# Tilebox Docs

## Docs

- [AI Assistance](https://docs.tilebox.com/ai-assistance.md): Large Language Models (LLMs) are powerful tools for exploring and learning about Tilebox. This section explains how to provide them with Tilebox-specific context for tailored, relevant and up-to-date responses.
- [As](https://docs.tilebox.com/api-reference/go/datasets/As.md)
- [Collect](https://docs.tilebox.com/api-reference/go/datasets/Collect.md)
- [CollectAs](https://docs.tilebox.com/api-reference/go/datasets/CollectAs.md)
- [Client.Collections.Create](https://docs.tilebox.com/api-reference/go/datasets/Collections.Create.md)
- [Client.Collections.Delete](https://docs.tilebox.com/api-reference/go/datasets/Collections.Delete.md)
- [Client.Collections.Get](https://docs.tilebox.com/api-reference/go/datasets/Collections.Get.md)
- [Client.Collections.GetOrCreate](https://docs.tilebox.com/api-reference/go/datasets/Collections.GetOrCreate.md)
- [Client.Collections.List](https://docs.tilebox.com/api-reference/go/datasets/Collections.List.md)
- [Client.Datapoints.Delete](https://docs.tilebox.com/api-reference/go/datasets/Datapoints.Delete.md)
- [Client.Datapoints.DeleteIDs](https://docs.tilebox.com/api-reference/go/datasets/Datapoints.DeleteIDs.md)
- [Client.Datapoints.GetInto](https://docs.tilebox.com/api-reference/go/datasets/Datapoints.GetInto.md)
- [Client.Datapoints.Ingest](https://docs.tilebox.com/api-reference/go/datasets/Datapoints.Ingest.md)
- [Client.Datapoints.Query](https://docs.tilebox.com/api-reference/go/datasets/Datapoints.Query.md)
- [Client.Datapoints.QueryInto](https://docs.tilebox.com/api-reference/go/datasets/Datapoints.QueryInto.md)
- [Client.Datasets.Get](https://docs.tilebox.com/api-reference/go/datasets/Get.md)
- [Client.Datasets.List](https://docs.tilebox.com/api-reference/go/datasets/List.md)
- [Client.Clusters.Create](https://docs.tilebox.com/api-reference/go/workflows/Clusters.Create.md)
- [Client.Clusters.Delete](https://docs.tilebox.com/api-reference/go/workflows/Clusters.Delete.md)
- [Client.Clusters.Get](https://docs.tilebox.com/api-reference/go/workflows/Clusters.Get.md)
- [Client.Clusters.List](https://docs.tilebox.com/api-reference/go/workflows/Clusters.List.md)
- [Collect](https://docs.tilebox.com/api-reference/go/workflows/Collect.md)
- [workflows.GetCurrentCluster](https://docs.tilebox.com/api-reference/go/workflows/GetCurrentCluster.md)
- [Client.Jobs.Cancel](https://docs.tilebox.com/api-reference/go/workflows/Jobs.Cancel.md)
- [Client.Jobs.Get](https://docs.tilebox.com/api-reference/go/workflows/Jobs.Get.md)
- [Client.Jobs.Query](https://docs.tilebox.com/api-reference/go/workflows/Jobs.Query.md)
- [Client.Jobs.Retry](https://docs.tilebox.com/api-reference/go/workflows/Jobs.Retry.md)
- [Client.Jobs.Submit](https://docs.tilebox.com/api-reference/go/workflows/Jobs.Submit.md)
- [Client.NewTaskRunner](https://docs.tilebox.com/api-reference/go/workflows/NewTaskRunner.md)
- [workflows.SubmitSubtask](https://docs.tilebox.com/api-reference/go/workflows/SubmitSubtask.md)
- [workflows.SubmitSubtasks](https://docs.tilebox.com/api-reference/go/workflows/SubmitSubtasks.md)
- [Task](https://docs.tilebox.com/api-reference/go/workflows/Task.md)
- [TaskRunner.GetRegisteredTask](https://docs.tilebox.com/api-reference/go/workflows/TaskRunner.GetRegisteredTask.md)
- [TaskRunner.RegisterTasks](https://docs.tilebox.com/api-reference/go/workflows/TaskRunner.RegisterTasks.md)
- [TaskRunner.Run](https://docs.tilebox.com/api-reference/go/workflows/TaskRunner.Run.md)
- [workflows.WithTaskSpan](https://docs.tilebox.com/api-reference/go/workflows/WithTaskSpan.md)
- [workflows.WithTaskSpanResult](https://docs.tilebox.com/api-reference/go/workflows/WithTaskSpanResult.md)
- [Client](https://docs.tilebox.com/api-reference/python/tilebox.datasets/Client.md)
- [Client.create_or_update_dataset](https://docs.tilebox.com/api-reference/python/tilebox.datasets/Client.create_or_update_dataset.md)
