Search Results for "python for windows" - Page 18
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Showing 2925 open source projects for "python for windows"
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Malicious PDF Generator
Generate a bunch of malicious pdf files with phone-home functionality
Generate ten different malicious PDF files with phone-home functionality. Can be used with Burp Collaborator or Interact.sh. Used for penetration testing and/or red-teaming etc. I created this tool because I needed a third-party tool to generate a bunch of PDF files with various links. -
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AdminSet
AdminSet for DevOps
Adminset is developed based on the DevOps concept and takes the integration of all operation and maintenance scenarios as its own responsibility. Adminset is a fully automated operation and maintenance platform developed based on operation and maintenance thinking. All functions of the client need to configure the ssh password-free login from the server to the client. -
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Terraform Examples and Modules for GC
End-to-end modular samples and landing zones toolkit for Terraform
Terraform Examples and Modules for GC is a comprehensive infrastructure-as-code toolkit built on Terraform that enables organizations to design, deploy, and manage enterprise-grade Google Cloud environments using modular and reusable components. It provides a collection of end-to-end blueprints and composable modules that allow teams to implement standardized cloud architectures such as landing zones, networking configurations, and security frameworks. The project is designed to accelerate... -
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Nevergrad
A Python toolbox for performing gradient-free optimization
Nevergrad is a Python library for derivative-free optimization, offering robust implementations of many algorithms suited for black-box functions (i.e. functions where gradients are unavailable or unreliable). It targets hyperparameter search, architecture search, control problems, and experimental tuning—domains in which gradient-based methods may fail or be inapplicable. The library provides an easy interface to define an optimization problem (parameter space, loss function, budget) and... -
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Strawberry GraphQL
A GraphQL library for Python that leverages type annotations
Python GraphQL library based on dataclasses. Strawberry's friendly API allows to create GraphQL API rather quickly, the debug server makes it easy to quickly test and debug. Django and ASGI support allow having your API deployed in production in a matter of minutes. The quick start method provides a server and CLI to get going quickly. Strawberry comes with a mypy plugin that enables statically type-checking your GraphQL schema. A Django view is provided for adding a GraphQL endpoint to your... -
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Graphene-Django
Integrate GraphQL into your Django project
Graphene-Django is built on top of Graphene. Graphene-Django provides some additional abstractions that make it easy to add GraphQL functionality to your Django project. First time? We recommend you start with the installation guide to get set up and the basic tutorial. It is worth reading the core graphene docs to familiarize yourself with the basic utilities. Graphene Django has a number of additional features that are designed to make working with Django easy. Our primary focus in this... -
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Flagsmith
Open source feature flagging and remote config service
Release features with confidence; manage feature flags across web, mobile, and server-side applications. Use our hosted API, deploy to your own private cloud, or run on-premises. Flagsmith provides an all-in-one platform for developing, implementing, and managing your feature flags. Whether you are moving off an in-house solution or using toggles for the first time, you will be amazed by the power and efficiency gained by using Flagsmith. Flagsmith makes it easy to create and manage feature... -
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Pipenv
Python Development Workflow for Humans
Pipenv is a package manager that brings all the best of the packaging world together to the Python world. It's got everything you could need: bundler, composer, npm, cargo, yarn and more all in one convenient package so you can easily set up a working environment. Pipenv creates and manages a virtualenv automatically, and can add or remove packages from your Pipfile as you install/uninstall packages. It also produces the Pipfile.lock, which is essential for deterministic... -
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Darts
A python library for easy manipulation and forecasting of time series
darts is a Python library for easy manipulation and forecasting of time series. It contains a variety of models, from classics such as ARIMA to deep neural networks. The models can all be used in the same way, using fit() and predict() functions, similar to scikit-learn. The library also makes it easy to backtest models, combine the predictions of several models, and take external data into account. Darts supports both univariate and multivariate time series and models. The ML-based models... -
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Claude Cookbooks
A collection of notebooks/recipes showcasing ways of using Claude
Claude Cookbooks is a curated collection of practical examples, notebooks, and implementation guides that demonstrate how to effectively use Claude’s API across a wide range of tasks. It serves as both a learning resource and a reference library, helping developers understand how to apply AI capabilities such as classification, summarization, and retrieval-augmented generation in real-world scenarios. The repository includes structured examples for integrating Claude with external tools,... -
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CTFd
CTFs as you need them
CTFd is a Capture The Flag framework focusing on ease of use and customizability. It comes with everything you need to run a CTF and it's easy to customize with plugins and themes. Create your own challenges, categories, hints, and flags from the Admin Interface. Dynamic Scoring Challenges. Unlockable challenge support. Challenge plugin architecture to create your own custom challenges. Static & Regex-based flags. Custom flag plugins. Unlockable hints. File uploads to the server or an Amazon... -
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SageMaker Training Toolkit
Train machine learning models within Docker containers
Train machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and... -
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SublimeLinter-eslint
