Bloomy (franccesco/bloomy-python)

Bloomy

https://github.com/franccesco/bloomy-python
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Bloomy is a Python SDK for interacting with the Bloom Growth API, providing easy access to users,...

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# Bloomy

Bloomy is a Python SDK for interacting with the Bloom Growth API, providing easy access to users, meetings, todos, goals, scorecards, issues, and headlines. It offers both synchronous and asynchronous clients with comprehensive Pydantic models for type-safe data handling.

The SDK supports multiple authentication methods including direct API key initialization, environment variables (BG_API_KEY), and configuration files. It features bulk operations for creating multiple resources efficiently, context manager support for proper connection handling, and a clean object-oriented interface organized around resource types (users, meetings, todos, goals, scorecards, issues, headlines).

## Client Initialization

The Client class is the main entry point for synchronous interactions with the Bloom Growth API. It automatically loads API keys from environment variables or configuration files if not provided directly.

```python
from bloomy import Client, Configuration

# Direct API key initialization
client = Client(api_key="your-api-key-here")

# Using environment variable BG_API_KEY
client = Client()

# Configure API key with username and password
config = Configuration()
config.configure_api_key("username", "password", store_key=True)
client = Client()

# Using context manager for automatic cleanup
with Client(api_key="your-api-key") as client:
    user = client.user.details()
    print(f"Hello, {user.name}")

# Custom base URL and timeout
client = Client(
    api_key="your-api-key",
    base_url="https://app.bloomgrowth.com/api/v1",
    timeout=60.0
)
```

## Async Client Initialization

The AsyncClient provides asynchronous access to all Bloom Growth API operations for better performance in async applications.

```python
import asyncio
from bloomy import AsyncClient

async def main():
    # Using async context manager (recommended)
    async with AsyncClient(api_key="your-api-key") as client:
        user = await client.user.details()
        meetings = await client.meeting.list()
        print(f"Hello {user.name}, you have {len(meetings)} meetings")

    # Without context manager
    client = AsyncClient(api_key="your-api-key")
    try:
        user = await client.user.details()
    finally:
        await client.close()

asyncio.run(main())
```

## User Operations

User operations provide methods to retrieve user details, search for users, list all users, and access direct reports and positions.

```python
from bloomy import Client

client = Client(api_key="your-api-key")

# Get current user details
user = client.user.details()
print(f"User: {user.name}, ID: {user.id}")

# Get specific user with additional details
user = client.user.details(
    user_id=123,
    include_direct_reports=True,
    include_positions=True
)
for report in user.direct_reports:
    print(f"Direct report: {report.name}")
for position in user.positions:
    print(f"Position: {position.name}")

# Get user with all details using shorthand
user = client.user.details(user_id=123, include_all=True)

# Search for users
results = client.user.search("john")
for result in results:
    print(f"Found: {result.name} ({result.email})")

# List all users
users = client.user.list()
for user in users:
    print(f"{user.name} - {user.position}")

# List all users including placeholders
users = client.user.list(include_placeholders=True)

# Get direct reports for a user
reports = client.user.direct_reports(user_id=123)

# Get positions for a user
positions = client.user.positions(user_id=123)
```

## Meeting Operations

Meeting operations allow listing, creating, deleting meetings, and accessing meeting details including attendees, issues, todos, and metrics.

```python
from bloomy import Client

client = Client(api_key="your-api-key")

# List all meetings for current user
meetings = client.meeting.list()
for meeting in meetings:
    print(f"Meeting: {meeting.name} (ID: {meeting.id})")

# List meetings for specific user
meetings = client.meeting.list(user_id=456)

# Get detailed meeting information
details = client.meeting.details(meeting_id=123)
print(f"Meeting: {details.name}")
print(f"Attendees: {len(details.attendees)}")
print(f"Issues: {len(details.issues)}")
print(f"Todos: {len(details.todos)}")

# Get meeting details including closed items
details = client.meeting.details(meeting_id=123, include_closed=True)

# Create a new meeting
result = client.meeting.create(
    title="Weekly Team Meeting",
    add_self=True,
    attendees=[456, 789]
)
print(f"Created meeting ID: {result['meeting_id']}")

# Delete a meeting
client.meeting.delete(meeting_id=123)

# Get meeting attendees
attendees = client.meeting.attendees(meeting_id=123)
for attendee in attendees:
    print(f"Attendee: {attendee.name}")

# Get meeting issues
issues = client.meeting.issues(meeting_id=123, include_closed=False)

# Get meeting todos
todos = client.meeting.todos(meeting_id=123, include_closed=False)

# Get meeting metrics
metrics = client.meeting.metrics(meeting_id=123)
for metric in metrics:
    print(f"{metric.title}: {metric.value}/{metric.target}")

# Bulk create meetings
result = client.meeting.create_many([
    {"title": "Weekly Team Meeting", "attendees": [2, 3]},
    {"title": "1:1 Meeting", "add_self": False}
])
print(f"Created {len(result.successful)} meetings")
for error in result.failed:
    print(f"Failed at index {error.index}: {error.error}")

# Bulk get meeting details
result = client.meeting.get_many([123, 456, 789])
for meeting in result.successful:
    print(f"{meeting.name} - {len(meeting.attendees)} attendees")
```

