brightwind

A Python library aims to empower wind resource analysts and establish a common industry standard toolset.
https://github.com/brightwind-dev/brightwind

Category: Renewable Energy
Sub Category: Wind Energy

Last synced: about 20 hours ago
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Repository metadata

Python library containing wind analysis functions

Host: GitHub
URL: https://github.com/brightwind-dev/brightwind
Owner: brightwind-dev
License: mit
Created: 2018-12-11T15:49:26.000Z (over 6 years ago)
Default Branch: master
Last Pushed: 2025-04-14T14:16:02.000Z (14 days ago)
Last Synced: 2025-04-20T09:44:34.262Z (8 days ago)
Language: Python
Homepage:
Size: 146 MB
Stars: 56
Watchers: 8
Forks: 20
Open Issues: 85
Releases: 15
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: contributing.md
- License: LICENSE.txt

README.md

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  / /_/ / /  / / /_/ / / / / /_ | |/ |/ / / / / / /_/ /
 /_.___/_/  /_/\__, /_/ /_/\__/ |__/|__/_/_/ /_/\__,_/
              /____/

A Python library primarily for wind resource assessments.

Brightwind is a Python library specifically built for wind analysis. It can load in wind speed, wind direction and
other metrological timeseries data. There are various plots you can use to understand this data and to find any
potential issues. You can perform many common functions to the data such as shear and long-term adjustments. The
resulting adjusted data is then outputted as a frequency distribution tab file which can be used in wind analysis
software such as WAsP.

This library can also be used for solar resource analysis.

Installation

You can use pip from the command line to install the library.

C:\Users\Stephen> pip install brightwind

It is advisable to use a separate environment to avoid any dependency clashes with other libraries such as Pandas, Numpy
or Matplotlib you may already have installed.

For those that do not have Python installed and are just getting started, we recommend installing Anaconda. Anaconda is
a Python distribution for scientific computing and so provides everything you need, Python, pip and Jupyter Notebook
along with libraries such as Pandas, Numpy and Matplotlib. Datacamp provide a good tutorial for installing
Anaconda on Windows to get started.

Once Anaconda is installed, you can use the Anaconda Prompt to run the above command line pip install brightwind.
Or first use Anaconda Navigator to create an environment.

Documentation

Documentation on how to get setup and use the library can be found at https://brightwind-dev.github.io/brightwind-docs/

Example usage of the brightwind library is shown below using Jupyter Notebook. Jupyter Notebook is a powerful way to
immediately see the results of code you have written.

demo_image_1
demo_image_2

Features

The library provides wind analysts with easy to use tools for working with
meteorological data. It supports loading of meteorological data, averaging,
filtering, plotting, correlations, shear analysis, long term adjustments, etc.
The library can then export a resulting long term adjusted tab file to be used in
other wind analysis software.

Benefits

The key benefits to an open-source library is that it provides complete transparency
and traceability. Anyone in the industry can review any part of the code and suggest changes,
thus creating a standardised, validated toolkit for the industry.

By default, during an assessment every manipulation or adjustment made to the wind data is
contained in a single file. This can easily be reviewed and checked by internal reviewers or,
as the underlying code is open-sourced, there is no reason why this file cannot be sent to
3rd parties for review thus increasing the effectiveness of a banks due diligence.

License

The library is licensed under the MIT license.

Test datasets

A test dataset is included in this repository and is used to demonstrate function and test functions in the code.
Other files and datasets are also included to complement this demo dataset. These are outlined below:

Dataset	Source	Notes
demo_data.csv	BrightWind	A modified 2 year met mast dataset in csv and Campbell Scientific format.
MERRA-2_XX_2000-01-01_2017-06-30.csv	NASA GES DISC	4 x MERRA-2 18-yr datasets to complement the demo data for long term analyses.
demo_cleaning_file.csv	BrightWind	A file containing information on what periods to clean out from the demo data.
windographer_flagging_log.txt	BrightWind	The same cleaning info as found in 'demo_cleaning_file.csv' formatted as a Windographer flagging file.
demo_data_iea43_wra_data_model.json	BrightWind	A JSON file formatted according to the IEA Wind Task 43 WRA Data Model standard which describes the mast configuration for the demo data.

Contributing

If you wish to be involved or find out more please contact [email protected].

More information can be found in the contributing.md section of the website.

