdm.tqdm` function to print a progress bar
to :data:`sys.stderr`.
``'tqdm_notebook'``
Use the :func:`tqdm.tqdm_notebook` function to display a
progress bar as a Jupyter notebook widget.
``'tqdm_gui'``
Use the :func:`tqdm.tqdm_gui` function to display a
progress bar as a graphical dialog box.
..versionadded:: 1.11.0
Returns:
pandas.DataFrame:
A :class:`~pandas.DataFrame` populated with row data and column
headers from the query results. The column headers are derived
from the destination table's schema.
Raises:
ValueError:
If the :mod:`pandas` library cannot be imported, or the
:mod:`google.cloud.bigquery_storage_v1beta1` module is
required but cannot be imported.
"""
if pandas is None:
raise ValueError(_NO_PANDAS_ERROR)
if dtypes is None:
dtypes = {}
progress_bar = self._get_progress_bar(progress_bar_type)
if bqstorage_client is not None:
try:
return self._to_dataframe_bqstorage(
bqstorage_client, dtypes, progress_bar=progress_bar
)
except google.api_core.exceptions.Forbidden:
# Don't hide errors such as insufficient permissions to create
# a read session, or the API is not enabled. Both of those are
# clearly problems if the developer has explicitly asked for
# BigQuery Storage API support.
raise
except google.api_core.exceptions.GoogleAPICallError:
# There is a known issue with reading from small anonymous
# query results tables, so some errors are expected. Rather
# than throw those errors, try reading the DataFrame again, but
# with the tabledata.list API.
pass
return self._to_dataframe_tabledata_list(dtypes, progress_bar=progress_bar)
|
python
|
def to_dataframe(self, bqstorage_client=None, dtypes=None, progress_bar_type=None):
"""Create a pandas DataFrame by loading all pages of a query.
Args:
bqstorage_client ( \
google.cloud.bigquery_storage_v1beta1.BigQueryStorageClient \
):
**Beta Feature** Optional. A BigQuery Storage API client. If
supplied, use the faster BigQuery Storage API to fetch rows
from BigQuery. This API is a billable API.
This method requires the ``fastavro`` and
``google-cloud-bigquery-storage`` libraries.
Reading from a specific partition or snapshot is not
currently supported by this method.
**Caution**: There is a known issue reading small anonymous
query result tables with the BQ Storage API. When a problem
is encountered reading a table, the tabledata.list method
from the BigQuery API is used, instead.
dtypes ( \
Map[str, Union[str, pandas.Series.dtype]] \
):
Optional. A dictionary of column names pandas ``dtype``s. The
provided ``dtype`` is used when constructing the series for
the column specified. Otherwise, the default pandas behavior
is used.
progress_bar_type (Optional[str]):
If set, use the `tqdm <https://tqdm.github.io/>`_ library to
display a progress bar while the data downloads. Install the
``tqdm`` package to use this feature.
Possible values of ``progress_bar_type`` include:
``None``
No progress bar.
``'tqdm'``
Use the :func:`tqdm.tqdm` function to print a progress bar
to :data:`sys.stderr`.
``'tqdm_notebook'``
Use the :func:`tqdm.tqdm_notebook` function to display a
progress bar as a Jupyter notebook widget.
``'tqdm_gui'``
Use the :func:`tqdm.tqdm_gui` function to display a
progress bar as a graphical dialog box.
..versionadded:: 1.11.0
Returns:
pandas.DataFrame:
A :class:`~pandas.DataFrame` populated with row data and column
headers from the query results. The column headers are derived
from the destination table's schema.
Raises:
ValueError:
If the :mod:`pandas` library cannot be imported, or the
:mod:`google.cloud.bigquery_storage_v1beta1` module is
required but cannot be imported.
"""
if pandas is None:
raise ValueError(_NO_PANDAS_ERROR)
if dtypes is None:
dtypes = {}
progress_bar = self._get_progress_bar(progress_bar_type)
if bqstorage_client is not None:
try:
return self._to_dataframe_bqstorage(
bqstorage_client, dtypes, progress_bar=progress_bar
)
except google.api_core.exceptions.Forbidden:
# Don't hide errors such as insufficient permissions to create
# a read session, or the API is not enabled. Both of those are
# clearly problems if the developer has explicitly asked for
# BigQuery Storage API support.
raise
except google.api_core.exceptions.GoogleAPICallError:
# There is a known issue with reading from small anonymous
# query results tables, so some errors are expected. Rather
# than throw those errors, try reading the DataFrame again, but
# with the tabledata.list API.
pass
return self._to_dataframe_tabledata_list(dtypes, progress_bar=progress_bar)
|
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Create a pandas DataFrame by loading all pages of a query.
Args:
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google.cloud.bigquery_storage_v1beta1.BigQueryStorageClient \
):
**Beta Feature** Optional. A BigQuery Storage API client. If
supplied, use the faster BigQuery Storage API to fetch rows
from BigQuery. This API is a billable API.
This method requires the ``fastavro`` and
``google-cloud-bigquery-storage`` libraries.
Reading from a specific partition or snapshot is not
currently supported by this method.
**Caution**: There is a known issue reading small anonymous
query result tables with the BQ Storage API. When a problem
is encountered reading a table, the tabledata.list method
from the BigQuery API is used, instead.
dtypes ( \
Map[str, Union[str, pandas.Series.dtype]] \
):
Optional. A dictionary of column names pandas ``dtype``s. The
provided ``dtype`` is used when constructing the series for
the column specified. Otherwise, the default pandas behavior
is used.
progress_bar_type (Optional[str]):
If set, use the `tqdm <https://tqdm.github.io/>`_ library to
display a progress bar while the data downloads. Install the
``tqdm`` package to use this feature.
Possible values of ``progress_bar_type`` include:
``None``
No progress bar.
``'tqdm'``
Use the :func:`tqdm.tqdm` function to print a progress bar
to :data:`sys.stderr`.
``'tqdm_notebook'``
Use the :func:`tqdm.tqdm_notebook` function to display a
progress bar as a Jupyter notebook widget.
``'tqdm_gui'``
Use the :func:`tqdm.tqdm_gui` function to display a
progress bar as a graphical dialog box.
..versionadded:: 1.11.0
Returns:
pandas.DataFrame:
A :class:`~pandas.DataFrame` populated with row data and column
headers from the query results. The column headers are derived
from the destination table's schema.
Raises:
ValueError:
If the :mod:`pandas` library cannot be imported, or the
:mod:`google.cloud.bigquery_storage_v1beta1` module is
required but cannot be imported.
|
[
"Create",
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"pandas",
"DataFrame",
"by",
"loading",
"all",
"pages",
"of",
"a",
"query",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L1608-L1695
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
_EmptyRowIterator.to_dataframe
|
def to_dataframe(self, bqstorage_client=None, dtypes=None, progress_bar_type=None):
"""Create an empty dataframe.
Args:
bqstorage_client (Any):
Ignored. Added for compatibility with RowIterator.
dtypes (Any):
Ignored. Added for compatibility with RowIterator.
progress_bar_type (Any):
Ignored. Added for compatibility with RowIterator.
Returns:
pandas.DataFrame:
An empty :class:`~pandas.DataFrame`.
"""
if pandas is None:
raise ValueError(_NO_PANDAS_ERROR)
return pandas.DataFrame()
|
python
|
def to_dataframe(self, bqstorage_client=None, dtypes=None, progress_bar_type=None):
"""Create an empty dataframe.
Args:
bqstorage_client (Any):
Ignored. Added for compatibility with RowIterator.
dtypes (Any):
Ignored. Added for compatibility with RowIterator.
progress_bar_type (Any):
Ignored. Added for compatibility with RowIterator.
Returns:
pandas.DataFrame:
An empty :class:`~pandas.DataFrame`.
"""
if pandas is None:
raise ValueError(_NO_PANDAS_ERROR)
return pandas.DataFrame()
|
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Create an empty dataframe.
Args:
bqstorage_client (Any):
Ignored. Added for compatibility with RowIterator.
dtypes (Any):
Ignored. Added for compatibility with RowIterator.
progress_bar_type (Any):
Ignored. Added for compatibility with RowIterator.
Returns:
pandas.DataFrame:
An empty :class:`~pandas.DataFrame`.
|
[
"Create",
"an",
"empty",
"dataframe",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L1710-L1727
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/table.py
|
TimePartitioning.from_api_repr
|
def from_api_repr(cls, api_repr):
"""Return a :class:`TimePartitioning` object deserialized from a dict.
This method creates a new ``TimePartitioning`` instance that points to
the ``api_repr`` parameter as its internal properties dict. This means
that when a ``TimePartitioning`` instance is stored as a property of
another object, any changes made at the higher level will also appear
here::
>>> time_partitioning = TimePartitioning()
>>> table.time_partitioning = time_partitioning
>>> table.time_partitioning.field = 'timecolumn'
>>> time_partitioning.field
'timecolumn'
Args:
api_repr (Mapping[str, str]):
The serialized representation of the TimePartitioning, such as
what is output by :meth:`to_api_repr`.
Returns:
google.cloud.bigquery.table.TimePartitioning:
The ``TimePartitioning`` object.
"""
instance = cls(api_repr["type"])
instance._properties = api_repr
return instance
|
python
|
def from_api_repr(cls, api_repr):
"""Return a :class:`TimePartitioning` object deserialized from a dict.
This method creates a new ``TimePartitioning`` instance that points to
the ``api_repr`` parameter as its internal properties dict. This means
that when a ``TimePartitioning`` instance is stored as a property of
another object, any changes made at the higher level will also appear
here::
>>> time_partitioning = TimePartitioning()
>>> table.time_partitioning = time_partitioning
>>> table.time_partitioning.field = 'timecolumn'
>>> time_partitioning.field
'timecolumn'
Args:
api_repr (Mapping[str, str]):
The serialized representation of the TimePartitioning, such as
what is output by :meth:`to_api_repr`.
Returns:
google.cloud.bigquery.table.TimePartitioning:
The ``TimePartitioning`` object.
"""
instance = cls(api_repr["type"])
instance._properties = api_repr
return instance
|
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Return a :class:`TimePartitioning` object deserialized from a dict.
This method creates a new ``TimePartitioning`` instance that points to
the ``api_repr`` parameter as its internal properties dict. This means
that when a ``TimePartitioning`` instance is stored as a property of
another object, any changes made at the higher level will also appear
here::
>>> time_partitioning = TimePartitioning()
>>> table.time_partitioning = time_partitioning
>>> table.time_partitioning.field = 'timecolumn'
>>> time_partitioning.field
'timecolumn'
Args:
api_repr (Mapping[str, str]):
The serialized representation of the TimePartitioning, such as
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google.cloud.bigquery.table.TimePartitioning:
The ``TimePartitioning`` object.
|
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"."
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/table.py#L1820-L1846
|
train
|
googleapis/google-cloud-python
|
storage/google/cloud/storage/batch.py
|
_generate_faux_mime_message
|
def _generate_faux_mime_message(parser, response):
"""Convert response, content -> (multipart) email.message.
Helper for _unpack_batch_response.
"""
# We coerce to bytes to get consistent concat across
# Py2 and Py3. Percent formatting is insufficient since
# it includes the b in Py3.
content_type = _helpers._to_bytes(response.headers.get("content-type", ""))
faux_message = b"".join(
[b"Content-Type: ", content_type, b"\nMIME-Version: 1.0\n\n", response.content]
)
if six.PY2:
return parser.parsestr(faux_message)
else: # pragma: NO COVER Python3
return parser.parsestr(faux_message.decode("utf-8"))
|
python
|
def _generate_faux_mime_message(parser, response):
"""Convert response, content -> (multipart) email.message.
Helper for _unpack_batch_response.
