pygeohydro VS clouddrift

Compare pygeohydro vs clouddrift and see what are their differences.

pygeohydro

A part of HyRiver software stack for accessing hydrology data through web services (by hyriver)

clouddrift

CloudDrift accelerates the use of Lagrangian data for atmospheric, oceanic, and climate sciences. (by Cloud-Drift)
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pygeohydro clouddrift
1 1
63 32
- -
9.2 8.8
7 days ago 2 days ago
Python Python
GNU General Public License v3.0 or later MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

pygeohydro

Posts with mentions or reviews of pygeohydro. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-03-04.

clouddrift

Posts with mentions or reviews of clouddrift. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-16.
  • Show HN: Clouddrift (Python lib) – 170 years of Cyclone Track Data
    2 projects | news.ycombinator.com | 16 Apr 2024
    Hey HN! I've recently taken on the role of lead developer for the clouddrift Python library, and I'd like to share a new dataset integration we've recently added. The purpose of the clouddrift library is to ease the process of working with ragged array data structures, particularly the ones encountered with Lagrangian datasets in atmospheric, oceanic, and climate sciences.

    For those who might not be familiar, Lagrangian datasets track the movement of sensing platforms or particles (or in the case below, atmospheric phenomena like cyclones) through space and time, providing a detailed path of their journey. This is in contrast to Eulerian datasets, which focus on changes in a fixed location.

    The new dataset we've incorporated is the HURDAT2 dataset [0] , offering access to cyclone track data from 1852 to 2022 for both the Atlantic and Pacific Ocean basins. This dataset is provided as an xarray [1] Dataset utilizing CF (Climate and Forecast) conventions [2] for data variables that are organized as a Ragged Arrays [3].

    To get started with `clouddrift` and the HURDAT2 dataset, check out our example Jupyter notebooks [4].

    If you'd like to receive regular updates on each release or just want to get an idea of features we've been working on checkout our latest [5].

    I'd love to hear from HN. How do you see clouddrift working with ragged array datasets of any kind you may be working with? Are there any challenges created by working with ragged arrays and/or Lagrangian datasets you have faced which clouddrift may not be accounting for? Any and all feedback is welcome as we look to make this tool as useful as possible for the scientific community!

    [0] https://github.com/Cloud-Drift/clouddrift/blob/main/clouddri...

What are some alternatives?

When comparing pygeohydro and clouddrift you can also consider the following projects:

Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]

coding-problems - Solutions for various coding/algorithmic problems and many useful resources for learning algorithms and data structures

HyRiver-examples - Example Notebooks for HyRiver software stack

iris - A powerful, format-agnostic, and community-driven Python package for analysing and visualising Earth science data

whiteboxgui - An interactive GUI for WhiteboxTools in a Jupyter-based environment

climatemind-backend - Your climate action is here 🌎 Our API is a source for learning how climate change personally affects you and the things you care about most. Additionally, it will teach a scientifically proven method for communicating to others that climate change is a personally relevant issue to inspire action.

hurdat2-get-started - Simple notebooks to get you started with the HURDAT2 dataset using python and xarray