# Fiddler Python Client SDK

- [Introduction](https://docs.fiddler.ai/api/fiddler-python-client-sdk/python-client.md): Complete API reference for fiddler
- [Connection](https://docs.fiddler.ai/api/fiddler-python-client-sdk/connection.md)
- [Connection](https://docs.fiddler.ai/api/fiddler-python-client-sdk/connection/connection.md): Manages authenticated connections to the Fiddler platform.
- [ConnectionMixin](https://docs.fiddler.ai/api/fiddler-python-client-sdk/connection/connection-mixin.md): Mixin class providing connection-related functionality to other classes.
- [Constants](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants.md)
- [AlertCondition](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/alert-condition.md): Alert trigger conditions for metric comparisons.
- [AlertThresholdAlgo](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/alert-threshold-algo.md): Threshold determination algorithms for alert rules.
- [ArtifactStatus](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/artifact-status.md): Model artifact upload and deployment status.
- [ArtifactType](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/artifact-type.md): Model artifact types for deployment.
- [BaselineType](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/baseline-type.md): Baseline computation strategies for data drift detection in Fiddler.
- [BinSize](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/bin-size.md): Time bin sizes for alert rule aggregation.
- [CompareTo](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/compare-to.md): Comparison baseline types for alert rule thresholds.
- [CustomFeatureType](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/custom-feature-type.md): Types of custom features for advanced model monitoring.
- [DataType](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/data-type.md): Data types supported for model columns in Fiddler.
- [DeploymentType](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/deployment-type.md): Model deployment types for explainability services.
- [DownloadFormat](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/download-format.md): File formats for downloading and exporting explanation data.
- [EnvType](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/env-type.md): Environment types for data publishing in Fiddler.
- [ExplainMethod](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/explain-method.md): Explanation methods for model interpretability and feature importance analysis.
- [JobStatus](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/job-status.md): Status values for asynchronous job operations in Fiddler.
- [ModelInputType](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/model-input-type.md): Input data types supported by Fiddler models.
- [ModelTask](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/model-task.md): Machine learning task types supported by Fiddler.
- [Priority](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/priority.md): Alert priority levels for notification routing and escalation.
- [WindowBinSize](https://docs.fiddler.ai/api/fiddler-python-client-sdk/constants/window-bin-size.md): Time granularities for rolling baseline window aggregation.
- [Entities](https://docs.fiddler.ai/api/fiddler-python-client-sdk/entities.md)
- [AlertRecord](https://docs.fiddler.ai/api/fiddler-python-client-sdk/entities/alert-record.md): Alert record representing a triggered alert instance.
- [AlertRule](https://docs.fiddler.ai/api/fiddler-python-client-sdk/entities/alert-rule.md): Alert rule for automated monitoring and alerting in ML systems.
- [Baseline](https://docs.fiddler.ai/api/fiddler-python-client-sdk/entities/baseline.md): Baseline for drift detection and model performance monitoring.
- [BaselineCompact](https://docs.fiddler.ai/api/fiddler-python-client-sdk/entities/baseline-compact.md): Fetch baseline instance
- [CustomMetric](https://docs.fiddler.ai/api/fiddler-python-client-sdk/entities/custom-metric.md): Custom metric for monitoring business-specific and domain-specific KPIs.
- [Dataset](https://docs.fiddler.ai/api/fiddler-python-client-sdk/entities/dataset.md): Represents a dataset containing data published to a Fiddler model.
- [DatasetCompact](https://docs.fiddler.ai/api/fiddler-python-client-sdk/entities/dataset-compact.md): Lightweight dataset representation for listing and basic operations.
- [File](https://docs.fiddler.ai/api/fiddler-python-client-sdk/entities/file.md): Construct a files instance.
- [Job](https://docs.fiddler.ai/api/fiddler-python-client-sdk/entities/job.md): Represents an asynchronous operation in the Fiddler platform.
- [Model](https://docs.fiddler.ai/api/fiddler-python-client-sdk/entities/model.md): Represents a machine learning model in the Fiddler platform.
- [ModelCompact](https://docs.fiddler.ai/api/fiddler-python-client-sdk/entities/model-compact.md): Lightweight model representation for listing and basic operations.
- [ModelDeployment](https://docs.fiddler.ai/api/fiddler-python-client-sdk/entities/model-deployment.md): Model deployment management for serving infrastructure.
- [Project](https://docs.fiddler.ai/api/fiddler-python-client-sdk/entities/project.md): Represents a project container for organizing ML models and resources.
- [ProjectCompact](https://docs.fiddler.ai/api/fiddler-python-client-sdk/entities/project-compact.md): Lightweight project representation for listing and basic operations.
- [Segment](https://docs.fiddler.ai/api/fiddler-python-client-sdk/entities/segment.md): Data segment for targeted monitoring and cohort analysis.
- [Webhook](https://docs.fiddler.ai/api/fiddler-python-client-sdk/entities/webhook.md): Webhook for integrating external notification systems with Fiddler alerts.
