# PyNLPl Reviews **Vendor:** BLLIP Parser **Category:** [Other Development Software](https://www.g2.com/categories/other-development) **Average Rating:** 4.4/5.0 **Total Reviews:** 11 ## About PyNLPl PyNLPl is a Python library for Natural Language Processing that contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. ## PyNLPl Reviews ### 1. Python NLP for Machine Learning Review **Rating:** 5.0/5.0 stars **Reviewed by:** Chandrashekhar K. | Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** November 19, 2019 **What do you like best about PyNLPl?** Very useful for Machine Learning and Data Science. It contains a lot of valuable modules for language processing. **What do you dislike about PyNLPl?** There isn't anything particular that I dislike about PyNLPI **Recommendations to others considering PyNLPl:** Practice before implementing. **What problems is PyNLPl solving and how is that benefiting you?** I have been doing projects on Machine Learning - Natural Language Processing. PyNLPI makes it very easy to do that. I have done some basic tasks such as the extraction of n-grams and frequency lists ### 2. Best and most complete library for data analysis **Rating:** 5.0/5.0 stars **Reviewed by:** Dejanira B. | Doutorado meteorologia, Small-Business (50 or fewer emp.) **Reviewed Date:** June 15, 2021 **What do you like best about PyNLPl?** I'm a meteorologist and I work with a large database. PyNLPI is fundamental for optimizing my work. Working with Python and without a shadow of a doubt it is the best tool in data analysis. **What do you dislike about PyNLPl?** I don't see any downsides, because everything I needed to do with this library I did. So far I have only praise and no criticism. **Recommendations to others considering PyNLPl:** Use python that will optimize your database work **What problems is PyNLPl solving and how is that benefiting you?** I use it for the data analysis process. I use data in Netcdf, tiff and grib2 format. These are very heavy data and with PyNLPI the process is much faster. ### 3. python is future **Rating:** 5.0/5.0 stars **Reviewed by:** Assem O. | Senior Cost Control Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** November 20, 2019 **What do you like best about PyNLPl?** python is an easy program to become programmer it was a super to use it for machine learning **What do you dislike about PyNLPl?** it must use interface to use this program such as jybter or spyder **Recommendations to others considering PyNLPl:** python is future for everything **What problems is PyNLPl solving and how is that benefiting you?** python guide me to solve more of problems such as complicated equation and uses it for big data can solve a lot of problems ### 4. BEST NLP Library for Python EVER **Rating:** 5.0/5.0 stars **Reviewed by:** Marnim Galib I. | Assistant Programmer, Mid-Market (51-1000 emp.) **Reviewed Date:** December 13, 2018 **What do you like best about PyNLPl?** PyNLPl, pronounced as ‘pineapple’, is a Python library for Natural Language Processing that contains modules for almost all of the NLP tasks that we face in research or industry. It contains both simple and complex data types and algorithms for all kinds of users and it's documentation is superb. **What do you dislike about PyNLPl?** I really have not found any issues to complain against it. Basically I have never come across any NLP tasks that does not contain support from PyNLPI. **Recommendations to others considering PyNLPl:** Users should focus on the documentation of PyNLPI to find for solutions rather than searching all over the Internet. It contains one of the most useful documentation on different modules that I have seen so far. **What problems is PyNLPl solving and how is that benefiting you?** Various search algorithms for example : Breadth-first, depth-first, beam-search etc. are easy to implement using PyNLPI. and also there is added benefit of using extra datatypes (priority queues, tries etc.) ### 5. PyNLPL, one of the NLP package **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** November 19, 2019 **What do you like best about PyNLPl?** PyNlpl commonly called as PINEAPPLE is one of the NLP packages which can be used with python language. **What do you dislike about PyNLPl?** Maybe not so robust for enterprise implementation **What problems is PyNLPl solving and how is that benefiting you?** Mainly used for research purposes for NLP in Python ### 6. Best Natural Language Processing library for python. **Rating:** 5.0/5.0 stars **Reviewed by:** ANAY P. | Software Developer, Small-Business (50 or fewer emp.) **Reviewed Date:** December 09, 2018 **What do you like best about PyNLPl?** It's very simple to use and superbly easy to implement software for natural language processing problems. I have been using it for the last few months and I have never looked back. Another best thing about the PyNLPL is that its open source hence no need of paying a huge amount for getting the license to use it. And apart from that the documentation for this open source python library is updated and explained in a very good manner that makes the life of developers like me super easy. It also works with FoLiA XML (Format for Linguistic Annotation) which is the most important feature of this library that makes me dependable on this library every day for solving NLP problem statements. **What do you dislike about PyNLPl?