Models

Auto-generate Streamlit UI from Pydantic Models and Dataclasses

Streamlit Pydantic Auto-generate Streamlit UI elements from Pydantic models. Streamlit-pydantic makes it easy to auto-generate UI elements from Pydantic models. Just define your data model and turn it into a full-fledged UI form. It supports data validation, nested models, and field limitations. Streamlit-pydantic can be easily integrated into any Streamlit app. Beta Version: Only suggested for experimental usage. Highlights 🪄  Auto-generated UI elements from Pydantic models. 📇  Out-of-the-box data validation. 📑  Supports nested Pydantic models. 📏  Supports field limits and […]

Read more
Python

Using FastAPI to Build Python Web APIs

Creating APIs, or application programming interfaces, is an important part of making your software accessible to a broad range of users. In this tutorial, you will learn the main concepts of FastAPI and how to use it to quickly create web APIs that implement best practices by default. By the end of it, you will be able to start creating production-ready web APIs, and you will have the understanding needed to go deeper and learn more for your specific use […]

Read more
Advanced, NLP, Project, Python, Text, Unstructured Data

Indexing in Natural Language Processing for Information Retrieval

This article was published as a part of the Data Science Blogathon Overview This blog covers GREP(Global-Regular-Expression-Print) and its drawbacks Then we move on to Document Term Matrix and Inverted Matrix Finally, we end with dynamic and distributed indexing image source-https://javarevisited.blogspot.com/2011/06/10-examples-of-grep-command-in-unix-and.html#axzz6zwakOXgt     Global Regular Expression Print Whenever we are dealing with a small amount of data, we can use the grep command very efficiently. It allows us to search one or more files for lines that contain a pattern. For […]

Read more
Beginner, Data Science, Libraries, Machine Learning, NLP, Python, Text

NLTK: A Beginners Hands-on Guide to Natural Language Processing

This article was published as a part of the Data Science Blogathon Introduction:  NLTK is a toolkit build for working with NLP in Python. It provides us various text processing libraries with a lot of test datasets. A variety of tasks can be performed using NLTK such as tokenizing, parse tree visualization, etc… In this article, we will go through how we can set up NLTK in our system and use them for performing various NLP tasks during the text processing […]

Read more
Testing

Codecov coverage standard for Python

Python-Standard This is a Python application, with basic unit tests, for which coverage is uploaded to Codecov on a daily basis. It can also serve as an example for how to integrate Codecov into your Python project. If the build is passing for this project, then Codecov’s Python report processing is functional and correct on codecov.io. Configuration This project is written in Python 3.9. Unit tests are written with the pytest framework and coverage reports are generated using the pytest-cov […]

Read more
API

An API wrapper around the pythonanywhere’s API

pyaww An API wrapper around the pythonanywhere’s API. The name stands for pythonanywherewrapper. 100% API coverage Most of the codebase is documented & typehinted Maintained # import the module from pyaww.user import User # construct the user class client = User(auth=’…’, username=’…’) for console in client.consoles(): print(console.name) Please look at the documentations: https://ammarsys.github.io/pyaww-docs/ PyPi: https://pypi.org/project/pyaww # Linux/MacOS python3 -m pip install pyaww # Windows py -m pip install pyaww For the dev version, do: git clone https://github.com/ammarsys/pyaww cd pyaww GitHub […]

Read more
Automation

A Python package to facilitate research on building and evaluating automated scoring models

Automated scoring of written and spoken test responses is a growing field in educational natural language processing. Automated scoring engines employ machine learning models to predict scores for such responses based on features extracted from the text/audio of these responses. Examples of automated scoring engines include Project Essay Grade for written responses and SpeechRater for spoken responses. Rater Scoring Modeling Tool (RSMTool) is a python package which automates and combines in a single pipeline multiple analyses that are commonly conducted […]

Read more
Face recognition

A lightweight face-recognition toolbox and pipeline based on tensorflow-lite

FaceIDLight A lightweight face-recognition toolbox and pipeline based on tensorflow-lite with MTCNN-Face-Detection and ArcFace-Face-Recognition. No need to install complete tensorflow, tflite-runtime is enough. All tools are using CPU only. 📘 Description A lightweight face-recognition toolbox and pipeline based on tensorflow-lite with MTCNN-Face-Detectionand ArcFace-Face-Recognition. No need to install complete tensorflow, tflite-runtime is enough. All tools areusing CPU only. Pull request are welcome! ⚡️ Features Online Face-Recognition Running completely on CPU Multi Faces ~4 FPS on a MacBookPro2015 Tools for Face-Detection, -Verification […]

Read more
Excel

Accelerated Excel XLSX Writing Library for Python 2/3

PyExcelerate Accelerated Excel XLSX writing library for Python PyExcelerate is a Python for writing Excel-compatible XLSX spreadsheet files, with an emphasis on speed. Benchmarks Benchmark code located in pyexcelerate/tests/benchmark.pyUbuntu 12.04 LTS, Core i5-3450, 8GB DDR3, Python 2.7.3 | TEST_NAME | NUM_ROWS | NUM_COLS | TIME_IN_SECONDS | |—————————–|———-|———-|—————–| | pyexcelerate value fastest | 1000 | 100 | 0.47 | | pyexcelerate value faster | 1000 | 100 | 0.51 | | pyexcelerate value fast | 1000 | 100 | 1.53 | […]

Read more
1 … 559 560 561 562 563 … 927