- [Client.dataset](https://docs.tilebox.com/api-reference/python/tilebox.datasets/Client.dataset.md)
- [Client.datasets](https://docs.tilebox.com/api-reference/python/tilebox.datasets/Client.datasets.md)
- [Collection.delete](https://docs.tilebox.com/api-reference/python/tilebox.datasets/Collection.delete.md)
- [Collection.find](https://docs.tilebox.com/api-reference/python/tilebox.datasets/Collection.find.md)
- [Collection.info](https://docs.tilebox.com/api-reference/python/tilebox.datasets/Collection.info.md)
- [Collection.ingest](https://docs.tilebox.com/api-reference/python/tilebox.datasets/Collection.ingest.md)
- [Collection.query](https://docs.tilebox.com/api-reference/python/tilebox.datasets/Collection.query.md)
- [Dataset.collection](https://docs.tilebox.com/api-reference/python/tilebox.datasets/Dataset.collection.md)
- [Dataset.collections](https://docs.tilebox.com/api-reference/python/tilebox.datasets/Dataset.collections.md)
- [Dataset.create_collection](https://docs.tilebox.com/api-reference/python/tilebox.datasets/Dataset.create_collection.md)
- [Dataset.delete_collection](https://docs.tilebox.com/api-reference/python/tilebox.datasets/Dataset.delete_collection.md)
- [Dataset.find](https://docs.tilebox.com/api-reference/python/tilebox.datasets/Dataset.find.md)
- [Dataset.get_or_create_collection](https://docs.tilebox.com/api-reference/python/tilebox.datasets/Dataset.get_or_create_collection.md)
- [Dataset.query](https://docs.tilebox.com/api-reference/python/tilebox.datasets/Dataset.query.md)
- [Client](https://docs.tilebox.com/api-reference/python/tilebox.workflows/Client.md)
- [Client.runner](https://docs.tilebox.com/api-reference/python/tilebox.workflows/Client.runner.md)
- [ClusterClient.all](https://docs.tilebox.com/api-reference/python/tilebox.workflows/ClusterClient.all.md)
- [ClusterClient.create](https://docs.tilebox.com/api-reference/python/tilebox.workflows/ClusterClient.create.md)
- [ClusterClient.delete](https://docs.tilebox.com/api-reference/python/tilebox.workflows/ClusterClient.delete.md)
- [ClusterClient.find](https://docs.tilebox.com/api-reference/python/tilebox.workflows/ClusterClient.find.md)
- [Context.job_cache](https://docs.tilebox.com/api-reference/python/tilebox.workflows/ExecutionContext.job_cache.md)
- [Context.submit_subtask](https://docs.tilebox.com/api-reference/python/tilebox.workflows/ExecutionContext.submit_subtask.md)
- [Context.submit_subtasks](https://docs.tilebox.com/api-reference/python/tilebox.workflows/ExecutionContext.submit_subtasks.md)
- [JobCache.__iter__](https://docs.tilebox.com/api-reference/python/tilebox.workflows/JobCache.__iter__.md)
- [JobCache.group](https://docs.tilebox.com/api-reference/python/tilebox.workflows/JobCache.group.md)
- [JobClient.cancel](https://docs.tilebox.com/api-reference/python/tilebox.workflows/JobClient.cancel.md)
- [JobClient.find](https://docs.tilebox.com/api-reference/python/tilebox.workflows/JobClient.find.md)
- [JobClient.query](https://docs.tilebox.com/api-reference/python/tilebox.workflows/JobClient.query.md)
- [JobClient.retry](https://docs.tilebox.com/api-reference/python/tilebox.workflows/JobClient.retry.md)
- [JobClient.submit](https://docs.tilebox.com/api-reference/python/tilebox.workflows/JobClient.submit.md)
- [JobClient.visualize](https://docs.tilebox.com/api-reference/python/tilebox.workflows/JobClient.visualize.md)
- [Task](https://docs.tilebox.com/api-reference/python/tilebox.workflows/Task.md)
- [TaskRunner.run_all](https://docs.tilebox.com/api-reference/python/tilebox.workflows/TaskRunner.run_all.md)
- [TaskRunner.run_forever](https://docs.tilebox.com/api-reference/python/tilebox.workflows/TaskRunner.run_forever.md)
- [Authentication](https://docs.tilebox.com/authentication.md): To access the Tilebox API, you must authenticate your requests. This guide explains how authentication works, focusing on API keys used as bearer tokens.