## Todo Operations

Todo operations provide CRUD functionality for managing todos, including creation, completion, updates, and bulk operations.

```python
from bloomy import Client

client = Client(api_key="your-api-key")

# List todos for current user
todos = client.todo.list()
for todo in todos:
    print(f"Todo: {todo.name}, Due: {todo.due_date}, Complete: {todo.complete}")

# List todos for specific user
todos = client.todo.list(user_id=456)

# List todos for a meeting
todos = client.todo.list(meeting_id=123)

# Get todo details
todo = client.todo.details(todo_id=789)
print(f"Todo: {todo.name}")

# Create a user todo
new_todo = client.todo.create(
    title="Complete project proposal",
    due_date="2024-12-31",
    notes="Include budget estimates"
)
print(f"Created todo ID: {new_todo.id}")

# Create a meeting todo
meeting_todo = client.todo.create(
    title="Follow up on action items",
    meeting_id=123,
    due_date="2024-12-15",
    user_id=456
)

# Complete a todo
completed = client.todo.complete(todo_id=789)
print(f"Completed: {completed.complete}")

# Update a todo
updated = client.todo.update(
    todo_id=789,
    title="Updated title",
    due_date="2024-12-25"
)

# Bulk create todos
result = client.todo.create_many([
    {"title": "Task 1", "meeting_id": 123, "due_date": "2024-12-31"},
    {"title": "Task 2", "meeting_id": 123, "user_id": 456}
])
print(f"Created {len(result.successful)} todos")
for error in result.failed:
    print(f"Failed at index {error.index}: {error.error}")
```

## Goal Operations

Goal operations (also known as "Rocks") provide functionality for creating, updating, archiving, and managing goals with status tracking.

```python
from bloomy import Client, GoalStatus

client = Client(api_key="your-api-key")

# List active goals for current user
goals = client.goal.list()
for goal in goals:
    print(f"Goal: {goal.title}, Status: {goal.status}")

# List goals including archived
response = client.goal.list(archived=True)
print(f"Active goals: {len(response.active)}")
print(f"Archived goals: {len(response.archived)}")

# Create a new goal
new_goal = client.goal.create(
    title="Increase sales by 20%",
    meeting_id=123,
    user_id=456
)
print(f"Created goal ID: {new_goal.id}")

# Update goal status using enum (recommended)
client.goal.update(goal_id=789, status=GoalStatus.ON_TRACK)

# Update goal status using string
client.goal.update(goal_id=789, status="on")  # on, off, or complete

# Update goal title and accountable user
client.goal.update(
    goal_id=789,
    title="Updated Goal Title",
    accountable_user=456,
    status=GoalStatus.COMPLETE
)

# Archive a goal
client.goal.archive(goal_id=789)

# Restore an archived goal
client.goal.restore(goal_id=789)

# Delete a goal
client.goal.delete(goal_id=789)

# Bulk create goals
result = client.goal.create_many([
    {"title": "Q1 Revenue Target", "meeting_id": 123},
    {"title": "Product Launch", "meeting_id": 123, "user_id": 456}
])
print(f"Created {len(result.successful)} goals")
for error in result.failed:
    print(f"Failed at index {error.index}: {error.error}")
```

## Scorecard Operations

Scorecard operations provide methods to retrieve and update scorecard metrics, including week-based filtering and scoring.

```python
from bloomy import Client

client = Client(api_key="your-api-key")

# Get current week information
week = client.scorecard.current_week()
print(f"Week {week.week_number}: {week.week_start} to {week.week_end}")

# List scorecards for current user
scorecards = client.scorecard.list()
for item in scorecards:
    print(f"{item.title}: {item.value}/{item.target}")

# List scorecards for specific user
scorecards = client.scorecard.list(user_id=456)

# List scorecards for a meeting
scorecards = client.scorecard.list(meeting_id=123)

# List scorecards including empty values
scorecards = client.scorecard.list(show_empty=True)

# List scorecards for previous week
scorecards = client.scorecard.list(week_offset=-1)

# List scorecards for next week
scorecards = client.scorecard.list(week_offset=1)

# Get a single scorecard item
item = client.scorecard.get(measurable_id=123)
if item:
    print(f"{item.title}: {item.value}/{item.target}")

# Get scorecard item for previous week
item = client.scorecard.get(measurable_id=123, week_offset=-1)

# Update a score for current week
success = client.scorecard.score(measurable_id=123, score=95.5)
print(f"Score updated: {success}")

# Update a score for previous week
success = client.scorecard.score(measurable_id=123, score=88.0, week_offset=-1)
```

