Metadata-Version: 2.1
Name: gspreadplusplus
Version: 2.0.0
Summary: Enhanced Google Sheets operations with advanced data type handling
Home-page: https://github.com/daniel-simanek/gspreadplusplus
Author: Daniel Simanek
Author-email: daniel.simanek@decathlon.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Office/Business :: Financial :: Spreadsheet
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: google-auth (>=2.0.0)
Requires-Dist: gspread (>=5.0.0)
Requires-Dist: pandas (>=1.0.0)
Requires-Dist: pyspark (>=3.0.0)

# 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

```bash
pip install gspreadplusplus
```

## Requirements

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

## Usage

### Basic DataFrame Export

```python
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

```python
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.

