> ## 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. # Retrieve dataset details > Retrieve dataset details by dataset key ## OpenAPI ````yaml api-reference/openapi.yaml GET /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}: get: tags: - Datasets summary: Retrieve dataset details description: Retrieve dataset details by dataset key operationId: getDatasetByKey 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: '200': description: Dataset details successfully retrieved content: application/json: schema: $ref: '#/components/schemas/DatasetDetailOutput' '400': description: Invalid dataset key supplied '404': description: Dataset not found '500': description: Internal server error components: schemas: DatasetDetailOutput: required: - createdOn - datasetKey - datasetName - status type: object properties: datasetKey: type: string format: uuid datasetName: type: string status: $ref: '#/components/schemas/DatasetCreationStatus' createdOn: type: string updatedOn: type: string numberOfBuckets: type: integer inputDataDownloadUrl: type: string metadata: $ref: '#/components/schemas/DatasetMetadata' errors: $ref: '#/components/schemas/DatasetErrors' warnings: $ref: '#/components/schemas/DatasetWarnings' inputs: description: >- The dataset's input files and which are still missing — so a client can say which upload is outstanding rather than only that the dataset is not ready. Empty on the single-file pipeline. type: array items: $ref: '#/components/schemas/DatasetInputStatus' inputDatasource: description: >- Where this dataset's inputs came from: UPLOAD when the caller uploaded them, FEATURE_REFINERY when they came from a completed refinement, CLOUD_STORAGE on the older single-file route. Settled when the dataset is created and never changes afterwards, so a client can decide once. In particular it is what says whether the refinement's column filter means anything here — it is offered only on a dataset that came from a refinement. type: string nullable: true featureRefinementKey: description: >- The refinement these inputs came from, when they did. Null otherwise. Present so a client can link back to the run without keeping its own record of which one was chosen. An opaque handle: pass it back as given rather than parsing it. type: string nullable: true uploadedTrainRowCount: description: >- How many training rows were uploaded. Absent on a dataset built before the count was kept. type: integer format: int64 nullable: true trainRowCount: description: The number of training rows the dataset was prepared from. type: integer format: int64 nullable: true recommendedThreshold: description: >- The performance target a training on this dataset should start from — the threshold the refinement it came from trained to. Absent when the files were uploaded directly, in which case the client's own default applies. type: number format: double nullable: true recommendedNumberOfBuckets: description: >- The bucket count this dataset was founded at, when that came from a refinement. Absent on a direct upload, where the caller chose it. On this route it cannot be changed: the refined files were produced at this bucket count. type: integer nullable: true DatasetCreationStatus: type: string description: >+ Status of dataset creation: * `PENDING` - The dataset has been created and is pending further actions. Mainly data addition * `PROCESSING` - The dataset is currently being processed. When this status is returned an url to check status is returned too * `COMPLETED` - The dataset has been processed and is completed. The dataset is now ready to be used for training models * `FAILED` - The dataset processing has failed enum: - PENDING - PROCESSING - COMPLETED - FAILED DatasetMetadata: type: object properties: numberOfColumns: type: integer numberOfRows: type: integer numberOfClasses: type: integer titlesOfDataColumns: type: string columnTypes: type: string detectedTargetClassLabels: type: string numberOfFeaturesPerClass: type: string columnsWithUniqueValues: type: string columnsWithTooManyFeatures: type: string DatasetErrors: type: object properties: errors: type: array items: type: string DatasetWarnings: type: object properties: warnings: type: array items: type: string DatasetInputStatus: description: One of a dataset's input files and whether it has arrived yet. required: - kind - uploaded type: object properties: kind: type: string enum: - TRAIN - TEST uploaded: type: boolean description: >- Checked against storage on every read, so it reflects what is actually there. securitySchemes: BearerAuth: type: http scheme: bearer bearerFormat: JWT ````