SHARPpy
A collection of open source sounding and hodograph analysis routines, a sounding plotting package, and an interactive, cross-platform application for analyzing real-time soundings all written in Python.
https://github.com/sharppy/SHARPpy
Category: Atmosphere
Sub Category: Atmospheric Composition and Dynamics
Keywords
hodograph meteorology skew-t sounding
Keywords from Contributors
nexrad
Last synced: about 21 hours ago
JSON representation
Repository metadata
Sounding/Hodograph Analysis and Research Program in Python
- Host: GitHub
- URL: https://github.com/sharppy/SHARPpy
- Owner: sharppy
- License: other
- Created: 2014-05-16T21:27:05.000Z (almost 11 years ago)
- Default Branch: main
- Last Pushed: 2023-04-07T00:45:56.000Z (about 2 years ago)
- Last Synced: 2025-04-25T13:04:03.092Z (2 days ago)
- Topics: hodograph, meteorology, skew-t, sounding
- Language: Python
- Homepage: https://sharppy.github.io/SHARPpy/index.html
- Size: 80.6 MB
- Stars: 232
- Watchers: 37
- Forks: 109
- Open Issues: 63
- Releases: 8
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.rst
- Contributing: CONTRIBUTING.rst
- License: LICENSE.rst
README.md
SHARPpy
Sounding/Hodograph Analysis and Research Program in Python
SHARPpy is a collection of open source sounding and hodograph analysis routines, a sounding plotting package, and an interactive, cross-platform application for analyzing real-time soundings all written in Python. It was developed to provide the atmospheric science community a free and consistent source of sounding analysis routines. SHARPpy is constantly updated and vetted by professional meteorologists and climatologists within the scientific community to help maintain a standard source of sounding routines.
The version of SHARPpy in this repository allows users to access NUCAPS, a satellite sounding product.
Important links:
- HTML Documentation: http://sharppy.github.io/SHARPpy/index.html
- GitHub repository: https://github.com/sharppy/SHARPpy
Table of Contents
- Install Pre-requisites
- Install SHARPpy
- Running SHARPpy from the Command Line
- SHARPpy Development Team
=======================================================================
Install Pre-requisites
You will need Python 3 to run SHARPpy. For instructions, visit the following websites:
- https://www.anaconda.com/products/individual for instructions on how to set-up Python.
You will need run a few simple commands in a command line program:
- Linux/MacOS: Open the Terminal application.
- Windows: Open the Anaconda Prompt application.
Note: If you are installing Anaconda for multiple users, ensure these additional steps are met, which includes checking the permissions using an administrator account.
=======================================================================
Install SHARPpy
For those wishing to run both the GUI and do scripting, we recommend you install the Python 3 Anaconda Python Distribution from Continuum Analytics. You can install SHARPpy from conda by using:
conda install -c conda-forge sharppy
Skip to the 'Running SHARPpy from the Command Line' section.
Download options
If you aren't downloading from conda forge, you can download sharppy using the following options.
Option 1: Manual download (easy)
You can manually download the coding by clicking the "Code" button at the top right of the repository, then select "Download Zip." Unzip the files in the directory that you want to permanently store them.
Option 2: Download using Git (intermediate)
If you have Git installed and are familiar with it, open the command line for your operating system (see above) to perform these steps.
git clone https://github.com/sharppy/SHARPpy
Install SHARPpy
Open the terminal (UNIX/Linux) or Anaconda Prompt (Windows) and change your directory to where you have downloaded SHARPpy (e.g. /home/{user}/SHARPpy).
cd /home/<user>/SHARPpy
Next, we to create an isolated Anaconda environment just for running SHARPpy with all the necessary libraries (using conda env create {options}; it may take several minutes to install the libraries). If you are interested, you can open the environment.yml file to see which libraries are used.
conda env create -f environment.yml
After creating the environment, we need to switch to this new environment (via conda activate {env_name}) which we have named devel.
conda activate devel
Run setup.py to update SHARPpy.
python setup.py install
Once the installation is complete, keep the terminal open and follow the steps in the next section to launch SHARPpy.
Running SHARPpy from the Command Line
In the command line, type the command sharppy to launch the program.
sharppy
If successful, a window will open which will give you access to soundings from NUCAPS, RAOBS, and select models. For instructions on using SHARPpy, see the “Display NUCAPS in SHARPpy” quick guide.
How to run SHARPpy next time you log on
If you close the terminal window, you will have to repeat the following steps:
- Open the terminal (Unix/Linux) or Anaconda Prompt (Windows)
- Switch your environment to devel ("conda activate devel")
- Type sharppy and the window should launch.
conda activate devel
sharppy
=======================================================================
SHARPpy Development Team
SHARPpy is currently managed by the following co-developers (in no particular order):
- Patrick Marsh (SPC)
- Kelton Halbert (UW-Madison)
- Greg Blumberg (NASA GSFC)
- Tim Supinie (OU School of Meteorology)
- Rebekah Esmaili (Science and Technology Corp.)
- Jeff Szkodzinski (Science and Technology Corp.)
