Comments (3)
Okay, I did some digging, and my proposed option to put argv=None
would not be correct.
One would have to implement something like:
def parse_command_line_arguments(mandatory_args, *optional_args_list, **kwargs):
argv = kwargs.get('argv', None)
I implemented this in my own fork of the code, but now I notice, this has not been the only place positional arguments have been used like that in the code. For instance, it is also used here, and in a couple other places in the package.
From this, I guess Python 2 support is not on the roadmap for the package, is it?
from bayespy.
Yep, Python 2 isn't supported unfortunately. BayesPy will raise an error in the future if one tries to install it with Python 2: 3fbb8d5 . It will be in the next release probably.
I chose not to support Python 2 because I liked some features in Python 3, and wanted to avoid doing the transition in the near future and needing to support two versions of Pythons. This same "bug" has been reported so many times that maybe it was a wrong choice. Anyway, I hope the installation error will at least avoid some confusion because the problem is then clearly stated.
from bayespy.
It all makes sense. In this case, I think preventing installation to complete for Python 2 is indeed the way to go.
from bayespy.
Related Issues (20)
- ImageComparisonFailure error during tests HOT 1
- Creating Gaussian Node Raises Error HOT 4
- Extended Marble Example HOT 1
- Fast Variational Bayesian Linear State-Space Model HOT 2
- Performance Doubt HOT 3
- Implamenting
- How to approach bayesian?
- Online/Iterative Learning for Bayespy?
- Higher order Markov chains? HOT 3
- Anaconda install of bayespy causes a downgrade of ipython HOT 6
- Gate for Non Categorical Variable HOT 4
- How to extract posterior over latent states from CategoricalMarkovChain HOT 2
- Remove deprecated time.clock() call HOT 1
- Array of counts doesn't work in multinomial mixture HOT 2
- Using the posterior distribution? HOT 1
- Gaussian mixture HOT 2
- Increase the usage of augmented assignment statements
- Errors in the demos HOT 1
- More projects for "Similar projects"
- Equations not showing in docs HOT 2
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from bayespy.