faux-pas | simplifies error handling for Functional Programming | Functional Programming library

by zalando Java Version: 0.9.0 License: MIT

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kandi X-RAY | faux-pas Summary

faux-pas is a Java library typically used in Programming Style, Functional Programming applications. faux-pas has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub, Maven.

Faux pas noun, /fəʊ pɑː/: blunder; misstep, false step. Faux Pas is a library that simplifies error handling for Functional Programming in Java. It fixes the issue that none of the functional interfaces in the Java Runtime by default is allowed to throw checked exceptions.

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Support

faux-pas has a low active ecosystem.

It has 117 star(s) with 12 fork(s). There are 14 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 14 have been closed. On average issues are closed in 23 days. There are 6 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of faux-pas is 0.9.0

Quality

faux-pas has 0 bugs and 0 code smells.

Security

faux-pas has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

faux-pas code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

faux-pas 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

faux-pas releases are available to install and integrate.

Deployable package is available in Maven.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

It has 1380 lines of code, 138 functions and 23 files.

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

Top functions reviewed by kandi - BETA

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

Start the Downloader
Downloads a file from the given URL
Shortcut to create a BiConsumer with the given type
Unpack throwable
Exceptions are exceptionally
Handle a CompletableFuture
Invokes the accept method
Calls the apply method and returns the result
Perform test
Overrides default accept method
Performs test
Runs the test
Gets a value

Get all kandi verified functions for this library.

faux-pas Key Features

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faux-pas Examples and Code Snippets

No Code Snippets are available at this moment for faux-pas.

Community Discussions

Trending Discussions on faux-pas

Quanteda - creating a corpus from a dataframe with multiple documents

Fast algorithm to find exactly k columns in binary matrix such that the sum of those columns is the 1-vector

QUESTION

Quanteda - creating a corpus from a dataframe with multiple documents

Asked 2021-Apr-08 at 17:23

First question here, so apologises for any faux-pas. I have a dataframe in R of 657 observations with 4 variables. Each observation is a speech or interview by the Australian Prime Minister. So the variables are:

date
title
URL
txt (full text of the speech/interview).

I'm trying to turn that into a corpus in Quanteda

I first tried corp <- corpus(all_content) but that gave me an error message

...

ANSWER

Answered 2021-Apr-08 at 17:23

It's hard to address this problem exactly, because there is no reproducible example of your data.frame object, but if the structure contains the variables you list, then this should do it:

Source https://stackoverflow.com/questions/66998866

QUESTION

Fast algorithm to find exactly k columns in binary matrix such that the sum of those columns is the 1-vector

Asked 2020-Jun-21 at 16:01

Suppose I have an (M x N) binary matrix where both M and N can be large. I want to find exactly k columns (k is relatively small, say less than 10) such that the sum of those k columns is the 1-vector (all elements are 1). One solution is adequate. Is there a fast algorithm for this?

For example, an algorithm working on the matrix

...

ANSWER

Answered 2020-Jun-20 at 17:30

My first attempt would be integer-programming using one of the available high-performance solvers (e.g. Cbc).

Assuming some sparsity in your incidence-matrix, those will be very efficient and are quite general (side-constraints / adaptations). They are also complete and might be able to prove infeasibility.

A simple formulation would look like:

Source https://stackoverflow.com/questions/62488280

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