gspreadplusplus 2.0.1

Enhanced Google Sheets operations with advanced data type handling

gspreadplusplus

A Python library that enhances Google Sheets operations with additional functionality and improved data type handling.

Features

• Transfer Spark DataFrames to Google Sheets with proper type conversion
• Intelligent handling of various data types (numbers, dates, timestamps, etc.)
• Preserve or update sheet headers
• Selective column clearing options
• Automatic date formatting
• Sheet dimension management

Installation

pip install gspreadplusplus

Requirements

• Python 3.7+
• gspread
• pyspark
• google-auth

Usage

Basic DataFrame Export

from gspreadplusplus import GPP
from pyspark.sql import SparkSession

# Initialize Spark and create a DataFrame
spark = SparkSession.builder.appName("example").getOrCreate()
df = spark.createDataFrame([
    ("2024-01-01", 100, "Complete"),
    ("2024-01-02", 150, "Pending")
], ["date", "amount", "status"])

# Your Google Sheets credentials
creds_json = {
    "type": "service_account",
    # ... rest of your service account credentials
}

# Export DataFrame to Google Sheets
GPP.df_to_sheets(
    df=df,
    spreadsheet_id="your_spreadsheet_id",
    sheet_name="Sheet1",
    creds_json=creds_json
)

Advanced Options

GPP.df_to_sheets(
    df=df,
    spreadsheet_id="your_spreadsheet_id",
    sheet_name="Sheet1",
    creds_json=creds_json,
    english_locale=True,  # Use '.' as decimal separator
    keep_header=True,     # Preserve existing header row
    erase_whole=False     # Clear only necessary columns
)

Data Type Support

• Strings
• Integers (regular, long, bigint)
• Floating point numbers (double, float)
• Decimals
• Dates
• Timestamps
• Booleans

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.