معرفی شرکت ها


ekorpkit-0.1.40.post0.dev8


Card image cap
تبلیغات ما

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

مشاهده بیشتر
Card image cap
تبلیغات ما

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

مشاهده بیشتر
Card image cap
تبلیغات ما

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

مشاهده بیشتر
Card image cap
تبلیغات ما

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

مشاهده بیشتر
Card image cap
تبلیغات ما

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

مشاهده بیشتر

توضیحات

eKorpkit provides a flexible interface for NLP and ML research pipelines such as extraction, transformation, tokenization, training, and visualization.
ویژگی مقدار
سیستم عامل -
نام فایل ekorpkit-0.1.40.post0.dev8
نام ekorpkit
نسخه کتابخانه 0.1.40.post0.dev8
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Young Joon Lee
ایمیل نویسنده -
آدرس صفحه اصلی https://github.com/entelecheia/ekorpkit
آدرس اینترنتی https://pypi.org/project/ekorpkit/
مجوز -
# ekorpkit 【iːkɔːkɪt】 : **eKo**nomic **R**esearch **P**ython Tool**kit** [![PyPI version](https://badge.fury.io/py/ekorpkit.svg)](https://badge.fury.io/py/ekorpkit) [![Jupyter Book Badge](https://jupyterbook.org/en/stable/_images/badge.svg)](https://entelecheia.github.io/ekorpkit-book/) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.6497226.svg)](https://doi.org/10.5281/zenodo.6497226) [![release](https://github.com/entelecheia/ekorpkit/actions/workflows/release.yaml/badge.svg)](https://github.com/entelecheia/ekorpkit/actions/workflows/release.yaml) [![CodeQL](https://github.com/entelecheia/ekorpkit/actions/workflows/codeql-analysis.yml/badge.svg)](https://github.com/entelecheia/ekorpkit/actions/workflows/codeql-analysis.yml) [![test](https://github.com/entelecheia/ekorpkit/actions/workflows/test.yaml/badge.svg)](https://github.com/entelecheia/ekorpkit/actions/workflows/test.yaml) [![CircleCI](https://circleci.com/gh/entelecheia/ekorpkit/tree/main.svg?style=shield)](https://circleci.com/gh/entelecheia/ekorpkit/tree/main) [![codecov](https://codecov.io/gh/entelecheia/ekorpkit/branch/main/graph/badge.svg?token=8I4ORHRREL)](https://codecov.io/gh/entelecheia/ekorpkit) [![markdown-autodocs](https://github.com/entelecheia/ekorpkit/actions/workflows/markdown-autodocs.yaml/badge.svg)](https://github.com/entelecheia/ekorpkit/actions/workflows/markdown-autodocs.yaml) eKorpkit provides a flexible interface for NLP and ML research pipelines such as extraction, transformation, tokenization, training, and visualization. Its powerful config composition is backed by [Hydra](https://hydra.cc/). ## Key features ### Easy Configuration - You can compose your configuration dynamically, enabling you to easily get the perfect configuration for each research. - You can override everything from the command line, which makes experimentation fast, and removes the need to maintain multiple similar configuration files. - With a help of the **eKonf** class, it is also easy to compose configurations in a jupyter notebook environment. ### No Boilerplate - eKorpkit lets you focus on the problem at hand instead of spending time on boilerplate code like command line flags, loading configuration files, logging etc. ### Workflows - A workflow is a configurable automated process that will run one or more jobs. - You can divide your research into several unit jobs (tasks), then combine those jobs into one workflow. - You can have multiple workflows, each of which can perform a different set of tasks. ### Sharable and Reproducible - With eKorpkit, you can easily share your datasets and models. - Sharing configs along with datasets and models makes every research reproducible. - You can share each unit jobs or an entire workflow. ### Pluggable Architecture - eKorpkit has a pluggable architecture, enabling it to combine with your own implementation. ## [Tutorials](https://entelecheia.github.io/ekorpkit-book) Tutorials for [ekorpkit](https://github.com/entelecheia/ekorpkit) package can be found at https://entelecheia.github.io/ekorpkit-book/ ## [Installation](https://entelecheia.github.io/ekorpkit-book/docs/basics/install.html) Install the latest version of ekorpkit: ```bash pip install ekorpkit ``` To install all extra dependencies, ```bash pip install ekorpkit[all] ``` ## [The eKorpkit Corpus](https://github.com/entelecheia/ekorpkit/blob/main/docs/corpus/README.md) The eKorpkit Corpus is a large, diverse, bilingual (ko/en) language modelling dataset. ![ekorpkit corpus](https://github.com/entelecheia/ekorpkit/blob/main/docs/figs/ekorpkit_corpus.png?raw=true) ## Citation ```tex @software{lee_2022_6497226, author = {Young Joon Lee}, title = {eKorpkit: eKonomic Research Python Toolkit}, month = apr, year = 2022, publisher = {Zenodo}, doi = {10.5281/zenodo.6497226}, url = {https://doi.org/10.5281/zenodo.6497226} } ``` ```tex @software{lee_2022_ekorpkit, author = {Young Joon Lee}, title = {eKorpkit: eKonomic Research Python Toolkit}, month = apr, year = 2022, publisher = {GitHub}, url = {https://github.com/entelecheia/ekorpkit} } ``` ## License - eKorpkit is licensed under the [MIT License](https://opensource.org/licenses/MIT). This license covers the eKorpkit package and all of its components. - Each corpus adheres to its own license policy. Please check the license of the corpus before using it!


