google-cloud-helper 0.1.4

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google-cloud-helper

This repository contains common functions for easy access to Google Cloud Infrastructure, such as Big Query or Google buckets.

Example Usage

from google_cloud_helper.BigQueryHelper import BigQueryHelper
from google_cloud_helper.GoogleBucketHelper import GoogleBucketHelper
from google_cloud_helper.SecretManagerHelper import SecretManagerHelper

# BigQuery
bq_helper = BigQueryHelper("your-gcp-project-id")
exists = bq_helper.table_exists("your-gcp-project-id.dataset.table")
print(f"Table exists: {exists}")

# Google Cloud Storage
bucket_helper = GoogleBucketHelper("your-gcp-project-id")
bucket_exists = bucket_helper.bucket_exists("your-bucket-name")
print(f"Bucket exists: {bucket_exists}")

# Secret Manager
secret_helper = SecretManagerHelper()
my_secret = secret_helper.get_secret("your-gcp-project-id", "your-secret-id")
print("Successfully retrieved secret!")

Available Functions

BigQueryHelper

Function	Description
table_exists(table_id)	Checks if a specific BigQuery table exists.
create_dataset(dataset_id)	Creates a new BigQuery dataset if it doesn't already exist.
delete_table(table_id)	Deletes a BigQuery table.
create_table_from_df(...)	Creates and populates a table from a pandas DataFrame, with options for partitioning and clustering.
upload_df_to_table(table_id, df)	Appends a pandas DataFrame to an existing BigQuery table.
incremental_insert_with_deduplication(...)	Inserts new rows from a DataFrame, avoiding duplicates based on a unique key.
generate_bigquery_schema(df)	Infers a BigQuery schema from a pandas DataFrame.

GoogleBucketHelper

Function	Description
download_as_text(bucket, path)	Downloads a file from a Google Cloud Storage bucket as text.
bucket_exists(bucket_name)	Checks if a specific Google Cloud Storage bucket exists.

SecretManagerHelper

Function	Description
get_secret(project_id, secret_id)	Retrieves the latest version of a secret from Secret Manager.

Testing

To run the tests, execute the following command:

uv run pytest

Build and Publish

To build and publish the package to PyPI, execute the following command:

uv build
uv publish --token <pypi-token>