kquika-trakt 1.0.9

Trakt System Integrations API client: fleet predictions and maintenance forecasts.

Trakt System SDK

Client libraries for the Trakt System Integrations API: fleet predictions and maintenance forecasts, in a few lines of code.

Trakt System predicts which components on your fleet need attention, when, and what to do about them. This SDK gives you that data directly, with authentication, retries, and rate limits handled for you.

Install

Python

pip install kquika-trakt              # core
pip install "kquika-trakt[pandas]"    # with DataFrame support

The distribution is named kquika-trakt and the import is trakt. That difference is normal: the package you install and the module you import do not have to share a name.

Node / TypeScript

npm install @kquika-inc/trakt

Requires Node 18 or newer. TypeScript types are included.

Quickstart

Python

from trakt import Trakt

trakt = Trakt(token="YOUR_API_KEY")   # or set TRAKT_TOKEN

# What can this token do?
cfg = trakt.config()
print(cfg.access_level, cfg.max_predictions, cfg.can_export)

# Per-component predictions, most urgent first
for c in trakt.components():
    print(c.name, c.aircraft_tail_number, c.health,
          c.failure_probability, c.recommended_action)

# The next 90 days of maintenance, soonest first
for item in trakt.forecast(days=90):
    if item.is_overdue:
        print("OVERDUE:", item.tail_number, item.component_name)

# Straight to a DataFrame for planning
df = trakt.components_dataframe()

Node / TypeScript

import { Trakt } from "@kquika/trakt";

const trakt = new Trakt({ token: process.env.TRAKT_TOKEN! });

const cfg = await trakt.config();
console.log(cfg.access_level, cfg.max_predictions);

// Per-component predictions, most urgent first
const components = await trakt.components();
for (const c of components) {
  console.log(c.name, c.aircraft_tail_number, c.health, c.recommended_action);
}

// The next 90 days of maintenance, soonest first
const forecast = await trakt.forecast({ days: 90 });
for (const item of forecast) {
  if (item.is_overdue) console.log("OVERDUE:", item.tail_number, item.component_name);
}

Handling errors

Both clients raise typed errors, so you can catch the case you care about.

from trakt import AuthenticationError, PermissionError_, RateLimitError

try:
    components = trakt.components()
except AuthenticationError:
    print("The token was not accepted.")
except PermissionError_:
    print("This token's access level does not cover that call.")
except RateLimitError:
    print("Quota exhausted. The client already retried with backoff.")

import { AuthenticationError, PermissionError, RateLimitError } from "@kquika-inc/trakt";

try {
  const components = await trakt.components();
} catch (e) {
  if (e instanceof AuthenticationError) console.error("The token was not accepted.");
  else if (e instanceof PermissionError) console.error("Access level does not cover that call.");
  else if (e instanceof RateLimitError) console.error("Quota exhausted.");
  else throw e;
}

What the clients do for you

• Auth. Set the token once; every request carries the bearer header.
• Retries. A rate limit or a transient server failure is retried with exponential backoff and jitter, honoring Retry-After when it is sent. A rejected token or a permission error is not retried, because retrying will not fix it.
• Typed errors. AuthenticationError, PermissionError, RateLimitError, NotFoundError, ServerError.
• Flattened objects. The nested prediction, survival, and maintenance blocks are lifted onto the component, so health and recommended_action are one attribute away.
• Useful ordering. Components come back most urgent first; forecast items come back soonest first.

Reading the fields

Field	Meaning
health	0 to 100, where higher is healthier.
health_trend	stable, declining, or critical.
predicted_rul_hours / predicted_rul_days	Remaining useful life before attention is due.
failure_probability	0 to 1, the modeled chance of failure in the near term.
recommended_action	do_nothing, inspect, repair, or replace.
priority	The urgency band for planning.
task_reference	The task identifier from your source system, so a row ties back to its task.
days_until_due	Negative means the item is already past due.

Access levels

Your token is issued at one of three levels, which control both the endpoints it can reach and how many records a request returns:

• read_only — read predictions and forecasts
• read_write — read, plus the write endpoints
• full — everything, including fleet export

A call outside your token's level raises a permission error. Call config() to see the level and limits for your token rather than guessing.

Need a client in another language?

The SDKs are built from an OpenAPI specification, so a client can be generated for most languages. Contact us and we will provide the spec.

Support

Questions, a token, or a raised limit: [e-mail]

License

MIT