نیازمندی

مقدار نام
- numpy
- tqdm
- pandas
>=1.2.0 hydra-core
- hydra-colorlog
- pydantic
- python-dotenv
- gdown
- chardet
- rehash
- requests
- scipy
>=0.64.0 pytablewriter
- ftfy
<3.0,>=2.0 requests
>=11.1 rich
<3.8,>=3.4 filelock
>=0.8.1 huggingface-hub
- dataclasses
<9.1.0 Pillow
- accelerate
- pysbd
- lsh
- jsonpath-ng
- tensorflow
- p-tqdm
- pysimdjson
- statsmodels
- flaml
- pynori
- mecab-python3
<2.0 emoji
- rich
- py7zr
- accelerate
- jsonlines
<9.1.0 Pillow
- dicttoxml
- scipy
- fredapi
- nasdaq-data-link
- pathos
- beautifulsoup4
- mecab-ko-dic
- evaluate
- datasets
- wordcloud
- joblib
- pyLDAvis
- cssutils
- nltk
- fugashi
- html-to-json
- zstandard
- tomotopy
- datasketch
- matplotlib
- sacremoses
- kaleido
- soynlp
- orjson
- seaborn
- loky
- openpyxl
- cleanlab
- plotly
- wget
>=0.63 simpletransformers
- flax
- timm
- unidecode
- jax
- lpips
- einops
==4.5.5.64 opencv-python
- flaml
- scipy
<2.0,>=1.0 boto3
- beautifulsoup4
- pyhwp
<2.0,>=1.0 boto3
<2.0,>=1.0 boto3
<0.9.0,>=0.8.1 huggingface-hub
<3.0,>=1.32.0 google-cloud-storage
- cleanlab
- cssutils
- flax
- jax
- pymongo
- pysbd
- lsh
- jsonpath-ng
- p-tqdm
- pysimdjson
<2.0 emoji
- py7zr
- jsonlines
- pathos
- beautifulsoup4
- datasets
- joblib
- zstandard
- loky
- tensorflow-datasets
- orjson
- openpyxl
- wget
- datasketch
- datasets
- datasketch
- ray
- modin
- dicttoxml
- timm
- unidecode
- lpips
- einops
==4.5.5.64 opencv-python
- matplotlib
- kaleido
- rich
- seaborn
- plotly
<9.1.0 Pillow
- pathos
- cssutils
- einops
<2.0 emoji
- evaluate
- pysbd
- lsh
- spacy
- rubrix
- mail-parser
- numba
<2.0,>=1.0 boto3
- jsonpath-ng
<0.9.0,>=0.8.1 huggingface-hub
- timm
- tensorflow
- p-tqdm
- pysimdjson
- statsmodels
- lpips
>=0.63 simpletransformers
- flaml
- pynori
- mecab-python3
<2.0 emoji
- pymongo
- rich
- py7zr
- flax
- yellowbrick
- accelerate
- jsonlines
<9.1.0 Pillow
- dicttoxml
- unidecode
- scipy
- pubmed-parser
<3.0,>=1.32.0 google-cloud-storage
- namu-wiki-extractor
- fredapi
- nasdaq-data-link
- pathos
- wikiextractor
- ray
- beautifulsoup4
- mecab-ko-dic
- evaluate
- datasets
- modin
- wordcloud
- joblib
- pyLDAvis
- cssutils
- fugashi
- nltk
- fasttext-langdetect
- html-to-json
- zstandard
- tomotopy
==4.5.5.64 opencv-python
