unique-quartr 0.2.3

Unique Quartr API client

Unique Quartr Connector

A Python connector library for the Quartr API, providing easy access to company events, documents, and financial data.

Features

• 🔍 Fetch company earnings calls and events
• 📄 Retrieve event documents (transcripts, reports, slides, etc.)
• 📝 Parse and export earnings call transcripts to markdown
• 🎯 Type-safe API with Pydantic models
• 🔄 Automatic pagination handling
• 📊 Support for multiple document and event types
• 🔐 Secure API key authentication with base64 encoding

Installation

poetry add unique_quartr

Or using pip:

pip install unique_quartr

Configuration

Environment Variables

Create a .env file in your project root with your Quartr API credentials:

# Base64-encoded JSON credentials
QUARTR_API_CREDS='xxxxxxxxxxx'
QUARTR_API_ACTIVATED_COMPANIES='["company_id_1", "company_id_2"]'

Note: The QUARTR_API_CREDS should be a base64-encoded JSON string containing:

{"api_key": "your_api_key_here", "valid_to": "2025-12-31"}

You can encode your credentials using:

import base64
import json

creds = {"api_key": "your_api_key_here", "valid_to": "2025-12-31"}
encoded = base64.b64encode(json.dumps(creds).encode()).decode()
print(encoded)

Test Environment

For testing, create tests/test.env:

QUARTR_API_CREDS='xxxxxxxxxxx'
QUARTR_API_ACTIVATED_COMPANIES='["test_company"]'

Quick Start

Basic Usage

from unique_quartr.service import QuartrService
from unique_quartr.constants.event_types import EventType
from unique_quartr.constants.document_types import DocumentType
from unique_toolkit._common.experimental.endpoint_requestor import RequestorType

# Initialize the service
service = QuartrService(
    company_id="your_company_id",
    requestor_type=RequestorType.REQUESTS,
)

# Define the event types you want to fetch
event_types = [EventType.EARNINGS_CALL]
event_ids = service.get_event_subtype_ids_from_event_types(event_types)

# Fetch company events
events = service.fetch_company_events(
    ticker="AAPL",
    exchange="NasdaqGS",
    country="US",
    event_ids=event_ids,
    start_date="2024-01-01",
    end_date="2024-12-31",
)

print(f"Found {len(events.data)} events")
for event in events.data:
    print(f"Event: {event.title} - {event.date}")

Fetching Documents

# Get event IDs from the events you fetched
event_ids = [event.id for event in events.data]

# Define document types you want
document_types = [DocumentType.TRANSCRIPT, DocumentType.SLIDES]
document_ids = service.get_document_ids_from_document_types(document_types)

# Fetch documents for these events
documents = service.fetch_event_documents(
    event_ids=event_ids,
    document_ids=document_ids,
)

print(f"Found {len(documents.data)} documents")
for doc in documents.data:
    print(f"Document: {doc.type_id} - {doc.file_url}")

Working with Earnings Call Transcripts

from unique_quartr.transcripts.earnings_call import QuartrEarningsCallTranscript

# Fetch transcript from Quartr URL
transcript_url = "https://quartr.com/transcript/12345.json"
transcript = QuartrEarningsCallTranscript.from_quartr_transcript_url(transcript_url)

# Or use async version
transcript = await QuartrEarningsCallTranscript.from_quartr_transcript_url_async(transcript_url)

# Export to markdown
markdown_content = transcript.to_markdown()
print(markdown_content)

# Access transcript data
print(f"Event ID: {transcript.event_id}")
print(f"Company ID: {transcript.company_id}")
print(f"Number of speakers: {transcript.transcript.number_of_speakers}")

# Iterate through paragraphs
for paragraph in transcript.transcript.paragraphs:
    speaker_name = transcript._get_speaker_name(paragraph.speaker)
    print(f"{speaker_name}: {paragraph.text[:100]}...")

Event Types

The library supports the following event types:

• Earnings Call: Q1, Q2, Q3, Q4, H1, H2
• Analyst Day
• Annual General Meeting: AGM, Scheme Meeting
• Business Combination
• C-level Sitdown: C-level Sitdown, CEO Sitdown
• Capital Markets Day
• Capital Raise
• Conference
• Extraordinary General Meeting
• FDA Announcement
• Fireside Chat
• Investor Day
• M&A Announcement
• Outlook / Guidance Update
• Partnerships / Collaborations: Partnership, Collaboration
• Product / Service Launch: Product Launch, Service Launch
• Slides: Investor Presentation, Corporate Presentation, Company Presentation
• Trading Update
• Update / Briefing: Status Update, Investor Update, ESG Update, Study Update, Study Result, KOL Event

