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Documentation Index

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Cloud Functions Database API

Complete guide to querying and managing data in your CocoBase cloud functions.

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Overview

The Database API provides a powerful, MongoDB-like query interface for your PostgreSQL database with automatic relationship detection and advanced filtering capabilities.

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Key Features

  • Advanced Querying - 12+ operators (eq, ne, lt, gt, contains, in, etc.)
  • Complex Logic - OR/AND combinations with grouping
  • Auto Relationships - Automatically detects users vs collections
  • Deep Population - Nested relationship loading (author.company.location)
  • Relationship Filtering - Filter by related data (author.role=admin)
  • User Relationships - Followers, friends, teams support
  • Zero Configuration - No manual relationship definitions needed

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Quick Start

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Basic Query

def main():
    # Get all published posts
    posts = db.query("posts",
        status="published",
        limit=10
    )

    return {"posts": posts["data"]}

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Query with Population

def main():
    # Get posts with author and category data
    posts = db.query("posts",
        status="published",
        populate=["author", "category"],
        sort="created_at",
        order="desc",
        limit=20
    )

    return {"posts": posts["data"]}

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Advanced Filtering

def main():
    # Get posts with views > 100, published after date
    posts = db.query("posts",
        status="published",
        views_gte="100",
        created_at_gt="2024-01-01",
        populate=["author"],
        limit=50
    )

    return {"posts": posts["data"]}

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Query Operations

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query() - Query Collection

Query documents with filters, population, sorting, and pagination. 
db.query(
    collection_name: str,
    populate: List[str] = None,
    select: List[str] = None,
    sort: str = None,
    order: str = "asc",
    limit: int = 10,
    offset: int = 0,
    **filters
)
Parameters:
  • collection_name - Name of the collection to query
  • populate - List of relationship fields to populate
  • select - List of fields to return (optional, returns all by default)
  • sort - Field name to sort by
  • order - Sort order: “asc” or “desc” (default: “asc”)
  • limit - Maximum number of documents to return (default: 10)
  • offset - Number of documents to skip for pagination (default: 0)
  • **filters - Dynamic filter parameters using operators
Returns: 
{
    "data": [...],      # List of documents
    "total": 42,        # Total count matching filters
    "has_more": True    # Whether more results exist
}
Example: 
def main():
    posts = db.query("posts",
        status="published",
        category_id="cat-123",
        populate=["author", "category"],
        sort="created_at",
        order="desc",
        limit=20,
        offset=0
    )

    return {
        "posts": posts["data"],
        "total": posts["total"],
        "has_more": posts["has_more"]
    }

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find_one() - Get Single Document

Get a single document matching filters. 
db.find_one(
    collection_name: str,
    populate: List[str] = None,
    select: List[str] = None,
    **filters
)
Returns: Single document or None if not found Example: 
def main():
    post_id = req.get("post_id")

    post = db.find_one("posts",
        id=post_id,
        populate=["author", "category"]
    )

    if not post:
        return {"error": "Post not found"}, 404

    return {"post": post}

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query_users() - Query Users

Query users with the same powerful features as collections. 
db.query_users(
    populate: List[str] = None,
    select: List[str] = None,
    sort: str = None,
    order: str = "asc",
    limit: int = 10,
    offset: int = 0,
    **filters
)
Example: 
def main():
    # Get premium users over 18
    users = db.query_users(
        role="premium",
        age_gte="18",
        email_endswith="@gmail.com",
        populate=["referred_by"],
        sort="created_at",
        order="desc",
        limit=50
    )

    return {"users": users["data"]}

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find_user() - Get Single User

Find a single user by ID or filters. 
db.find_user(
    populate: List[str] = None,
    select: List[str] = None,
    **filters
)
Example: 
def main():
    # By ID
    user = db.find_user(
        id="user-123",
        populate=["company", "manager"]
    )

    # By email
    user = db.find_user(email="john@example.com")

    if not user:
        return {"error": "User not found"}, 404

    return {"user": user}

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Comparison Operators

Use operator suffixes to filter data:
OperatorSuffixExampleDescription
Equal(none) or _eqstatus="published"Exact match
Not Equal_nestatus_ne="draft"Not equal
Greater Than_gtprice_gt="100"Greater than
Greater or Equal_gteage_gte="18"Greater than or equal
Less Than_ltprice_lt="1000"Less than
Less or Equal_ltestock_lte="10"Less than or equal
Contains_containstitle_contains="python"String contains (case-insensitive)
Starts With_startswithname_startswith="john"String starts with
Ends With_endswithemail_endswith="@gmail.com"String ends with
In Array_instatus_in="published,draft"Value in comma-separated list
Not In Array_notincategory_notin="spam,nsfw"Value not in list
Is Null_isnulldeleted_at_isnull="true"Check if field is null/not null

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Examples

Greater Than: 
products = db.query("products", price_gt="50")
Contains (case-insensitive): 
users = db.query_users(name_contains="john")
In Array: 
posts = db.query("posts",
    status_in="published,featured,trending"
)
Multiple Operators: 
products = db.query("products",
    price_gte="50",
    price_lte="500",
    stock_gt="0",
    category_ne="discontinued"
)

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Boolean Logic

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Simple OR Queries

Use [or] prefix to create OR conditions: 
# Posts with status = published OR featured
posts = db.query("posts", **{
    "[or]status": "published",
    "[or]status_2": "featured"
})

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Named OR Groups

Create multiple independent OR groups: 
# (category=tech OR category=programming) AND (status=published OR status=featured)
posts = db.query("posts", **{
    "[or:cats]category": "tech",
    "[or:cats]category_2": "programming",
    "[or:status]status": "published",
    "[or:status]status_2": "featured"
})

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Search Across Multiple Fields

# Posts where title OR content contains keyword
posts = db.query("posts", **{
    "[or:search]title_contains": "python",
    "[or:search]content_contains": "python"
})

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CLI Commands

# Initialize project
cocobase init

# Test function locally
cocobase test functions/hello.py

# Test with parameters
cocobase test functions/hello.py --params '{"name": "Alice"}'

# Deploy single function
cocobase deploy functions/hello.py

# Deploy all functions
cocobase deploy --all

# View deployed functions
cocobase list

# View logs
cocobase logs --function hello --limit 50

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Environment Variables

# API Key (required for deployment)
export COCOBASE_API_KEY=your_api_key

# Project ID
export COCOBASE_PROJECT_ID=your_project_id

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Calling Your Function

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Via HTTP

curl "https://api.cocobase.buzz/projects/your-project/execute/hello?name=Alice"

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Via JavaScript

fetch('https://api.cocobase.buzz/projects/your-project/execute/hello?name=Alice')
  .then(res => res.json())
  .then(data => console.log(data));

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Via Python

import requests
response = requests.get(
    "https://api.cocobase.buzz/projects/your-project/execute/hello",
    params={"name": "Alice"}
)
print(response.json())

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Next Steps