Skip to main content

Fast and direct raster I/O for use with Numpy and SciPy

Project description

Rasterio reads and writes geospatial raster data.

https://travis-ci.com/mapbox/rasterio.png?branch=master https://coveralls.io/repos/github/mapbox/rasterio/badge.svg?branch=master

Geographic information systems use GeoTIFF and other formats to organize and store gridded, or raster, datasets. Rasterio reads and writes these formats and provides a Python API based on N-D arrays.

Rasterio 1.2 works with Python versions 3.6 through 3.9, Numpy versions 1.15 and newer, and GDAL versions 2.3 through 3.2. Official binary packages for Linux and Mac OS X are available on PyPI. Unofficial binary packages for Windows are available through other channels.

Read the documentation for more details: https://rasterio.readthedocs.io/.

Example

Here’s an example of some basic features that Rasterio provides. Three bands are read from an image and averaged to produce something like a panchromatic band. This new band is then written to a new single band TIFF.

import numpy as np
import rasterio

# Read raster bands directly to Numpy arrays.
#
with rasterio.open('tests/data/RGB.byte.tif') as src:
    r, g, b = src.read()

# Combine arrays in place. Expecting that the sum will
# temporarily exceed the 8-bit integer range, initialize it as
# a 64-bit float (the numpy default) array. Adding other
# arrays to it in-place converts those arrays "up" and
# preserves the type of the total array.
total = np.zeros(r.shape)
for band in r, g, b:
    total += band
total /= 3

# Write the product as a raster band to a new 8-bit file. For
# the new file's profile, we start with the meta attributes of
# the source file, but then change the band count to 1, set the
# dtype to uint8, and specify LZW compression.
profile = src.profile
profile.update(dtype=rasterio.uint8, count=1, compress='lzw')

with rasterio.open('example-total.tif', 'w', **profile) as dst:
    dst.write(total.astype(rasterio.uint8), 1)

The output:

http://farm6.staticflickr.com/5501/11393054644_74f54484d9_z_d.jpg

API Overview

Rasterio gives access to properties of a geospatial raster file.

with rasterio.open('tests/data/RGB.byte.tif') as src:
    print(src.width, src.height)
    print(src.crs)
    print(src.transform)
    print(src.count)
    print(src.indexes)

# Printed:
# (791, 718)
# {u'units': u'm', u'no_defs': True, u'ellps': u'WGS84', u'proj': u'utm', u'zone': 18}
# Affine(300.0379266750948, 0.0, 101985.0,
#        0.0, -300.041782729805, 2826915.0)
# 3
# [1, 2, 3]

A rasterio dataset also provides methods for getting extended array slices given georeferenced coordinates.

with rasterio.open('tests/data/RGB.byte.tif') as src:
    print src.window(**src.window_bounds(((100, 200), (100, 200))))

# Printed:
# ((100, 200), (100, 200))

Rasterio CLI

Rasterio’s command line interface, named “rio”, is documented at cli.rst. Its rio insp command opens the hood of any raster dataset so you can poke around using Python.

$ rio insp tests/data/RGB.byte.tif
Rasterio 0.10 Interactive Inspector (Python 3.4.1)
Type "src.meta", "src.read(1)", or "help(src)" for more information.
>>> src.name
'tests/data/RGB.byte.tif'
>>> src.closed
False
>>> src.shape
(718, 791)
>>> src.crs
{'init': 'epsg:32618'}
>>> b, g, r = src.read()
>>> b
masked_array(data =
 [[-- -- -- ..., -- -- --]
 [-- -- -- ..., -- -- --]
 [-- -- -- ..., -- -- --]
 ...,
 [-- -- -- ..., -- -- --]
 [-- -- -- ..., -- -- --]
 [-- -- -- ..., -- -- --]],
             mask =
 [[ True  True  True ...,  True  True  True]
 [ True  True  True ...,  True  True  True]
 [ True  True  True ...,  True  True  True]
 ...,
 [ True  True  True ...,  True  True  True]
 [ True  True  True ...,  True  True  True]
 [ True  True  True ...,  True  True  True]],
       fill_value = 0)

>>> np.nanmin(b), np.nanmax(b), np.nanmean(b)
(0, 255, 29.94772668847656)

Rio Plugins

Rio provides the ability to create subcommands using plugins. See cli.rst for more information on building plugins.