"""
# We coerce to bytes to get consistent concat across
# Py2 and Py3. Percent formatting is insufficient since
# it includes the b in Py3.
content_type = _helpers._to_bytes(response.headers.get("content-type", ""))
faux_message = b"".join(
[b"Content-Type: ", content_type, b"\nMIME-Version: 1.0\n\n", response.content]
)
if six.PY2:
return parser.parsestr(faux_message)
else: # pragma: NO COVER Python3
return parser.parsestr(faux_message.decode("utf-8"))
|
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[
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/storage/google/cloud/storage/batch.py#L284-L301
|
train
|
googleapis/google-cloud-python
|
storage/google/cloud/storage/batch.py
|
_unpack_batch_response
|
def _unpack_batch_response(response):
"""Convert requests.Response -> [(headers, payload)].
Creates a generator of tuples of emulating the responses to
:meth:`requests.Session.request`.
:type response: :class:`requests.Response`
:param response: HTTP response / headers from a request.
"""
parser = Parser()
message = _generate_faux_mime_message(parser, response)
if not isinstance(message._payload, list):
raise ValueError("Bad response: not multi-part")
for subrequest in message._payload:
status_line, rest = subrequest._payload.split("\n", 1)
_, status, _ = status_line.split(" ", 2)
sub_message = parser.parsestr(rest)
payload = sub_message._payload
msg_headers = dict(sub_message._headers)
content_id = msg_headers.get("Content-ID")
subresponse = requests.Response()
subresponse.request = requests.Request(
method="BATCH", url="contentid://{}".format(content_id)
).prepare()
subresponse.status_code = int(status)
subresponse.headers.update(msg_headers)
subresponse._content = payload.encode("utf-8")
yield subresponse
|
python
|
def _unpack_batch_response(response):
"""Convert requests.Response -> [(headers, payload)].
Creates a generator of tuples of emulating the responses to
:meth:`requests.Session.request`.
:type response: :class:`requests.Response`
:param response: HTTP response / headers from a request.
"""
parser = Parser()
message = _generate_faux_mime_message(parser, response)
if not isinstance(message._payload, list):
raise ValueError("Bad response: not multi-part")
for subrequest in message._payload:
status_line, rest = subrequest._payload.split("\n", 1)
_, status, _ = status_line.split(" ", 2)
sub_message = parser.parsestr(rest)
payload = sub_message._payload
msg_headers = dict(sub_message._headers)
content_id = msg_headers.get("Content-ID")
subresponse = requests.Response()
subresponse.request = requests.Request(
method="BATCH", url="contentid://{}".format(content_id)
).prepare()
subresponse.status_code = int(status)
subresponse.headers.update(msg_headers)
subresponse._content = payload.encode("utf-8")
yield subresponse
|
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Convert requests.Response -> [(headers, payload)].
Creates a generator of tuples of emulating the responses to
:meth:`requests.Session.request`.
:type response: :class:`requests.Response`
:param response: HTTP response / headers from a request.
|
[
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/storage/google/cloud/storage/batch.py#L304-L335
|
train
|
googleapis/google-cloud-python
|
storage/google/cloud/storage/batch.py
|
Batch._do_request
|
def _do_request(self, method, url, headers, data, target_object):
"""Override Connection: defer actual HTTP request.
Only allow up to ``_MAX_BATCH_SIZE`` requests to be deferred.
:type method: str
:param method: The HTTP method to use in the request.
:type url: str
:param url: The URL to send the request to.
:type headers: dict
:param headers: A dictionary of HTTP headers to send with the request.
:type data: str
:param data: The data to send as the body of the request.
:type target_object: object
:param target_object:
(Optional) This allows us to enable custom behavior in our batch
connection. Here we defer an HTTP request and complete
initialization of the object at a later time.
:rtype: tuple of ``response`` (a dictionary of sorts)
and ``content`` (a string).
:returns: The HTTP response object and the content of the response.
"""
if len(self._requests) >= self._MAX_BATCH_SIZE:
raise ValueError(
"Too many deferred requests (max %d)" % self._MAX_BATCH_SIZE
)
self._requests.append((method, url, headers, data))
result = _FutureDict()
self._target_objects.append(target_object)
if target_object is not None:
target_object._properties = result
return _FutureResponse(result)
|
python
|
def _do_request(self, method, url, headers, data, target_object):
"""Override Connection: defer actual HTTP request.
Only allow up to ``_MAX_BATCH_SIZE`` requests to be deferred.
:type method: str
:param method: The HTTP method to use in the request.
:type url: str
:param url: The URL to send the request to.
:type headers: dict
:param headers: A dictionary of HTTP headers to send with the request.
:type data: str
:param data: The data to send as the body of the request.
:type target_object: object
:param target_object:
(Optional) This allows us to enable custom behavior in our batch
connection. Here we defer an HTTP request and complete
initialization of the object at a later time.
:rtype: tuple of ``response`` (a dictionary of sorts)
and ``content`` (a string).
:returns: The HTTP response object and the content of the response.
"""
if len(self._requests) >= self._MAX_BATCH_SIZE:
raise ValueError(
"Too many deferred requests (max %d)" % self._MAX_BATCH_SIZE
)
self._requests.append((method, url, headers, data))
result = _FutureDict()
self._target_objects.append(target_object)
if target_object is not None:
target_object._properties = result
return _FutureResponse(result)
|
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Override Connection: defer actual HTTP request.
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:param method: The HTTP method to use in the request.
:type url: str
:param url: The URL to send the request to.
:type headers: dict
:param headers: A dictionary of HTTP headers to send with the request.
:type data: str
:param data: The data to send as the body of the request.
:type target_object: object
:param target_object:
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connection. Here we defer an HTTP request and complete
initialization of the object at a later time.
:rtype: tuple of ``response`` (a dictionary of sorts)
and ``content`` (a string).
:returns: The HTTP response object and the content of the response.
|
[
"Override",
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] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/storage/google/cloud/storage/batch.py#L153-L189
|
train
|
googleapis/google-cloud-python
|
storage/google/cloud/storage/batch.py
|
Batch._prepare_batch_request
|
def _prepare_batch_request(self):
"""Prepares headers and body for a batch request.
:rtype: tuple (dict, str)
:returns: The pair of headers and body of the batch request to be sent.
:raises: :class:`ValueError` if no requests have been deferred.
"""
if len(self._requests) == 0:
raise ValueError("No deferred requests")
multi = MIMEMultipart()
for method, uri, headers, body in self._requests:
subrequest = MIMEApplicationHTTP(method, uri, headers, body)
multi.attach(subrequest)
# The `email` package expects to deal with "native" strings
if six.PY3: # pragma: NO COVER Python3
buf = io.StringIO()
else:
buf = io.BytesIO()
generator = Generator(buf, False, 0)
generator.flatten(multi)
payload = buf.getvalue()
# Strip off redundant header text
_, body = payload.split("\n\n", 1)
return dict(multi._headers), body
|
python
|
def _prepare_batch_request(self):
"""Prepares headers and body for a batch request.
:rtype: tuple (dict, str)
:returns: The pair of headers and body of the batch request to be sent.
:raises: :class:`ValueError` if no requests have been deferred.
"""
if len(self._requests) == 0:
raise ValueError("No deferred requests")
multi = MIMEMultipart()
for method, uri, headers, body in self._requests:
subrequest = MIMEApplicationHTTP(method, uri, headers, body)
multi.attach(subrequest)
# The `email` package expects to deal with "native" strings
if six.PY3: # pragma: NO COVER Python3
buf = io.StringIO()
else:
buf = io.BytesIO()
generator = Generator(buf, False, 0)
generator.flatten(multi)
payload = buf.getvalue()
# Strip off redundant header text
_, body = payload.split("\n\n", 1)
return dict(multi._headers), body
|
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Prepares headers and body for a batch request.
:rtype: tuple (dict, str)
:returns: The pair of headers and body of the batch request to be sent.
:raises: :class:`ValueError` if no requests have been deferred.
|
[
"Prepares",
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"a",
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"request",
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] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/storage/google/cloud/storage/batch.py#L191-L218
|
train
|
googleapis/google-cloud-python
|
storage/google/cloud/storage/batch.py
|
Batch._finish_futures
|
def _finish_futures(self, responses):
"""Apply all the batch responses to the futures created.
:type responses: list of (headers, payload) tuples.
:param responses: List of headers and payloads from each response in
the batch.
:raises: :class:`ValueError` if no requests have been deferred.
"""
# If a bad status occurs, we track it, but don't raise an exception
# until all futures have been populated.
exception_args = None
if len(self._target_objects) != len(responses):
raise ValueError("Expected a response for every request.")
for target_object, subresponse in zip(self._target_objects, responses):
if not 200 <= subresponse.status_code < 300:
exception_args = exception_args or subresponse
elif target_object is not None:
try:
target_object._properties = subresponse.json()
except ValueError:
target_object._properties = subresponse.content
if exception_args is not None:
raise exceptions.from_http_response(exception_args)
|
python
|
def _finish_futures(self, responses):
"""Apply all the batch responses to the futures created.
:type responses: list of (headers, payload) tuples.
:param responses: List of headers and payloads from each response in
the batch.
:raises: :class:`ValueError` if no requests have been deferred.
"""
# If a bad status occurs, we track it, but don't raise an exception
# until all futures have been populated.
exception_args = None
if len(self._target_objects) != len(responses):
raise ValueError("Expected a response for every request.")
for target_object, subresponse in zip(self._target_objects, responses):
if not 200 <= subresponse.status_code < 300:
exception_args = exception_args or subresponse
elif target_object is not None:
try:
target_object._properties = subresponse.json()
except ValueError:
target_object._properties = subresponse.content
if exception_args is not None:
raise exceptions.from_http_response(exception_args)
|
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:type responses: list of (headers, payload) tuples.
:param responses: List of headers and payloads from each response in
the batch.
:raises: :class:`ValueError` if no requests have been deferred.
|
[
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"to",
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"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/storage/google/cloud/storage/batch.py#L220-L246
|
train
|
googleapis/google-cloud-python
|
storage/google/cloud/storage/batch.py
|
Batch.finish
|
def finish(self):
"""Submit a single `multipart/mixed` request with deferred requests.
:rtype: list of tuples
:returns: one ``(headers, payload)`` tuple per deferred request.
"""
headers, body = self._prepare_batch_request()
url = "%s/batch/storage/v1" % self.API_BASE_URL
# Use the private ``_base_connection`` rather than the property
# ``_connection``, since the property may be this
# current batch.
response = self._client._base_connection._make_request(
"POST", url, data=body, headers=headers
)
responses = list(_unpack_batch_response(response))
self._finish_futures(responses)
return responses
|
python
|
def finish(self):
"""Submit a single `multipart/mixed` request with deferred requests.
:rtype: list of tuples
:returns: one ``(headers, payload)`` tuple per deferred request.
"""
headers, body = self._prepare_batch_request()
url = "%s/batch/storage/v1" % self.API_BASE_URL
# Use the private ``_base_connection`` rather than the property
# ``_connection``, since the property may be this
# current batch.
response = self._client._base_connection._make_request(
"POST", url, data=body, headers=headers
)
responses = list(_unpack_batch_response(response))
self._finish_futures(responses)
return responses
|
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Submit a single `multipart/mixed` request with deferred requests.
:rtype: list of tuples
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|
[
"Submit",
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"multipart",
"/",
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"request",
"with",
"deferred",
"requests",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/storage/google/cloud/storage/batch.py#L248-L266
|
train
|
googleapis/google-cloud-python
|
spanner/google/cloud/spanner_v1/snapshot.py
|
_restart_on_unavailable
|
def _restart_on_unavailable(restart):
"""Restart iteration after :exc:`.ServiceUnavailable`.
:type restart: callable
:param restart: curried function returning iterator
"""
resume_token = b""
item_buffer = []
iterator = restart()
while True:
try:
for item in iterator:
item_buffer.append(item)
if item.resume_token:
resume_token = item.resume_token
break
except ServiceUnavailable:
del item_buffer[:]
iterator = restart(resume_token=resume_token)
continue
if len(item_buffer) == 0:
break
for item in item_buffer:
yield item
del item_buffer[:]
|
python
|
def _restart_on_unavailable(restart):
"""Restart iteration after :exc:`.ServiceUnavailable`.
