npmi | NodeJS package that gives a simplier API | REST library
kandi X-RAY | npmi Summary
kandi X-RAY | npmi Summary
NodeJS package that gives a simplier API to npm install (programatically installs things)
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Top functions reviewed by kandi - BETA
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of npmi
npmi Key Features
npmi Examples and Code Snippets
$ echo "$ARTIFACTORY_URL"
https://arielk.jfrog.io/arielk
$ echo "$ARTIFACTORY_USER"
npm
$ echo "$ARTIFACTORY_NPM_REPOSITORY"
npm
$ chmod 777 jfrog
$ ./jfrog rt config --url=$ARTIFACTORY_URL --user=$ARTIFACTORY_USER --password=$ARTIFACTORY_
Community Discussions
Trending Discussions on npmi
QUESTION
We want to use AsyncAPI to document our RabbitMQ messaging. Therefore, we installed asyncapi/generator as a npm dependency.
If you have a look at the package.json
you can see that it references npmi as a dependency which in turn is referencing to global-npm. If we want to run it, a globally installed node and npm is necessary.
Now if we run the generator ($ ag ./docs/asyncapi.yaml @asyncapi/html-template --output ./docs/asyncapi/ --force-write
) on a machine which has no globally installed npm following error message appears:
ANSWER
Answered 2021-Feb-03 at 14:32if you run ag
you must have installed it with npm initially right? so npm is most probably on this machine already.
The error you have, I saw it on windows only, when you have the generator as dependency, and most likely you use nvm.
Solution was this, so manual bump of global-npm
to have this fixed in npmi
. This is a workaround,long term I think we need to get rid of npmi
dependency from the generator I think
QUESTION
I am using Gensim's Phraser model to find bigrams in some reviews, to be later used in an LDA topic modelling scenario. My issue is that the reviews mention the word "service" quite often and so Phraser finds lots of different bigrams with "service" as one of the pairs (e.g "helpful_service", "good_service", "service_price").
These are then present across multiple topics in the final result*. I'm thinking that I could prevent this from occurring if I was able to tell Phraser not to include "service" when making bigrams. Is this possible?
(*) I am aware that "service"-related bigrams being present across multiple topics might indeed be the optimal result, but I just want to experiment with leaving them out.
Sample code:
...ANSWER
Answered 2021-Jan-13 at 16:19Caution: The following behavior seems to change with version 4.0.0!
If you are indeed only working with bigrams, you can utilize the common_terms={}
parameter of the function, which is (according to the docs
[a] list of “stop words” that won’t affect frequency count of expressions containing them. Allow to detect expressions like “bank_of_america” or “eye_of_the_beholder”.
If I add a simple common_terms={"service"}
to your sample code, I am left with tge following result:
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