## Issue Operations

Issue operations provide CRUD functionality for managing issues, including creation, completion, updates, and bulk operations.

```python
from bloomy import Client

client = Client(api_key="your-api-key")

# List issues for current user
issues = client.issue.list()
for issue in issues:
    print(f"Issue: {issue.title}, Meeting: {issue.meeting_title}")

# List issues for specific user
issues = client.issue.list(user_id=456)

# List issues for a meeting
issues = client.issue.list(meeting_id=123)

# Get issue details
issue = client.issue.details(issue_id=789)
print(f"Issue: {issue.title}")
print(f"Created: {issue.created_at}")
print(f"Owner: {issue.user_name}")

# Create an issue
new_issue = client.issue.create(
    meeting_id=123,
    title="Server performance degradation",
    notes="Response times increased by 50%"
)
print(f"Created issue ID: {new_issue.id}")

# Create an issue assigned to specific user
new_issue = client.issue.create(
    meeting_id=123,
    title="Review security audit",
    user_id=456
)

# Update an issue
updated = client.issue.update(
    issue_id=789,
    title="Updated Issue Title",
    notes="Additional context"
)

# Complete/solve an issue
completed = client.issue.complete(issue_id=789)
print(f"Completed at: {completed.completed_at}")

# Bulk create issues
result = client.issue.create_many([
    {"meeting_id": 123, "title": "Issue 1", "notes": "Details"},
    {"meeting_id": 123, "title": "Issue 2", "user_id": 456}
])
print(f"Created {len(result.successful)} issues")
for error in result.failed:
    print(f"Failed at index {error.index}: {error.error}")
```

## Headline Operations

Headline operations provide methods for creating, updating, listing, and deleting headlines associated with meetings.

```python
from bloomy import Client

client = Client(api_key="your-api-key")

# List headlines for current user
headlines = client.headline.list()
for headline in headlines:
    print(f"Headline: {headline.title}")
    print(f"Meeting: {headline.meeting_details.title}")
    print(f"Owner: {headline.owner_details.name}")

# List headlines for specific user
headlines = client.headline.list(user_id=456)

# List headlines for a meeting
headlines = client.headline.list(meeting_id=123)

# Get headline details
headline = client.headline.details(headline_id=789)
print(f"Headline: {headline.title}")
print(f"Created: {headline.created_at}")
print(f"Archived: {headline.archived}")

# Create a headline
new_headline = client.headline.create(
    meeting_id=123,
    title="Product launch successful",
    notes="Exceeded targets by 15%"
)
print(f"Created headline ID: {new_headline.id}")

# Create a headline with specific owner
new_headline = client.headline.create(
    meeting_id=123,
    title="New partnership announcement",
    owner_id=456
)

# Update a headline
client.headline.update(headline_id=789, title="Updated headline title")

# Delete a headline
client.headline.delete(headline_id=789)
```

## Error Handling

The SDK provides specific exception classes for different error scenarios, enabling precise error handling in applications.

```python
from bloomy import Client
from bloomy.exceptions import (
    BloomyError,
    ConfigurationError,
    AuthenticationError,
    APIError
)

try:
    client = Client()  # May raise ConfigurationError if no API key
except ConfigurationError as e:
    print(f"Configuration error: {e}")
    # Handle missing API key

try:
    client = Client(api_key="invalid-key")
    user = client.user.details()
except AuthenticationError as e:
    print(f"Authentication failed: {e}")
    # Handle invalid credentials

try:
    meeting = client.meeting.details(meeting_id=99999)
except APIError as e:
    print(f"API error: {e}")
    print(f"Status code: {e.status_code}")
    # Handle API errors (404, 500, etc.)

try:
    client.todo.update(todo_id=123)  # No fields provided
except ValueError as e:
    print(f"Validation error: {e}")

# Catch all Bloomy errors
try:
    client.goal.create(title="Goal", meeting_id=123)
except BloomyError as e:
    print(f"Bloomy error occurred: {e}")
```

## Configuration Management

The Configuration class handles API key management with support for environment variables, configuration files, and username/password authentication.

```python
from bloomy import Configuration
from bloomy.exceptions import AuthenticationError, ConfigurationError

# Create configuration (loads from env or file automatically)
config = Configuration()
print(f"API Key loaded: {config.api_key is not None}")

# Create configuration with explicit API key
config = Configuration(api_key="your-api-key")

# Configure API key using username and password
config = Configuration()
try:
    config.configure_api_key(
        username="your-username",
        password="your-password",
        store_key=True  # Saves to ~/.bloomy/config.yaml
    )
    print(f"API key configured: {config.api_key[:10]}...")
except AuthenticationError as e:
    print(f"Authentication failed: {e}")

# Configuration file location: ~/.bloomy/config.yaml
# Format:
# version: 1
# api_key: your-api-key-here
```

## Summary

Bloomy SDK is ideal for building integrations with Bloom Growth for business management applications. Common use cases include automating meeting management, tracking team goals and performance metrics through scorecards, managing action items (todos), and handling team communication through headlines and issues. The SDK supports batch operations for efficient bulk data processing and provides both sync and async interfaces.

Integration patterns typically involve initializing a client with API credentials, using resource-specific operations (client.user, client.meeting, client.todo, etc.), handling responses through Pydantic models for type safety, and implementing error handling using the exception hierarchy. The bulk operations (create_many, get_many) are particularly useful for data migration and synchronization tasks, returning BulkCreateResult objects that separate successful operations from failures for comprehensive error handling.