Sorry for confusing
- last release (0.9.0) is java client/server system
- current version in 'master' branch (still unreleased) is simple java
API library (without client server)
- next step, which we are discussing, is simple scala API library (like
current master version, but with scala API instead of java)
Regards,
Sergey
On 10.06.2022 15:13, Paul King wrote:
So, just for my own understanding, is the server Java but the client
would be Scala?
Not questioning the decision but the first email in this thread said:
After these changes NlpCraft becomes simple library with java API.
I am actually seeing a bit of a renaissance of Java for Data Science
with numerous new projects like Amazon's DJL opting for Java as the
base language.
Disclosure, for data science, I mostly use Groovy as a "Python for the
JVM", so that probably skews the world I see. Most of the NLP folks I
speak to use Python these days. And concurring with Sergey, Stanford
and OpenNLP are probably the two more widely used Java libraries I see
for those folks on the JVM with Datumbox and Smile occasionally used
as well.
Cheers, Paul.
On Wed, Jun 8, 2022 at 5:49 AM Kamov Sergey<skhdlem...@gmail.com> wrote:
Hi!
All google requests like "NLP libraries" return that most popular is
Python (out of competition )
First result for me
https://www.upgrad.com/blog/python-nlp-libraries-and-applications/
https://medium.com/nlplanet/awesome-nlp-21-popular-nlp-libraries-of-2022-2e07a914248b
Java is mentioned for Stanford, sometimes Apache openNlp
Regards,
Sergey
On 07.06.2022 19:21, Furkan KAMACI wrote:
Hi Sergey,
Is there any survey about which programming languages popular among NLP
developers?
Kind Regards,
Furkan KAMACI
On 7 Jun 2022 Tue at 17:37 Kamov Sergey<skhdlem...@gmail.com> wrote:
Hi
One more important thing. We want to support Scala API only for next
library’s version.
Now seems better to narrow this technological focus too.Current
approach, java API and Scala implementation, provoke a lot of technical
compromises (collections conversion, performance issues etc)
But at the same time, support of java API also doesn’t give us
significant benefits, because Java is not so popular among NLP
engineers.Focus on Scala allows to have more elegant user API and
implementation, also we can promote this solution for members of not so
big but active Scala community.
If library is successful we always can add java API support again over
Scala layer.
Regards,
Sergey Kamov
On 04.06.2022 17:56, Kamov Sergey wrote:
Hi
I want to enumerate next NlpCraft release changes.
Main goals of next release:
- Simplifying of the system usage.
- Narrowing of focus - NLP, deleting all unrelated, auxiliary
components.
- Possibility of custom multi-language support.
- Simplifying of code, technical debt minimization.
1. Removed
- Client-server approach components, servers cluster support.
- Any database usage.
- CLI management console.
- Docker related stuff.
- Complex semantic components support.
After these changes NlpCraft becomes simple library with java API.
2.Added and changed
All components plugability support added, including such base as
tokenizer etc, with EN default implementations of all of them.
Note, that components testability was also significantly simplified,
which is especially useful for user custom components.
As results - all goals seem in general achieved.
Code, including examples on different languages (EN, FR, RU) are
accessible in `master` branch.
Th best way to look at the code and review API, components work -
start and debug 'light-switch' example, EN and FR versions.
Remained tasks: some additional examples, user API clarifying,
documentation.
Please ask the questions if you have.
Regards,
Sergey Kamov