:type restart: callable
:param restart: curried function returning iterator
"""
resume_token = b""
item_buffer = []
iterator = restart()
while True:
try:
for item in iterator:
item_buffer.append(item)
if item.resume_token:
resume_token = item.resume_token
break
except ServiceUnavailable:
del item_buffer[:]
iterator = restart(resume_token=resume_token)
continue
if len(item_buffer) == 0:
break
for item in item_buffer:
yield item
del item_buffer[:]
|
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":",
"yield",
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"[",
":",
"]"
] |
Restart iteration after :exc:`.ServiceUnavailable`.
:type restart: callable
:param restart: curried function returning iterator
|
[
"Restart",
"iteration",
"after",
":",
"exc",
":",
".",
"ServiceUnavailable",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/spanner/google/cloud/spanner_v1/snapshot.py#L34-L61
|
train
|
googleapis/google-cloud-python
|
spanner/google/cloud/spanner_v1/snapshot.py
|
_SnapshotBase.read
|
def read(self, table, columns, keyset, index="", limit=0, partition=None):
"""Perform a ``StreamingRead`` API request for rows in a table.
:type table: str
:param table: name of the table from which to fetch data
:type columns: list of str
:param columns: names of columns to be retrieved
:type keyset: :class:`~google.cloud.spanner_v1.keyset.KeySet`
:param keyset: keys / ranges identifying rows to be retrieved
:type index: str
:param index: (Optional) name of index to use, rather than the
table's primary key
:type limit: int
:param limit: (Optional) maximum number of rows to return.
Incompatible with ``partition``.
:type partition: bytes
:param partition: (Optional) one of the partition tokens returned
from :meth:`partition_read`. Incompatible with
``limit``.
:rtype: :class:`~google.cloud.spanner_v1.streamed.StreamedResultSet`
:returns: a result set instance which can be used to consume rows.
:raises ValueError:
for reuse of single-use snapshots, or if a transaction ID is
already pending for multiple-use snapshots.
"""
if self._read_request_count > 0:
if not self._multi_use:
raise ValueError("Cannot re-use single-use snapshot.")
if self._transaction_id is None:
raise ValueError("Transaction ID pending.")
database = self._session._database
api = database.spanner_api
metadata = _metadata_with_prefix(database.name)
transaction = self._make_txn_selector()
restart = functools.partial(
api.streaming_read,
self._session.name,
table,
columns,
keyset._to_pb(),
transaction=transaction,
index=index,
limit=limit,
partition_token=partition,
metadata=metadata,
)
iterator = _restart_on_unavailable(restart)
self._read_request_count += 1
if self._multi_use:
return StreamedResultSet(iterator, source=self)
else:
return StreamedResultSet(iterator)
|
python
|
def read(self, table, columns, keyset, index="", limit=0, partition=None):
"""Perform a ``StreamingRead`` API request for rows in a table.
:type table: str
:param table: name of the table from which to fetch data
:type columns: list of str
:param columns: names of columns to be retrieved
:type keyset: :class:`~google.cloud.spanner_v1.keyset.KeySet`
:param keyset: keys / ranges identifying rows to be retrieved
:type index: str
:param index: (Optional) name of index to use, rather than the
table's primary key
:type limit: int
:param limit: (Optional) maximum number of rows to return.
Incompatible with ``partition``.
:type partition: bytes
:param partition: (Optional) one of the partition tokens returned
from :meth:`partition_read`. Incompatible with
``limit``.
:rtype: :class:`~google.cloud.spanner_v1.streamed.StreamedResultSet`
:returns: a result set instance which can be used to consume rows.
:raises ValueError:
for reuse of single-use snapshots, or if a transaction ID is
already pending for multiple-use snapshots.
"""
if self._read_request_count > 0:
if not self._multi_use:
raise ValueError("Cannot re-use single-use snapshot.")
if self._transaction_id is None:
raise ValueError("Transaction ID pending.")
database = self._session._database
api = database.spanner_api
metadata = _metadata_with_prefix(database.name)
transaction = self._make_txn_selector()
restart = functools.partial(
api.streaming_read,
self._session.name,
table,
columns,
keyset._to_pb(),
transaction=transaction,
index=index,
limit=limit,
partition_token=partition,
metadata=metadata,
)
iterator = _restart_on_unavailable(restart)
self._read_request_count += 1
if self._multi_use:
return StreamedResultSet(iterator, source=self)
else:
return StreamedResultSet(iterator)
|
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Perform a ``StreamingRead`` API request for rows in a table.
:type table: str
:param table: name of the table from which to fetch data
:type columns: list of str
:param columns: names of columns to be retrieved
:type keyset: :class:`~google.cloud.spanner_v1.keyset.KeySet`
:param keyset: keys / ranges identifying rows to be retrieved
:type index: str
:param index: (Optional) name of index to use, rather than the
table's primary key
:type limit: int
:param limit: (Optional) maximum number of rows to return.
Incompatible with ``partition``.
:type partition: bytes
:param partition: (Optional) one of the partition tokens returned
from :meth:`partition_read`. Incompatible with
``limit``.
:rtype: :class:`~google.cloud.spanner_v1.streamed.StreamedResultSet`
:returns: a result set instance which can be used to consume rows.
:raises ValueError:
for reuse of single-use snapshots, or if a transaction ID is
already pending for multiple-use snapshots.
|
[
"Perform",
"a",
"StreamingRead",
"API",
"request",
"for",
"rows",
"in",
"a",
"table",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/spanner/google/cloud/spanner_v1/snapshot.py#L89-L152
|
train
|
googleapis/google-cloud-python
|
spanner/google/cloud/spanner_v1/snapshot.py
|
_SnapshotBase.execute_sql
|
def execute_sql(
self,
sql,
params=None,
param_types=None,
query_mode=None,
partition=None,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
):
"""Perform an ``ExecuteStreamingSql`` API request.
:type sql: str
:param sql: SQL query statement
:type params: dict, {str -> column value}
:param params: values for parameter replacement. Keys must match
the names used in ``sql``.
:type param_types: dict[str -> Union[dict, .types.Type]]
:param param_types:
(Optional) maps explicit types for one or more param values;
required if parameters are passed.
:type query_mode:
:class:`google.cloud.spanner_v1.proto.ExecuteSqlRequest.QueryMode`
:param query_mode: Mode governing return of results / query plan. See
https://cloud.google.com/spanner/reference/rpc/google.spanner.v1#google.spanner.v1.ExecuteSqlRequest.QueryMode1
:type partition: bytes
:param partition: (Optional) one of the partition tokens returned
from :meth:`partition_query`.
:rtype: :class:`~google.cloud.spanner_v1.streamed.StreamedResultSet`
:returns: a result set instance which can be used to consume rows.
:raises ValueError:
for reuse of single-use snapshots, or if a transaction ID is
already pending for multiple-use snapshots.
"""
if self._read_request_count > 0:
if not self._multi_use:
raise ValueError("Cannot re-use single-use snapshot.")
if self._transaction_id is None:
raise ValueError("Transaction ID pending.")
if params is not None:
if param_types is None:
raise ValueError("Specify 'param_types' when passing 'params'.")
params_pb = Struct(
fields={key: _make_value_pb(value) for key, value in params.items()}
)
else:
params_pb = None
database = self._session._database
metadata = _metadata_with_prefix(database.name)
transaction = self._make_txn_selector()
api = database.spanner_api
restart = functools.partial(
api.execute_streaming_sql,
self._session.name,
sql,
transaction=transaction,
params=params_pb,
param_types=param_types,
query_mode=query_mode,
partition_token=partition,
seqno=self._execute_sql_count,
metadata=metadata,
retry=retry,
timeout=timeout,
)
iterator = _restart_on_unavailable(restart)
self._read_request_count += 1
self._execute_sql_count += 1
if self._multi_use:
return StreamedResultSet(iterator, source=self)
else:
return StreamedResultSet(iterator)
|
python
|
def execute_sql(
self,
sql,
params=None,
param_types=None,
query_mode=None,
partition=None,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
):
"""Perform an ``ExecuteStreamingSql`` API request.
:type sql: str
:param sql: SQL query statement
:type params: dict, {str -> column value}
:param params: values for parameter replacement. Keys must match
the names used in ``sql``.
:type param_types: dict[str -> Union[dict, .types.Type]]
:param param_types:
(Optional) maps explicit types for one or more param values;
required if parameters are passed.
:type query_mode:
:class:`google.cloud.spanner_v1.proto.ExecuteSqlRequest.QueryMode`
:param query_mode: Mode governing return of results / query plan. See
https://cloud.google.com/spanner/reference/rpc/google.spanner.v1#google.spanner.v1.ExecuteSqlRequest.QueryMode1
:type partition: bytes
:param partition: (Optional) one of the partition tokens returned
from :meth:`partition_query`.
:rtype: :class:`~google.cloud.spanner_v1.streamed.StreamedResultSet`
:returns: a result set instance which can be used to consume rows.
:raises ValueError:
for reuse of single-use snapshots, or if a transaction ID is
already pending for multiple-use snapshots.
"""
if self._read_request_count > 0:
if not self._multi_use:
raise ValueError("Cannot re-use single-use snapshot.")
if self._transaction_id is None:
raise ValueError("Transaction ID pending.")
if params is not None:
if param_types is None:
raise ValueError("Specify 'param_types' when passing 'params'.")
params_pb = Struct(
fields={key: _make_value_pb(value) for key, value in params.items()}
)
else:
params_pb = None
database = self._session._database
metadata = _metadata_with_prefix(database.name)
transaction = self._make_txn_selector()
api = database.spanner_api
restart = functools.partial(
api.execute_streaming_sql,
self._session.name,
sql,
transaction=transaction,
params=params_pb,
param_types=param_types,
query_mode=query_mode,
partition_token=partition,
seqno=self._execute_sql_count,
metadata=metadata,
retry=retry,
timeout=timeout,
)
iterator = _restart_on_unavailable(restart)
self._read_request_count += 1
self._execute_sql_count += 1
if self._multi_use:
return StreamedResultSet(iterator, source=self)
else:
return StreamedResultSet(iterator)
|
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Perform an ``ExecuteStreamingSql`` API request.
:type sql: str
:param sql: SQL query statement
:type params: dict, {str -> column value}
:param params: values for parameter replacement. Keys must match
the names used in ``sql``.
:type param_types: dict[str -> Union[dict, .types.Type]]
:param param_types:
(Optional) maps explicit types for one or more param values;
required if parameters are passed.
:type query_mode:
:class:`google.cloud.spanner_v1.proto.ExecuteSqlRequest.QueryMode`
:param query_mode: Mode governing return of results / query plan. See
https://cloud.google.com/spanner/reference/rpc/google.spanner.v1#google.spanner.v1.ExecuteSqlRequest.QueryMode1
:type partition: bytes
:param partition: (Optional) one of the partition tokens returned
from :meth:`partition_query`.
:rtype: :class:`~google.cloud.spanner_v1.streamed.StreamedResultSet`
:returns: a result set instance which can be used to consume rows.
:raises ValueError:
for reuse of single-use snapshots, or if a transaction ID is
already pending for multiple-use snapshots.
|
[
"Perform",
"an",
"ExecuteStreamingSql",
"API",
"request",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/spanner/google/cloud/spanner_v1/snapshot.py#L154-L237
|
train
|
googleapis/google-cloud-python
|
spanner/google/cloud/spanner_v1/snapshot.py
|
_SnapshotBase.partition_read
|
def partition_read(
self,
table,
columns,
keyset,
index="",
partition_size_bytes=None,
max_partitions=None,
):
"""Perform a ``ParitionRead`` API request for rows in a table.
:type table: str
:param table: name of the table from which to fetch data
:type columns: list of str
:param columns: names of columns to be retrieved
:type keyset: :class:`~google.cloud.spanner_v1.keyset.KeySet`
:param keyset: keys / ranges identifying rows to be retrieved
:type index: str
:param index: (Optional) name of index to use, rather than the
table's primary key
:type partition_size_bytes: int
:param partition_size_bytes:
(Optional) desired size for each partition generated. The service
uses this as a hint, the actual partition size may differ.