Owner metadata

Name: brightwind
Login: brightwind-dev
Email:
Kind: organization
Description: The brightwind library aims to empower wind resource analysts and establish a common industry standard toolset.
Website:
Location:
Twitter:
Company:
Icon url: https://avatars.githubusercontent.com/u/45794645?v=4
Repositories: 1
Last ynced at: 2023-03-02T12:45:38.582Z
Profile URL: https://github.com/brightwind-dev

GitHub Events

Total

Create event: 15
Release event: 1
Issues event: 53
Watch event: 7
Delete event: 21
Issue comment event: 83
Push event: 250
Pull request review event: 147
Pull request review comment event: 116
Pull request event: 39
Fork event: 2

Last Year

Create event: 15
Release event: 1
Issues event: 53
Watch event: 7
Delete event: 21
Issue comment event: 83
Push event: 250
Pull request review event: 147
Pull request review comment event: 116
Pull request event: 39
Fork event: 2

Committers metadata

Last synced: 5 days ago

Total Commits: 1,359
Total Committers: 13
Avg Commits per committer: 104.538
Development Distribution Score (DDS): 0.624

Commits in past year: 64
Committers in past year: 5
Avg Commits per committer in past year: 12.8
Development Distribution Score (DDS) in past year: 0.422

Name	Email	Commits
stephenholleran	s**n@b**m	511
BiancaMorandi	b**i@g**m	347
Inder	s**5@g**m	303
Luke Cunningham	l**n@t**e	112
rach185	r**l@b**m	36
AndyBrightWind	4****d	16
olivia-bentley	o**y@b**m	15
ShaneBrightWind	3****d	9
r-molins-mrp	r**s@m**m	4
shwetajoshi601	s**1@g**m	3
Rowan Molony	r**y@m**m	1
abohara	t**2@g**m	1
amralaa95	a**3@g**m	1

Committer domains:

Issue and Pull Request metadata

Last synced: 2 days ago

Total issues: 291
Total pull requests: 222
Average time to close issues: 6 months
Average time to close pull requests: about 1 month
Total issue authors: 22
Total pull request authors: 13
Average comments per issue: 2.18
Average comments per pull request: 0.67
Merged pull request: 194
Bot issues: 0
Bot pull requests: 0

Past year issues: 45
Past year pull requests: 35
Past year average time to close issues: 3 months
Past year average time to close pull requests: 21 days
Past year issue authors: 11
Past year pull request authors: 7
Past year average comments per issue: 1.04
Past year average comments per pull request: 1.31
Past year merged pull request: 27
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/brightwind-dev/brightwind

Top Issue Authors

stephenholleran (120)
BiancaMorandi (92)
ShaneBrightWind (22)
rach185 (11)
AndyBrightWind (11)
inder-preet-kakkar (8)
lucunnin (7)
Ilirmc (4)
py-jv (2)
geekwg (2)
mdavid800 (1)
r-molins-mrp (1)
SteveCordleBW (1)
conorcoady (1)
amralaa95 (1)

Top Pull Request Authors

stephenholleran (74)
BiancaMorandi (55)
inder-preet-kakkar (27)
lucunnin (18)
olivia-bentley (17)
AndyBrightWind (11)
rach185 (9)
ShaneBrightWind (3)
r-molins-mrp (3)
amralaa95 (2)
Ilirmc (1)
rdmolony (1)
abohara (1)

Top Issue Labels

bug (93)
function improvement (66)
enhancement (66)
documentation (22)
tutorial (7)
good first issue (5)
question (4)

Top Pull Request Labels

bug (45)
function improvement (14)
enhancement (14)
good first issue (1)

Package metadata

Total packages: 1
Total downloads:
- pypi: 617 last-month
Total dependent packages: 0
Total dependent repositories: 1
Total versions: 12
Total maintainers: 1

pypi.org: brightwind

Scripts for wind resource data processing.

Homepage: https://github.com/brightwind-dev/brightwind.git
Documentation: https://brightwind.readthedocs.io/
Licenses: MIT
Latest release: 2.3.0 (published 14 days ago)
Last Synced: 2025-04-26T12:35:03.658Z (2 days ago)
Versions: 12
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 617 Last month
Rankings:
- Dependent packages count: 7.306%
- Forks count: 9.37%
- Stargazers count: 10.454%
- Average: 15.295%
- Dependent repos count: 22.077%
- Downloads: 27.265%
Maintainers (1)
- sholleran

Dependencies

requirements.txt pypi

boto3 >=1.9.66
gmaps >=0.9.0
ipython >=7.4.0
ipywidgets >=7.4.2
matplotlib >=3.0.3
numpy >=1.16.4
pandas >=0.24.0,<=0.25.3
pytest >=4.1.0
python-dateutil >=2.8.0
requests >=2.20.0
scikit-learn >=0.19.1
scipy >=0.19.1
six >=1.12.0

setup.py pypi

boto3 >=1.9.66
gmaps >=0.9.0
ipython >=7.4.0
ipywidgets >=7.4.2
matplotlib >=3.0.3
numpy >=1.16.4
pandas >=0.24.0,
pytest >=
python-dateutil >=2.8.0
requests >=2.20.0
scikit-learn >=0.19.1
scipy >=0.19.1
six >=

.github/workflows/tests.yml actions

actions/checkout v3 composite
actions/setup-python v4 composite

Score: 13.941814520524302

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