prekit-sdk 0.1.0

User-friendly Python SDK for the PREKIT edge computing platform

prekit-sdk

User-friendly Python SDK for the PREKIT edge computing platform. Django-inspired API, self-documenting objects, pandas-native data access.

Architecture

How prekit-sdk wraps the auto-generated API client. The __getattr__ proxy in models.py is the critical boundary — new fields from client regeneration appear automatically.

Installation

# Install the API client wheel first (from GitHub Releases or local build)
pip install prekit_edge_node_api-1.10.0-py3-none-any.whl

# Install the SDK
pip install prekit-sdk

# Or from git
pip install git+https://github.com/alpamayo-solutions/prekit-sdk.git

# Or for local development
pip install -e "./prekit-sdk[dev]"

CA Certificate

PREKIT deployments use a private PKI. The SDK can auto-download and cache the Alpamayo root CA certificate using ca_cert="alpamayo":

pk = Prekit.connect(url="https://edge.local", api_key="my-key", ca_cert="alpamayo")

The certificate is cached at ~/.prekit/alpamayo-root-ca.crt. You can also pass an explicit path to any CA cert file:

pk = Prekit.connect(url="https://edge.local", api_key="my-key", ca_cert="/path/to/ca.crt")

The root CA certificate is also available in this repo at certs/alpamayo-root-ca.crt.

SHA-256 Fingerprint: 62:96:51:A7:63:CC:14:B3:74:2A:BB:4B:A3:7A:17:20:5E:6D:58:9F:46:E9:CC:D8:E6:38:94:FE:3B:3C:7C:5C
Valid: 2025-04-30 to 2035-04-28

Quick Start

from prekit_sdk import Prekit

# Connect with API key (auto-downloads CA cert)
pk = Prekit.connect(url="https://edge.local", api_key="my-key", ca_cert="alpamayo")
print(pk)
# PREKIT SDK
#   URL:     https://edge.local
#   Health:  healthy
#   User:    [e-mail]
#   Roles:   reader

# Browse the asset tree
tree = pk.tree()
print(tree)
# Factory
# ├── LineA
# │   ├── CNC-Mill [3 signals]
# │   └── Lathe [2 signals]
# └── LineB
#     └── Press [1 signal]

# Find a machine
machine = pk.elements.get(name="CNC-Mill")
machine.help()

# Get its signals
sigs = machine.signals()

# Fetch historian data
df = machine.data(last="1h")

Connection & Authentication

Keycloak Client Credentials

For scripts and service accounts:

pk = Prekit.connect(
    url="https://edge.local",
    client_id="prekit-test",
    client_secret="your-secret",
    verify_ssl=False,
)

Azure / Entra ID

Interactive browser login with Microsoft account:

pk = Prekit.connect(
    url="https://edge.local",
    auth="azure",
    tenant_id="your-tenant-id",
    client_id="your-app-id",
)

API Key

pk = Prekit.connect(url="https://edge.local", api_key="my-key")

From Environment Variables

pk = Prekit.connect_from_env()

Reads: PREKIT_URL, PREKIT_AUTH_METHOD (api_key/oauth/azure), API_KEY, KEYCLOAK_URL, KEYCLOAK_CLIENT_ID, KEYCLOAK_CLIENT_SECRET, AZURE_TENANT_ID, AZURE_CLIENT_ID, PREKIT_VERIFY_SSL, CA_CERT_FILE.

Escape Hatch

Direct access to the raw AutoRefreshApiClient:

pk.api  # for any API call not covered by the SDK

Browsing the Asset Tree

# Full tree (compact, with signal counts)
pk.tree().print()

# Full tree (expanded, showing individual signals)
pk.tree().print(signals=True)

# Subtree from a specific element
pk.tree(root=machine).print()
pk.tree(root="01JABCDE...").print()  # by ID

Compact output

Factory
├── LineA
│   ├── CNC-Mill [3 signals]
│   └── Lathe [2 signals]
└── LineB
    └── Press [1 signal]

Expanded output (signals=True)

Factory
├── LineA
│   ├── CNC-Mill
│   │   ├─ Temperature (float, C)
│   │   ├─ Vibration (float, mm/s)
│   │   └─ SpindleSpeed (int, rpm)
│   └── Lathe
│       └─ Temperature (float, C)
└── LineB
    └── Press
        └─ Pressure (float, bar)

Finding Things (Django-style)

The SDK provides managers with .get(), .filter(), .all(), and .create(), inspired by Django's ORM.