See the plugin registry for a list of available plugins.

Installation

Please install Rasterio in a virtual environment so that its requirements don’t tamper with your system’s Python.

SSL certs

The Linux wheels on PyPI are built on CentOS and libcurl expects certs to be in /etc/pki/tls/certs/ca-bundle.crt. Ubuntu’s certs, for example, are in a different location. You may need to use the CURL_CA_BUNDLE environment variable to specify the location of SSL certs on your computer. On an Ubuntu system set the variable as shown below.

$ export CURL_CA_BUNDLE=/etc/ssl/certs/ca-certificates.crt

Dependencies

Rasterio has a C library dependency: GDAL >= 2.3. GDAL itself depends on some other libraries provided by most major operating systems and also depends on the non standard GEOS and PROJ4 libraries. How to meet these requirement will be explained below.

Rasterio’s Python dependencies are listed in its requirements.txt file.

Development also requires (see requirements-dev.txt) Cython and other packages.

Binary Distributions

Use a binary distributions that directly or indirectly provide GDAL if possible.

Linux

Rasterio distributions are available from UbuntuGIS and Anaconda’s conda-forge channel.

Manylinux1 wheels are available on PyPI.

OS X

Binary distributions with GDAL, GEOS, and PROJ4 libraries included are available for OS X versions 10.9+. To install, run pip install rasterio. These binary wheels are preferred by newer versions of pip.

If you don’t want these wheels and want to install from a source distribution, run pip install rasterio --no-binary rasterio instead.

The included GDAL library is fairly minimal, providing only the format drivers that ship with GDAL and are enabled by default. To get access to more formats, you must build from a source distribution (see below).

Windows

Binary wheels for rasterio and GDAL are created by Christoph Gohlke and are available from his website.

To install rasterio, simply download both binaries for your system (rasterio and GDAL) and run something like this from the downloads folder, adjusting for your Python version.

$ pip install -U pip
$ pip install GDAL‑3.1.4‑cp39‑cp39‑win_amd64.whl
$ pip install rasterio‑1.1.8‑cp39‑cp39‑win_amd64.whl

You can also install rasterio with conda using Anaconda’s conda-forge channel.

$ conda install -c conda-forge rasterio

Source Distributions

Rasterio is a Python C extension and to build you’ll need a working compiler (XCode on OS X etc). You’ll also need Numpy preinstalled; the Numpy headers are required to run the rasterio setup script. Numpy has to be installed (via the indicated requirements file) before rasterio can be installed. See rasterio’s Travis configuration for more guidance.

Linux

The following commands are adapted from Rasterio’s Travis-CI configuration.

$ sudo add-apt-repository ppa:ubuntugis/ppa
$ sudo apt-get update
$ sudo apt-get install gdal-bin libgdal-dev
$ pip install -U pip
$ pip install rasterio

Adapt them as necessary for your Linux system.

OS X

For a Homebrew based Python environment, do the following.

$ brew update
$ brew install gdal
$ pip install -U pip
$ pip install --no-binary rasterio

Windows

You can download a binary distribution of GDAL from here. You will also need to download the compiled libraries and headers (include files).

When building from source on Windows, it is important to know that setup.py cannot rely on gdal-config, which is only present on UNIX systems, to discover the locations of header files and libraries that rasterio needs to compile its C extensions. On Windows, these paths need to be provided by the user. You will need to find the include files and the library files for gdal and use setup.py as follows. You will also need to specify the installed gdal version through the GDAL_VERSION environment variable.

$ python setup.py build_ext -I<path to gdal include files> -lgdal_i -L<path to gdal library> install

With pip

$ pip install --no-use-pep517 --global-option -I<path to gdal include files> -lgdal_i -L<path to gdal library> .

Note: --no-use-pep517 is required as pip currently hasn’t implemented a way for optional arguments to be passed to the build backend when using PEP 517. See here for more details.

Alternatively environment variables (e.g. INCLUDE and LINK) used by MSVC compiler can be used to point to include directories and library files.

