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sbxcloudpython

This is the first version of Python Library for SbxCloud. The min Python version require is 3.12, this library depends on courutines with asyncio in order to use concurrent task, and uses aiohttp to do the request. You can test using the test.py file, before execute it, configuring your credentials in the environment.

SBXCloud Project

Project Setup

  • Package manager: uv
  • Python: >= 3.12
  • Run: uv run main.py
  • Install deps: uv sync
  • Add dep: uv add <package>

Environment Variables (.env)

SBX_DOMAIN=<domain_id>       # Domain ID in SBXCloud
SBX_APP_KEY=<app_key>        # Application key for authentication
SBX_TOKEN=<token>            # Auth token
SBX_BASE_URL=https://sbxcloud.com/api

SBXCloud Platform Overview

SBXCloud is a BaaS (Backend as a Service) platform that allows creating models (equivalent to database tables) within domains (equivalent to databases/projects). Each domain has an APP_KEY for identification and a TOKEN for authentication.

Core Concepts

  • Domain: A project/workspace that contains models. Identified by DOMAIN ID.
  • Model: Equivalent to a database table. Has a name and contains records.
  • Record: Each record automatically gets a _KEY field (primary key, auto-generated on insert).
  • Fetch Models: Equivalent to JOINs - resolve references to other models.

sbxpy Library Usage

Initialization

from sbxpy import SbxCore
from sbxpy.sbx import SBX, SBXResponse
from dotenv import load_dotenv

load_dotenv()
sbx: SbxCore = SBX.get_instance()

SBX.get_instance() reads SBX_DOMAIN, SBX_APP_KEY, SBX_TOKEN from environment.

Defining Models

Models extend SBXModel and use the @sbx(model="model_name") decorator. The model_name must match the model name in SBXCloud.

from typing import Optional, List
from pydantic import BaseModel
from sbxpy.domain import SBXModel, sbx

@sbx(model="category")
class SBXCategory(SBXModel):
    category: str

@sbx(model="color")
class SBXColor(SBXModel):
    color_name: str
    html_code_1: Optional[str] = None
    color_group: Optional[str] = None

Key rules for models:

  • All models inherit from SBXModel (which provides key field mapped to _KEY).
  • Use the @sbx(model="model_name") decorator to bind to a SBXCloud model.
  • Fields use Python type hints. Use Optional[type] = None for nullable fields.
  • References to other models are stored as str (the _KEY of the referenced record).
  • You can type a reference field as Optional[ModelClass] when it will be populated via fetch_models.

Querying Data

Basic Query

sbx: SbxCore = SBX.get_instance()
query = sbx.with_model("model_name")
response = SBXResponse(**await query.find())
items = response.all(SBXModelClass)  # Returns List[SBXModelClass]

Find All (paginated automatically)

response = SBXResponse(**await query.find_all())

find() returns a single page. find_all() iterates all pages automatically.

Where Clauses

# Filter by specific keys
query = sbx.with_model("variety").where_with_keys(["key1", "key2", "key3"])

# Greater or equal than
query = sbx.with_model("cart_box_item").and_where_greater_or_equal_than("cart_box.packing_date", "20260131")

# Other where methods (follow the pattern):
# .and_where_equal_to(field, value)
# .and_where_not_equal_to(field, value)
# .and_where_less_than(field, value)
# .and_where_greater_than(field, value)
# .and_where_less_or_equal_than(field, value)
# .and_where_is_not_null(field)
# .and_where_is_null(field)

Fetch Models (JOINs)

Resolve references to other models in a single query. Pass a list of model field names or nested paths.

query = (sbx.with_model("variety")
         .where_with_keys(variety_keys)
         .fetch_models(["product_group", "product_group.category"]))

response = SBXResponse(**await query.find())

# Access fetched/joined data:
# response.fetched_results["product_group"][key_value] -> dict of the referenced record
# response.fetched_results["category"][key_value] -> dict of nested reference

Nested fetch: "product_group.category" means: from the product_group reference, also fetch its category reference. The fetched results are stored flat by model name in response.fetched_results.

