> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mathfi.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Non-destructive delete of a dataset

> A non-destructive delete.

- Nothing is destroyed. The dataset's files, the models trained from it and their predictions
  all remain, and anything running against them keeps working.
- `204` means the request was accepted, **not** that the dataset is gone. A later read or
  listing may still return it.
- `404` for a dataset that does not exist.
- Safe to retry; nothing is ever lost by calling it.




## OpenAPI

````yaml api-reference/openapi.yaml DELETE /api/v1/datasets/{datasetKey}
openapi: 3.0.1
info:
  title: MathFi.ai API
  description: >
    The MathFi.ai REST API runs the two products end to end.


    **Feature Refinery** takes your labelled data and works out which columns

    actually carry the signal. It returns a reduced train and test pair, a

    per-column keep/remove decision, and the performance target the refined data

    reached.


    **Model Crucible** takes a dataset, trains every algorithm family against it

    at once, ranks the results on held-out data by fewest wrong decisions, and

    keeps the best three as versions of one model. You pick which one
    predictions

    run against.


    Everything is asynchronous: you create a thing, upload to a signed URL,
    start

    it, then poll until the state is terminal. Nothing streams and nothing
    blocks.
  contact:
    name: MathFi.ai
    url: https://mathfi.ai
    email: support@mathfi.ai
  license:
    name: MathFi.ai
    url: https://mathfi.ai
  version: 1.0.0
servers:
  - url: https://{tenant}-api.mathfi.ai
    description: >-
      Your tenant's API. Each customer has their own, so the host varies.
      Replace {tenant} with the name issued when your tenant was created.
    variables:
      tenant:
        default: your-tenant
        description: The tenant name issued to you.
security:
  - BearerAuth: []
tags:
  - name: Authentication
    description: Exchange credentials for a bearer token
  - name: Feature Refinery
    description: Reduce a dataset to the columns that earn their place
  - name: Datasets
    description: >-
      Prepare labelled data for training, from uploads or from a finished
      refinement
  - name: Training
    description: Run the Crucible against a dataset and choose the champion model
  - name: Models
    description: Trained models and their versions
  - name: Predictions
    description: Score unlabelled data against a champion model
paths:
  /api/v1/datasets/{datasetKey}:
    delete:
      tags:
        - Datasets
      summary: Non-destructive delete of a dataset
      description: >
        A non-destructive delete.


        - Nothing is destroyed. The dataset's files, the models trained from it
        and their predictions
          all remain, and anything running against them keeps working.
        - `204` means the request was accepted, **not** that the dataset is
        gone. A later read or
          listing may still return it.
        - `404` for a dataset that does not exist.

        - Safe to retry; nothing is ever lost by calling it.
      operationId: deleteDataset
      parameters:
        - name: datasetKey
          in: path
          required: true
          schema:
            pattern: >-
              ^[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[4][0-9a-fA-F]{3}-[89aAbB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}$
            type: string
            format: uuid
      responses:
        '204':
          description: Accepted. Nothing was destroyed.
        '500':
          description: Internal server error
components:
  securitySchemes:
    BearerAuth:
      type: http
      scheme: bearer
      bearerFormat: JWT

````