lighthouse-private-markets-sdk 0.1.1

Python SDK for Lighthouse Private Markets API with PostgREST-style querying

Lighthouse API Client (Python)

Simple and powerful Python client for interacting with the Lighthouse API. Perfect for managing and analyzing your startup's data.

Features

• 🚀 Easy to use API
• 📦 Built on Supabase
• 💪 Python support
• ⚡ Lightweight

Installation

Using pip:

pip install lighthouse-private-markets-sdk

Quick Start

Importing and Initialization

from lighthouse import Lighthouse

# Initialize the client
lighthouse = Lighthouse('your-api-key')

Fetching Startups

def get_startups():
    try:
        response = lighthouse.from_('startups').select('*').limit(10).execute()
        if response.error:
            raise Exception(response.error)
        print("Startups:", response.data)
    except Exception as err:
        print("Error:", err)

get_startups()

Common Query Examples

Select Single Record

# Get a specific startup
response = lighthouse.from_('startups').select('*').eq('id', 123).single().execute()

Filter Records

# Get all startups valued over $1M
response = lighthouse.from_('startups').select('name, valuation').gte('valuation', 1000000).order('valuation', ascending=False).execute()

Select with Relationships

# Get startups with their founders
response = lighthouse.from_('startups').select('name, founders (name, role)').execute()

Pagination

# Get 10 records with offset
response = lighthouse.from_('startups').select('*').range(0, 9).execute()

Full Text Search

# Search startups by name
response = lighthouse.from_('startups').select('*').text_search('name', 'tech').execute()

API Reference

Initialization Options

lighthouse = Lighthouse('your-api-key', url='https://your-custom-url.com')  # Optional

Available Methods

• select(): Choose fields to return
• single(): Return a single record
• eq(): Equal to
• neq(): Not equal to
• gt(): Greater than
• gte(): Greater than or equal to
• lt(): Less than
• lte(): Less than or equal to
• like(): Pattern matching
• ilike(): Case insensitive pattern matching
• in_(): In array
• order(): Order results
• limit(): Limit number of records
• range(): Select range of records

Error Handling

response = lighthouse.from_('startups').select('*').execute()
if response.error:
    if response.error.code == 'PGRST116':
        print('Invalid API key')
    elif response.error.code == '42P01':
        print('Table does not exist')
    else:
        print('An error occurred:', response.error)
    exit()

# Process your data
print(response.data)

Best Practices

1. Always check for errors before using data
2. Use try/except blocks for error handling
3. Limit your selections to required fields only
4. Use pagination for large datasets
5. Cache results when appropriate

Support

• 📧 Email: [e-mail]

License

MIT License - see the LICENSE file for details.