:type max_partitions: int
:param max_partitions:
(Optional) desired maximum number of partitions generated. The
service uses this as a hint, the actual number of partitions may
differ.
:rtype: iterable of bytes
:returns: a sequence of partition tokens
:raises ValueError:
for single-use snapshots, or if a transaction ID is
already associtated with the snapshot.
"""
if not self._multi_use:
raise ValueError("Cannot use single-use snapshot.")
if self._transaction_id is None:
raise ValueError("Transaction not started.")
database = self._session._database
api = database.spanner_api
metadata = _metadata_with_prefix(database.name)
transaction = self._make_txn_selector()
partition_options = PartitionOptions(
partition_size_bytes=partition_size_bytes, max_partitions=max_partitions
)
response = api.partition_read(
session=self._session.name,
table=table,
columns=columns,
key_set=keyset._to_pb(),
transaction=transaction,
index=index,
partition_options=partition_options,
metadata=metadata,
)
return [partition.partition_token for partition in response.partitions]
|
python
|
def partition_read(
self,
table,
columns,
keyset,
index="",
partition_size_bytes=None,
max_partitions=None,
):
"""Perform a ``ParitionRead`` API request for rows in a table.
:type table: str
:param table: name of the table from which to fetch data
:type columns: list of str
:param columns: names of columns to be retrieved
:type keyset: :class:`~google.cloud.spanner_v1.keyset.KeySet`
:param keyset: keys / ranges identifying rows to be retrieved
:type index: str
:param index: (Optional) name of index to use, rather than the
table's primary key
:type partition_size_bytes: int
:param partition_size_bytes:
(Optional) desired size for each partition generated. The service
uses this as a hint, the actual partition size may differ.
:type max_partitions: int
:param max_partitions:
(Optional) desired maximum number of partitions generated. The
service uses this as a hint, the actual number of partitions may
differ.
:rtype: iterable of bytes
:returns: a sequence of partition tokens
:raises ValueError:
for single-use snapshots, or if a transaction ID is
already associtated with the snapshot.
"""
if not self._multi_use:
raise ValueError("Cannot use single-use snapshot.")
if self._transaction_id is None:
raise ValueError("Transaction not started.")
database = self._session._database
api = database.spanner_api
metadata = _metadata_with_prefix(database.name)
transaction = self._make_txn_selector()
partition_options = PartitionOptions(
partition_size_bytes=partition_size_bytes, max_partitions=max_partitions
)
response = api.partition_read(
session=self._session.name,
table=table,
columns=columns,
key_set=keyset._to_pb(),
transaction=transaction,
index=index,
partition_options=partition_options,
metadata=metadata,
)
return [partition.partition_token for partition in response.partitions]
|
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] |
Perform a ``ParitionRead`` API request for rows in a table.
:type table: str
:param table: name of the table from which to fetch data
:type columns: list of str
:param columns: names of columns to be retrieved
:type keyset: :class:`~google.cloud.spanner_v1.keyset.KeySet`
:param keyset: keys / ranges identifying rows to be retrieved
:type index: str
:param index: (Optional) name of index to use, rather than the
table's primary key
:type partition_size_bytes: int
:param partition_size_bytes:
(Optional) desired size for each partition generated. The service
uses this as a hint, the actual partition size may differ.
:type max_partitions: int
:param max_partitions:
(Optional) desired maximum number of partitions generated. The
service uses this as a hint, the actual number of partitions may
differ.
:rtype: iterable of bytes
:returns: a sequence of partition tokens
:raises ValueError:
for single-use snapshots, or if a transaction ID is
already associtated with the snapshot.
|
[
"Perform",
"a",
"ParitionRead",
"API",
"request",
"for",
"rows",
"in",
"a",
"table",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/spanner/google/cloud/spanner_v1/snapshot.py#L239-L306
|
train
|
googleapis/google-cloud-python
|
spanner/google/cloud/spanner_v1/snapshot.py
|
_SnapshotBase.partition_query
|
def partition_query(
self,
sql,
params=None,
param_types=None,
partition_size_bytes=None,
max_partitions=None,
):
"""Perform a ``ParitionQuery`` API request.
:type sql: str
:param sql: SQL query statement
:type params: dict, {str -> column value}
:param params: values for parameter replacement. Keys must match
the names used in ``sql``.
:type param_types: dict[str -> Union[dict, .types.Type]]
:param param_types:
(Optional) maps explicit types for one or more param values;
required if parameters are passed.
:type partition_size_bytes: int
:param partition_size_bytes:
(Optional) desired size for each partition generated. The service
uses this as a hint, the actual partition size may differ.
:type max_partitions: int
:param max_partitions:
(Optional) desired maximum number of partitions generated. The
service uses this as a hint, the actual number of partitions may
differ.
:rtype: iterable of bytes
:returns: a sequence of partition tokens
:raises ValueError:
for single-use snapshots, or if a transaction ID is
already associtated with the snapshot.
"""
if not self._multi_use:
raise ValueError("Cannot use single-use snapshot.")
if self._transaction_id is None:
raise ValueError("Transaction not started.")
if params is not None:
if param_types is None:
raise ValueError("Specify 'param_types' when passing 'params'.")
params_pb = Struct(
fields={key: _make_value_pb(value) for key, value in params.items()}
)
else:
params_pb = None
database = self._session._database
api = database.spanner_api
metadata = _metadata_with_prefix(database.name)
transaction = self._make_txn_selector()
partition_options = PartitionOptions(
partition_size_bytes=partition_size_bytes, max_partitions=max_partitions
)
response = api.partition_query(
session=self._session.name,
sql=sql,
transaction=transaction,
params=params_pb,
param_types=param_types,
partition_options=partition_options,
metadata=metadata,
)
return [partition.partition_token for partition in response.partitions]
|
python
|
def partition_query(
self,
sql,
params=None,
param_types=None,
partition_size_bytes=None,
max_partitions=None,
):
"""Perform a ``ParitionQuery`` API request.
:type sql: str
:param sql: SQL query statement
:type params: dict, {str -> column value}
:param params: values for parameter replacement. Keys must match
the names used in ``sql``.
:type param_types: dict[str -> Union[dict, .types.Type]]
:param param_types:
(Optional) maps explicit types for one or more param values;
required if parameters are passed.
:type partition_size_bytes: int
:param partition_size_bytes:
(Optional) desired size for each partition generated. The service
uses this as a hint, the actual partition size may differ.
:type max_partitions: int
:param max_partitions:
(Optional) desired maximum number of partitions generated. The
service uses this as a hint, the actual number of partitions may
differ.
:rtype: iterable of bytes
:returns: a sequence of partition tokens
:raises ValueError:
for single-use snapshots, or if a transaction ID is
already associtated with the snapshot.
"""
if not self._multi_use:
raise ValueError("Cannot use single-use snapshot.")
if self._transaction_id is None:
raise ValueError("Transaction not started.")
if params is not None:
if param_types is None:
raise ValueError("Specify 'param_types' when passing 'params'.")
params_pb = Struct(
fields={key: _make_value_pb(value) for key, value in params.items()}
)
else:
params_pb = None
database = self._session._database
api = database.spanner_api
metadata = _metadata_with_prefix(database.name)
transaction = self._make_txn_selector()
partition_options = PartitionOptions(
partition_size_bytes=partition_size_bytes, max_partitions=max_partitions
)
response = api.partition_query(
session=self._session.name,
sql=sql,
transaction=transaction,
params=params_pb,
param_types=param_types,
partition_options=partition_options,
metadata=metadata,
)
return [partition.partition_token for partition in response.partitions]
|
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Perform a ``ParitionQuery`` API request.
:type sql: str
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:param params: values for parameter replacement. Keys must match
the names used in ``sql``.
:type param_types: dict[str -> Union[dict, .types.Type]]
:param param_types:
(Optional) maps explicit types for one or more param values;
required if parameters are passed.
:type partition_size_bytes: int
:param partition_size_bytes:
(Optional) desired size for each partition generated. The service
uses this as a hint, the actual partition size may differ.
:type max_partitions: int
:param max_partitions:
(Optional) desired maximum number of partitions generated. The
service uses this as a hint, the actual number of partitions may
differ.
:rtype: iterable of bytes
:returns: a sequence of partition tokens
:raises ValueError:
for single-use snapshots, or if a transaction ID is
already associtated with the snapshot.
|
[
"Perform",
"a",
"ParitionQuery",
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"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/spanner/google/cloud/spanner_v1/snapshot.py#L308-L381
|
train
|
googleapis/google-cloud-python
|
spanner/google/cloud/spanner_v1/snapshot.py
|
Snapshot._make_txn_selector
|
def _make_txn_selector(self):
"""Helper for :meth:`read`."""
if self._transaction_id is not None:
return TransactionSelector(id=self._transaction_id)
if self._read_timestamp:
key = "read_timestamp"
value = _datetime_to_pb_timestamp(self._read_timestamp)
elif self._min_read_timestamp:
key = "min_read_timestamp"
value = _datetime_to_pb_timestamp(self._min_read_timestamp)
elif self._max_staleness:
key = "max_staleness"
value = _timedelta_to_duration_pb(self._max_staleness)
elif self._exact_staleness:
key = "exact_staleness"
value = _timedelta_to_duration_pb(self._exact_staleness)
else:
key = "strong"
value = True
options = TransactionOptions(
read_only=TransactionOptions.ReadOnly(**{key: value})
)
if self._multi_use:
return TransactionSelector(begin=options)
else:
return TransactionSelector(single_use=options)
|
python
|
def _make_txn_selector(self):
"""Helper for :meth:`read`."""
if self._transaction_id is not None:
return TransactionSelector(id=self._transaction_id)
if self._read_timestamp:
key = "read_timestamp"
value = _datetime_to_pb_timestamp(self._read_timestamp)
elif self._min_read_timestamp:
key = "min_read_timestamp"
value = _datetime_to_pb_timestamp(self._min_read_timestamp)
elif self._max_staleness:
key = "max_staleness"
value = _timedelta_to_duration_pb(self._max_staleness)
elif self._exact_staleness:
key = "exact_staleness"
value = _timedelta_to_duration_pb(self._exact_staleness)
else:
key = "strong"
value = True
options = TransactionOptions(
read_only=TransactionOptions.ReadOnly(**{key: value})
)
if self._multi_use:
return TransactionSelector(begin=options)
else:
return TransactionSelector(single_use=options)
|
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Helper for :meth:`read`.
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[
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/spanner/google/cloud/spanner_v1/snapshot.py#L449-L477
|
train
|
googleapis/google-cloud-python
|
spanner/google/cloud/spanner_v1/snapshot.py
|
Snapshot.begin
|
def begin(self):
"""Begin a read-only transaction on the database.
:rtype: bytes
:returns: the ID for the newly-begun transaction.
:raises ValueError:
if the transaction is already begun, committed, or rolled back.
"""
if not self._multi_use:
raise ValueError("Cannot call 'begin' on single-use snapshots")
if self._transaction_id is not None:
raise ValueError("Read-only transaction already begun")
if self._read_request_count > 0:
raise ValueError("Read-only transaction already pending")
database = self._session._database
api = database.spanner_api
metadata = _metadata_with_prefix(database.name)
txn_selector = self._make_txn_selector()
response = api.begin_transaction(
self._session.name, txn_selector.begin, metadata=metadata
)
self._transaction_id = response.id
return self._transaction_id
|
python
|
def begin(self):
"""Begin a read-only transaction on the database.
:rtype: bytes
:returns: the ID for the newly-begun transaction.
:raises ValueError:
if the transaction is already begun, committed, or rolled back.
