covid19-sir
Epidemiology101
| covid19-sir | Epidemiology101 | |
|---|---|---|
| 3 | 2 | |
| 108 | 278 | |
| - | 2.2% | |
| 9.3 | 5.6 | |
| 4 days ago | about 1 month ago | |
| Python | Jupyter Notebook | |
| Apache License 2.0 | MIT License |
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.
covid19-sir
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Show HN: Deptry, a tool to check for dependency issues in a Python project
I have recently been working on a project called `deptry`, a command line tool to check for issues in the dependencies of Python projects. It can be used to find obsolete, missing, transitive and misplaced development dependencies. It supports the following types of projects:
- Projects that use Poetry and a corresponding pyproject.toml file
- Projects that use a requirements.txt file according to the pip standards
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* Documentation: https://fpgmaas.github.io/deptry/
* GitHub repository: https://github.com/fpgmaas/deptry
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I am quite happy with the project in its current form, but I also realise there is still a lot of room left for improvement. Therefore, I hope some people are willing to give it a try and provide me with feedback. So; if you have a project with a long list of dependencies and a little bit of spare time on your hands, please give it a try and let me know what you think!
If you encounter any issues, find a bug, or have any other form of feedback, please don't hesitate to raise an issue in the GitHub repository, or leave a comment here.
Kind regards,
Florian
P.S. Many thanks to Hirokazu Takaya (https://github.com/lisphilar) for incorporating it in the CI/CD pipeline of his project covid19-sir (https://github.com/lisphilar/covid19-sir). It provided me with very valuable early feedback.
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Deptry 0.4.4, a tool to check for dependency issues in a Python project
* [*GitHub repository*](https://github.com/fpgmaas/deptry)
I am quite happy with the project in its current form, but I also realise there is still a lot of room left for improvement. Therefore, I hope some people are willing to give it a try and provide me with feedback. So; if you have a project with a long list of dependencies and a little bit of spare time on your hands, please give it a try and let me know what you think!
If you encounter any issues, find a bug, or have any other form of feedback, please don't hesitate to raise an issue in the GitHub repository, or leave a comment here.
Kind regards,
Florian
P.S. Many thanks to [Hirokazu Takaya](https://github.com/lisphilar) for incorporating it in the CI/CD pipeline of his project [covid19-sir](https://github.com/lisphilar/covid19-sir). It provided me with very valuable early feedback.
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I recently released deptry; a utility to check your Poetry-managed Python projects for obsolete, transitive, missing and misplaced dependencies.
P.S. Many thanks to Hirokazu Takaya for incorporating it in the CI/CD pipeline of his project covid19-sir. It provided me with very valuable early feedback.
Epidemiology101
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Show HN: What Are You Working On?
Trying to put the finishing touches on a Python package [1] for epidemic modeling using Compartmental models. This grew out of a series of blog posts I started writing during the pandemic [2] based on my professional experience in epidemic modeling in a previous life where I was the lead developer for a state of the art global epidemic model [3].
[1] http://github.com/DataForScience/epidemik
[2] https://github.com/DataForScience/Epidemiology101
[3] https://www.gleamviz.org/explore.html
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AI outperforms conventional weather forecasting for the first time: Google study
No worries, Google does tend to do a good job of monopolizing attention in whatever they do and Epidemic Modeling is... complicated. Probably much more complicated than pretty much any other kind of modeling since people have the bad habit of thinking and acting in whatever way they want (sometimes with the explicit purpose of breaking your model :).
Now, if you want to see the real-world state-of-the-art epidemic modeling on a global scale, checkout GLEaM/GLEaMViz https://www.gleamviz.org/ (full disclaimer, in a previous life I was the lead developer).
And if you're interested in a basic intro, you can also checkout my (somewhat neglected) series of blog posts from the pandemic days: https://github.com/DataForScience/Epidemiology101
What are some alternatives?
richkit - Domain Enrichment Toolkit $ pip install richkit
covid-19 - Coronavirus COVID-19 Dashboard - Global Kaggle Data
COVID19_AgentBasedSimulation - COVID-ABS: An Agent-Based Model of COVID-19 Epidemic to Simulate Health and Economic Effects of Social Distancing Interventions
california-coronavirus-scrapers - The open-source web scrapers that feed the Los Angeles Times California coronavirus tracker.
zEpid - Epidemiology analysis package
Face-Mask-Detection - Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras
deptry - Find unused, missing and transitive dependencies in a Python project.
covid_project - Data analysis project on a COVID-19 data set provided by Our World in Data
lockdowndates - Retrieve the dates of the restrictions imposed by governments in countries around the world during the covid-19 pandemic.
CSGO-Pro-Gear-Performance-and-EDA - Modeling Professional (CS:GO) Gamer's Accuracy Performance Based on Gear and Settings, and Exploratory Data Analysis.