- [Product Updates](https://docs.tilebox.com/changelog.md): A chronological record of new features, improvements, and other notable changes shipped across the Tilebox platform. Updated regularly with each new release.
- [Console](https://docs.tilebox.com/console.md): A web interface for exploring your datasets and workflows, managing API keys and team members, and keeping track of your usage of the Tilebox platform.
- [Collections](https://docs.tilebox.com/datasets/concepts/collections.md): Collections organize data points within a dataset into logical groups that are commonly queried together, such as groupings by satellite or instrument.
- [Datasets](https://docs.tilebox.com/datasets/concepts/datasets.md): Datasets are strongly typed containers in which every data point within a collection shares the same structure, ensuring consistent and reliable data access.
- [Deleting Data](https://docs.tilebox.com/datasets/delete.md): Remove individual datapoints from a dataset collection by specifying their unique identifiers, or delete many at once by selecting an entire time range.
- [Working with Geometries](https://docs.tilebox.com/datasets/geometries.md): Best practices for handling geometries in Tilebox, covering winding order conventions and reference systems as well as edge cases like antimeridian crossings.
- [Ingesting Data](https://docs.tilebox.com/datasets/ingest.md): Populate your dataset collections by defining schemas, preparing structured data points, and submitting them efficiently to Tilebox for storage and querying.
- [Tilebox Datasets](https://docs.tilebox.com/datasets/introduction.md): A high-performance platform for structuring and querying satellite metadata, with curated open data catalogs and support for custom dataset collections.
- [Open Data](https://docs.tilebox.com/datasets/open-data.md): Browse the public satellite datasets available in Tilebox, ready to use for prototyping and building your applications before your own data is available.
- [Querying individual datapoints by ID](https://docs.tilebox.com/datasets/query/filter-by-id.md): Look up specific datapoints by ID across one or more dataset collections, without needing to construct and execute a broader query.
- [Filtering by a location](https://docs.tilebox.com/datasets/query/filter-by-location.md): Narrow down your query results to only include datapoints within a specific geographic area of interest by providing a geometry for the target region.
- [Querying by temporal extent](https://docs.tilebox.com/datasets/query/filter-by-time.md): Retrieve datapoints that fall within a given time period, with support for precise time intervals, open-ended time ranges, and exact timestamp lookups.
- [Querying data](https://docs.tilebox.com/datasets/query/querying-data.md): Access and filter data stored in your datasets using time-based and spatial queries, with built-in support for pagination and progress tracking.
- [Spatio-temporal](https://docs.tilebox.com/datasets/types/spatiotemporal.md): Spatio-temporal datasets associate each data point with both a timestamp and a geographic location on Earth, enabling queries that span time and space.
- [Timeseries](https://docs.tilebox.com/datasets/types/timeseries.md): Timeseries datasets associate each data point with a specific timestamp, making them well suited for organizing and querying time-ordered observations.
- [Access Sentinel-2 data](https://docs.tilebox.com/guides/datasets/access-sentinel2-data.md): Query Sentinel-2 satellite imagery metadata from a Tilebox dataset, filtering results by geographic area and time range to find exactly the data you need.
- [Creating a dataset](https://docs.tilebox.com/guides/datasets/create.md): Walk through creating a custom dataset in the Tilebox Console, from choosing the right dataset kind to defining your schema fields and organizing groups.
- [Ingesting data](https://docs.tilebox.com/guides/datasets/ingest.md): Walk through the full process of ingesting GeoParquet data into a Tilebox timeseries dataset, from downloading source files to previewing the results.
- [Ingesting from common file formats](https://docs.tilebox.com/guides/datasets/ingest-format.md): Convert data from common geospatial and tabular file formats into Tilebox datasets by loading them as DataFrames or xarray Datasets and ingesting directly.
- [Multi-language Workflows](https://docs.tilebox.com/guides/workflows/multi-language.md): Combine tasks written in different programming languages within a single workflow, letting you choose the best language for each individual processing step.
- [Tilebox](https://docs.tilebox.com/introduction.md): Tilebox is a developer-friendly tool for space data management and workflow orchestration, purpose-built for ground segment and orbital applications alike.
