Python Community Interview With Moshe Zadka

This week, I’m joined by Moshe Zadka, a senior site reliability engineer at SurveyMonkey. Moshe is a core developer for the Twisted framework and a Real Python author. In this interview, we discuss a variety of topics, including the Twisted framework, Python for DevOps, writing Python books, and tai chi. Ricky: Thanks for joining me, Moshe. I’d like to start with the same questions I do with all my interview guests: how did you get into programming, and when did […]

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How to Use Google’s NLP API to Analyze and Produce Better Content

Introduction Machine learning has revolutionized the way content marketers create content. It gave deep insights into what actually the search engine bots crawl and how they understand the natural language. Writing content today is a lot different than it was 15 years ago. In the past, the content was created for the Search Engines, which was enough to rank the website high. But, today, valuable content is not the one made specifically for search engines. In fact, creating such content […]

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The first dataset for learning Object Depth via Motion and Detection

ODMD Dataset ODMD is the first dataset for learning Object Depth via Motion and Detection. ODMD training data are configurable and extensible, with each training example consisting of a series of object detection bounding boxes, camera movement distances, and ground truth object depth. As a benchmark evaluation, we provide four ODMD validation and test sets with 21,600 examples in multiple domains, and we also convert 15,650 examples from the ODMS benchmark for detection. In our paper, we use a single […]

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OpenAI CLIP text encoders for any language

Multilingual-CLIP OpenAI CLIP text encoders for any language. OpenAI recently released the paper Learning Transferable Visual Models From Natural Language Supervision in which they present the CLIP (Contrastive Language–Image Pre-training) model. This model is trained to connect text and images, by matching their corresponding vector representations using a contrastive learning objective. CLIP consists of two separate models, a visual encoder and a text encoder. These were trained on a wooping 400 Million images and corresponding captions. OpenAI has since released […]

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A research-oriented benchmarking framework for advancing federated learning

FedNLP FedNLP is a research-oriented benchmarking framework for advancing federated learning (FL) in natural language processing (NLP). It uses FedML repository as the git submodule. In other words, FedNLP only focuses on adavanced models and dataset, while FedML supports various federated optimizers (e.g., FedAvg) and platforms (Distributed Computing, IoT/Mobile, Standalone). The figure below is the overall structure of FedNLP. avatar Installation After git clone-ing this repository, please run the following command to install our dependencies. conda create -n fednlp python=3.7 […]

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A command-line program to download media on OnlyFans

onlyfans-scraper A command-line program to download media, like posts, and more from creators on OnlyFans. Installation You can install this program by entering the following in your console: pip install onlyfans-scraper Setup Before you can fully use it, you need to fill out some fields in a auth.json file. This file will be created for you when you run the program for the first time. These are the fields: { “auth”: { “app-token”: “33d57ade8c02dbc5a333db99ff9ae26a”, “sess”: “”, “auth_id”: “”, “auth_uniq_”: “”, […]

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A Delaunay-based unstructured mesh generator

JIGSAW JIGSAW is an unstructured mesh generator and tessellation library; designed to generate high-quality triangulations and polyhedral decompositions of general planar, surface and volumetric domains. JIGSAW includes refinement-based algorithms for the construction of new meshes, optimisation-driven techniques for the improvement of existing grids, as well as routines to assemble (restricted) Delaunay tessellations, Voronoi complexes and Power diagrams. This package provides a Python based scripting interface to the underlying JIGSAW mesh generator, including a range of additional facilities for file I/O, […]

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Fault tolerant, stealthy, distributed web crawling with Pyppeteer

crawler-cluster Distributed, Fault-Tolerant Web Crawling. Multi-process, multiple workers Client process queues tasks in Redis. Worker nodes pull tasks from Redis, execute task, and store results in Redis. Client process pulls results from Redis. Pros: Worker nodes can run on any machine. Add or remove worker nodes at runtime without disrupting the system. Achieves fault-tolerance through process isolation and monitoring. Workers are ran as systemd services, where each service is the smallest possible processing unit (either a single browser with a […]

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A fast and powerful Graphical User Interface Toolkit for Python

Dear PyGui Dear PyGui is a simple to use (but powerful) Python GUI framework. Dear PyGui is NOT a wrapping of Dear ImGui in the normal sense. It is a library built with Dear ImGui which simulates a traditional retained mode GUI (as opposed to Dear ImGui’s immediate mode paradigm). Dear PyGui is fundamentally different than other Python GUI frameworks. Under the hood, Dear PyGui uses the immediate mode paradigm and your computer’s GPU to facilitate extremely dynamic interfaces. Dear […]

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A Fast End-to-End Neural Speech Recognition Toolkit

Espresso Espresso is an open-source, modular, extensible end-to-end neural automatic speech recognition (ASR) toolkit based on the deep learning library PyTorch and the popular neural machine translation toolkit fairseq. Espresso supports distributed training across GPUs and computing nodes, and features various decoding approaches commonly employed in ASR, including look-ahead word-based language model fusion, for which a fast, parallelized decoder is implemented. We provide state-of-the-art training recipes for the following speech datasets: Requirements and Installation PyTorch version >= 1.5.0 Python version […]

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