We have had success compiling code using the same version of Microsoft’s Visual Studio used to compile the targeted version of Python (more info on versions used here.).

Note: The GDAL DLL and gdal-data directory need to be in your Windows PATH otherwise rasterio will fail to work.

Support

The primary forum for questions about installation and usage of Rasterio is https://rasterio.groups.io/g/main. The authors and other users will answer questions when they have expertise to share and time to explain. Please take the time to craft a clear question and be patient about responses.

Please do not bring these questions to Rasterio’s issue tracker, which we want to reserve for bug reports and other actionable issues.

While Rasterio’s repo is in the Mapbox GitHub organization, Mapbox’s Support team is focused on customer support for its commercial platform and Rasterio support requests may be perfunctorily closed with or without a link to https://rasterio.groups.io/g/main. It’s better to bring questions directly to the main Rasterio group at groups.io.

Development and Testing

See CONTRIBUTING.rst.

Documentation

See docs/.

License

See LICENSE.txt.

Authors

See AUTHORS.txt.

Changes

See CHANGES.txt.

Who is Using Rasterio?

See here.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

rasterio-1.2b3.tar.gz (2.2 MB view details)

Uploaded Source

Built Distributions

rasterio-1.2b3-cp39-cp39-manylinux1_x86_64.whl (19.1 MB view details)

Uploaded CPython 3.9

rasterio-1.2b3-cp39-cp39-macosx_10_9_x86_64.whl (20.6 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

rasterio-1.2b3-cp38-cp38-manylinux1_x86_64.whl (19.1 MB view details)

Uploaded CPython 3.8

rasterio-1.2b3-cp38-cp38-macosx_10_9_x86_64.whl (20.5 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

rasterio-1.2b3-cp37-cp37m-manylinux1_x86_64.whl (19.1 MB view details)

Uploaded CPython 3.7m

rasterio-1.2b3-cp37-cp37m-macosx_10_9_x86_64.whl (20.5 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

rasterio-1.2b3-cp36-cp36m-manylinux1_x86_64.whl (19.1 MB view details)

Uploaded CPython 3.6m

rasterio-1.2b3-cp36-cp36m-macosx_10_9_x86_64.whl (20.6 MB view details)

Uploaded CPython 3.6m macOS 10.9+ x86-64

File details

Details for the file rasterio-1.2b3.tar.gz.

File metadata

  • Download URL: rasterio-1.2b3.tar.gz
  • Upload date:
  • Size: 2.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/51.1.2 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.7.5

File hashes

Hashes for rasterio-1.2b3.tar.gz
Algorithm Hash digest
SHA256 ad11e925df52dccc5aa9c300ee1c7eab7e8ace40d8b7ca08b53e10abd3480d9f
MD5 dc5b95d951999ed3224275840856aaf3
BLAKE2b-256 415451e7e972c248043b8df5dec833b2aff57b300064c8b87e7150d729419978

See more details on using hashes here.

File details

Details for the file rasterio-1.2b3-cp39-cp39-manylinux1_x86_64.whl.

File metadata

  • Download URL: rasterio-1.2b3-cp39-cp39-manylinux1_x86_64.whl
  • Upload date:
  • Size: 19.1 MB
  • Tags: CPython 3.9
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/51.1.2 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.7.5

File hashes

Hashes for rasterio-1.2b3-cp39-cp39-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 e7460c51e313d62cc1a4cbf5bdbe6688b9402112bc91b335bf89a317acc38071
MD5 d3e2e07cce4b73e5f50f095a0ecb08a8
BLAKE2b-256 3ad8aae35471898b0e9e1c5df7d2c0053382a6d533317b53b1665160fc79fa5d

See more details on using hashes here.

File details

Details for the file rasterio-1.2b3-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: rasterio-1.2b3-cp39-cp39-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 20.6 MB
  • Tags: CPython 3.9, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/51.1.2 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.7.5

File hashes

Hashes for rasterio-1.2b3-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 b0e86d0dc185ed74113aea72c9fb2d0c489a37f4c5e8316d71dc35c7e0a7dad5
MD5 a9951bbafd4cd66d47efad125f19d5c9
BLAKE2b-256 558cf96426b3e0ed4c42ade4cb7ee8dcedd417c77b83ffee7b5f534ba1995968

See more details on using hashes here.

