tifffile
Read and write TIFF files
Decision gist · record as of 2026-08-14
Yes. Tifffile is a mature, actively maintained library with low install friction, no known vulnerabilities, and permissive licensing. It is the standard choice for TIFF I/O in scientific Python when you need broad format support and bioimaging compatibility. Install it if you work with TIFF files, microscopy data, or need to convert between TIFF variants.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.12 or later.
- Optional dependencies (imagecodecs, zarr, xarray, lxml) unlock compression, Zarr stores, and advanced metadata handling.
- Low install friction with a single runtime dependency (numpy).
License · maintenance · safety
BSD-3-Clause (permissive) — BSD-3-Clause is permissive; you can use, modify, and distribute tifffile with minimal restrictions, provided you include the license notice.
last release 2026-08-01 (13 days) · last repo commit 2026-08-01 · 662 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 29,553,745 downloads/mo, #812 on PyPI
Alternatives
Verify before relying
pip install tifffile
import tifffile
import numpy as np
# Read a TIFF file
image = tifffile.imread('file.tiff')
# Write a NumPy array to TIFF
tifffile.imwrite('output.tiff', image)- Whether optional dependencies (imagecodecs, zarr, xarray, lxml, matplotlib, kerchunk) are automatically installed or must be manually added for specific workflows.
- Performance characteristics and memory efficiency when reading or writing large multi-dimensional TIFF files.
What it is and what it does
Tifffile is a comprehensive Python library for reading and writing TIFF files and related bioimaging formats. It stores NumPy arrays directly in TIFF (Tagged Image File Format) files and reads image data and metadata from TIFF, BigTIFF, OME-TIFF, GeoTIFF, Adobe DNG, and many proprietary bioimaging formats used in microscopy and medical imaging. The library handles strips, tiles, pages, multi-dimensional series, and pyramidal levels, returning data as NumPy or Zarr arrays.
Tifffile supports a wide range of compression schemes (LZW, JPEG, JPEG 2000, Zstd, WebP, PNG, and others) via the imagecodecs library, and can write multi-page, volumetric, pyramidal, and memory-mappable TIFF files. It also provides tools to inspect TIFF structures, read multi-dimensional file sequences, write fsspec ReferenceFileSystem metadata, and parse proprietary metadata formats. The package is actively maintained and includes a command-line interface for inspecting and previewing TIFF files.
Use it for
- Store and retrieve NumPy arrays in TIFF format for scientific imaging workflows.
- Read microscopy and bioimaging files (OME-TIFF, Zeiss LSM, Hamamatsu NDPI) with metadata preservation.
- Convert between TIFF variants and compression schemes for interoperability across imaging software.
- Access large multi-dimensional image data as memory-mapped or Zarr arrays without loading entire files.
- Inspect TIFF file structure and metadata from the command line or programmatically.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Tifffile is a mature, actively maintained library with low install friction, no known vulnerabilities, and permissive licensing. It is the standard choice for TIFF I/O in scientific Python when you need broad format support and bioimaging compatibility. Install it if you work with TIFF files, microscopy data, or need to convert between TIFF variants.
Install
tifffile on PyPI
Before you install
Low install friction with a single runtime dependency (numpy). Active maintenance with a release 13 days old and recent commits; the package is in Beta status but has been maintained since 2014.
Requires Python 3.12 or later. Optional dependencies (imagecodecs, zarr, xarray, lxml) unlock compression, Zarr stores, and advanced metadata handling.
License in practice
BSD-3-Clause is permissive; you can use, modify, and distribute tifffile with minimal restrictions, provided you include the license notice.
Quickstart
pip install tifffile
import tifffile
import numpy as np
# Read a TIFF file
image = tifffile.imread('file.tiff')
# Write a NumPy array to TIFF
tifffile.imwrite('output.tiff', image)Verify before relying
- Whether optional dependencies (imagecodecs, zarr, xarray, lxml, matplotlib, kerchunk) are automatically installed or must be manually added for specific workflows.
- Performance characteristics and memory efficiency when reading or writing large multi-dimensional TIFF files.
Package facts
| License | BSD-3-Clause permissive |
| Python support | Supports the current Python release >=3.12 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagenumpy |
| Maintenance | Actively maintained 13 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 29,553,745 / month, #812 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersIntended Audience :: Science/ResearchOperating System :: OS IndependentProgramming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.15 |
Evidence: tifffile-2026.7.31-py3-none-any.whl
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