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Build Text Summarizer in Python

by kandikits Updated: Oct 20, 2022


NLP text summarizer, is a Python package that summarizes texts and extracts the most important sentences from a given text. Text summarizer is commonly used in news feeding websites to summarize long articles. Summarizer shortens long texts such that the summarized text preserves all the essential points of the actual text. It uses spaCy, nltk, and NumPy to do the job. This solution is also used to summarize texts (in Extractive and abstractive techniques), extract key sentences and find their TF-IDF values. You can use this package for your own projects; we are sure you'll find it useful!


Extraction-based summarization involves selecting sentences from an original document and organizing them into a cohesive summary. In contrast to extraction-based summarization, abstraction-based summaries are created by using algorithms to produce abstracts that can be used as templates.


spaCy is a library for Natural Language Processing (NLP). It provides functions for tokenization, part of speech tagging, and parsing. The library also includes pre-trained models for some languages. NLTK (Natural Language Toolkit) is another popular toolkit for NLP tasks. It is used in many research papers to solve different problems related to NLP.

Deployment Information

Please find the kit solution in this group.

  1. Download, extract and double-click the kit installer file to install the kit.
  2. After the successful installation of the kit, press 'Y' to run the kit.
  3. To run the kit manually, press 'N' and locate the zip file 'Text_Summarizer.zip'
  4. Extract the zip file and navigate to the directory 'bert-extractive-summarizer-master'
  5. Open command prompt in the extracted directory 'bert-extractive-summarizer-master' and run the command 'jupyter notebook'
  6. Locate and open the 'Text_Summarizer.ipynb' notebook from the Jupyter Notebook browser window.
  7. Execute cells in the notebook


Click on the button below to download the solution and follow the deployment instructions to begin set-up. This 1-click kit has all the required dependencies and resources you may need to build your Text Summarizer in Python.

For a detailed tutorial on installing & executing the solution as well as learning resources including training & certification opportunities, please visit the OpenWeaver Community

Development Environment

VSCode and Jupyter Notebook are used for development and debugging. Jupyter Notebook is a web based interactive environment often used for experiments, whereas VSCode is used to get a typical experience of IDE for developers.

notebookby jupyter

Jupyter Notebook star image 8966 Version:v7.0.0a2

License: Others (Non-SPDX)

Jupyter Interactive Notebook

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notebookby jupyter

Jupyter Notebook star image 8966 Version:v7.0.0a2 License: Others (Non-SPDX)

Jupyter Interactive Notebook
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vscodeby microsoft

TypeScript star image 130477 Version:1.66.2

License: Permissive (MIT)

Visual Studio Code

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vscodeby microsoft

TypeScript star image 130477 Version:1.66.2 License: Permissive (MIT)

Visual Studio Code
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Exploratory Data Analysis

For extensive analysis and exploration of data, and to deal with arrays, these libraries are used. They are also used for performing scientific computation and data manipulation.

numpyby numpy

Python star image 20101 Version:v1.22.3

License: Permissive (BSD-3-Clause)

The fundamental package for scientific computing with Python.

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numpyby numpy

Python star image 20101 Version:v1.22.3 License: Permissive (BSD-3-Clause)

The fundamental package for scientific computing with Python.
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pandasby pandas-dev

Python star image 33259 Version:v1.4.1

License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

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pandasby pandas-dev

Python star image 33259 Version:v1.4.1 License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
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Text Mining

Libraries in this group are used for analysis and processing of unstructured natural language.

spaCyby explosion

Python star image 23063 Version:v3.1.6

License: Permissive (MIT)

💫 Industrial-strength Natural Language Processing (NLP) in Python

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spaCyby explosion

Python star image 23063 Version:v3.1.6 License: Permissive (MIT)

💫 Industrial-strength Natural Language Processing (NLP) in Python
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sentencepieceby google

C++ star image 5313 Version:v0.1.96

License: Permissive (Apache-2.0)

Unsupervised text tokenizer for Neural Network-based text generation.

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sentencepieceby google

C++ star image 5313 Version:v0.1.96 License: Permissive (Apache-2.0)

Unsupervised text tokenizer for Neural Network-based text generation.
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nltkby nltk

Python star image 10427 Version:Current

License: Permissive (Apache-2.0)

NLTK Source

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nltkby nltk

Python star image 10427 Version:Current License: Permissive (Apache-2.0)

NLTK Source
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Machine Learning & Natural Language Processing

The library offers state-of-the-art pre-trained models for Natural Language Processing (NLP).

scikit-learnby scikit-learn

Python star image 49728 Version:1.0.2

License: Permissive (BSD-3-Clause)

scikit-learn: machine learning in Python

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scikit-learnby scikit-learn

Python star image 49728 Version:1.0.2 License: Permissive (BSD-3-Clause)

scikit-learn: machine learning in Python
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pytorchby pytorch

C++ star image 55457 Version:v1.11.0

License: Others (Non-SPDX)

Tensors and Dynamic neural networks in Python with strong GPU acceleration

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pytorchby pytorch

C++ star image 55457 Version:v1.11.0 License: Others (Non-SPDX)

Tensors and Dynamic neural networks in Python with strong GPU acceleration
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transformersby huggingface

Python star image 61400 Version:v4.18.0

License: Permissive (Apache-2.0)

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

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transformersby huggingface

Python star image 61400 Version:v4.18.0 License: Permissive (Apache-2.0)

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
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sentence-transformersby UKPLab

Python star image 5944 Version:v2.0.0

License: Permissive (Apache-2.0)

Multilingual Sentence & Image Embeddings with BERT

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sentence-transformersby UKPLab

Python star image 5944 Version:v2.0.0 License: Permissive (Apache-2.0)

Multilingual Sentence & Image Embeddings with BERT
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Utilities

library tqdm can be used to show progress bar for any long running process step in the code

tqdmby tqdm

Python star image 21618 Version:v4.63.2

License: Others (Non-SPDX)

A Fast, Extensible Progress Bar for Python and CLI

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tqdmby tqdm

Python star image 21618 Version:v4.63.2 License: Others (Non-SPDX)

A Fast, Extensible Progress Bar for Python and CLI
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Testing

The libraries listed here can be used for unit testing as well as integration testing

pytestby pytest-dev

Python star image 8655 Version:7.1.1

License: Permissive (MIT)

The pytest framework makes it easy to write small tests, yet scales to support complex functional testing

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pytestby pytest-dev

Python star image 8655 Version:7.1.1 License: Permissive (MIT)

The pytest framework makes it easy to write small tests, yet scales to support complex functional testing
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Kit Solution Source

bert-extractive-summarizerby dmmiller612

Python star image 851 Version:0.10.1

License: Permissive (MIT)

Easy to use extractive text summarization with BERT

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bert-extractive-summarizerby dmmiller612

Python star image 851 Version:0.10.1 License: Permissive (MIT)

Easy to use extractive text summarization with BERT
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Support

If you need help using this kit, you may reach us at the OpenWeaver Community.

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