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samples/insert_data_sample.py

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from sample_helper import run_sample
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from model import Singer, Album, Track
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# Shows how to insert data using SQLAlchemy, including relationships that are
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# defined both as foreign keys and as interleaved tables.
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def insert_data():

samples/insert_or_ignore_sample.py

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from sample_helper import run_sample
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from model import Singer
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# Shows how to use insert-or-ignore using SQLAlchemy and Spanner.
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def insert_or_ignore_sample():
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engine = create_engine(

samples/insert_or_update_sample.py

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from sample_helper import run_sample
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from model import Singer
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# Shows how to use insert-or-update using SQLAlchemy and Spanner.
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def insert_or_update_sample():
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engine = create_engine(

samples/interleaved_table_sample.py

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from sample_helper import run_sample
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from model import Singer, Album, Track
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# Shows how INTERLEAVE IN PARENT can be used in SQLAlchemy.
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# INTERLEAVE IN PARENT can be modelled as if it were a normal relationship
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# in SQLAlchemy. SQLAlchemy can also generate the correct DDL for this.

samples/parse_json_sample.py

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from sample_helper import run_sample
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from model import Venue
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# Shows how to use the PARSE_JSON function in Spanner using SQLAlchemy.
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def parse_json_sample():
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engine = create_engine(

samples/partitioned_dml_sample.py

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from sample_helper import run_sample
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# Shows how to use Partitioned DML using SQLAlchemy and Spanner.
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def partitioned_dml_sample():
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engine = create_engine(

samples/pickle_type_sample.py

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from sample_helper import run_sample
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from model import Singer
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# Shows how to use PickleType with Spanner.
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def pickle_type():
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engine = create_engine(

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