Search Results for "common" - Page 3
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Showing 166 open source projects for "common"
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Python-Spider
Python3 web crawler practice
...As part of the author’s public learning-path repositories, python-spider likely includes examples of HTTP requests, HTML parsing, maybe concurrency or scheduling to crawl multiple pages, and techniques to handle common web-scraping issues. For people wanting to get hands-on with building scrapers, collecting data, or learning how to navigate web programming in Python, this repository acts as a didactic reference or starting point. Because it’s published publicly under an open license, users are free to fork and adapt the code. -
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AWS Chalice
Python Serverless Microframework for AWS
...It also manages per-stage configuration, environment variables, IAM permissions scaffolding, and packaging optimizations to keep cold starts small. While it’s intentionally lightweight, it supports common production needs like CORS, custom authorizers, binary responses, and fine-grained IAM so you can grow from prototype to production without rewriting your stack. -
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Google Toolbox for Mac
Google Toolbox for Mac
...It consolidates reusable code components drawn from various internal Google projects, offering developers a wide range of tools for building efficient, maintainable Apple platform software. The library includes modules for networking, logging, testing, data handling, and user interface extensions, helping developers avoid reinventing common functionality. Its modular design allows developers to integrate only the components they need, improving project flexibility and performance. With well-documented interfaces and consistent coding standards, Google Toolbox for Mac serves as a reliable foundation for both small and large-scale applications. It continues to be widely used across open source and internal projects that target Apple ecosystems. -
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Misago
Misago is fully featured modern forum application
Misago aims to be a complete, featured and modern forum solution that has no fear to say 'NO' to common and outdated opinions about how forum software should be made and what it should do. Your users may register accounts, set avatars, change options and edit their profiles. They have the option to reset forgotten passwords. Site admins may require users to confirm validity of their e-mail addresses via e-mail sent activation link, or limit user account activation to administrator action. ... -
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Ansible-lint
Best practices checker for Ansible
Ansible Lint is a command-line tool for linting playbooks, roles and collections aimed towards any Ansible users. Its main goal is to promote proven practices, patterns and behaviors while avoiding common pitfalls that can easily lead to bugs or make code harder to maintain. Ansible lint is also supposed to help users upgrade their code to work with newer versions of Ansible. Due to this reason we recommend using it with the newest version of Ansible, even if the version used in production may be older. As any other linter, it is opinionated. ... -
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torchvision
Datasets, transforms and models specific to Computer Vision
The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision. We recommend Anaconda as Python package management system. Torchvision currently supports Pillow (default), Pillow-SIMD, which is a much faster drop-in replacement for Pillow with SIMD, if installed will be used as the default. Also, accimage, if installed can be activated by calling torchvision.set_image_backend('accimage'), libpng, which can be installed via conda conda install libpng or any of the package managers for debian-based and RHEL-based Linux distributions, and libjpeg, which can be installed via conda conda install jpeg or any of the package managers for debian-based and RHEL-based Linux distributions. ... -
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Luigi
Python module that helps you build complex pipelines of batch jobs
...These tasks can be anything, but are typically long running things like Hadoop jobs, dumping data to/from databases, running machine learning algorithms, or anything else. You can build pretty much any task you want, but Luigi also comes with a toolbox of several common task templates that you use. It includes support for running Python mapreduce jobs in Hadoop, as well as Hive, and Pig, jobs. It also comes with file system abstractions for HDFS, and local files that ensures all file system operations are atomic. -
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sqlite-utils
Python CLI utility and library for manipulating SQLite databases
sqlite-utils is both a Python library and a command-line tool for creating, inspecting, and transforming SQLite databases with minimal boilerplate. It focuses on making common tasks like importing CSV/JSON, exploring tables, and running ad-hoc queries feel ergonomic and scriptable. As a CLI, it lets you build databases from structured data in one line, run queries against local files or in-memory databases, output results as JSON, CSV, or pretty tables, and configure full-text search. As a library, it exposes high-level APIs for inserting records, creating or transforming tables, normalizing schemas, and running migrations that SQLite’s limited ALTER TABLE cannot handle directly. ... -
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Prompt Engineering Interactive Tutorial
Anthropic's Interactive Prompt Engineering Tutorial
...The course leans heavily on realistic failure modes (ambiguity, hallucination, brittle instructions) and shows how to iteratively debug prompts the way you would debug code. Lessons include building prompts from scratch for common tasks like extraction, classification, transformation, and step-by-step reasoning, with checkpoints that let you compare your outputs against solid baselines. You’ll also practice advanced patterns such as tool use, constrained generation, and response validation so outputs are trustworthy and machine-consumable. -
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uwsgi-nginx-flask
Docker image with uWSGI and Nginx for Flask applications in Python
...This Docker image allows you to create Flask web applications in Python that run with uWSGI and Nginx in a single container. The combination of uWSGI with Nginx is a common way to deploy Python Flask web applications. It is widely used in the industry and would give you decent performance. If you are starting a new project, you might benefit from a newer and faster framework based on ASGI instead of WSGI (Flask and Django are WSGI-based). Also, if you want to use new technologies like WebSockets it would be easier (and possible) with a newer framework based on ASGI, like FastAPI or Starlette. ... -
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django-sspanel
Diango shadowsocks