Owner metadata
- Name: sharppy
- Login: sharppy
- Email:
- Kind: organization
- Description:
- Website:
- Location:
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/10359202?v=4
- Repositories: 2
- Last ynced at: 2024-04-16T01:09:29.821Z
- Profile URL: https://github.com/sharppy
GitHub Events
Total
- Issues event: 4
- Watch event: 12
- Issue comment event: 8
Last Year
- Issues event: 4
- Watch event: 12
- Issue comment event: 8
Committers metadata
Last synced: 4 days ago
Total Commits: 1,786
Total Committers: 19
Avg Commits per committer: 94.0
Development Distribution Score (DDS): 0.521
Commits in past year: 0
Committers in past year: 0
Avg Commits per committer in past year: 0.0
Development Distribution Score (DDS) in past year: 0.0
Name | Commits | |
---|---|---|
Greg Blumberg | w****g@o****u | 856 |
keltonhalbert | k****t@t****m | 381 |
Tim Supinie | t****e@o****u | 339 |
tsupinie | t****e@g****m | 85 |
keltonhalbert | k****t@o****u | 40 |
Jeff Szkodzinski | j****i@g****m | 28 |
Jeff Szkodzinski | j****i@s****m | 16 |
Rebekah Esmaili | b****h@u****u | 13 |
Rebekah Esmaili | r****i@g****m | 7 |
Greg Blumberg | b****w@g****m | 5 |
Patrick Marsh | p****x@g****m | 5 |
Zac Flamig | Z****c@W****m | 3 |
Aaron Anderson | a****n@n****v | 2 |
Blumberg W G | w****g@b****v | 1 |
Kelton Halbert | k****t@K****t | 1 |
Nick Guy | n****r@g****m | 1 |
brettjrob | 5****b | 1 |
Niall Robinson | n****n@g****m | 1 |
keltonhalbert | k****t@w****u | 1 |
Committer domains:
- ou.edu: 3
- wisc.edu: 1
- keltons-mbp.attlocal.net: 1
- bds2-vm1.ornl.gov: 1
- noaa.gov: 1
- weatherwary.com: 1
- umd.edu: 1
- stcnet.com: 1
- tempestchasing.com: 1
Issue and Pull Request metadata
Last synced: 2 days ago
Total issues: 87
Total pull requests: 24
Average time to close issues: 5 months
Average time to close pull requests: about 2 months
Total issue authors: 64
Total pull request authors: 11
Average comments per issue: 3.48
Average comments per pull request: 1.25
Merged pull request: 7
Bot issues: 0
Bot pull requests: 1
Past year issues: 8
Past year pull requests: 0
Past year average time to close issues: N/A
Past year average time to close pull requests: N/A
Past year issue authors: 5
Past year pull request authors: 0
Past year average comments per issue: 1.25
Past year average comments per pull request: 0
Past year merged pull request: 0
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- rpdale (7)
- wblumberg (4)
- georgephillips1 (3)
- cjn1979 (3)
- dziban303 (2)
- mekkelley (2)
- Chun-ChihWang (2)
- tjturnage (2)
- odvigajlo (2)
- Linuxuser1234 (2)
- PerLundquist (2)
- dustwx28 (2)
- Ozzy405 (2)
- wedgef5 (2)
- weather01089 (1)
Top Pull Request Authors
- Jeff-Szkodzinski (6)
- collin-volk (4)
- wblumberg (4)
- keltonhalbert (2)
- resmaili (2)
- chird (1)
- blizzardwarriorwx (1)
- skovic (1)
- brettjrob (1)
- azure-pipelines[bot] (1)
- GeorgeMJ23 (1)
Top Issue Labels
- bug (3)
- enhancement (3)
- question (1)
- core_numerics (1)
- help wanted (1)
Top Pull Request Labels
- enhancement (2)
- bug (1)
Package metadata
- Total packages: 2
-
Total downloads:
- pypi: 2,707 last-month
- Total dependent packages: 0 (may contain duplicates)
- Total dependent repositories: 2 (may contain duplicates)
- Total versions: 6
- Total maintainers: 1
pypi.org: sharppy
Sounding/Hodograph Analysis and Research Program for Python
- Homepage: https://github.com/sharppy/SHARPpy
- Documentation: https://sharppy.readthedocs.io/
- Licenses: BSD
- Latest release: 1.4.0a5 (published over 5 years ago)
- Last Synced: 2025-04-25T13:05:06.611Z (2 days ago)
- Versions: 3
- Dependent Packages: 0
- Dependent Repositories: 1
- Downloads: 2,707 Last month
-
Rankings:
- Forks count: 4.48%
- Stargazers count: 4.76%
- Dependent packages count: 7.31%
- Average: 12.951%
- Dependent repos count: 22.088%
- Downloads: 26.116%
- Maintainers (1)
conda-forge.org: sharppy
SHARPpy is a collection of open source sounding and hodograph analysis routines, a sounding plotting package, and an interactive, cross-platform application for analyzing real-time soundings all written in Python. It was developed to provide the atmospheric science community a free and consistent source of sounding analysis routines. SHARPpy is updated and vetted by professional meteorologists and climatologists within the scientific community to help maintain a standard source of sounding routines.
- Homepage: https://github.com/sharppy/SHARPpy
- Licenses: BSD-3-Clause
- Latest release: 1.4.0 (published almost 5 years ago)
- Last Synced: 2025-04-01T02:09:04.709Z (26 days ago)
- Versions: 3
- Dependent Packages: 0
- Dependent Repositories: 1
-
Rankings:
- Forks count: 18.018%
- Dependent repos count: 24.103%
- Stargazers count: 27.157%
- Average: 30.205%
- Dependent packages count: 51.54%
Dependencies
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- sphinx-prompt *
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- thedoctor0/zip-release main composite
- ncipollo/release-action v1 composite
- EnricoMi/publish-unit-test-result-action v1 composite
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- ./.github/actions/run-release * composite
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- python 2.7 build
Score: 16.536118249380007