tiled
Structured Scientific Data Access Service
Decision gist · record as of 2026-08-14
Yes, if you work with scientific data at scale or need to share datasets with collaborators. The package is actively maintained, has low install friction, carries a permissive license, and solves a real problem in scientific data access. Install just the client if you only need to consume data from an existing Tiled server.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Accessing remote data requires a running Tiled server or public instance URL.
- Low install friction with a pure-Python wheel and active maintenance—last release 3 days ago.
License · maintenance · safety
permissive license (permissive) — Permissive BSD license allows commercial and private use without restriction.
last release 2026-08-11 (3 days) · last repo commit 2026-08-11 · 92 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 177,189 downloads/mo, #10,222 on PyPI
Alternatives
Verify before relying
pip install tiled
from tiled.client import from_uri
client = from_uri('http://example.com')
data = client['dataset_name'].read()- Whether the package includes built-in server deployment tooling or if server setup requires separate infrastructure.
- Performance characteristics when slicing or streaming large datasets over the network.
- Authentication and access control mechanisms beyond the 'secure' description in the project summary.
- Specific example code patterns for common workflows like metadata search and format transcoding.
What it is and what it does
Tiled is a Python service that provides structured, secure access to scientific data stored locally or remotely. It acts as an intermediary layer between scientists and their data, enabling search across metadata, remote slicing into arrays and tables, format conversion, and live data streaming. The package includes both client and server components—scientists can use the client to query and retrieve data from a Tiled server, or deploy their own server to share datasets with collaborators.
The client-side library handles communication with Tiled servers via HTTP, supporting operations like metadata search, remote slicing so you fetch only what you need, transcoding into different formats, and downloading underlying data files. It's designed to work at any scale, from a single laptop to a facility data center, and integrates with scientific Python tools through standard formats like arrays and tables.
Use it for
- Search and retrieve specific subsets of large scientific datasets without downloading entire files.
- Convert data between formats on the server side before transfer to reduce bandwidth.
- Stream live experimental data or replay recent data for analysis and visualization.
- Share datasets across a research group with fine-grained access control and metadata discovery.
- Build data catalogs where scientists can locate and access datasets by metadata without knowing file paths.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you work with scientific data at scale or need to share datasets with collaborators.
The package is actively maintained, has low install friction, carries a permissive license, and solves a real problem in scientific data access. Install just the client if you only need to consume data from an existing Tiled server.
Install
tiled on PyPI
Before you install
Low install friction with a pure-Python wheel and active maintenance—last release 3 days ago. Requires Python 3.10 or later and pulls in 11 runtime dependencies including httpx, pydantic, and msgpack.
Requires Python 3.10 or later. Accessing remote data requires a running Tiled server or public instance URL.
License in practice
Permissive BSD license allows commercial and private use without restriction.
Quickstart
pip install tiled
from tiled.client import from_uri
client = from_uri('http://example.com')
data = client['dataset_name'].read()Verify before relying
- Whether the package includes built-in server deployment tooling or if server setup requires separate infrastructure.
- Performance characteristics when slicing or streaming large datasets over the network.
- Authentication and access control mechanisms beyond the 'secure' description in the project summary.
- Specific example code patterns for common workflows like metadata search and format transcoding.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 11 packageshttpxjson-merge-patchjsonpatchjsonschemamsgpackorjsonplatformdirspydantic-settingspydanticpyyamltyper |
| Maintenance | Actively maintained 3 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 177,189 / month, #10,222 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaLicense :: OSI Approved :: BSD LicenseProgramming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Scientific/Engineering :: Physics |
Evidence: tiled-0.2.15-py3-none-any.whl
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See also multiscale-spatial-image · pytiled-parser · pmtiles · tensordict · geos · large-image · raft-dask-cu12 · mosaicml-streaming · odc-loader · rerun-sdk