SPGL | simple Python game library / framework for creating 2D games | Game Engine library

by wynand1004 Python Version: Current License: GPL-3.0

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | SPGL Summary

SPGL is a Python library typically used in Telecommunications, Media, Media, Entertainment, Gaming, Game Engine, Framework, Pygame applications. SPGL has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However SPGL build file is not available. You can download it from GitHub.

SPGL is a simple Python game library / framework for creating 2D games. It is built on the Python Turtle module and is compatible with Python 2.x and 3.x.

Support

Quality

Security

License

Reuse

Support

SPGL has a low active ecosystem.

It has 17 star(s) with 11 fork(s). There are 17 watchers for this library.

It had no major release in the last 6 months.

SPGL has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of SPGL is current.

Quality

SPGL has 0 bugs and 0 code smells.

Security

SPGL has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

SPGL code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

SPGL is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

SPGL releases are not available. You will need to build from source code and install.

SPGL has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are available. Examples and code snippets are not available.

Top functions reviewed by kandi - BETA

kandi has reviewed SPGL and discovered the below as its top functions. This is intended to give you an instant insight into SPGL implemented functionality, and help decide if they suit your requirements.

Ticks the game
Show splash screen
Update the screen
Prints information about the game
Print error logs
Set a key binding
Play sound
Load data from disk
Save data to disk
Clear terminal screen
Micks the button
Move the game
Update the progress bar
Clears the text
Explodes all particles in the mesh
Terminate the sound
Stop all sounds
Make tick

Get all kandi verified functions for this library.

SPGL Key Features

No Key Features are available at this moment for SPGL.

SPGL Examples and Code Snippets

No Code Snippets are available at this moment for SPGL.

Community Discussions

Trending Discussions on SPGL

Difference in closeness function in R and manual computation

Ranking based on significant difference in list of lists

QUESTION

Difference in closeness function in R and manual computation

Asked 2021-Aug-03 at 23:02

I have a undirected weighted graph where I want to calculate the closeness measure for. As per igraph documentation, it is the reciprocal of average shortest paths. I compute the shortest paths and inverse their average but still don't get the same value as in closeness function. Why is this happening? What am I missing?

Here's my code:

...

ANSWER

Answered 2021-Aug-03 at 23:02

There are two places you may need to be aware of:

You should enable normalized = TRUE in closeness
When you attempt to use shortest path lengths to define closeness centrality, you should know that the the distance is averaged over the distances excluding itself. Thus, vcount(g)-1 is the denominator for averaging, instead of vcount(g), and that's why should shouldn't use rowMeans.

From the code below, you can see that the results by two methods are close to each other (minor difference might come from the precision, but I am not sure)

Source https://stackoverflow.com/questions/68642801

QUESTION

Ranking based on significant difference in list of lists

Asked 2021-Jul-28 at 16:37

I have a list of lists, where each list is sorted. What I want to look into is how many times a certain element has appeared in a specific position and take into account if the value is significantly different from the previous element. (For example in the first list gs, ms, bofa and citi have the same value but they are ranked differently). I realize that the length of the rankings would not be the same because each list's elements are different. How can I do this in a manner where it is correct and also shows the result in a decent way?

What I have so far with ranking solidly based on the sort function output:

...

ANSWER

Answered 2021-Jul-28 at 16:37

We loop over the named list ('degree.l'), get the rank on the rounded vectors with dense_rank, named it with the original vector names, stack into a two column data.frame, rbind the list elements and get the frequency table

Source https://stackoverflow.com/questions/68550099

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install SPGL

Download the repository to your computer. There are 2 demo files, SPGL_Demo.py which is a simple game using primitives (squares, triangles, arrows, and circles). Use the arrow keys to control the player. There is also SPGL_Minimal_Example.py which contains a simple game framework which will create a window - use this as the basis of your own programs.