Python hello world

This example is a "hello world" application, written in Python, that illustrates how to do the following:

• Set up authentication.
• Connect to a Bigtable instance.
• Create a new table.
• Write data to the table.
• Read the data back.
• Delete the table.

The Python client library for Bigtable offers two APIs, asyncio and a synchronous API. If your application is asynchronous, use asyncio.

Set up authentication

To use the Python samples on this page in a local development environment, install and initialize the gcloud CLI, and then set up Application Default Credentials with your user credentials.

1. Install the Google Cloud CLI.

2. To initialize the gcloud CLI, run the following command:

   gcloud init

3. If you're using a local shell, then create local authentication credentials for your user account:

   gcloud auth application-default login

   You don't need to do this if you're using Cloud Shell.

For more information, see Set up authentication for a local development environment.

Run the sample

This example uses the Bigtable package of the Cloud Client Libraries for Python to communicate with Bigtable. The Bigtable package is the best choice for new applications. If you need to move an existing HBase workload to Bigtable, see the "hello world" example that uses the HappyBase package.

To run this sample program, follow the instructions for the sample on GitHub.

Use the Cloud Client Libraries with Bigtable

The sample application connects to Bigtable and demonstrates some operations.

Install and import the client library

Use PIP to install the required Python packages into a virtualenv environment. The sample includes a requirements file defining the needed packages.

google-cloud-bigtable==2.25.0
google-cloud-core==2.4.1

Import the modules.

Asyncio

To learn how to install and use the client library for Bigtable, see Bigtable client libraries.

To authenticate to Bigtable, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

from google.cloud import bigtable
from google.cloud.bigtable.data import row_filters

Sync

To learn how to install and use the client library for Bigtable, see Bigtable client libraries.

To authenticate to Bigtable, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

import datetime

from google.cloud import bigtable
from google.cloud.bigtable import column_family
from google.cloud.bigtable import row_filters

Connect to Bigtable

Connect to Bigtable using a bigtable.Client.

Asyncio

To learn how to install and use the client library for Bigtable, see Bigtable client libraries.

To authenticate to Bigtable, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

client = bigtable.data.BigtableDataClientAsync(project=project_id)
table = client.get_table(instance_id, table_id)

Sync

To learn how to install and use the client library for Bigtable, see Bigtable client libraries.

To authenticate to Bigtable, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

# The client must be created with admin=True because it will create a
# table.
client = bigtable.Client(project=project_id, admin=True)
instance = client.instance(instance_id)

Create a table

Instantiate a table object using Instance.table(). Create a column family and set its garbage collection policy, then pass the column family to Table.create() to create the table.

Note: Columns that are related to one another are typically grouped into a column family. For more information about column families, see the Bigtable storage model. The async client only supports Data API. Table creation is an admin operation and uses the regular admin client.

print("Creating the {} table.".format(table_id))
table = instance.table(table_id)

print("Creating column family cf1 with Max Version GC rule...")
# Create a column family with GC policy : most recent N versions
# Define the GC policy to retain only the most recent 2 versions
max_versions_rule = bigtable.column_family.MaxVersionsGCRule(2)
column_family_id = "cf1"
column_families = {column_family_id: max_versions_rule}
if not table.exists():
    table.create(column_families=column_families)
else:
    print("Table {} already exists.".format(table_id))

Write rows to a table

Loop through a list of greeting strings to create some new rows for the table. In each iteration, use Table.row() to define a row and assign it a row key; call Row.set_cell() to set a value for the current cell; and append the new row to an array of rows. Finally, call Table.mutate_rows() to add the rows to the table.

Asyncio

To learn how to install and use the client library for Bigtable, see Bigtable client libraries.

To authenticate to Bigtable, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

print("Writing some greetings to the table.")
greetings = ["Hello World!", "Hello Cloud Bigtable!", "Hello Python!"]
mutations = []
column = "greeting"
for i, value in enumerate(greetings):
    # Note: This example uses sequential numeric IDs for simplicity,
    # but this can result in poor performance in a production
    # application.  Since rows are stored in sorted order by key,
    # sequential keys can result in poor distribution of operations
    # across nodes.
    #
    # For more information about how to design a Bigtable schema for
    # the best performance, see the documentation:
    #
    #     https://cloud.google.com/bigtable/docs/schema-design
    row_key = "greeting{}".format(i).encode()
    row_mutation = bigtable.data.RowMutationEntry(
        row_key, bigtable.data.SetCell(column_family_id, column, value)
    )
    mutations.append(row_mutation)
await table.bulk_mutate_rows(mutations)

Sync

To learn how to install and use the client library for Bigtable, see Bigtable client libraries.

