gcloudy 3.0.1

A more intuitive approach to using Google's existing Google Cloud Platform (GCP) framework of cloud services in Python

LEGAL DISCLAIMER

Neither this package nor the author, tomathon, are affiliated with or endorsed by Google. The inclusion of Google trademark(s), if any, upon this webpage is solely to identify Google contributors, goods, or services, and not for commercial purposes.

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ABOUT

gcloudy is a wrapper for Google's GCP Python package(s) that aims to make interacting with GCP and its services more intuitive, especially for new GCP users. In doing so, it adheres to pandas-like syntax for function/method calls.

The gcloudy package is not meant to be a replacement for GCP power-users, but rather an alternative for GCP users who are interested in using Python in GCP to interact with certain GCP services, especially BigQuery.

The gcloudy package is built on top of canonical Google Python packages(s) without any alteration to Google's base code.

Documentation can be found here

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QUICKSTART

gcloudy is installed using pip with the command:

$ pip install gcloudy

Once installed, the main BigQuery class can be imported from the main GoogleCloud module with:

from gcloudy.GoogleCloud import BigQuery

The bq object is initialized using your GCP Project:

bq = BigQuery(project_id = "gcp-project-name")

To initialize using a specific service account key, pass the full key path to your key.json:

bq = BigQuery(
    project_id = "gcp-project-name",
    service_acct_key_path = "/full/path/to/your/service/account/key.json"
)

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COMMON METHODS

NOTE: See docs for full documentation

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bq.read_bigquery

Read an existing BigQuery table into a DataFrame

read_bigquery(bq_dataset_dot_table = None, date_cols = [], preview_top = None, to_verbose = True)

• bq_dataset_dot_table : the "dataset-name.table-name" path of the existing BigQuery table
• date_cols : [optional] column(s) passed inside a list that should be parsed as dates
• preview_top : [optional] only read in the top N rows
• to_verbose : should info be printed? defaults to True
• use_polars : should a polars DataFrame be returned instead of a pandas DataFrame? Defaults to False

EX:

my_table = bq.read_bigquery("my_bq_dataset.my_bq_table")
my_table = bq.read_bigquery("my_bq_dataset.my_bq_table", date_cols = ['date'])
my_table = bq.read_bigquery("my_bq_dataset.my_bq_table", use_polars = True)

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bq.read_custom_query

Read in a custom BigQuery SQL query into a DataFrame

read_custom_query(custom_query, to_verbose = True)

• custom_query : the custom BigQuery SQL query that will produce a table to be read into a DataFrame
• to_verbose : should info be printed? defaults to True
• use_polars : should a polars DataFrame be returned instead of a pandas DataFrame? Defaults to False

EX:

my_custom_table = bq.read_custom_query("""
    SELECT
        date,
        sales,
        products
    FROM
        my_bq_project_id.my_bq_dataset.my_bq_table
    WHERE
        sales_month = 'June'
""")

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bq.write_bigquery

Write a DataFrame to a BigQuery table

write_bigquery(df, bq_dataset_dot_table = None, use_schema = None, append_to_existing = False, to_verbose = True)

• df : the DataFrame to be written to a BigQuery table
• bq_dataset_dot_table : the "dataset-name.table-name" path of the existing BigQuery table
• use_schema : [optional] a custom schema for the BigQuery table. NOTE: see bq.guess_schema below
• append_to_existing : should the DataFrame be appended to an existing BigQuery table? defaults to False (create new / overwrite)
• to_verbose : should info be printed? defaults to True

EX:

bq.write_bigquery(my_data, "my_bq_dataset.my_data")
bq.write_bigquery(my_data, "my_bq_dataset.my_data", append_to_existing = True)

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bq.send_query

Send a custom SQL query to BigQuery. Process is carried out within BigQuery. Nothing is returned

send_query(que, to_verbose = True)

• que : the custom SQL query to be sent and carried out within BigQuery
• to_verbose : should info be printed? defaults to True

EX:

bq.send_query("""
    CREATE TABLE my_bq_project_id.my_bq_dataset.my_new_bq_table AS 
    (
        SELECT
            date,
            sales,
            products
        FROM
            my_bq_project_id.my_bq_dataset.my_bq_table
        WHERE
            sales_month = 'June'
    )
""")

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