Insert / Update (Upsert)

The upsert function handles both inserts and updates in a single call:

sbx: SbxCore = SBX.get_instance()

# Insert new records (no _KEY field)
result = await sbx.upsert("model_name", [
    {"field1": "value1", "field2": "value2"},
    {"field1": "value3", "field2": "value4"},
])
# result contains "keys" array with the new _KEY values in the same order

# Update existing records (include _KEY field)
await sbx.upsert("model_name", [
    {"_KEY": "existing_key_1", "field1": "new_value"},
    {"_KEY": "existing_key_2", "field2": "new_value"},
])

# Mixed insert + update in one call
await sbx.upsert("model_name", [
    {"field1": "new_record"},              # Will INSERT (no _KEY)
    {"_KEY": "abc123", "field1": "updated"} # Will UPDATE (has _KEY)
])

Important upsert rules:

  • Limit: Maximum 1000 records per upsert call. Batch larger sets.
  • Insert detection: Records without _KEY are inserted.
  • Update detection: Records with _KEY are updated.
  • Response on insert: The response includes a "keys" array with the new _KEY values in the same order as the input records.
  • Only send fields you want to update; unchanged fields don't need to be included.

Models & Fields Management

You can list existing models, create new models, and add fields (attributes) to them programmatically.

List Models

sbx: SbxCore = SBX.get_instance()

# Returns the list of models in the domain
result = await sbx.list_domain()
models = result.get("items", [])
for model in models:
    print(model["name"], model["id"], model.get("properties", []))

Create a Model

# Create a new model (table) in the domain
result = await sbx.create_model("my_new_model")
model_id = result["row_model"]["id"]

Create Fields (Attributes)

# Add a STRING field
await sbx.create_field(model_id, "name", "STRING")

# Add an INT field
await sbx.create_field(model_id, "quantity", "INT")

# Add a FLOAT field
await sbx.create_field(model_id, "price", "FLOAT")

# Add a BOOLEAN field
await sbx.create_field(model_id, "active", "BOOLEAN")

# Add a TEXT field
await sbx.create_field(model_id, "description", "TEXT")

# Add a REFERENCE field (foreign key to another model)
await sbx.create_field(model_id, "category", "REFERENCE", reference_type=other_model_id)

Available field types: STRING, INT, FLOAT, BOOLEAN, TEXT, REFERENCE.

CloudScripts

CloudScripts are server-side JavaScript functions that run on SBXCloud. You can create, list, get, update, and execute them.

Execute a CloudScript

sbx: SbxCore = SBX.get_instance()

# Run a cloudscript by key with parameters
result = await sbx.run("cloudscript_key", {"param1": "value1", "param2": "value2"})

Create a CloudScript

result = await sbx.create_cloudscript("my_script", '{"key": "value"}')
# result contains the created cloudscript info

List CloudScripts

# List cloudscripts (paginated, default page=1)
result = await sbx.list_cloudscripts(page=1)

Get a CloudScript by Key

result = await sbx.get_cloudscript("cloudscript_key")

Update a CloudScript

# Update the script code and optionally a test script
result = await sbx.update_cloudscript(
    "cloudscript_key",
    script='console.log("hello world")',
    test_script='console.log("test")'
)

SBXResponse

response = SBXResponse(**await query.find())

# Get typed list of results
items: list[SBXModelClass] = response.all(SBXModelClass)

# Access fetched (joined) model data
fetched_data = response.fetched_results["model_name"]  # dict[str, dict]
# Key is the _KEY of the fetched record, value is a dict of its fields

Common Patterns

Grouping items by reference key

items_by_ref: dict[str, list[ItemClass]] = {}
for item in items:
    if item.ref_key not in items_by_ref:
        items_by_ref[item.ref_key] = []
    items_by_ref[item.ref_key].append(item)

Batching upserts (>1000 records)

BATCH_SIZE = 1000
for i in range(0, len(records), BATCH_SIZE):
    batch = records[i:i + BATCH_SIZE]
    await sbx.upsert("model_name", batch)

Date format

Dates in SBXCloud are often stored as int in YYYYMMDD format (e.g., 20260131).

from datetime import datetime

def date_to_number_date(d: datetime) -> int:
    return int(d.strftime("%Y%m%d"))