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arxivterminal-0.3.1


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مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

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توضیحات

An application for summarizing Arxiv results within the terminal
ویژگی مقدار
سیستم عامل -
نام فایل arxivterminal-0.3.1
نام arxivterminal
نسخه کتابخانه 0.3.1
نگهدارنده []
ایمیل نگهدارنده []
نویسنده John Bencina
ایمیل نویسنده jbencina@users.noreply.github.com
آدرس صفحه اصلی https://github.com/jbencina/arxivterminal
آدرس اینترنتی https://pypi.org/project/arxivterminal/
مجوز GPL-3.0-or-later
# Arxiv Terminal ![Tests](https://github.com/jbencina/arxivterminal/actions/workflows/main.yaml/badge.svg) ![PyPI](https://img.shields.io/pypi/v/arxivterminal) ![PyPI - Downloads](https://img.shields.io/pypi/dm/arxivterminal) Arxiv Terminal is a command-line interface (CLI) tool for fetching, searching, and displaying papers from the [arXiv](https://arxiv.org/) preprint repository. The tool allows you to fetch papers from specified categories, search the fetched papers, and display their statistics. ## Features - Fetch paper abstracts from specified categories and save them in a local sqllite database. - Show fetched papers and interatively open for more detailed abstracts - Search fetched papers based on a query (Currently supports pattern + LSA semantic search) - Download papers locally as PDF ![Demo](https://raw.githubusercontent.com/jbencina/arxivterminal/main/static/demo.gif) ## Contributors A special call out to ChatGPT (v4) which helped write and modify various code and documentation in this repository. ## Installation ```bash pip install arxivterminal ``` For local builds, you should have Poetry installed: [User Guide](https://python-poetry.org/docs/#installation). After installation you may clone and build this repo: ```bash poetry install poetry shell arxiv <command> # Build the wheels poetry build ``` ## Usage The CLI is invoked using the `arxiv` command, followed by one of the available commands: - `arxiv fetch [--num-days] [--categories]`: Fetch papers from the specified categories and store them in the database. - `arxiv delete_all`: Delete all papers from the database. - `arxiv show [--days-ago]`: Show papers fetched from the specified number of days ago. - `arxiv stats`: Show statistics of the papers stored in the database. - `arxiv search <query>`: Search papers in the database based on a query. ### Examples Fetch papers from the "cs.AI" and "cs.CL" categories from the last 7 days: ```bash arxiv fetch --num-days 7 --categories cs.AI,cs.CL ``` Delete all papers from database: ```bash arxiv delete_all ``` Show papers fetched in the last 7 days ```bash arxiv show --days-ago 7 # On this screen the user can select a paper for more # details by typing a line number. Additional options # allow for searching & downloading ``` Display statistics of the papers stored in the database: ```bash arxiv stats ``` Show papers containing the phrase "deep learning": ```bash arxiv search "deep learning" ``` Show papers containing the phrase "deep learning" using LSA matching: ```bash arxiv search -e "deep learning" ``` ### LSA Search Model > Note: This approach is likely to be replaced in the future by more robust methodology The LSA search model is largely adapted from the implementation featured in the scikit-learn [User Guide]( https://scikit-learn.org/stable/auto_examples/text/plot_document_clustering.html#sphx-glr-auto-examples-text-plot-document-clustering-py) example. When used, the model is trained over the entire corpus of abstracts present in the user's local database. The model is persisted in the app cache folder and automatically reloaded on subsequent runs. During a search query, all abstracts from the database are encoded as n-dimensional vectors using the trained LSA model. The search query is also represented as a vector, and a cosine similarity is performed to find the top ranking items. You may want to force a refresh of the underlying model after loading new papers. This can be done by using the `-f` flag when performing a search: ```bash arxiv search -e -f "deep learning" ```


نیازمندی

مقدار نام
>=1.10.7,<2.0.0 pydantic
>=1.4.3,<2.0.0 arxiv
>=8.1.3,<9.0.0 click
>=2.2.0,<3.0.0 termcolor
>=1.4.4,<2.0.0 appdirs
>=1.2.2,<2.0.0 scikit-learn


زبان مورد نیاز

مقدار نام
>=3.9,<4.0 Python


نحوه نصب


نصب پکیج whl arxivterminal-0.3.1:

    pip install arxivterminal-0.3.1.whl


نصب پکیج tar.gz arxivterminal-0.3.1:

    pip install arxivterminal-0.3.1.tar.gz