- [Quickstart](https://docs.tilebox.com/quickstart.md): This guide helps you set up and get started using Tilebox. It covers how to install a Tilebox client for your preferred language and how to use it to query data from a dataset and run a workflow.
- [Examples](https://docs.tilebox.com/sdks/go/examples.md): Get started quickly with standalone, runnable examples that demonstrate common patterns for building workflows and accessing datasets with the Go SDK.
- [Installation](https://docs.tilebox.com/sdks/go/install.md): Install and set up the Tilebox Go SDK and its companion code generation tool to start building workflows and accessing datasets from your applications.
- [Protobuf](https://docs.tilebox.com/sdks/go/protobuf.md): Understand how Protocol Buffers provide strongly typed data structures for working with Tilebox datasets in Go, and how to generate them for your projects.
- [Tilebox languages and SDKs](https://docs.tilebox.com/sdks/introduction.md): Official SDKs for Python and Go that provide full access to Tilebox datasets, storage, and workflow orchestration in your preferred programming language.
- [Async support](https://docs.tilebox.com/sdks/python/async.md): The Tilebox Python SDK offers full async support with asyncio, allowing you to run data operations in parallel for significantly better performance.
- [Installation](https://docs.tilebox.com/sdks/python/install.md): Install the Tilebox Python SDK packages using your preferred package manager to start working with datasets, workflows, and satellite data storage.
- [Sample notebooks](https://docs.tilebox.com/sdks/python/sample-notebooks.md): Get started quickly with ready-to-run Jupyter notebooks that demonstrate common satellite data access and analysis workflows using the Tilebox Python SDK.
- [Xarray](https://docs.tilebox.com/sdks/python/xarray.md): Tilebox uses Xarray as its primary data structure for representing and analyzing multi-dimensional satellite data with labeled dimensions and coordinates.
- [Storage Clients](https://docs.tilebox.com/storage/clients.md): Configure and use storage clients in the Tilebox Python SDK to access satellite data products from public providers and local file systems.
- [Caches](https://docs.tilebox.com/workflows/caches.md): Sharing data between tasks is crucial for workflows, especially in satellite imagery processing, where large datasets are the norm. Tilebox Workflows offers a straightforward API for storing and retrieving data from a shared cache.
- [Clusters](https://docs.tilebox.com/workflows/concepts/clusters.md)
- [Jobs](https://docs.tilebox.com/workflows/concepts/jobs.md)
- [Task Runners](https://docs.tilebox.com/workflows/concepts/task-runners.md)
- [Understanding and Creating Tasks](https://docs.tilebox.com/workflows/concepts/tasks.md)
- [Tilebox Workflows](https://docs.tilebox.com/workflows/introduction.md): The Tilebox workflow orchestrator is a parallel processing engine. It simplifies the creation of dynamic tasks that can be executed across various computing environments, including on-premise and auto-scaling clusters in public clouds.
- [Automations](https://docs.tilebox.com/workflows/near-real-time/automations.md): Trigger workflow jobs automatically in response to external events such as schedules or file changes, enabling near-real-time data processing pipelines.
- [Cron triggers](https://docs.tilebox.com/workflows/near-real-time/cron.md): Schedule recurring workflow jobs using cron expressions so that tasks run automatically at defined intervals, without requiring manual job submission.
- [Storage Event Triggers](https://docs.tilebox.com/workflows/near-real-time/storage-events.md): Trigger workflow jobs automatically whenever new objects are created or modified in a storage bucket, enabling event-driven data processing pipelines.
- [Logging](https://docs.tilebox.com/workflows/observability/logging.md): Collect logs from distributed task runners into a centralized observability backend so you can search and correlate them across your workflow cluster.
- [OpenTelemetry Integration](https://docs.tilebox.com/workflows/observability/open-telemetry.md): Gain full visibility into your workflow execution by integrating OpenTelemetry for distributed tracing and structured logging across your task runners.
- [Tracing](https://docs.tilebox.com/workflows/observability/tracing.md): Record and visualize workflow job execution as structured traces to understand task ordering, parallelism, and duration across distributed task runners.
- [Progress](https://docs.tilebox.com/workflows/progress.md): Report and visualize user-defined progress indicators during job execution to provide visibility into completion status and the estimated remaining time.

## OpenAPI Specs

- [openapi](https://docs.tilebox.com/api-reference/openapi.json)

## Optional

- [Console](https://console.tilebox.com)
- [Book a Demo](https://book.vimcal.com/p/lauracosta/tilebox-demo)
- [Discord](https://tilebox.com/discord)