"""
if not self._multi_use:
raise ValueError("Cannot call 'begin' on single-use snapshots")
if self._transaction_id is not None:
raise ValueError("Read-only transaction already begun")
if self._read_request_count > 0:
raise ValueError("Read-only transaction already pending")
database = self._session._database
api = database.spanner_api
metadata = _metadata_with_prefix(database.name)
txn_selector = self._make_txn_selector()
response = api.begin_transaction(
self._session.name, txn_selector.begin, metadata=metadata
)
self._transaction_id = response.id
return self._transaction_id
|
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|
[
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] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/spanner/google/cloud/spanner_v1/snapshot.py#L479-L505
|
train
|
googleapis/google-cloud-python
|
api_core/google/api_core/gapic_v1/client_info.py
|
ClientInfo.to_user_agent
|
def to_user_agent(self):
"""Returns the user-agent string for this client info."""
# Note: the order here is important as the internal metrics system
# expects these items to be in specific locations.
ua = ""
if self.user_agent is not None:
ua += "{user_agent} "
ua += "gl-python/{python_version} "
if self.grpc_version is not None:
ua += "grpc/{grpc_version} "
ua += "gax/{api_core_version} "
if self.gapic_version is not None:
ua += "gapic/{gapic_version} "
if self.client_library_version is not None:
ua += "gccl/{client_library_version} "
return ua.format(**self.__dict__).strip()
|
python
|
def to_user_agent(self):
"""Returns the user-agent string for this client info."""
# Note: the order here is important as the internal metrics system
# expects these items to be in specific locations.
ua = ""
if self.user_agent is not None:
ua += "{user_agent} "
ua += "gl-python/{python_version} "
if self.grpc_version is not None:
ua += "grpc/{grpc_version} "
ua += "gax/{api_core_version} "
if self.gapic_version is not None:
ua += "gapic/{gapic_version} "
if self.client_library_version is not None:
ua += "gccl/{client_library_version} "
return ua.format(**self.__dict__).strip()
|
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85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/api_core/google/api_core/gapic_v1/client_info.py#L75-L98
|
train
|
googleapis/google-cloud-python
|
bigquery_storage/google/cloud/bigquery_storage_v1beta1/client.py
|
BigQueryStorageClient.read_rows
|
def read_rows(
self,
read_position,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None,
):
"""
Reads rows from the table in the format prescribed by the read
session. Each response contains one or more table rows, up to a
maximum of 10 MiB per response; read requests which attempt to read
individual rows larger than this will fail.
Each request also returns a set of stream statistics reflecting the
estimated total number of rows in the read stream. This number is
computed based on the total table size and the number of active
streams in the read session, and may change as other streams continue
to read data.
Example:
>>> from google.cloud import bigquery_storage_v1beta1
>>>
>>> client = bigquery_storage_v1beta1.BigQueryStorageClient()
>>>
>>> # TODO: Initialize ``table_reference``:
>>> table_reference = {
... 'project_id': 'your-data-project-id',
... 'dataset_id': 'your_dataset_id',
... 'table_id': 'your_table_id',
... }
>>>
>>> # TODO: Initialize `parent`:
>>> parent = 'projects/your-billing-project-id'
>>>
>>> session = client.create_read_session(table_reference, parent)
>>> read_position = bigquery_storage_v1beta1.types.StreamPosition(
... stream=session.streams[0], # TODO: Read the other streams.
... )
>>>
>>> for element in client.read_rows(read_position):
... # process element
... pass
Args:
read_position (Union[ \
dict, \
~google.cloud.bigquery_storage_v1beta1.types.StreamPosition \
]):
Required. Identifier of the position in the stream to start
reading from. The offset requested must be less than the last
row read from ReadRows. Requesting a larger offset is
undefined. If a dict is provided, it must be of the same form
as the protobuf message
:class:`~google.cloud.bigquery_storage_v1beta1.types.StreamPosition`
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will not
be retried.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
~google.cloud.bigquery_storage_v1beta1.reader.ReadRowsStream:
An iterable of
:class:`~google.cloud.bigquery_storage_v1beta1.types.ReadRowsResponse`.
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid.
"""
gapic_client = super(BigQueryStorageClient, self)
stream = gapic_client.read_rows(
read_position, retry=retry, timeout=timeout, metadata=metadata
)
return reader.ReadRowsStream(
stream,
gapic_client,
read_position,
{"retry": retry, "timeout": timeout, "metadata": metadata},
)
|
python
|
def read_rows(
self,
read_position,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None,
):
"""
Reads rows from the table in the format prescribed by the read
session. Each response contains one or more table rows, up to a
maximum of 10 MiB per response; read requests which attempt to read
individual rows larger than this will fail.
Each request also returns a set of stream statistics reflecting the
estimated total number of rows in the read stream. This number is
computed based on the total table size and the number of active
streams in the read session, and may change as other streams continue
to read data.
Example:
>>> from google.cloud import bigquery_storage_v1beta1
>>>
>>> client = bigquery_storage_v1beta1.BigQueryStorageClient()
>>>
>>> # TODO: Initialize ``table_reference``:
>>> table_reference = {
... 'project_id': 'your-data-project-id',
... 'dataset_id': 'your_dataset_id',
... 'table_id': 'your_table_id',
... }
>>>
>>> # TODO: Initialize `parent`:
>>> parent = 'projects/your-billing-project-id'
>>>
>>> session = client.create_read_session(table_reference, parent)
>>> read_position = bigquery_storage_v1beta1.types.StreamPosition(
... stream=session.streams[0], # TODO: Read the other streams.
... )
>>>
>>> for element in client.read_rows(read_position):
... # process element
... pass
Args:
read_position (Union[ \
dict, \
~google.cloud.bigquery_storage_v1beta1.types.StreamPosition \
]):
Required. Identifier of the position in the stream to start
reading from. The offset requested must be less than the last
row read from ReadRows. Requesting a larger offset is
undefined. If a dict is provided, it must be of the same form
as the protobuf message
:class:`~google.cloud.bigquery_storage_v1beta1.types.StreamPosition`
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will not
be retried.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
~google.cloud.bigquery_storage_v1beta1.reader.ReadRowsStream:
An iterable of
:class:`~google.cloud.bigquery_storage_v1beta1.types.ReadRowsResponse`.
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid.
"""
gapic_client = super(BigQueryStorageClient, self)
stream = gapic_client.read_rows(
read_position, retry=retry, timeout=timeout, metadata=metadata
)
return reader.ReadRowsStream(
stream,
gapic_client,
read_position,
{"retry": retry, "timeout": timeout, "metadata": metadata},
)
|
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Reads rows from the table in the format prescribed by the read
session. Each response contains one or more table rows, up to a
maximum of 10 MiB per response; read requests which attempt to read
individual rows larger than this will fail.
Each request also returns a set of stream statistics reflecting the
estimated total number of rows in the read stream. This number is
computed based on the total table size and the number of active
streams in the read session, and may change as other streams continue
to read data.
Example:
>>> from google.cloud import bigquery_storage_v1beta1
>>>
>>> client = bigquery_storage_v1beta1.BigQueryStorageClient()
>>>
>>> # TODO: Initialize ``table_reference``:
>>> table_reference = {
... 'project_id': 'your-data-project-id',
... 'dataset_id': 'your_dataset_id',
... 'table_id': 'your_table_id',
... }
>>>
>>> # TODO: Initialize `parent`:
>>> parent = 'projects/your-billing-project-id'
>>>
>>> session = client.create_read_session(table_reference, parent)
>>> read_position = bigquery_storage_v1beta1.types.StreamPosition(
... stream=session.streams[0], # TODO: Read the other streams.
... )
>>>
>>> for element in client.read_rows(read_position):
... # process element
... pass
Args:
read_position (Union[ \
dict, \
~google.cloud.bigquery_storage_v1beta1.types.StreamPosition \
]):
Required. Identifier of the position in the stream to start
reading from. The offset requested must be less than the last
row read from ReadRows. Requesting a larger offset is
undefined. If a dict is provided, it must be of the same form
as the protobuf message
:class:`~google.cloud.bigquery_storage_v1beta1.types.StreamPosition`
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will not
be retried.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
~google.cloud.bigquery_storage_v1beta1.reader.ReadRowsStream:
An iterable of
:class:`~google.cloud.bigquery_storage_v1beta1.types.ReadRowsResponse`.
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid.
|
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] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery_storage/google/cloud/bigquery_storage_v1beta1/client.py#L42-L126
|
train
|
googleapis/google-cloud-python
|
trace/google/cloud/trace/v1/_gapic.py
|
make_trace_api
|
def make_trace_api(client):
"""
Create an instance of the gapic Trace API.
Args:
client (~google.cloud.trace.client.Client): The client that holds
configuration details.
Returns:
A :class:`~google.cloud.trace._gapic._TraceAPI` instance with the
proper configurations.
"""
generated = trace_service_client.TraceServiceClient(
credentials=client._credentials, client_info=_CLIENT_INFO
)
return _TraceAPI(generated, client)
|
python
|
def make_trace_api(client):
"""
Create an instance of the gapic Trace API.
Args:
client (~google.cloud.trace.client.Client): The client that holds
configuration details.
Returns:
A :class:`~google.cloud.trace._gapic._TraceAPI` instance with the
proper configurations.
"""
generated = trace_service_client.TraceServiceClient(
credentials=client._credentials, client_info=_CLIENT_INFO
)
return _TraceAPI(generated, client)
|
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"=",
"_CLIENT_INFO",
")",
"return",
"_TraceAPI",
"(",
"generated",
",",
"client",
")"
] |
Create an instance of the gapic Trace API.
Args:
client (~google.cloud.trace.client.Client): The client that holds
configuration details.
Returns:
A :class:`~google.cloud.trace._gapic._TraceAPI` instance with the
proper configurations.
|
[
"Create",
"an",
"instance",
"of",
"the",
"gapic",
"Trace",
"API",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/trace/google/cloud/trace/v1/_gapic.py#L168-L183
|
train
|
googleapis/google-cloud-python
|
trace/google/cloud/trace/v1/_gapic.py
|
_TraceAPI.patch_traces
|
def patch_traces(self, project_id, traces):
"""
Sends new traces to Stackdriver Trace or updates existing traces.
Args:
project_id (Optional[str]): ID of the Cloud project where the trace
data is stored.
traces (dict): Required. The traces to be patched in the API call.
"""
traces_pb = _traces_mapping_to_pb(traces)
self._gapic_api.patch_traces(project_id, traces_pb)
|
python
|
def patch_traces(self, project_id, traces):
"""
Sends new traces to Stackdriver Trace or updates existing traces.
Args:
project_id (Optional[str]): ID of the Cloud project where the trace
data is stored.
traces (dict): Required. The traces to be patched in the API call.
"""
traces_pb = _traces_mapping_to_pb(traces)
self._gapic_api.patch_traces(project_id, traces_pb)
|
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"self",
".",
"_gapic_api",
".",
"patch_traces",
"(",
"project_id",
",",
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")"
] |
Sends new traces to Stackdriver Trace or updates existing traces.
Args:
project_id (Optional[str]): ID of the Cloud project where the trace
data is stored.
traces (dict): Required. The traces to be patched in the API call.
|
[
"Sends",
"new",
"traces",
"to",
"Stackdriver",
"Trace",
"or",
"updates",
"existing",
"traces",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/trace/google/cloud/trace/v1/_gapic.py#L47-L57
|
train
|
googleapis/google-cloud-python
|
trace/google/cloud/trace/v1/_gapic.py
|
_TraceAPI.get_trace
|
def get_trace(self, project_id, trace_id):
"""
Gets a single trace by its ID.
Args:
trace_id (str): ID of the trace to return.
project_id (str): Required. ID of the Cloud project where the trace
data is stored.
Returns:
A Trace dict.
"""
trace_pb = self._gapic_api.get_trace(project_id, trace_id)
trace_mapping = _parse_trace_pb(trace_pb)
return trace_mapping
|
python
|
def get_trace(self, project_id, trace_id):
"""
Gets a single trace by its ID.
Args:
trace_id (str): ID of the trace to return.
project_id (str): Required. ID of the Cloud project where the trace
data is stored.
Returns:
A Trace dict.