File details

Details for the file rasterio-1.2b3-cp38-cp38-manylinux1_x86_64.whl.

File metadata

  • Download URL: rasterio-1.2b3-cp38-cp38-manylinux1_x86_64.whl
  • Upload date:
  • Size: 19.1 MB
  • Tags: CPython 3.8
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/51.1.2 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.7.5

File hashes

Hashes for rasterio-1.2b3-cp38-cp38-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 4a41d5ab8e61ea65fe6700c916307a1f5df68b0de52fd27fa99b34aa5dd9c877
MD5 db6c9e633a3e8b4a7bf07cc3cd3d7568
BLAKE2b-256 8b245dae0d0f0c3741736fdd236784e1d0b6317e61fe2e61f9b7403c72cac231

See more details on using hashes here.

File details

Details for the file rasterio-1.2b3-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: rasterio-1.2b3-cp38-cp38-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 20.5 MB
  • Tags: CPython 3.8, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/51.1.2 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.7.5

File hashes

Hashes for rasterio-1.2b3-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 36e407844f073e97c4903540471be8b765a77f5411232fc8ee33f211e3ba8d52
MD5 e04de238bdd4398cebb3ee553f10c4ff
BLAKE2b-256 c9941fe9d774ef3ee1686c9972f661f0c7bf329997a5bf94ddb58edb4544f83f

See more details on using hashes here.

File details

Details for the file rasterio-1.2b3-cp37-cp37m-manylinux1_x86_64.whl.

File metadata

  • Download URL: rasterio-1.2b3-cp37-cp37m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 19.1 MB
  • Tags: CPython 3.7m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/51.1.2 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.7.5

File hashes

Hashes for rasterio-1.2b3-cp37-cp37m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 1d0c49e32c147bd1cdf92db1f7c7bb8542f857c98049861b4e2c193084355d81
MD5 60b87d52fef328e92ddc3967d2d18014
BLAKE2b-256 15ab583c9a8866c116d55e03706845b43240a6aae5c42a4c801ff89e7d12c0ad

See more details on using hashes here.

File details

Details for the file rasterio-1.2b3-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: rasterio-1.2b3-cp37-cp37m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 20.5 MB
  • Tags: CPython 3.7m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/51.1.2 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.7.5

File hashes

Hashes for rasterio-1.2b3-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 42ab24c81cbfbfcc751e2674728bbb31d948c6500faa8c0173bb6a25189fdca8
MD5 b480bcd85bc974ce4cd60b3f572b56f6
BLAKE2b-256 904b8c63ee5b3f01f3703912ac75d6aa0e1da2b20edcd709114cc3d67e7a73b9

See more details on using hashes here.

File details

Details for the file rasterio-1.2b3-cp36-cp36m-manylinux1_x86_64.whl.

File metadata

  • Download URL: rasterio-1.2b3-cp36-cp36m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 19.1 MB
  • Tags: CPython 3.6m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/51.1.2 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.7.5

File hashes

Hashes for rasterio-1.2b3-cp36-cp36m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 358bc67f917f27a6c766b2ea4035412d67aa352b465fee3c3f88e18d1533dc72
MD5 1959b0b11ec693a9b45f0797e1c12fdb
BLAKE2b-256 e1a17ead1145d44dd5d307a08dd65b0b7d62534a188b38584b4b57a842f31cb6

See more details on using hashes here.

File details

Details for the file rasterio-1.2b3-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: rasterio-1.2b3-cp36-cp36m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 20.6 MB
  • Tags: CPython 3.6m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/51.1.2 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.7.5

File hashes

Hashes for rasterio-1.2b3-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 0ae62b68e28beec9a3df9dd4eaf59c07da32f0b2c7aa44d5cb2d5f547e7d828b
MD5 3ebf4d373274ca6d7b4934ed7ce14eae
BLAKE2b-256 3e0e343b9365f579e680cb871c4adfe35ef316906df112a49a308d28cc489b53

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page