Example: Getting Earnings Call Event IDs

from unique_quartr.constants.event_types import EventType

event_types = [EventType.EARNINGS_CALL]
event_ids = QuartrService.get_event_subtype_ids_from_event_types(event_types)
# Returns: [26, 27, 28, 29, 35, 36] (Q1, Q2, Q3, Q4, H1, H2)

Document Types

The library supports various document types:

• Slides 📊
• Report 📄
• Quarterly Report (10-Q) 📑
• Earnings Release (8-K) 📢
• Annual Report (10-K) 📘
• Annual Report (20-F) 📙
• Annual Report (40-F) 📕
• Earnings Release (6-K) 📣
• Transcript 🗒️
• Interim Report 📜
• Press Release 🗞️
• Earnings Release 💰
• In-house Transcript 🎤

Example: Getting Document Type Information

from unique_quartr.constants.document_types import DocumentType

doc_type = DocumentType.QUARTERLY_REPORT_10Q

print(doc_type.name)  # "Quarterly report"
print(doc_type.form)  # "10-Q"
print(doc_type.emoji)  # "📑"
print(doc_type.get_file_prefix())  # "Quarterly report (10-Q)"

Advanced Usage

Custom Pagination

Control pagination parameters for large datasets:

events = service.fetch_company_events(
    ticker="AAPL",
    exchange="NasdaqGS",
    country="US",
    event_ids=event_ids,
    limit=100,  # Items per page (max 500)
    max_iteration=10,  # Maximum number of pages
)

Filtering by Date Range

events = service.fetch_company_events(
    ticker="AAPL",
    exchange="NasdaqGS",
    country="US",
    event_ids=event_ids,
    start_date="2024-01-01T00:00:00Z",  # ISO format
    end_date="2024-03-31T23:59:59Z",
)

Fetching Multiple Event Types

from unique_quartr.constants.event_types import EventType

# Combine multiple event types
event_types = [
    EventType.EARNINGS_CALL,
    EventType.ANALYST_DAY,
    EventType.INVESTOR_DAY,
]

event_ids = QuartrService.get_event_subtype_ids_from_event_types(event_types)

events = service.fetch_company_events(
    ticker="AAPL",
    exchange="NasdaqGS",
    country="US",
    event_ids=event_ids,
)

API Reference

QuartrService

class QuartrService:
    def __init__(
        self,
        *,
        company_id: str,
        requestor_type: RequestorType,
    ):
        """
        Initialize the Quartr service.
        
        Args:
            company_id: Company identifier for API access
            requestor_type: Type of requestor (SYNC or ASYNC)
        """

Methods

fetch_company_events

# Method signature (overloaded)
def fetch_company_events(
    self,
    *,
    company_ids: list[int | float] | None = None,
    ticker: str | None = None,
    exchange: str | None = None,
    country: str | None = None,
    event_ids: list[int] | None = None,
    start_date: str | None = None,
    end_date: str | None = None,
    limit: int = 500,
    max_iteration: int = 20,
) -> EventResults:
    """
    Retrieve events for a given company.
    
    Args:
        company_ids: List of company IDs (alternative to ticker/exchange/country)
        ticker: Company ticker symbol (e.g., 'AAPL', 'AMZN')
        exchange: Exchange code (e.g., 'NasdaqGS', 'NYSE')
        country: Country code (e.g., 'US', 'CA')
        event_ids: List of event type IDs to filter
        start_date: Optional start date in ISO format
        end_date: Optional end date in ISO format
        limit: Items per request (max 500)
        max_iteration: Maximum number of pagination iterations
    
    Returns:
        EventResults object with .data containing list of EventDto objects
        
    Note:
        Either company_ids OR (ticker, exchange, country) must be provided
    """

Example with company IDs:

events = service.fetch_company_events(
    company_ids=[4742, 5025],
    event_ids=event_ids,
    start_date="2024-01-01",
)

Example with ticker/exchange:

events = service.fetch_company_events(
    ticker="AAPL",
    exchange="NasdaqGS",
    country="US",
    event_ids=event_ids,
)

fetch_event_documents

def fetch_event_documents(
    self,
    event_ids: list[int],
    document_ids: list[int],
    limit: int = 500,
    max_iteration: int = 20,
) -> DocumentResults:
    """
    Retrieve documents for a list of events.
    