"""
trace_pb = self._gapic_api.get_trace(project_id, trace_id)
trace_mapping = _parse_trace_pb(trace_pb)
return trace_mapping
|
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"trace_mapping",
"=",
"_parse_trace_pb",
"(",
"trace_pb",
")",
"return",
"trace_mapping"
] |
Gets a single trace by its ID.
Args:
trace_id (str): ID of the trace to return.
project_id (str): Required. ID of the Cloud project where the trace
data is stored.
Returns:
A Trace dict.
|
[
"Gets",
"a",
"single",
"trace",
"by",
"its",
"ID",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/trace/google/cloud/trace/v1/_gapic.py#L59-L73
|
train
|
googleapis/google-cloud-python
|
trace/google/cloud/trace/v1/_gapic.py
|
_TraceAPI.list_traces
|
def list_traces(
self,
project_id,
view=None,
page_size=None,
start_time=None,
end_time=None,
filter_=None,
order_by=None,
page_token=None,
):
"""
Returns of a list of traces that match the filter conditions.
Args:
project_id (Optional[str]): ID of the Cloud project where the trace
data is stored.
view (Optional[~google.cloud.trace_v1.gapic.enums.
ListTracesRequest.ViewType]): Type of data returned for traces
in the list. Default is ``MINIMAL``.
page_size (Optional[int]): Maximum number of traces to return. If
not specified or <= 0, the implementation selects a reasonable
value. The implementation may return fewer traces than the
requested page size.
start_time (Optional[~datetime.datetime]): Start of the time
interval (inclusive) during which the trace data was collected
from the application.
end_time (Optional[~datetime.datetime]): End of the time interval
(inclusive) during which the trace data was collected from the
application.
filter_ (Optional[str]): An optional filter for the request.
order_by (Optional[str]): Field used to sort the returned traces.
page_token (Optional[str]): opaque marker for the next "page" of
entries. If not passed, the API will return the first page of
entries.
Returns:
A :class:`~google.api_core.page_iterator.Iterator` of traces that
match the specified filter conditions.
"""
page_iter = self._gapic_api.list_traces(
project_id=project_id,
view=view,
page_size=page_size,
start_time=start_time,
end_time=end_time,
filter_=filter_,
order_by=order_by,
)
page_iter.item_to_value = _item_to_mapping
page_iter.next_page_token = page_token
return page_iter
|
python
|
def list_traces(
self,
project_id,
view=None,
page_size=None,
start_time=None,
end_time=None,
filter_=None,
order_by=None,
page_token=None,
):
"""
Returns of a list of traces that match the filter conditions.
Args:
project_id (Optional[str]): ID of the Cloud project where the trace
data is stored.
view (Optional[~google.cloud.trace_v1.gapic.enums.
ListTracesRequest.ViewType]): Type of data returned for traces
in the list. Default is ``MINIMAL``.
page_size (Optional[int]): Maximum number of traces to return. If
not specified or <= 0, the implementation selects a reasonable
value. The implementation may return fewer traces than the
requested page size.
start_time (Optional[~datetime.datetime]): Start of the time
interval (inclusive) during which the trace data was collected
from the application.
end_time (Optional[~datetime.datetime]): End of the time interval
(inclusive) during which the trace data was collected from the
application.
filter_ (Optional[str]): An optional filter for the request.
order_by (Optional[str]): Field used to sort the returned traces.
page_token (Optional[str]): opaque marker for the next "page" of
entries. If not passed, the API will return the first page of
entries.
Returns:
A :class:`~google.api_core.page_iterator.Iterator` of traces that
match the specified filter conditions.
"""
page_iter = self._gapic_api.list_traces(
project_id=project_id,
view=view,
page_size=page_size,
start_time=start_time,
end_time=end_time,
filter_=filter_,
order_by=order_by,
)
page_iter.item_to_value = _item_to_mapping
page_iter.next_page_token = page_token
return page_iter
|
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Returns of a list of traces that match the filter conditions.
Args:
project_id (Optional[str]): ID of the Cloud project where the trace
data is stored.
view (Optional[~google.cloud.trace_v1.gapic.enums.
ListTracesRequest.ViewType]): Type of data returned for traces
in the list. Default is ``MINIMAL``.
page_size (Optional[int]): Maximum number of traces to return. If
not specified or <= 0, the implementation selects a reasonable
value. The implementation may return fewer traces than the
requested page size.
start_time (Optional[~datetime.datetime]): Start of the time
interval (inclusive) during which the trace data was collected
from the application.
end_time (Optional[~datetime.datetime]): End of the time interval
(inclusive) during which the trace data was collected from the
application.
filter_ (Optional[str]): An optional filter for the request.
order_by (Optional[str]): Field used to sort the returned traces.
page_token (Optional[str]): opaque marker for the next "page" of
entries. If not passed, the API will return the first page of
entries.
Returns:
A :class:`~google.api_core.page_iterator.Iterator` of traces that
match the specified filter conditions.
|
[
"Returns",
"of",
"a",
"list",
"of",
"traces",
"that",
"match",
"the",
"filter",
"conditions",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/trace/google/cloud/trace/v1/_gapic.py#L75-L133
|
train
|
googleapis/google-cloud-python
|
storage/google/cloud/storage/client.py
|
_item_to_bucket
|
def _item_to_bucket(iterator, item):
"""Convert a JSON bucket to the native object.
:type iterator: :class:`~google.api_core.page_iterator.Iterator`
:param iterator: The iterator that has retrieved the item.
:type item: dict
:param item: An item to be converted to a bucket.
:rtype: :class:`.Bucket`
:returns: The next bucket in the page.
"""
name = item.get("name")
bucket = Bucket(iterator.client, name)
bucket._set_properties(item)
return bucket
|
python
|
def _item_to_bucket(iterator, item):
"""Convert a JSON bucket to the native object.
:type iterator: :class:`~google.api_core.page_iterator.Iterator`
:param iterator: The iterator that has retrieved the item.
:type item: dict
:param item: An item to be converted to a bucket.
:rtype: :class:`.Bucket`
:returns: The next bucket in the page.
"""
name = item.get("name")
bucket = Bucket(iterator.client, name)
bucket._set_properties(item)
return bucket
|
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Convert a JSON bucket to the native object.
:type iterator: :class:`~google.api_core.page_iterator.Iterator`
:param iterator: The iterator that has retrieved the item.
:type item: dict
:param item: An item to be converted to a bucket.
:rtype: :class:`.Bucket`
:returns: The next bucket in the page.
|
[
"Convert",
"a",
"JSON",
"bucket",
"to",
"the",
"native",
"object",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/storage/google/cloud/storage/client.py#L374-L389
|
train
|
googleapis/google-cloud-python
|
storage/google/cloud/storage/client.py
|
Client.create_anonymous_client
|
def create_anonymous_client(cls):
"""Factory: return client with anonymous credentials.
.. note::
Such a client has only limited access to "public" buckets:
listing their contents and downloading their blobs.
:rtype: :class:`google.cloud.storage.client.Client`
:returns: Instance w/ anonymous credentials and no project.
"""
client = cls(project="<none>", credentials=AnonymousCredentials())
client.project = None
return client
|
python
|
def create_anonymous_client(cls):
"""Factory: return client with anonymous credentials.
.. note::
Such a client has only limited access to "public" buckets:
listing their contents and downloading their blobs.
:rtype: :class:`google.cloud.storage.client.Client`
:returns: Instance w/ anonymous credentials and no project.
"""
client = cls(project="<none>", credentials=AnonymousCredentials())
client.project = None
return client
|
[
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"AnonymousCredentials",
"(",
")",
")",
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] |
Factory: return client with anonymous credentials.
.. note::
Such a client has only limited access to "public" buckets:
listing their contents and downloading their blobs.
:rtype: :class:`google.cloud.storage.client.Client`
:returns: Instance w/ anonymous credentials and no project.
|
[
"Factory",
":",
"return",
"client",
"with",
"anonymous",
"credentials",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/storage/google/cloud/storage/client.py#L81-L94
|
train
|
googleapis/google-cloud-python
|
storage/google/cloud/storage/client.py
|
Client.get_service_account_email
|
def get_service_account_email(self, project=None):
"""Get the email address of the project's GCS service account
:type project: str
:param project:
(Optional) Project ID to use for retreiving GCS service account
email address. Defaults to the client's project.
:rtype: str
:returns: service account email address
"""
if project is None:
project = self.project
path = "/projects/%s/serviceAccount" % (project,)
api_response = self._base_connection.api_request(method="GET", path=path)
return api_response["email_address"]
|
python
|
def get_service_account_email(self, project=None):
"""Get the email address of the project's GCS service account
:type project: str
:param project:
(Optional) Project ID to use for retreiving GCS service account
email address. Defaults to the client's project.
:rtype: str
:returns: service account email address
"""
if project is None:
project = self.project
path = "/projects/%s/serviceAccount" % (project,)
api_response = self._base_connection.api_request(method="GET", path=path)
return api_response["email_address"]
|
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Get the email address of the project's GCS service account
:type project: str
:param project:
(Optional) Project ID to use for retreiving GCS service account
email address. Defaults to the client's project.
:rtype: str
:returns: service account email address
|
[
"Get",
"the",
"email",
"address",
"of",
"the",
"project",
"s",
"GCS",
"service",
"account"
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/storage/google/cloud/storage/client.py#L157-L172
|
train
|
googleapis/google-cloud-python
|
storage/google/cloud/storage/client.py
|
Client.bucket
|
def bucket(self, bucket_name, user_project=None):
"""Factory constructor for bucket object.
.. note::
This will not make an HTTP request; it simply instantiates
a bucket object owned by this client.
:type bucket_name: str
:param bucket_name: The name of the bucket to be instantiated.
:type user_project: str
:param user_project: (Optional) the project ID to be billed for API
requests made via the bucket.
:rtype: :class:`google.cloud.storage.bucket.Bucket`
:returns: The bucket object created.
"""
return Bucket(client=self, name=bucket_name, user_project=user_project)
|
python
|
def bucket(self, bucket_name, user_project=None):
"""Factory constructor for bucket object.
.. note::
This will not make an HTTP request; it simply instantiates
a bucket object owned by this client.
:type bucket_name: str
:param bucket_name: The name of the bucket to be instantiated.
:type user_project: str
:param user_project: (Optional) the project ID to be billed for API
requests made via the bucket.
:rtype: :class:`google.cloud.storage.bucket.Bucket`
:returns: The bucket object created.
"""
return Bucket(client=self, name=bucket_name, user_project=user_project)
|
[
"def",
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"=",
"self",
",",
"name",
"=",
"bucket_name",
",",
"user_project",
"=",
"user_project",
")"
] |
Factory constructor for bucket object.
.. note::
This will not make an HTTP request; it simply instantiates
a bucket object owned by this client.
:type bucket_name: str
:param bucket_name: The name of the bucket to be instantiated.
:type user_project: str
:param user_project: (Optional) the project ID to be billed for API
requests made via the bucket.
:rtype: :class:`google.cloud.storage.bucket.Bucket`
:returns: The bucket object created.
|
[
"Factory",
"constructor",
"for",
"bucket",
"object",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/storage/google/cloud/storage/client.py#L174-L191
|
train
|
googleapis/google-cloud-python
|
storage/google/cloud/storage/client.py
|
Client.get_bucket
|
def get_bucket(self, bucket_name):
"""Get a bucket by name.
If the bucket isn't found, this will raise a
:class:`google.cloud.exceptions.NotFound`.
For example:
.. literalinclude:: snippets.py
:start-after: [START get_bucket]
:end-before: [END get_bucket]
This implements "storage.buckets.get".
:type bucket_name: str
:param bucket_name: The name of the bucket to get.
:rtype: :class:`google.cloud.storage.bucket.Bucket`
:returns: The bucket matching the name provided.
:raises: :class:`google.cloud.exceptions.NotFound`
"""
bucket = Bucket(self, name=bucket_name)
bucket.reload(client=self)
return bucket
|
python
|
def get_bucket(self, bucket_name):
"""Get a bucket by name.