...Smart subscription system , support ss/clash/clash premium version. Deep integration with transit tunnels , convenient and fast construction of transit tunnels d7e4380-6532-* Backend supports common protocols. Registration adopts the invitation system to bid farewell to bad users. Unified and perfect background management interface. Perfect commodity purchase logic. Alipay face-to-face payment module. Invitation rebate system. -
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Flask-SQLAlchemy
Adds SQLAlchemy support to Flask
Flask-SQLAlchemy is an extension for Flask that adds support for SQLAlchemy to your application. It simplifies using SQLAlchemy with Flask by setting up common objects and patterns for using those objects, such as a session tied to each web request, models, and engines. Flask-SQLAlchemy does not change how SQLAlchemy works or is used. See the SQLAlchemy documentation to learn how to work with the ORM in depth. The documentation here will only cover setting up the extension, not how to use SQLAlchemy. -
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whiteboxgui
An interactive GUI for WhiteboxTools in a Jupyter-based environment
The whiteboxgui Python package is a Jupyter frontend for WhiteboxTools, an advanced geospatial data analysis platform developed by Prof. John Lindsay (webpage; jblindsay) at the University of Guelph's Geomorphometry and Hydrogeomatics Research Group. WhiteboxTools can be used to perform common geographical information systems (GIS) analysis operations, such as cost-distance analysis, distance buffering, and raster reclassification. Remote sensing and image processing tasks include image enhancement (e.g. panchromatic sharpening, contrast adjustments), image mosaicing, numerous filtering operations, simple classification (k-means), and common image transformations. ... -
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DIG
A library for graph deep learning research
...If you are working or plan to work on research in graph deep learning, DIG enables you to develop your own methods within our extensible framework, and compare with current baseline methods using common datasets and evaluation metrics without extra efforts. It includes unified implementations of data interfaces, common algorithms, and evaluation metrics for several advanced tasks. Our goal is to enable researchers to easily implement and benchmark algorithms. -
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ImageAI
A python library built to empower developers
...ImageAI provides API to recognize 1000 different objects in a picture using pre-trained models that were trained on the ImageNet-1000 dataset. The model implementations provided are SqueezeNet, ResNet, InceptionV3 and DenseNet. ImageAI provides API to detect, locate and identify 80 most common objects in everyday life in a picture using pre-trained models that were trained on the COCO Dataset. -
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UnionML
Build and deploy machine learning microservices
...Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. Using industry-standard machine learning methods, implement endpoints for fetching data, training models, serving predictions (and much more) to write a complete ML stack in one place. Data science, ML engineering, and MLOps practitioners can all gather around UnionML apps as a way of defining a single source of truth about your ML system’s behavior. ... -
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FairScale
PyTorch extensions for high performance and large scale training
...Its components are modular, so teams can adopt just the sharding optimizer or the pipeline engine without rewriting their training loop. FairScale puts emphasis on correctness and debuggability, offering hook points, logging, and reference examples for common trainer patterns. Although many ideas have since landed in core PyTorch, FairScale remains a valuable reference and a practical toolbox for squeezing more performance out of multi-GPU and multi-node jobs. -
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CommandlineConfig
A library for users to write configurations in Python
...One of its core strengths is the ability to override configuration values directly from the command line, making it convenient to run many experimental variants without editing files repeatedly. The library supports arbitrarily deep nested structures, type handling, enumerated value constraints, and even tuple types, which are common in ML experiment setups. It also includes features for automatic version checking and convenient help output, so users can quickly see available parameters and their descriptions via a -h flag. -
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Jraph
A Graph Neural Network Library in Jax
...The library includes a comprehensive set of utilities for batching, padding, masking, and partitioning graph data, making it ideal for distributed and large-scale GNN experiments. Jraph also comes with a model zoo—a collection of forkable reference implementations of common message-passing GNN architectures, such as Graph Networks, Graph Convolutional Networks, and Graph Attention Networks. -
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Rank-BM25
A Collection of BM25 Algorithms in Python
A collection of algorithms for querying a set of documents and returning the ones most relevant to the query. The most common use case for these algorithms is, as you might have guessed, to create search engines. -
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AWS Step Functions Data Science SDK
For building machine learning (ML) workflows and pipelines on AWS
The AWS Step Functions Data Science SDK is an open-source library that allows data scientists to easily create workflows that process and publish machine learning models using Amazon SageMaker and AWS Step Functions. You can create machine learning workflows in Python that orchestrate AWS infrastructure at scale, without having to provision and integrate the AWS services separately. The best way to quickly review how the AWS Step Functions Data Science SDK works is to review the related... -
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Interpret-Text
State-of-the-art explainers for text-based machine learning models
A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard. Interpret-Text builds on Interpret, an open source python package for training interpretable models and helping to explain blackbox machine learning systems. We have added extensions to support text models. Interpret-Text incorporates community-developed interpretability techniques for NLP models and a visualization dashboard to view the results.... -
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The Common Event Driven Application Runtime (CEDAR) is set of software to design, code generate and run, event driven applications. This formalism is an extension of the Shlaer–Mellor method and executable UML, facilitating deployment of domains across multiple hosts, using networked bridges to process and pass events between them. Core technologies: XML, Python, Qt/PySide.
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FormatFuzzer
FormatFuzzer is a framework for generation and parsing of binary input
FormatFuzzer is a framework for high-efficiency, high-quality generation and parsing of binary inputs. It takes a binary template that describes the format of a binary input and generates an executable that produces and parses the given binary format.