This linter plugin for SublimeLinter provides an interface to ESLint
This linter plugin for SublimeLinter provides an interface to ESLint. It will be used with "JavaScript" files, but since eslint is pluggable, it can actually lint a variety of other files as well. SublimeLinter will detect some installed local plugins, and thus it should work automatically for e.g. .vue or .ts files. If it works on the command line, there is a chance it works in Sublime without further ado. Make sure the plugins are installed locally colocated to eslint itself. T.i.,... -
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Deepchecks
Test Suites for validating ML models & data
Deepchecks is the leading tool for testing and for validating your machine learning models and data, and it enables doing so with minimal effort. Deepchecks accompany you through various validation and testing needs such as verifying your data’s integrity, inspecting its distributions, validating data splits, evaluating your model and comparing between different models. While you’re in the research phase, and want to validate your data, find potential methodological problems, and/or validate... -
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Luigi
Python module that helps you build complex pipelines of batch jobs
Luigi is a Python (3.6, 3.7, 3.8, 3.9 tested) package that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization, handling failures, command line integration, and much more. The purpose of Luigi is to address all the plumbing typically associated with long-running batch processes. You want to chain many tasks, automate them, and failures will happen. These tasks can be anything, but are typically long running things like Hadoop... -
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TurboGears
Python web framework with full-stack layer
TurboGears is a hybrid web framework able to act both as a Full Stack framework or as a Microframework. TurboGears helps you get going fast and gets out of your way when you want it! TurboGears can be used both as a full stack framework or as a microframework in single-file mode. TurboGears 2 is built on top of the experience of several next-generation web frameworks including TurboGears 1 (of course), Django, and Rails. All of these frameworks had limitations that frustrated us, and TG2 was... -
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CodiumAI PR-Agent
AI-Powered tool for automated pull request analysis
CodiumAI PR-Agent is an open-source tool aiming to help developers review pull requests faster and more efficiently. It automatically analyzes the pull request and can provide several types of commands. See the Usage Guide for instructions how to run the different tools from CLI, online usage, Or by automatically triggering them when a new PR is opened. You can try GPT-4 powered PR-Agent, on your public GitHub repository, instantly. Just mention @CodiumAI-Agent and add the desired command in... -
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Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior... -
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Kornia
Open Source Differentiable Computer Vision Library
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within... -
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Anomalib
An anomaly detection library comprising state-of-the-art algorithms
Anomalib is an open-source deep learning library focused on anomaly detection and localization tasks, collecting state-of-the-art algorithms and tools under one modular framework. It provides implementations of leading anomaly detection methods drawn from current research, as well as a full set of utilities for training, evaluating, benchmarking, and deploying these models on both public and private datasets. Anomalib emphasizes flexibility and reproducibility: you can use its simple APIs to... -
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Meridian
Meridian is an MMM framework
Meridian is a comprehensive, open source marketing mix modeling (MMM) framework developed by Google to help advertisers analyze and optimize the impact of their marketing investments. Built on Bayesian causal inference principles, Meridian enables organizations to evaluate how different marketing channels influence key performance indicators (KPIs) such as revenue or conversions while accounting for external factors like seasonality or economic trends. The framework provides a robust... -
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GitSavvy
Full git and GitHub integration with Sublime Text
Sublime Text plugin providing probably all git has to offer. Sublime Text 2 is not supported. Also, GitSavvy takes advantage of modern features of Sublime Text (like annotations). For the best experience, use the latest Sublime Text dev build. The documentation is probably outdated. Yeah it's sad but you can contribute and I will eventually get onto it but every special view has help available, just press ?. GitSavvy requires Git versions at or greater than 2.18.0. basic Git functionality;... -
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DVC
Data Version Control | Git for Data & Models
DVC is built to make ML models shareable and reproducible. It is designed to handle large files, data sets, machine learning models, and metrics as well as code. Version control machine learning models, data sets and intermediate files. DVC connects them with code and uses Amazon S3, Microsoft Azure Blob Storage, Google Drive, Google Cloud Storage, Aliyun OSS, SSH/SFTP, HDFS, HTTP, network-attached storage, or disc to store file contents. Version control machine learning models, data sets,... -
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hosts
Consolidate and extend hosts files from several well-curated sources
Consolidating and extending hosts files from several well-curated sources. You can optionally pick extensions to block pornography, social media, and other categories. The unified hosts file is optionally extensible. Extensions are used to include domains by category. Currently, we offer the following categories: fakenews, social, gambling, and porn. Extensions are optional, and can be combined in various ways with the base hosts file. The combined products are stored in the alternates... -
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Smallpond
A lightweight data processing framework built on DuckDB and 3FS
smallpond is a lightweight distributed data processing framework built by DeepSeek, designed to scale DuckDB workloads over clusters using their 3FS (Fire-Flyer File System) backend. The idea is to preserve DuckDB’s fast analytics engine but lift it from single-node to multi-node settings, giving you the ability to operate on large datasets (e.g. petabyte scale) without moving to a heavyweight system like Spark. Users write Python-like code (via DataFrame APIs or SQL strings) to express...