- pdfplumber
- google-api-python-client
- matplotlib
- sacremoses
- kaleido
- soynlp
- orjson
- seaborn
- loky
- openpyxl
- cleanlab
- plotly
- tensorflow-datasets
- guesslang
- jax
- wget
- pyhwp
- einops
- datasketch
- fasttext-langdetect
- wget
- zstandard
- py7zr
- flaml
- flax
- nasdaq-data-link
- fredapi
- pdfplumber
- statsmodels
- fredapi
- fredapi
- fugashi
- google-api-python-client
<3.0,>=1.32.0 google-cloud-storage
- google-api-python-client
<3.0,>=1.32.0 google-cloud-storage
- guesslang
<0.9.0,>=0.8.1 huggingface-hub
- html-to-json
- html-to-json
<0.9.0,>=0.8.1 huggingface-hub
- pyhwp
- jax
- joblib
- jsonlines
- jsonpath-ng
- kaleido
- cleanlab
- rubrix
- fasttext-langdetect
- loky
- lpips
- lsh
- mail-parser
- mail-parser
- matplotlib
- mecab-python3
- mecab-ko-dic
- mecab-ko-dic
- mecab-python3
- flaml
- datasets
- evaluate
- tensorflow
- accelerate
- scipy
>=0.63 simpletransformers
- modin
- namu-wiki-extractor
- nasdaq-data-link
- nasdaq-data-link
- nltk
- numba
==4.5.5.64 opencv-python
- openpyxl
- orjson
- p-tqdm
- mail-parser
- jsonpath-ng
- p-tqdm
- pysimdjson
- jsonlines
- pubmed-parser
- namu-wiki-extractor
- wikiextractor
- pathos
- beautifulsoup4
- joblib
- cssutils
- fasttext-langdetect
- html-to-json
- pdfplumber
- loky
- orjson
- openpyxl
- pyhwp
- pathos
- pdfplumber
- plotly
- pubmed-parser
- pubmed-parser
- py7zr
- pyLDAvis
- pyhwp
- pymongo
- pynori
- pysbd
- pysimdjson
- ray
- rich
- rubrix
- sacremoses
- scipy
- seaborn
>=0.63 simpletransformers
- soynlp
- spacy
- statsmodels
- statsmodels
- tensorflow
- tensorflow-datasets
- timm
- pysbd
- mecab-ko-dic
- spacy
- pynori
- mecab-python3
- sacremoses
<2.0 emoji
- soynlp
- nltk
- fugashi
- nltk
- pysbd
- tomotopy
- wordcloud
- pyLDAvis
- tomotopy
- datasets
- accelerate
- evaluate
>=0.63 simpletransformers
- unidecode
- matplotlib
- wordcloud
- kaleido
- rich
- seaborn
- plotly
<9.1.0 Pillow
- wget
- namu-wiki-extractor
- wikiextractor
- wikiextractor
- wordcloud
- dicttoxml
- yellowbrick
- zstandard


زبان مورد نیاز

مقدار نام
>=3.7 Python


نحوه نصب


نصب پکیج whl ekorpkit-0.1.40.post0.dev8:

    pip install ekorpkit-0.1.40.post0.dev8.whl


نصب پکیج tar.gz ekorpkit-0.1.40.post0.dev8:

    pip install ekorpkit-0.1.40.post0.dev8.tar.gz