To authenticate to Bigtable, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

print("Writing some greetings to the table.")
greetings = ["Hello World!", "Hello Cloud Bigtable!", "Hello Python!"]
rows = []
column = "greeting".encode()
for i, value in enumerate(greetings):
    # Note: This example uses sequential numeric IDs for simplicity,
    # but this can result in poor performance in a production
    # application.  Since rows are stored in sorted order by key,
    # sequential keys can result in poor distribution of operations
    # across nodes.
    #
    # For more information about how to design a Bigtable schema for
    # the best performance, see the documentation:
    #
    #     https://cloud.google.com/bigtable/docs/schema-design
    row_key = "greeting{}".format(i).encode()
    row = table.direct_row(row_key)
    row.set_cell(
        column_family_id, column, value, timestamp=datetime.datetime.utcnow()
    )
    rows.append(row)
table.mutate_rows(rows)

Create a filter

Before you read the data that you wrote, create a filter using row_filters.CellsColumnLimitFilter() to limit the data that Bigtable returns. This filter tells Bigtable to return only the most recent cell in each column, even if the table contains older cells that haven't been removed yet during garbage collection.

Asyncio

To learn how to install and use the client library for Bigtable, see Bigtable client libraries.

To authenticate to Bigtable, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

# Create a filter to only retrieve the most recent version of the cell
# for each column across entire row.
row_filter = bigtable.data.row_filters.CellsColumnLimitFilter(1)

Sync

To learn how to install and use the client library for Bigtable, see Bigtable client libraries.

To authenticate to Bigtable, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

row_filter = bigtable.row_filters.CellsColumnLimitFilter(1)

Read a row by its row key

Call the table's Table.read_row() method to get a reference to the row with a specific row key, passing in the key and the filter, to get one version of each value in that row.

Asyncio

To learn how to install and use the client library for Bigtable, see Bigtable client libraries.

To authenticate to Bigtable, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

print("Getting a single greeting by row key.")
key = "greeting0".encode()

row = await table.read_row(key, row_filter=row_filter)
cell = row.cells[0]
print(cell.value.decode("utf-8"))

Sync

To learn how to install and use the client library for Bigtable, see Bigtable client libraries.

To authenticate to Bigtable, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

print("Getting a single greeting by row key.")
key = "greeting0".encode()

row = table.read_row(key, row_filter)
cell = row.cells[column_family_id][column][0]
print(cell.value.decode("utf-8"))

Scan all table rows

Use Table.read_rows() to read a range of rows from a table.

Asyncio

To learn how to install and use the client library for Bigtable, see Bigtable client libraries.

To authenticate to Bigtable, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

print("Scanning for all greetings:")
query = bigtable.data.ReadRowsQuery(row_filter=row_filter)
async for row in await table.read_rows_stream(query):
    cell = row.cells[0]
    print(cell.value.decode("utf-8"))

Sync

To learn how to install and use the client library for Bigtable, see Bigtable client libraries.

To authenticate to Bigtable, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

print("Scanning for all greetings:")
partial_rows = table.read_rows(filter_=row_filter)

for row in partial_rows:
    cell = row.cells[column_family_id][column][0]
    print(cell.value.decode("utf-8"))

Delete a table

Delete a table with Table.delete().

Note: The async client only supports the Data API. Table creation is an admin operation and uses the regular admin client.

print("Deleting the {} table.".format(table_id))
table.delete()

Put it all together

Here is the full example without comments.

Asyncio

To learn how to install and use the client library for Bigtable, see Bigtable client libraries.

To authenticate to Bigtable, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

"""Demonstrates how to connect to Cloud Bigtable and run some basic operations with the async APIs

Prerequisites:

- Create a Cloud Bigtable instance.
  https://cloud.google.com/bigtable/docs/creating-instance
- Set your Google Application Default Credentials.
  https://developers.google.com/identity/protocols/application-default-credentials
"""

import argparse
import asyncio
from ..utils import wait_for_table

from google.cloud import bigtable
from google.cloud.bigtable.data import row_filters

row_filters


async def main(project_id, instance_id, table_id):
    client = bigtable.data.BigtableDataClientAsync(project=project_id)
    table = client.get_table(instance_id, table_id)

    from google.cloud.bigtable import column_family

    print("Creating the {} table.".format(table_id))
    admin_client = bigtable.Client(project=project_id, admin=True)
    admin_instance = admin_client.instance(instance_id)
    admin_table = admin_instance.table(table_id)

    print("Creating column family cf1 with Max Version GC rule...")
    max_versions_rule = column_family.MaxVersionsGCRule(2)
    column_family_id = "cf1"
    column_families = {column_family_id: max_versions_rule}
    if not admin_table.exists():
        admin_table.create(column_families=column_families)
    else:
        print("Table {} already exists.".format(table_id))