    Args:
        event_ids: List of event IDs
        document_ids: List of document type IDs to filter
        limit: Items per request (max 500)
        max_iteration: Maximum number of pagination iterations
    
    Returns:
        DocumentResults object with .data containing list of DocumentDto objects
    """

Static Methods

@staticmethod
def get_event_subtype_ids_from_event_types(
    event_types: list[EventType],
) -> list[int]:
    """
    Convert EventType enums to Quartr API event subtype IDs.
    
    Args:
        event_types: List of EventType enums
    
    Returns:
        List of event subtype IDs
    """

@staticmethod
def get_document_ids_from_document_types(
    document_types: list[DocumentType],
) -> list[int]:
    """
    Convert DocumentType enums to Quartr API document type IDs.
    
    Args:
        document_types: List of DocumentType enums
    
    Returns:
        List of document type IDs
    """

Response Models

EventResults

Wrapper object returned by fetch_company_events:

class EventResults:
    data: list[EventDto]  # Access events via .data attribute

EventDto

class EventDto:
    company_id: float
    date: datetime
    id: float
    title: str
    type_id: float
    fiscal_year: float | None
    fiscal_period: str | None
    backlink_url: str
    updated_at: datetime
    created_at: datetime

DocumentResults

Wrapper object returned by fetch_event_documents:

class DocumentResults:
    data: list[DocumentDto]  # Access documents via .data attribute

DocumentDto

class DocumentDto:
    company_id: float | None
    event_id: float | None
    file_url: str
    id: float
    type_id: float
    updated_at: datetime
    created_at: datetime

QuartrEarningsCallTranscript

Complete earnings call transcript with speaker mapping:

class QuartrEarningsCallTranscript:
    version: str
    event_id: int
    company_id: int
    transcript: Transcript
    speaker_mapping: list[SpeakerMapping]
    
    # Methods
    def to_markdown(self) -> str
    @classmethod
    def from_quartr_transcript_url(cls, url: str) -> Self
    @classmethod
    async def from_quartr_transcript_url_async(cls, url: str) -> Self

Testing

Run the test suite:

poetry run pytest

Run with coverage:

poetry run pytest --cov=unique_quartr --cov-report=html

Run specific test files:

poetry run pytest tests/test_service.py
poetry run pytest tests/test_constants.py

Error Handling

The library will raise exceptions in the following cases:

• Missing API Credentials: ValueError when QUARTR_API_CREDS is not set
• Company Not Activated: ValueError when the company_id is not in QUARTR_API_ACTIVATED_COMPANIES
• API Errors: Various HTTP errors from the Quartr API

Example Error Handling

from unique_quartr.service import QuartrService

try:
    service = QuartrService(
        company_id="invalid_company",
        requestor_type=RequestorType.SYNC,
    )
except ValueError as e:
    print(f"Configuration error: {e}")

Development

Setup Development Environment

# Clone the repository
git clone <repository_url>
cd unique_quartr

# Install dependencies
poetry install

# Run linting
poetry run ruff check .

# Run formatting
poetry run ruff format .

Project Structure

unique_quartr/
├── constants/
│   ├── document_types.py    # Document type enums and mappings
│   └── event_types.py        # Event type enums and mappings
├── endpoints/
│   ├── api.py                # API endpoint definitions
│   └── schemas.py            # Pydantic models for API requests/responses
├── transcripts/
│   └── earnings_call/
│       ├── __init__.py       # Transcript module exports
│       ├── schema.py          # Transcript data models
│       └── transcript_template.j2  # Jinja2 template for markdown export
├── service.py                # Main service class
└── settings.py               # Configuration and settings

License

Proprietary

Authors

• Rami Azouz [e-mail]

Support

For issues and questions, please contact the maintainers or refer to the Quartr API documentation.

Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[0.2.3] - 2026-01-13

• Add deptry to dev dependencies for CI dependency checks

[0.2.2] - 2026-01-05

• Bump unique_toolkit version

[0.2.1] - 2025-11-18

• Fix to use correct field (query_params_dump_options) for model_params_dump_options

[0.2.0] - 2025-11-18

• Add QuartrEarningsCallTranscript class for parsing and exporting earnings call transcripts to markdown
• Add support for fetching events by company_ids as alternative to ticker/exchange/country
• Change fetch_company_events() to return EventResults object with .data attribute
• Change fetch_event_documents() to return DocumentResults object with .data attribute
• Change API credentials to require base64 encoding in environment variables
• Update to unique-toolkit v1.27.0 experimental endpoint builder
• Add jinja2 dependency for template rendering
• Fix credential validation and datetime serialization

[0.1.0] - 2025-08-18

• Initial release of unique_quartr