- [Exceptions](https://docs.fiddler.ai/api/fiddler-python-client-sdk/exceptions.md)
- [ApiError](https://docs.fiddler.ai/api/fiddler-python-client-sdk/exceptions/api-error.md): Raised when the Fiddler API returns an HTTP error response.
- [AsyncJobFailed](https://docs.fiddler.ai/api/fiddler-python-client-sdk/exceptions/async-job-failed.md): Raised when an asynchronous job fails to execute successfully.
- [Conflict](https://docs.fiddler.ai/api/fiddler-python-client-sdk/exceptions/conflict.md): Raised when a request conflicts with the current state of a resource (HTTP 409).
- [ConnError](https://docs.fiddler.ai/api/fiddler-python-client-sdk/exceptions/conn-error.md): Raised when a connection error occurs during HTTP requests.
- [ConnTimeout](https://docs.fiddler.ai/api/fiddler-python-client-sdk/exceptions/conn-timeout.md): Raised when a connection timeout occurs during HTTP requests.
- [HttpError](https://docs.fiddler.ai/api/fiddler-python-client-sdk/exceptions/http-error.md): Base class for all HTTP-related errors.
- [IncompatibleClient](https://docs.fiddler.ai/api/fiddler-python-client-sdk/exceptions/incompatible-client.md): Raised when the Python client version is incompatible with the Fiddler platform version.
- [NotFound](https://docs.fiddler.ai/api/fiddler-python-client-sdk/exceptions/not-found.md): Raised when a requested resource is not found (HTTP 404).
- [Unsupported](https://docs.fiddler.ai/api/fiddler-python-client-sdk/exceptions/unsupported.md): Raised when an unsupported operation is attempted.
- [Schemas](https://docs.fiddler.ai/api/fiddler-python-client-sdk/schemas.md)
- [Column](https://docs.fiddler.ai/api/fiddler-python-client-sdk/schemas/column.md): Represents a single column in a model schema with its metadata and constraints.
- [CustomFeature](https://docs.fiddler.ai/api/fiddler-python-client-sdk/schemas/custom-feature.md): Base class for all custom feature types in Fiddler models.
- [DatasetDataSource](https://docs.fiddler.ai/api/fiddler-python-client-sdk/schemas/dataset-data-source.md): Data source for explainability analysis using a sample from a dataset.
- [DeploymentParams](https://docs.fiddler.ai/api/fiddler-python-client-sdk/schemas/deployment-params.md): Configuration parameters for deploying a model in the Fiddler platform.
- [Enrichment](https://docs.fiddler.ai/api/fiddler-python-client-sdk/schemas/enrichment.md): Represents custom features derived from enrichment operations (Private Preview).
- [EventIdDataSource](https://docs.fiddler.ai/api/fiddler-python-client-sdk/schemas/event-id-data-source.md): Data source for explainability analysis using a specific event ID.
- [ImageEmbedding](https://docs.fiddler.ai/api/fiddler-python-client-sdk/schemas/image-embedding.md): Represents custom features derived from image embeddings for visual content analysis.
- [ModelSchema](https://docs.fiddler.ai/api/fiddler-python-client-sdk/schemas/model-schema.md): Defines the complete schema structure for a model's input data.
- [ModelSpec](https://docs.fiddler.ai/api/fiddler-python-client-sdk/schemas/model-spec.md): Defines how model columns are categorized and used along with model task configuration.
- [ModelTaskParams](https://docs.fiddler.ai/api/fiddler-python-client-sdk/schemas/model-task-params.md): Configuration parameters for different model task types and evaluation metrics.
- [Multivariate](https://docs.fiddler.ai/api/fiddler-python-client-sdk/schemas/multivariate.md): Represents custom features derived from multiple columns using clustering analysis.
- [RowDataSource](https://docs.fiddler.ai/api/fiddler-python-client-sdk/schemas/row-data-source.md): Data source for explainability analysis using a single row of data.
- [TextEmbedding](https://docs.fiddler.ai/api/fiddler-python-client-sdk/schemas/text-embedding.md): Represents custom features derived from text embeddings with TF-IDF analysis.
- [VectorFeature](https://docs.fiddler.ai/api/fiddler-python-client-sdk/schemas/vector-feature.md): Represents custom features derived from a single vector column using clustering analysis.
- [XaiParams](https://docs.fiddler.ai/api/fiddler-python-client-sdk/schemas/xai-params.md): Configuration parameters for explainability (XAI) analysis in Fiddler models.
- [Utils](https://docs.fiddler.ai/api/fiddler-python-client-sdk/utils.md)
- [create\_columns\_from\_df](https://docs.fiddler.ai/api/fiddler-python-client-sdk/utils/create-columns-from-df.md): Helper function to create Columns from a pandas DataFrame column dtypes.
- [group\_by](https://docs.fiddler.ai/api/fiddler-python-client-sdk/utils/group-by.md): Group the events by a column. Use this method to form the grouped data for ranking models.


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