Skip to main content

"SunPy: Python for Solar Physics"

Project description

Latest Version codecov matrix Research software impact DOI Powered by NumFOCUS

SunPy is an open-source Python library for Solar Physics data analysis and visualization. Our homepage SunPy has more information about the project.

For some examples of using SunPy see our gallery, to see the latest changes in SunPy see our Changelog.

Installation

The recommended way to install SunPy is with miniconda. To install SunPy once conda is installed run the following two commands:

$ conda config --append channels conda-forge
$ conda install sunpy

For detailed installation instructions, see the installation guide in the SunPy docs.

Developing

If you want to develop SunPy you will need to install from GitHub. For detailed installation instructions, see Development installation in the SunPy docs.

Usage

Here is a quick example of plotting an AIA image:

>>> import sunpy.map
>>> from sunpy.data.sample import AIA_171_IMAGE
>>> aia = sunpy.map.Map(AIA_171_IMAGE)
>>> aia.peek()

Getting Help

For more information or to ask questions about SunPy, check out:

Contributing

Open Source Helpers

If you would like to get involved, start by joining the SunPy mailing list and check out the Developers Guide section of the SunPy docs. Stop by our chat room #sunpy:openastronomy.org if you have any questions. Help is always welcome so let us know what you like to work on, or check out the issues page for the list of known outstanding items.

For more information on contributing to SunPy, please read our Newcomers’ guide.

Code of Conduct

When you are interacting with the SunPy community you are asked to follow our Code of Conduct.

Project details


Release history Release notifications | RSS feed

This version

3.1.2

Download files

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

Source Distribution

sunpy-3.1.2.tar.gz (7.4 MB view details)

Uploaded Source

Built Distributions

sunpy-3.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (6.0 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

sunpy-3.1.2-cp310-cp310-macosx_10_9_x86_64.whl (5.9 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

sunpy-3.1.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (6.0 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

sunpy-3.1.2-cp39-cp39-macosx_10_9_x86_64.whl (5.9 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

sunpy-3.1.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (6.0 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

sunpy-3.1.2-cp38-cp38-macosx_10_9_x86_64.whl (5.9 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

sunpy-3.1.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (6.0 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

sunpy-3.1.2-cp37-cp37m-macosx_10_9_x86_64.whl (5.9 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

File details

Details for the file sunpy-3.1.2.tar.gz.

File metadata

  • Download URL: sunpy-3.1.2.tar.gz
  • Upload date:
  • Size: 7.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.0 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for sunpy-3.1.2.tar.gz
Algorithm Hash digest
SHA256 5eeb479c3f2424bf46355165249a1caa849872f8bee525349c4dca4d15b271fd
MD5 3ec09683e6b92571a49106e2c7d17ab4
BLAKE2b-256 40a02bd7ee67300e15c81a9535ab8bcefae737950ddc23ecd67b510b400fd6f0

See more details on using hashes here.

File details

Details for the file sunpy-3.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for sunpy-3.1.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 a36d53c4a25c0b59851e395ee23fe6cb9b91a0c6c10067a0cc58a2b0b9be071c
MD5 65f9f171ddaa808106dfa155f654a747
BLAKE2b-256 8e16560d2d53d5e72d6e7b335f6606b47b1145c1e72e5af69f49d81720e2a07c

See more details on using hashes here.

File details

Details for the file sunpy-3.1.2-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: sunpy-3.1.2-cp310-cp310-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 5.9 MB
  • Tags: CPython 3.10, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.0 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for sunpy-3.1.2-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 c676aa04ff822f4ae339583e9123c063d63c970648e6d319cf83077c3b1b9b09
MD5 41d94e6d96bb2cb5670418784c36ff6f
BLAKE2b-256 656865f27b20ed30dba3b33fe1aa3ec70de0a1629eadc1f621146e02e7051bcf

See more details on using hashes here.

File details

Details for the file sunpy-3.1.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for sunpy-3.1.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 768648fe9ddfb2ba4d79bdf9bd0f214b962a15865206ff8e3778e5e046a410ee
MD5 27f597398eb95678be61e84debfd0fbd
BLAKE2b-256 311e604160abf0431e0224813c87a04a3287b8f7ad442b4a17c0d51f8203c3e0

See more details on using hashes here.

File details

Details for the file sunpy-3.1.2-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: sunpy-3.1.2-cp39-cp39-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 5.9 MB
  • Tags: CPython 3.9, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.0 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for sunpy-3.1.2-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 c3c24da420c2d8e0383c20e0cf270ba90d1ece51f8fd27bfc6fad21b79d613b1
MD5 e36526d059e4375160c39003f05e7a5a
BLAKE2b-256 a64c3a017d4fa64339ef6200e137071e899c6f75c849dc9fe80d59f28fdf3ed2

See more details on using hashes here.

File details

Details for the file sunpy-3.1.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for sunpy-3.1.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 689e0c00ed60707c930120b67574d700ea5e00dc72fc1c947eebe3907d407e0b
MD5 1c9fd2fff9a28d720e4f5954eb162188
BLAKE2b-256 50930a7c744f2f8ca9bc20f454871166cb5dac7edbb3b45b2a3c052df4f2c04e

See more details on using hashes here.

File details

Details for the file sunpy-3.1.2-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: sunpy-3.1.2-cp38-cp38-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 5.9 MB
  • Tags: CPython 3.8, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.0 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for sunpy-3.1.2-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 d2765b91e7b37b31874d66fee7f2be42e735973ad949f916adb09ea9192429ff
MD5 59ecee643b6a39a44a4e34c1427f8009
BLAKE2b-256 d39d11e0551da23b46e34d544e9c40da106223f337465db722aed05e6f9c27fa

See more details on using hashes here.

File details

Details for the file sunpy-3.1.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for sunpy-3.1.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6156070f3cf80a078ddc3154a0445dd60291a20f1efac44ce68724d44886f555
MD5 4ed5aef551ca1cdbee2503a0aef72f5b
BLAKE2b-256 5c7677677a68d706c8675190d892899baaa45219d24317e4da3c3d87e9d5e823

See more details on using hashes here.

File details

Details for the file sunpy-3.1.2-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: sunpy-3.1.2-cp37-cp37m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 5.9 MB
  • Tags: CPython 3.7m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.0 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9

File hashes

Hashes for sunpy-3.1.2-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 2257df9fadefe3c32d412461e7a8e2b77e2dee1ad24bace2e660b2db703a8c05
MD5 bd6609b43ac3856a431c26d15d8d19be
BLAKE2b-256 84431c3d1d49539d840c4212faa89d928806ac2fb98759a9b820d81b6df9e591

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