# Overview
This library contains useful wrappers around the Tonic.ai API.
## Usage
Instantiate the API wrapper using the following code:
```
from tonic_api.api import TonicApi
# Do not include trailing backslash in TONIC_URL
api = TonicApi(TONIC_URL, API_KEY)
```
Once instantiated, the following endpoints are available for consumption. Note that available endpoints and response types are limited. Available fields may be severely limited compared to the current Tonic API.
```
TonicApi:
get_workspace(workspace_id) => Workspace
Workspace:
id => string
name => string
models => Model[]
train(model_id) => new job ID
get_trained_model_by_training_job_id(job_id) => TrainedModel (or None if training is not done)
get_training_status_by_training_job_id(job_id) => TrainingJobStatus
get_most_recent_trained_model_by_model_id => TrainedModel
describe() => debugger helper for printing fields
Model:
id => string
name => string
query => string
parameters => {}
encodings => {}
describe() => debugger helper for printing fields
TrainedModel:
id => string
job_id => string
model => Model
sample(num_rows) => pandas DataFrame (defaults to 1 row if num_rows not provided)
sample_source(num_rows) => pandas DataFrame (defaults to 1 row if num_rows not provided). Note: NOT randomized. Upper limit is limited to row count in source.
get_numeric_columns() => string[]
get_categorical_columns() => string[]
describe() => debugger helper for printing fields
TrainingJobStatus:
state => string
error => string[] or None
tasks => {}
current_epoch_progress() => dict or None
describe() => debugger helper for printing fields
```
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