sports-betting | Collection of sports betting AI tools | Machine Learning library

by georgedouzas Python Version: 0.8.1 License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | sports-betting Summary

sports-betting is a Python library typically used in Artificial Intelligence, Machine Learning applications. sports-betting has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However sports-betting build file is not available. You can install using 'pip install sports-betting' or download it from GitHub, PyPI.

Collection of sports betting AI tools.

Support

Quality

Security

License

Reuse

Support

sports-betting has a low active ecosystem.

It has 161 star(s) with 41 fork(s). There are 15 watchers for this library.

There were 1 major release(s) in the last 12 months.

There are 3 open issues and 10 have been closed. On average issues are closed in 133 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of sports-betting is 0.8.1

Quality

sports-betting has 0 bugs and 0 code smells.

Security

sports-betting has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

sports-betting code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

sports-betting is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

sports-betting releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

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

It has 2903 lines of code, 87 functions and 25 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Compute cross - validation regression
Check back test parameters
Predict proba of the model
Checks the input data
Extract a portfolio from the prices and orders
Returns a list of odds types
Return the list of columns that match the given type
Extract training data
Load the data from the grid
Check that the parameter grid is valid
Validate the data
Get training data
Read a csv file
Convert a parameter grid to a list of csv URLs
Returns a pandas DataFrame containing all parameters
Get all parameters
Return a list of ParameterGrid instances
Extract data from url
Predict class probabilities
Return the predicted probabilities for the model
Predict on the model
Extract match quality scores
Fit the classifier

Get all kandi verified functions for this library.

sports-betting Key Features

No Key Features are available at this moment for sports-betting.

sports-betting Examples and Code Snippets

No Code Snippets are available at this moment for sports-betting.

Community Discussions

Trending Discussions on sports-betting

Web scraping with Python and beautifulsoup: What is saved by the BeautifulSoup function?

QUESTION

Web scraping with Python and beautifulsoup: What is saved by the BeautifulSoup function?

Asked 2021-Feb-19 at 23:22

This question follows this previous question. I want to scrape data from a betting site using Python. I first tried to follow this tutorial, but the problem is that the site tipico is not available from Switzerland. I thus chose another betting site: Winamax. In the tutorial, the webpage tipico is first inspected, in order to find where the betting rates are located in the html file. In the tipico webpage, they were stored in buttons of class “c_but_base c_but". By writing the following lines, the rates could therefore be saved and printed using the Beautiful soup module:

...

ANSWER

Answered 2020-Dec-30 at 16:19

That's because the website is using JavaScript to display these details and BeautifulSoup does not interact with JS on it's own.

First try to find out if the element you want to scrape is present in the page source, if so you can scrape, pretty much everything! In your case the button/span tag's were not in the page source(meaning hidden or it's pulled through a script)

No tag in the page source :

So I suggest using Selenium as the solution, and I tried a basic scrape of the website.

Here is the code I used :

Source https://stackoverflow.com/questions/65509322

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

Vulnerabilities

No vulnerabilities reported

Install sports-betting

You can install using 'pip install sports-betting' or download it from GitHub, PyPI.
You can use sports-betting like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: