Metadata-Version: 2.4
Name: brownllama
Version: 0.1.25
Summary: Standard PIP Package for GCP integration apps.
Author-email: Sanu Maharjan <inbox.sanu@gmail.com>
License-File: LICENSE
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Requires-Python: >=3.12
Requires-Dist: google-cloud-bigquery>=3.34
Requires-Dist: google-cloud-secret-manager>=2.23.3
Requires-Dist: google-cloud-storage>=3.1
Requires-Dist: pandas>=2.2.3
Requires-Dist: pydantic>=2.11.5
Description-Content-Type: text/markdown

# brownLlama Pip Package

## Overview

`brownllama-pip` (or `brownllama` when imported in Python) is a utility library designed to provide common functionalities and standardized components for VNP's Python projects. It aims to reduce code duplication and promote best practices across different projects.

## Modules

The package currently includes the following modules:

- **bigquery.py**:
  - Provides the `BigQueryController` class for simplified interaction with Google BigQuery.
  - Supports creating tables, checking table existence, loading data from JSON, loading data from Google Cloud Storage (GCS), and executing queries.
  - Offers methods for schema inference from JSON data and efficient data loading via GCS staging.

- **logger.py**:
  - Provides the `get_logger` function for obtaining configured logger instances.
  - Standardizes logging format and setup across projects.
  - Configures both root logger and common third-party library loggers to ensure consistent logging behavior.

- **secret_manager.py**
  - Provides the `get_secret` function for retrieving secrets from Google Secret Manager.
  - Enables to get, create, delete and lists the secrets.

- **storage.py**:
  - Provides the `StorageManager` class for managing Google Cloud Storage operations.
  - Supports uploading data (dictionaries, lists of dictionaries, Pandas DataFrames) to GCS as JSON files.
  - Includes functionality for deleting files from GCS.

## Building and Publishing

To build and publish the package, follow these steps:

1.  Install build dependencies:

    ```bash
    uv add build twine
    ```

2.  Change the version number in `pyproject.toml` file

    ```toml
    version = "0.1.XXX"
    ```

3.  Build the package:

    ```bash
    uv build
    ```

4.  Publish the package in PyPI

    ```bash
    uvx twine upload --verbose dist/*
    ```

    NOTE: PyPI is public and should not be used for sensitive information. Also, you need to setup `~/.pypirc` with your PyPI credentials.

## Usage

After installation, you can import and use the modules and classes provided by `brownllama` in your Python projects.

**Example (using BigQueryController):**

```python
from brownllama.bigquery import BigQueryController


bq_controller = BigQueryController(bigquery_payload=bigquery_payload, key_path=key_path)

# Example: Export JSON data to BigQuery via GCS
gcs_uri = bq_controller.export_to_bq_via_gcs(json_data=data)
print(f"Data loaded to BigQuery via GCS: {gcs_uri}")
```

Refer to the individual module files (`bigquery.py`, `logger.py`, `storage.py`) for detailed class and function documentation and usage examples.
