PinappleClient 1.4.1

Client for interacting with Pinapple

🍍 PinappleClient 🍍

A Python client for interacting with the Pinapple encryption API.

🚀 Features

• Authentication 🔐 - Token-based API authentication with automatic refresh
• Flexible Encryption ⚡ - Support for strict and loose encryption modes
• Fallback Strategy 🔄 - Automatic fallback from strict to loose encryption
• Smart Token Management ⏰ - Configurable token refresh with expiration handling
• Robust Network Handling 🔁 - Automatic retries with configurable backoff for network issues

📦 Installation

pip install PinappleClient

🔧 Quick Start

from pinapple_client import PinappleClient

# Initialize client with automatic token refresh and network resilience
client = PinappleClient(
    user="your_username",
    password="your_password",
    api_url="https://api.pinapple.com",
    refresh_token_after_x_minutes=5,  # Refresh token 5 minutes before expiration
    timeout=30,                       # Request timeout in seconds
    max_retries=3,                    # Number of retry attempts
    backoff_base=2                    # Exponential backoff base (2s, 4s, 8s)
)

# Encrypt a single PIN
encrypted_pin = client.encrypt_pin_strict("123456")
print(f"Encrypted: {encrypted_pin}")

# Decrypt data
decrypted_pin = client.decrypt_pin(encrypted_data)
print(f"Decrypted: {decrypted_pin}")

📊 DataFrame Operations

encrypt_dataframe(df, column, strict=True, strict_then_loose=False) -> DataFrame

Encrypts an entire column in a pandas DataFrame.

import pandas as pd

df = pd.DataFrame({
    'id': [1, 2, 3],
    'pin': ['123456', '789012', '345678']
})

# Encrypt the 'pin' column
encrypted_df = client.encrypt_dataframe(df, 'pin', strict=True)

# Use fallback strategy
encrypted_df = client.encrypt_dataframe(df, 'pin', strict_then_loose=True)

Parameters:

• df: Input DataFrame
• column: Column name to encrypt
• strict: Use strict encryption (default: True)
• strict_then_loose: Enable fallback strategy (default: False)

🔒 Authentication & Token Management

The client automatically handles token management with intelligent refresh:

Automatic Token Refresh

• Requests a bearer token on first API call
• Caches the token for subsequent requests
• Automatically refreshes tokens before expiration based on configurable buffer time
• Handles long-running operations without token expiry issues

Token Configuration

# Refresh token 10 minutes before it expires
client = PinappleClient(..., refresh_token_after_x_minutes=10)

# Check token status
expiration = client.get_token_expiration()
should_refresh = client.should_refresh_token()

Token Utilities

• get_token_expiration() - Returns token expiration as datetime
• should_refresh_token() - Checks if token needs refresh based on buffer
• Automatic refresh during long DataFrame operations

Perfect for long-running encryption jobs - no manual token management required!

🔁 Network Resilience

The client includes robust network error handling for unreliable connections:

Automatic Retry Logic

• Connection errors (DNS resolution, network unreachable)
• Timeout errors (slow network responses)
• Request exceptions (various network issues)

Configurable Retry Parameters

client = PinappleClient(
    ...,
    timeout=45,        # Longer timeout for slow networks
    max_retries=5,     # More retry attempts
    backoff_base=3     # Aggressive backoff (3s, 9s, 27s, 81s, 243s)
)

Retry Behavior

• Exponential backoff: Wait time = backoff_base ^ (attempt + 1)
• Default settings: 3 retries with 2s, 4s, 8s delays
• Progress feedback: Logs each retry attempt with wait time
• Final failure: Clear error message after all retries exhausted

Ideal for corporate networks and VPN connections with intermittent connectivity issues!

📄 License

This project is licensed under the GPL-3.0 License.

🔗 Links

• Homepage
• Issues
• Pypi