** I personally didn't find any flaws in this library. By far the best Natural language processing library I have ever used for developing software for natural language processing problems. **Recommendations to others considering PyNLPl:** If you are working on python to solve a natural language processing problem them PyNLPl is the library to be used. I highly recommend using this library. **What problems is PyNLPl solving and how is that benefiting you?** I have been using it in my laboratory for solving natural language processing problems where I need to develop automated virtual assistants that can help a person in doing day to day simple work like turn on the lights, set alarm, answer a simple query like check the weather for a requested location, etc. ### 7. Improve productivity **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Education Management | Mid-Market (51-1000 emp.) **Reviewed Date:** August 07, 2019 **What do you like best about PyNLPl?** The ability of the software to be suited for different applications **What do you dislike about PyNLPl?** Some limitations for more complex operations **What problems is PyNLPl solving and how is that benefiting you?** Automating basic messaging. Saving a lot of time for my business ### 8. Good for Complex natural language processing **Rating:** 4.0/5.0 stars **Reviewed by:** Nikhil G. | Part Time Trainer, Small-Business (50 or fewer emp.) **Reviewed Date:** January 23, 2019 **What do you like best about PyNLPl?** It is mainly used for understanding the sentences in matrix form where problem of understanding complex text becomes simple for classification. **What do you dislike about PyNLPl?** It is only good for preprocessing complex sentence into n -gram but requires a good terminology like nltk package of python **What problems is PyNLPl solving and how is that benefiting you?** We used this package for handeling complex sentences sentiment analysis where if have more than one compound or. Complex sentence in review text we can easily understand using this package. ### 9. A set of library having unlimited applications for data science **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Consumer Goods | Small-Business (50 or fewer emp.) **Reviewed Date:** March 19, 2019 **What do you like best about PyNLPl?** It was provided great functionality for the analysis I was working on. Made my code simpler **What do you dislike about PyNLPl?** I did not come across anything negative to talk about yet **What problems is PyNLPl solving and how is that benefiting you?** I was trying to implement sentiment analysis on the greater than 5million of records and to get the desired outcome of it. I realized it make tokenization, stemming and every other process much easier ### 10. Good open source library for natural language processing **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Hardware | Enterprise (> 1000 emp.) **Reviewed Date:** February 14, 2019 **What do you like best about PyNLPl?** I like the fact that the library is open source and provides good documentation. Classification problems become quite easy to solve. **What do you dislike about PyNLPl?** Has to be used in conjunction with more sophisticated libraries for harder problems **What problems is PyNLPl solving and how is that benefiting you?** Data processing ### 11. PyNLPI **Rating:** 2.5/5.0 stars **Reviewed by:** Verified User in Medical Devices | Enterprise (> 1000 emp.) **Reviewed Date:** January 30, 2018 **What do you like best about PyNLPl?** Simple to use and implementable , open source **What do you dislike about PyNLPl?** Open source and as a result not very reliable enterprise level. **What problems is PyNLPl solving and how is that benefiting you?** Clinical Decision Support. ## PyNLPl Discussions - [What is PyNLPl used for?](https://www.g2.com/discussions/what-is-pynlpl-used-for) - [What is the best website for support?](https://www.g2.com/discussions/what-is-the-best-website-for-support-44658fea-e88a-4418-ac33-dc5b246e8690) - 1 upvote - [What is the best website for support?](https://www.g2.com/discussions/what-is-the-best-website-for-support) - 1 upvote - [View PyNLPl pricing details and edition comparison](https://www.g2.com/products/pynlpl/reviews?section=pricing&secure%5Bexpires_at%5D=2026-05-15+14%3A21%3A32+-0500&secure%5Bsession_id%5D=3c59db9b-2184-4d52-9c00-0f76cebb8bad&secure%5Btoken%5D=08bbe3eaca83780ffbc992701e214224724700e4cb1aaca573f11d3d5481b35d&format=llm_user) ## Top PyNLPl Alternatives - [Okta](https://www.g2.com/products/okta/reviews) - 4.5/5.0 (1,196 reviews) - [Termius](https://www.g2.com/products/termius/reviews) - 4.8/5.0 (254 reviews) - [SAP Fiori](https://www.g2.com/products/sap-fiori/reviews) - 4.3/5.0 (128 reviews)