If the bucket isn't found, this will raise a
:class:`google.cloud.exceptions.NotFound`.
For example:
.. literalinclude:: snippets.py
:start-after: [START get_bucket]
:end-before: [END get_bucket]
This implements "storage.buckets.get".
:type bucket_name: str
:param bucket_name: The name of the bucket to get.
:rtype: :class:`google.cloud.storage.bucket.Bucket`
:returns: The bucket matching the name provided.
:raises: :class:`google.cloud.exceptions.NotFound`
"""
bucket = Bucket(self, name=bucket_name)
bucket.reload(client=self)
return bucket
|
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")",
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] |
Get a bucket by name.
If the bucket isn't found, this will raise a
:class:`google.cloud.exceptions.NotFound`.
For example:
.. literalinclude:: snippets.py
:start-after: [START get_bucket]
:end-before: [END get_bucket]
This implements "storage.buckets.get".
:type bucket_name: str
:param bucket_name: The name of the bucket to get.
:rtype: :class:`google.cloud.storage.bucket.Bucket`
:returns: The bucket matching the name provided.
:raises: :class:`google.cloud.exceptions.NotFound`
|
[
"Get",
"a",
"bucket",
"by",
"name",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/storage/google/cloud/storage/client.py#L205-L228
|
train
|
googleapis/google-cloud-python
|
storage/google/cloud/storage/client.py
|
Client.create_bucket
|
def create_bucket(self, bucket_name, requester_pays=None, project=None):
"""Create a new bucket.
For example:
.. literalinclude:: snippets.py
:start-after: [START create_bucket]
:end-before: [END create_bucket]
This implements "storage.buckets.insert".
If the bucket already exists, will raise
:class:`google.cloud.exceptions.Conflict`.
To set additional properties when creating a bucket, such as the
bucket location, use :meth:`~.Bucket.create`.
:type bucket_name: str
:param bucket_name: The bucket name to create.
:type requester_pays: bool
:param requester_pays:
(Optional) Whether requester pays for API requests for this
bucket and its blobs.
:type project: str
:param project: (Optional) the project under which the bucket is to
be created. If not passed, uses the project set on
the client.
:rtype: :class:`google.cloud.storage.bucket.Bucket`
:returns: The newly created bucket.
"""
bucket = Bucket(self, name=bucket_name)
if requester_pays is not None:
bucket.requester_pays = requester_pays
bucket.create(client=self, project=project)
return bucket
|
python
|
def create_bucket(self, bucket_name, requester_pays=None, project=None):
"""Create a new bucket.
For example:
.. literalinclude:: snippets.py
:start-after: [START create_bucket]
:end-before: [END create_bucket]
This implements "storage.buckets.insert".
If the bucket already exists, will raise
:class:`google.cloud.exceptions.Conflict`.
To set additional properties when creating a bucket, such as the
bucket location, use :meth:`~.Bucket.create`.
:type bucket_name: str
:param bucket_name: The bucket name to create.
:type requester_pays: bool
:param requester_pays:
(Optional) Whether requester pays for API requests for this
bucket and its blobs.
:type project: str
:param project: (Optional) the project under which the bucket is to
be created. If not passed, uses the project set on
the client.
:rtype: :class:`google.cloud.storage.bucket.Bucket`
:returns: The newly created bucket.
"""
bucket = Bucket(self, name=bucket_name)
if requester_pays is not None:
bucket.requester_pays = requester_pays
bucket.create(client=self, project=project)
return bucket
|
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"(",
"client",
"=",
"self",
",",
"project",
"=",
"project",
")",
"return",
"bucket"
] |
Create a new bucket.
For example:
.. literalinclude:: snippets.py
:start-after: [START create_bucket]
:end-before: [END create_bucket]
This implements "storage.buckets.insert".
If the bucket already exists, will raise
:class:`google.cloud.exceptions.Conflict`.
To set additional properties when creating a bucket, such as the
bucket location, use :meth:`~.Bucket.create`.
:type bucket_name: str
:param bucket_name: The bucket name to create.
:type requester_pays: bool
:param requester_pays:
(Optional) Whether requester pays for API requests for this
bucket and its blobs.
:type project: str
:param project: (Optional) the project under which the bucket is to
be created. If not passed, uses the project set on
the client.
:rtype: :class:`google.cloud.storage.bucket.Bucket`
:returns: The newly created bucket.
|
[
"Create",
"a",
"new",
"bucket",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/storage/google/cloud/storage/client.py#L251-L288
|
train
|
googleapis/google-cloud-python
|
storage/google/cloud/storage/client.py
|
Client.list_buckets
|
def list_buckets(
self,
max_results=None,
page_token=None,
prefix=None,
projection="noAcl",
fields=None,
project=None,
):
"""Get all buckets in the project associated to the client.
This will not populate the list of blobs available in each
bucket.
.. literalinclude:: snippets.py
:start-after: [START list_buckets]
:end-before: [END list_buckets]
This implements "storage.buckets.list".
:type max_results: int
:param max_results: Optional. The maximum number of buckets to return.
:type page_token: str
:param page_token:
Optional. If present, return the next batch of buckets, using the
value, which must correspond to the ``nextPageToken`` value
returned in the previous response. Deprecated: use the ``pages``
property of the returned iterator instead of manually passing the
token.
:type prefix: str
:param prefix: Optional. Filter results to buckets whose names begin
with this prefix.
:type projection: str
:param projection:
(Optional) Specifies the set of properties to return. If used, must
be 'full' or 'noAcl'. Defaults to 'noAcl'.
:type fields: str
:param fields:
(Optional) Selector specifying which fields to include in a partial
response. Must be a list of fields. For example to get a partial
response with just the next page token and the language of each
bucket returned: 'items/id,nextPageToken'
:type project: str
:param project: (Optional) the project whose buckets are to be listed.
If not passed, uses the project set on the client.
:rtype: :class:`~google.api_core.page_iterator.Iterator`
:raises ValueError: if both ``project`` is ``None`` and the client's
project is also ``None``.
:returns: Iterator of all :class:`~google.cloud.storage.bucket.Bucket`
belonging to this project.
"""
if project is None:
project = self.project
if project is None:
raise ValueError("Client project not set: pass an explicit project.")
extra_params = {"project": project}
if prefix is not None:
extra_params["prefix"] = prefix
extra_params["projection"] = projection
if fields is not None:
extra_params["fields"] = fields
return page_iterator.HTTPIterator(
client=self,
api_request=self._connection.api_request,
path="/b",
item_to_value=_item_to_bucket,
page_token=page_token,
max_results=max_results,
extra_params=extra_params,
)
|
python
|
def list_buckets(
self,
max_results=None,
page_token=None,
prefix=None,
projection="noAcl",
fields=None,
project=None,
):
"""Get all buckets in the project associated to the client.
This will not populate the list of blobs available in each
bucket.
.. literalinclude:: snippets.py
:start-after: [START list_buckets]
:end-before: [END list_buckets]
This implements "storage.buckets.list".
:type max_results: int
:param max_results: Optional. The maximum number of buckets to return.
:type page_token: str
:param page_token:
Optional. If present, return the next batch of buckets, using the
value, which must correspond to the ``nextPageToken`` value
returned in the previous response. Deprecated: use the ``pages``
property of the returned iterator instead of manually passing the
token.
:type prefix: str
:param prefix: Optional. Filter results to buckets whose names begin
with this prefix.
:type projection: str
:param projection:
(Optional) Specifies the set of properties to return. If used, must
be 'full' or 'noAcl'. Defaults to 'noAcl'.
:type fields: str
:param fields:
(Optional) Selector specifying which fields to include in a partial
response. Must be a list of fields. For example to get a partial
response with just the next page token and the language of each
bucket returned: 'items/id,nextPageToken'
:type project: str
:param project: (Optional) the project whose buckets are to be listed.
If not passed, uses the project set on the client.
:rtype: :class:`~google.api_core.page_iterator.Iterator`
:raises ValueError: if both ``project`` is ``None`` and the client's
project is also ``None``.
:returns: Iterator of all :class:`~google.cloud.storage.bucket.Bucket`
belonging to this project.
"""
if project is None:
project = self.project
if project is None:
raise ValueError("Client project not set: pass an explicit project.")
extra_params = {"project": project}
if prefix is not None:
extra_params["prefix"] = prefix
extra_params["projection"] = projection
if fields is not None:
extra_params["fields"] = fields
return page_iterator.HTTPIterator(
client=self,
api_request=self._connection.api_request,
path="/b",
item_to_value=_item_to_bucket,
page_token=page_token,
max_results=max_results,
extra_params=extra_params,
)
|
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"max_results",
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"=",
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",",
")"
] |
Get all buckets in the project associated to the client.
This will not populate the list of blobs available in each
bucket.
.. literalinclude:: snippets.py
:start-after: [START list_buckets]
:end-before: [END list_buckets]
This implements "storage.buckets.list".
:type max_results: int
:param max_results: Optional. The maximum number of buckets to return.
:type page_token: str
:param page_token:
Optional. If present, return the next batch of buckets, using the
value, which must correspond to the ``nextPageToken`` value
returned in the previous response. Deprecated: use the ``pages``
property of the returned iterator instead of manually passing the
token.
:type prefix: str
:param prefix: Optional. Filter results to buckets whose names begin
with this prefix.
:type projection: str
:param projection:
(Optional) Specifies the set of properties to return. If used, must
be 'full' or 'noAcl'. Defaults to 'noAcl'.
:type fields: str
:param fields:
(Optional) Selector specifying which fields to include in a partial
response. Must be a list of fields. For example to get a partial
response with just the next page token and the language of each
bucket returned: 'items/id,nextPageToken'
:type project: str
:param project: (Optional) the project whose buckets are to be listed.
If not passed, uses the project set on the client.
:rtype: :class:`~google.api_core.page_iterator.Iterator`
:raises ValueError: if both ``project`` is ``None`` and the client's
project is also ``None``.
:returns: Iterator of all :class:`~google.cloud.storage.bucket.Bucket`
belonging to this project.
|
[
"Get",
"all",
"buckets",
"in",
"the",
"project",
"associated",
"to",
"the",
"client",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/storage/google/cloud/storage/client.py#L290-L371
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/client.py
|
_make_job_id
|
def _make_job_id(job_id, prefix=None):
"""Construct an ID for a new job.
:type job_id: str or ``NoneType``
:param job_id: the user-provided job ID
:type prefix: str or ``NoneType``
:param prefix: (Optional) the user-provided prefix for a job ID
:rtype: str
:returns: A job ID
"""
if job_id is not None:
return job_id
elif prefix is not None:
return str(prefix) + str(uuid.uuid4())
else:
return str(uuid.uuid4())
|
python
|
def _make_job_id(job_id, prefix=None):
"""Construct an ID for a new job.
:type job_id: str or ``NoneType``
:param job_id: the user-provided job ID
:type prefix: str or ``NoneType``
:param prefix: (Optional) the user-provided prefix for a job ID
:rtype: str
:returns: A job ID
"""
if job_id is not None:
return job_id
elif prefix is not None:
return str(prefix) + str(uuid.uuid4())
else:
return str(uuid.uuid4())
|
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Construct an ID for a new job.
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:param prefix: (Optional) the user-provided prefix for a job ID
:rtype: str
:returns: A job ID
|
[
"Construct",
"an",
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"for",
"a",
"new",
"job",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/client.py#L2059-L2076
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/client.py
|
_check_mode
|
def _check_mode(stream):
"""Check that a stream was opened in read-binary mode.
:type stream: IO[bytes]
:param stream: A bytes IO object open for reading.
:raises: :exc:`ValueError` if the ``stream.mode`` is a valid attribute
and is not among ``rb``, ``r+b`` or ``rb+``.
"""
mode = getattr(stream, "mode", None)
if isinstance(stream, gzip.GzipFile):
if mode != gzip.READ:
raise ValueError(
"Cannot upload gzip files opened in write mode: use "
"gzip.GzipFile(filename, mode='rb')"
)
else:
if mode is not None and mode not in ("rb", "r+b", "rb+"):
raise ValueError(
"Cannot upload files opened in text mode: use "
"open(filename, mode='rb') or open(filename, mode='r+b')"
)
|
python
|
def _check_mode(stream):
"""Check that a stream was opened in read-binary mode.