.get() -- single object

# By name
machine = pk.elements.get(name="CNC-Mill")

# By ID (direct API call, fast)
sig = pk.signals.get(id="01JABCDE...")

# By hierarchy path
line = pk.elements.get(path="Factory/LineA")

.filter() -- multiple objects

# Substring match
machines = pk.elements.filter(name__contains="CNC")

# Multiple criteria
sigs = pk.signals.filter(data_type="float", unit="C")

# By parent element (accepts object or ID)
sigs = pk.signals.filter(system_element=machine)

Available lookups

Lookup	Example	Behavior
name	name="CNC"	Exact match
name__contains	name__contains="Mill"	Substring
name__startswith	name__startswith="CNC"	Prefix
name__icontains	name__icontains="mill"	Case-insensitive substring
system_element	system_element=machine	FK (object or ID)
id	id="01JAB..."	Direct ID lookup
path	path="Factory/LineA"	Hierarchy path (elements only)

Handling non-unique signal names

Signal names are not unique. "Temperature" may exist on multiple machines:

pk.signals.get(name="Temperature")
# -> MultipleObjectsReturned: 3 signals match name="Temperature"

# Disambiguate by scoping to an element:
sig = pk.signals.get(name="Temperature", system_element=machine)

# Or get all matches:
temps = pk.signals.filter(name="Temperature")

.create()

elem = pk.elements.create(name="NewMachine", parent=line_a)
sig = pk.signals.create(name="Temp", element=elem, data_type="float", unit="C")

Data Access

All data access uses signal IDs internally (always unambiguous). Returns pandas DataFrames.

Single signal

sig = pk.signals.get(name="Temperature", system_element=machine)

df = sig.data(last="1h")                                    # relative time
df = sig.data(start="2026-03-17", end="2026-03-18")         # absolute range
latest = sig.latest()                                        # {"value": 23.5, "timestamp": ...}

All signals on an element

df = machine.data(last="1h")
# Pivoted DataFrame: timestamp | Temperature | Vibration | SpindleSpeed

Multiple specific signals

df = pk.data(signals=[sig1, sig2], last="1h")

Rich Models & .help()

Every object returned by the SDK is a thin proxy over the generated Pydantic model. Generated fields are accessible directly; the SDK adds navigation methods.

machine = pk.elements.get(name="CNC-Mill")

# Generated fields (from prekit_edge_node_api)
machine.name           # "CNC-Mill"
machine.id             # "01JABCDE..."
machine.created_at     # datetime

# SDK navigation methods
machine.signals()      # -> [<Signal: Temperature>, ...]
machine.children()     # -> []
machine.parent()       # -> <Element: LineA>
machine.path()         # -> "Factory/LineA/CNC-Mill"

# Escape hatch
machine._raw           # the generated SystemElement Pydantic model

.help() -- self-documenting objects

machine.help()

Output:

SystemElement: CNC-Mill (01JABCDE...)
Path: Factory/LineA/CNC-Mill

Fields (from generated model):
  name, id, created_at, updated_at, parent, level, ...

Relationships:
  .signals()              child signals (3 items)
  .children()             child elements (0 items)
  .parent()               parent element -> LineA

Actions:
  .data(last="1h")        DataFrame (all child signals)
  .tree()                 subtree from here
  .update(name=...)       patch this element
  ._raw                   generated SystemElement model

Health check

pk.is_healthy()   # -> True/False
pk.health()       # -> {"status": "healthy", ...}

API Client Updates

The SDK is designed to be resilient to API client regeneration:

• __getattr__ proxy: element.name delegates to _raw.name. New fields on the generated model appear automatically.
• .help() introspects dynamically: reads model_fields from the Pydantic model at runtime. New fields show up in help output without SDK changes.
• Managers resolve API classes by name: getattr(prekit, "SystemElementApi") at init time, not hardcoded imports.

Update workflow: regenerate the API client -> pip install the new wheel -> the SDK picks up new models and fields automatically. No SDK code changes needed unless adding new navigation methods.

Development

# Setup
pip install tests/edge-node/api-client-whl/*.whl
pip install -e "./prekit-sdk[dev]"

# Run tests
pytest prekit-sdk/tests/ -v

# Lint
ruff check prekit-sdk/src/

# Demo notebook
jupyter notebook prekit-sdk/notebooks/demo.ipynb