itemcf | Recommend system recall algorithms based on Pandas | Learning library

by tushushu Python Version: Current License: No License

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

kandi X-RAY | itemcf Summary

itemcf is a Python library typically used in Tutorial, Learning, Numpy, Example Codes applications. itemcf has no bugs, it has no vulnerabilities and it has low support. However itemcf build file is not available. You can download it from GitHub.

Recommend system recall algorithms based on Pandas and Cython.

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Quality

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Support

itemcf has a low active ecosystem.

It has 6 star(s) with 1 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

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

It has a neutral sentiment in the developer community.

The latest version of itemcf is current.

Quality

itemcf has no bugs reported.

Security

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

License

itemcf does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

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

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

Top functions reviewed by kandi - BETA

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

Run the jaccardItem model
Return a list of items with n_recommend
Compute the nlargest map from score_map
Check if a number is zero
Recommend a set of k items
Aggregate a score from top_k
Calculate the best k value for a set of items
Get the similar elements from the given list of elements
Compute the jaccard similarity between two sets
Get popular items
Predict the prediction for a user
Get aggregation function
Get a dataframe from a dataframe
Find the n most frequent elements in the set
Get the values for each item in a dataframe
Estimate matrices
Compile a cpp11 file

Get all kandi verified functions for this library.

itemcf Key Features

No Key Features are available at this moment for itemcf.

itemcf Examples and Code Snippets

No Code Snippets are available at this moment for itemcf.

Community Discussions

Trending Discussions on itemcf

Firestore, get the document ID using snapshot

QUESTION

Firestore, get the document ID using snapshot

Asked 2020-Aug-27 at 15:10

I´m trying to get the collection data from firestore, and save that data in JSON format, right now I can do both and everytime there's a change my list is being updated, the problem is that it doesn´t show up the ID field, so all the collections that suffer a change are being saved without any Doc ID. I tried some of the solutions that have being suggested in the attached post but it hasn't work at all. Any suggestion or idea that could help me.

Get document id firestore angular

How to get firestore document ID from document snapshot?

...

ANSWER

Answered 2020-Aug-27 at 15:09

If I correctly understand, in addition to get the data of the doc through the DocumentChange by doing change.doc.data(), you want to get the doc ID.

You need to do change.doc.id, since the doc property of a DocumentChange returns a QueryDocumentSnapshot.

Source https://stackoverflow.com/questions/63618525

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

Vulnerabilities

No vulnerabilities reported

Install itemcf

You can download it from GitHub.
You can use itemcf 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 .

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