:type stream: IO[bytes]
:param stream: A bytes IO object open for reading.
:raises: :exc:`ValueError` if the ``stream.mode`` is a valid attribute
and is not among ``rb``, ``r+b`` or ``rb+``.
"""
mode = getattr(stream, "mode", None)
if isinstance(stream, gzip.GzipFile):
if mode != gzip.READ:
raise ValueError(
"Cannot upload gzip files opened in write mode: use "
"gzip.GzipFile(filename, mode='rb')"
)
else:
if mode is not None and mode not in ("rb", "r+b", "rb+"):
raise ValueError(
"Cannot upload files opened in text mode: use "
"open(filename, mode='rb') or open(filename, mode='r+b')"
)
|
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] |
Check that a stream was opened in read-binary mode.
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:param stream: A bytes IO object open for reading.
:raises: :exc:`ValueError` if the ``stream.mode`` is a valid attribute
and is not among ``rb``, ``r+b`` or ``rb+``.
|
[
"Check",
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"a",
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"opened",
"in",
"read",
"-",
"binary",
"mode",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/client.py#L2079-L2101
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/client.py
|
Client.get_service_account_email
|
def get_service_account_email(self, project=None):
"""Get the email address of the project's BigQuery service account
Note:
This is the service account that BigQuery uses to manage tables
encrypted by a key in KMS.
Args:
project (str, optional):
Project ID to use for retreiving service account email.
Defaults to the client's project.
Returns:
str: service account email address
Example:
>>> from google.cloud import bigquery
>>> client = bigquery.Client()
>>> client.get_service_account_email()
my_service_account@my-project.iam.gserviceaccount.com
"""
if project is None:
project = self.project
path = "/projects/%s/serviceAccount" % (project,)
api_response = self._connection.api_request(method="GET", path=path)
return api_response["email"]
|
python
|
def get_service_account_email(self, project=None):
"""Get the email address of the project's BigQuery service account
Note:
This is the service account that BigQuery uses to manage tables
encrypted by a key in KMS.
Args:
project (str, optional):
Project ID to use for retreiving service account email.
Defaults to the client's project.
Returns:
str: service account email address
Example:
>>> from google.cloud import bigquery
>>> client = bigquery.Client()
>>> client.get_service_account_email()
my_service_account@my-project.iam.gserviceaccount.com
"""
if project is None:
project = self.project
path = "/projects/%s/serviceAccount" % (project,)
api_response = self._connection.api_request(method="GET", path=path)
return api_response["email"]
|
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",",
")",
"api_response",
"=",
"self",
".",
"_connection",
".",
"api_request",
"(",
"method",
"=",
"\"GET\"",
",",
"path",
"=",
"path",
")",
"return",
"api_response",
"[",
"\"email\"",
"]"
] |
Get the email address of the project's BigQuery service account
Note:
This is the service account that BigQuery uses to manage tables
encrypted by a key in KMS.
Args:
project (str, optional):
Project ID to use for retreiving service account email.
Defaults to the client's project.
Returns:
str: service account email address
Example:
>>> from google.cloud import bigquery
>>> client = bigquery.Client()
>>> client.get_service_account_email()
my_service_account@my-project.iam.gserviceaccount.com
|
[
"Get",
"the",
"email",
"address",
"of",
"the",
"project",
"s",
"BigQuery",
"service",
"account"
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/client.py#L164-L191
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/client.py
|
Client.list_projects
|
def list_projects(self, max_results=None, page_token=None, retry=DEFAULT_RETRY):
"""List projects for the project associated with this client.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/projects/list
:type max_results: int
:param max_results: (Optional) maximum number of projects to return,
If not passed, defaults to a value set by the API.
:type page_token: str
:param page_token:
(Optional) Token representing a cursor into the projects. If
not passed, the API will return the first page of projects.
The token marks the beginning of the iterator to be returned
and the value of the ``page_token`` can be accessed at
``next_page_token`` of the
:class:`~google.api_core.page_iterator.HTTPIterator`.
:type retry: :class:`google.api_core.retry.Retry`
:param retry: (Optional) How to retry the RPC.
:rtype: :class:`~google.api_core.page_iterator.Iterator`
:returns: Iterator of :class:`~google.cloud.bigquery.client.Project`
accessible to the current client.
"""
return page_iterator.HTTPIterator(
client=self,
api_request=functools.partial(self._call_api, retry),
path="/projects",
item_to_value=_item_to_project,
items_key="projects",
page_token=page_token,
max_results=max_results,
)
|
python
|
def list_projects(self, max_results=None, page_token=None, retry=DEFAULT_RETRY):
"""List projects for the project associated with this client.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/projects/list
:type max_results: int
:param max_results: (Optional) maximum number of projects to return,
If not passed, defaults to a value set by the API.
:type page_token: str
:param page_token:
(Optional) Token representing a cursor into the projects. If
not passed, the API will return the first page of projects.
The token marks the beginning of the iterator to be returned
and the value of the ``page_token`` can be accessed at
``next_page_token`` of the
:class:`~google.api_core.page_iterator.HTTPIterator`.
:type retry: :class:`google.api_core.retry.Retry`
:param retry: (Optional) How to retry the RPC.
:rtype: :class:`~google.api_core.page_iterator.Iterator`
:returns: Iterator of :class:`~google.cloud.bigquery.client.Project`
accessible to the current client.
"""
return page_iterator.HTTPIterator(
client=self,
api_request=functools.partial(self._call_api, retry),
path="/projects",
item_to_value=_item_to_project,
items_key="projects",
page_token=page_token,
max_results=max_results,
)
|
[
"def",
"list_projects",
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"self",
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"max_results",
"=",
"None",
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"page_token",
"=",
"None",
",",
"retry",
"=",
"DEFAULT_RETRY",
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":",
"return",
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"HTTPIterator",
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"partial",
"(",
"self",
".",
"_call_api",
",",
"retry",
")",
",",
"path",
"=",
"\"/projects\"",
",",
"item_to_value",
"=",
"_item_to_project",
",",
"items_key",
"=",
"\"projects\"",
",",
"page_token",
"=",
"page_token",
",",
"max_results",
"=",
"max_results",
",",
")"
] |
List projects for the project associated with this client.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/projects/list
:type max_results: int
:param max_results: (Optional) maximum number of projects to return,
If not passed, defaults to a value set by the API.
:type page_token: str
:param page_token:
(Optional) Token representing a cursor into the projects. If
not passed, the API will return the first page of projects.
The token marks the beginning of the iterator to be returned
and the value of the ``page_token`` can be accessed at
``next_page_token`` of the
:class:`~google.api_core.page_iterator.HTTPIterator`.
:type retry: :class:`google.api_core.retry.Retry`
:param retry: (Optional) How to retry the RPC.
:rtype: :class:`~google.api_core.page_iterator.Iterator`
:returns: Iterator of :class:`~google.cloud.bigquery.client.Project`
accessible to the current client.
|
[
"List",
"projects",
"for",
"the",
"project",
"associated",
"with",
"this",
"client",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/client.py#L193-L227
|
train
|
googleapis/google-cloud-python
|
bigquery/google/cloud/bigquery/client.py
|
Client.list_datasets
|
def list_datasets(
self,
project=None,
include_all=False,
filter=None,
max_results=None,
page_token=None,
retry=DEFAULT_RETRY,
):
"""List datasets for the project associated with this client.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets/list
Args:
project (str):
Optional. Project ID to use for retreiving datasets. Defaults
to the client's project.
include_all (bool):
Optional. True if results include hidden datasets. Defaults
to False.
filter (str):
Optional. An expression for filtering the results by label.
For syntax, see
https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets/list#filter.
max_results (int):
Optional. Maximum number of datasets to return.
page_token (str):
Optional. Token representing a cursor into the datasets. If
not passed, the API will return the first page of datasets.
The token marks the beginning of the iterator to be returned
and the value of the ``page_token`` can be accessed at
``next_page_token`` of the
:class:`~google.api_core.page_iterator.HTTPIterator`.
retry (google.api_core.retry.Retry):
Optional. How to retry the RPC.
Returns:
google.api_core.page_iterator.Iterator:
Iterator of
:class:`~google.cloud.bigquery.dataset.DatasetListItem`.
associated with the project.
"""
extra_params = {}
if project is None:
project = self.project
if include_all:
extra_params["all"] = True
if filter:
# TODO: consider supporting a dict of label -> value for filter,
# and converting it into a string here.
extra_params["filter"] = filter
path = "/projects/%s/datasets" % (project,)
return page_iterator.HTTPIterator(
client=self,
api_request=functools.partial(self._call_api, retry),
path=path,
item_to_value=_item_to_dataset,
items_key="datasets",
page_token=page_token,
max_results=max_results,
extra_params=extra_params,
)
|
python
|
def list_datasets(
self,
project=None,
include_all=False,
filter=None,
max_results=None,
page_token=None,
retry=DEFAULT_RETRY,
):
"""List datasets for the project associated with this client.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets/list
Args:
project (str):
Optional. Project ID to use for retreiving datasets. Defaults
to the client's project.
include_all (bool):
Optional. True if results include hidden datasets. Defaults
to False.
filter (str):
Optional. An expression for filtering the results by label.
For syntax, see
https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets/list#filter.
max_results (int):
Optional. Maximum number of datasets to return.
page_token (str):
Optional. Token representing a cursor into the datasets. If
not passed, the API will return the first page of datasets.
The token marks the beginning of the iterator to be returned
and the value of the ``page_token`` can be accessed at
``next_page_token`` of the
:class:`~google.api_core.page_iterator.HTTPIterator`.
retry (google.api_core.retry.Retry):
Optional. How to retry the RPC.
Returns:
google.api_core.page_iterator.Iterator:
Iterator of
:class:`~google.cloud.bigquery.dataset.DatasetListItem`.
associated with the project.
"""
extra_params = {}
if project is None:
project = self.project
if include_all:
extra_params["all"] = True
if filter:
# TODO: consider supporting a dict of label -> value for filter,
# and converting it into a string here.
extra_params["filter"] = filter
path = "/projects/%s/datasets" % (project,)
return page_iterator.HTTPIterator(
client=self,
api_request=functools.partial(self._call_api, retry),
path=path,
item_to_value=_item_to_dataset,
items_key="datasets",
page_token=page_token,
max_results=max_results,
extra_params=extra_params,
)
|
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"def",
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",",
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"=",
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",",
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"# and converting it into a string here.",
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",",
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",",
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"page_token",
",",
"max_results",
"=",
"max_results",
",",
"extra_params",
"=",
"extra_params",
",",
")"
] |
List datasets for the project associated with this client.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets/list
Args:
project (str):
Optional. Project ID to use for retreiving datasets. Defaults
to the client's project.
include_all (bool):
Optional. True if results include hidden datasets. Defaults
to False.
filter (str):
Optional. An expression for filtering the results by label.
For syntax, see
https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets/list#filter.
max_results (int):
Optional. Maximum number of datasets to return.
page_token (str):
Optional. Token representing a cursor into the datasets. If
not passed, the API will return the first page of datasets.
The token marks the beginning of the iterator to be returned
and the value of the ``page_token`` can be accessed at
``next_page_token`` of the
:class:`~google.api_core.page_iterator.HTTPIterator`.
retry (google.api_core.retry.Retry):
Optional. How to retry the RPC.
Returns:
google.api_core.page_iterator.Iterator:
Iterator of
:class:`~google.cloud.bigquery.dataset.DatasetListItem`.
associated with the project.
|
[
"List",
"datasets",
"for",
"the",
"project",
"associated",
"with",
"this",
"client",
"."
] |
85e80125a59cb10f8cb105f25ecc099e4b940b50
|
https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/client.py#L229-L291
|
train
|
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