    try:
        wait_for_table(admin_table)
        print("Writing some greetings to the table.")
        greetings = ["Hello World!", "Hello Cloud Bigtable!", "Hello Python!"]
        mutations = []
        column = "greeting"
        for i, value in enumerate(greetings):
            row_key = "greeting{}".format(i).encode()
            row_mutation = bigtable.data.RowMutationEntry(
                row_key, bigtable.data.SetCell(column_family_id, column, value)
            )
            mutations.append(row_mutation)
        await table.bulk_mutate_rows(mutations)

        row_filter = bigtable.data.row_filters.CellsColumnLimitFilter(1)

        print("Getting a single greeting by row key.")
        key = "greeting0".encode()

        row = await table.read_row(key, row_filter=row_filter)
        cell = row.cells[0]
        print(cell.value.decode("utf-8"))

        print("Scanning for all greetings:")
        query = bigtable.data.ReadRowsQuery(row_filter=row_filter)
        async for row in await table.read_rows_stream(query):
            cell = row.cells[0]
            print(cell.value.decode("utf-8"))
    finally:
        print("Deleting the {} table.".format(table_id))
        admin_table.delete()


if __name__ == "__main__":
    parser = argparse.ArgumentParser(
        description=__doc__, formatter_class=argparse.ArgumentDefaultsHelpFormatter
    )
    parser.add_argument("project_id", help="Your Cloud Platform project ID.")
    parser.add_argument(
        "instance_id", help="ID of the Cloud Bigtable instance to connect to."
    )
    parser.add_argument(
        "--table", help="Table to create and destroy.", default="Hello-Bigtable"
    )

    args = parser.parse_args()
    asyncio.run(main(args.project_id, args.instance_id, args.table))

Sync

To learn how to install and use the client library for Bigtable, see Bigtable client libraries.

To authenticate to Bigtable, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

"""Demonstrates how to connect to Cloud Bigtable and run some basic operations.

Prerequisites:

- Create a Cloud Bigtable instance.
  https://cloud.google.com/bigtable/docs/creating-instance
- Set your Google Application Default Credentials.
  https://developers.google.com/identity/protocols/application-default-credentials
"""

import argparse
from ..utils import wait_for_table

import datetime

from google.cloud import bigtable
from google.cloud.bigtable import column_family
from google.cloud.bigtable import row_filters


row_filters
column_family


def main(project_id, instance_id, table_id):
    client = bigtable.Client(project=project_id, admin=True)
    instance = client.instance(instance_id)

    print("Creating the {} table.".format(table_id))
    table = instance.table(table_id)

    print("Creating column family cf1 with Max Version GC rule...")
    max_versions_rule = bigtable.column_family.MaxVersionsGCRule(2)
    column_family_id = "cf1"
    column_families = {column_family_id: max_versions_rule}
    if not table.exists():
        table.create(column_families=column_families)
    else:
        print("Table {} already exists.".format(table_id))

    try:
        wait_for_table(table)

        print("Writing some greetings to the table.")
        greetings = ["Hello World!", "Hello Cloud Bigtable!", "Hello Python!"]
        rows = []
        column = "greeting".encode()
        for i, value in enumerate(greetings):
            row_key = "greeting{}".format(i).encode()
            row = table.direct_row(row_key)
            row.set_cell(
                column_family_id, column, value, timestamp=datetime.datetime.utcnow()
            )
            rows.append(row)
        table.mutate_rows(rows)

        row_filter = bigtable.row_filters.CellsColumnLimitFilter(1)

        print("Getting a single greeting by row key.")
        key = "greeting0".encode()

        row = table.read_row(key, row_filter)
        cell = row.cells[column_family_id][column][0]
        print(cell.value.decode("utf-8"))

        print("Scanning for all greetings:")
        partial_rows = table.read_rows(filter_=row_filter)

        for row in partial_rows:
            cell = row.cells[column_family_id][column][0]
            print(cell.value.decode("utf-8"))

    finally:
        print("Deleting the {} table.".format(table_id))
        table.delete()


if __name__ == "__main__":
    parser = argparse.ArgumentParser(
        description=__doc__, formatter_class=argparse.ArgumentDefaultsHelpFormatter
    )
    parser.add_argument("project_id", help="Your Cloud Platform project ID.")
    parser.add_argument(
        "instance_id", help="ID of the Cloud Bigtable instance to connect to."
    )
    parser.add_argument(
        "--table", help="Table to create and destroy.", default="Hello-Bigtable"
    )

    args = parser.parse_args()
    main(args.project_id, args.instance_id, args.table)