gspread-models 1.0

Model based ORM interface into Google Sheets, using the gspread package.

gspread-models-py

Model based ORM interface into Google Sheets, using the gspread package.

Installation

Install this package from PyPI:

pip install gspread_models

Setup

Follow the Google Cloud Setup Guide to setup a Google Cloud project with a service account access to the Google Sheets API, obtain a service account credentials JSON file.

Follow the Google Sheets Setup Guide to setup a Google Sheet document and share editor access with your service account.

Usage Example

Sheet Setup

To setup this example, create a sheet called "products", and populate the first row with the following column headers (including metadata columns):

• id
• name
• description
• price
• url
• created_at

The column names and order must match the COLUMNS defined in the model class (see below). The id column should be first, and the timestamps (created_at) should be last.

Model Class Definition

Define your own light-weight class that inherits from the base model:

from gspread_models.base import BaseModel

# your custom model class, which inherits from BaseModel:
class Product(BaseModel):

    # the name of the sheet to use for this model class:
    SHEET_NAME = "products"

    # the model-specific columns (excluding metadata columns):
    COLUMNS = ["name", "description", "price", "url"]

In addition to the model-specific COLUMNS list, the base model will manage metadata columns, including:

• an auto-incrementing integer (id), which acts as the record's unique identifier
• auto-updating timestamps (created_at)

Query Interface

The base model provides an intuitive query interface.

Find All Records

Find all records from the sheet:

Product.all()

Find Record

Find a record given its unique identifier:

Product.find(1)

Filtering Records

Filter records based on class-specific attribute values (returns records that match ALL criteria):

Product.where(name="Strawberries")

Product.where(name="Strawberries", price=1000)

Creating Records

If the model class defines SEEDS as a list of dictionaries (see product.py example), you can populate the sheet with these initial values:

Product.seed()

Creating and persisting new records:

Product.create(dict(name="Blueberries", price=3.99, description="organic blues"))

Product.create_all([{"name":"Product X"}, {"name":"Product Y"}])

Destroying Records

Clear the sheet by removing all records:

Product.destroy_all()

Contributing

License