Search Results for "nvm-setup"
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Showing 83 open source projects for "nvm-setup"
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1
PokeAPI
The Pokémon API
This setup allows you to deploy a production-like environment, with separate containers for each service and is recommended if you need to simply spin up PokéAPI. -
2
GAM
Command line management for Google Workspace
...GAM requires paid (or Education/non-profit) editions of Google Workspace. G Suite Legacy Free Edition has limited API support and not all GAM commands work. While many GAM functions do not require domain administrative privileges, the setup does. Download GAM, then run the MSI installer. By default, GAM will install to C:\GAM but you can change this to wherever you prefer. GAM will also be added to your path so you can run GAM even if you're not in the GAM folder. At the end of the MSI install process, GAM will open a command prompt to allow you to setup a project and authorize GAM for admin management and user data/config access. -
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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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Google Cloud Platform Python Samples
Code samples used on cloud.google
...The repository is organized into product-specific directories, allowing developers to quickly locate examples relevant to their use case and adapt them into production workflows. It emphasizes hands-on learning by guiding users through setup steps such as creating virtual environments, installing dependencies, and running scripts locally. These samples are designed to accelerate development by showing best practices for connecting services, handling data, and managing cloud resources programmatically. -
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PyInstaller
Freeze (package) Python programs into stand-alone executables
...This means that, with PyInstaller, all the required tricks to make external packages work are already integrated within PyInstaller itself so that there is no user intervention required. You’ll never be required to look for tricks in wikis and apply custom modification to your files or your setup scripts. As an example, libraries like PyQt, Django or matplotlib are fully supported, without having to handle plugins or external data files manually. -
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cheat.sh
The only cheat sheet you need
...You can query it from the terminal (for example curl cht.sh/rsync or curl cheat.sh/ls) or browse the web front page; it also supports a shorthand hostname (cht.sh) and provides both online and standalone/local installation modes. The repository contains the server and client code, instructions to run a local standalone instance (including Python virtualenv setup), and tooling to fetch or maintain the upstream cheat-sheet data; installation documentation explains disk-space needs and dependency setup for offline use. Cheat.sh is intentionally minimal and scriptable, so it fits naturally into shells, CI scripts, editors, and quick lookups without leaving the terminal, while also offering ways to extend or host personal cheat sheets. -
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Claude Quickstarts
A collection of projects for building deployable applications
...Each quickstart provides a foundational codebase with preconfigured settings and examples for common deployment scenarios, so developers can focus on customizing functionality instead of bootstrapping infrastructure. The repository includes demos, sample integrations, and instructions to get environments running with minimal setup while handling authentication, API calls, and error handling best practices. Because it’s designed as a learning and prototyping resource, Claude Quickstarts supports exploration of interactive applications, backend services, and workflows that benefit from large language model capabilities. -
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Testcontainers Python
Testcontainers is a Python library that providing a friendly API
Testcontainers is a Python library that provides a friendly API to run a Docker container. It is designed to create a runtime environment to use during your automatic tests. -
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Flask RESTX
Fully featured framework for fast, easy and documented API development
Fork of Flask-RESTPlus fully featured framework for fast, easy and documented API development with Flask. Flask-RESTX is an extension for Flask that adds support for quickly building REST APIs. Flask-RESTX encourages best practices with minimal setup. If you are familiar with Flask, Flask-RESTX should be easy to pick up. It provides a coherent collection of decorators and tools to describe your API and expose its documentation properly using Swagger. With Flask-RESTX, you only import the api instance to route and document your endpoints. -
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Courses (Anthropic)
Anthropic's educational courses
...Assignments emphasize realistic tasks such as building small utilities, testing prompts against edge cases, and measuring quality so you learn to ship things that work. The materials are written for developers but remain friendly to newcomers, with clear setup instructions and minimal boilerplate. Because the repo is live and maintained, lessons are updated as the SDK and models evolve, and issues are used to track fixes, clarifications, and new modules. -
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Cobbler
Cobbler is a versatile Linux deployment server
Cobbler is a Linux installation server that allows for rapid setup of network installation environments. It glues together and automates many associated Linux tasks so you do not have to hop between many various commands and applications when deploying new systems, and, in some cases, changing existing ones. Cobbler can help with provisioning, managing DNS and DHCP, package updates, power management, configuration management orchestration, and much more. -
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Cookiecutter Django
Framework for jumpstarting production-ready Django projects quickly
...Optimized development and production settings. Registration is handled via django-allauth. It comes with custom user model ready to go. Provides an optional basic ASGI setup for Websockets and an optional custom static build using Gulp and livereload. Send emails via Anymail (using Mailgun by default or Amazon SES if AWS is selected cloud provider, but switchable). Media storage using Amazon S3 or Google Cloud Storage. Docker support using docker-compose for development and production (using Traefik with LetsEncrypt support). ... -
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Poetry
Python packaging and dependency management made easy
Poetry is a comprehensive Python dependency management and packaging tool that streamlines project setup and maintenance. By consolidating various configuration files into a single pyproject.toml, it simplifies the management of dependencies, virtual environments, and package publishing. Poetry ensures consistency across development environments and facilitates the creation of reproducible builds, making it an essential tool for Python developers seeking efficiency and reliability. -
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Hera
Hera is an Argo Python SDK
Hera is an Argo Python SDK. Hera aims to make the construction and submission of various Argo Project resources easy and accessible to everyone! Hera abstracts away low-level setup details while still maintaining a consistent vocabulary with Argo. -
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Django RQ
A simple app that provides django integration for RQ
...If you have django-redis or django-redis-cache installed, you can instruct django_rq to use the same connection information from your Redis cache. This has two advantages, it's DRY and it takes advantage of any optimization that may be going on in your cache setup (like using connection pooling or Hiredis.) -
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FastUI
Build better UIs faster
FastUI is a library that lets developers build interactive user interfaces for FastAPI applications using Pydantic models. It automatically generates frontend components based on data schemas and endpoint logic, reducing the need for manual UI development. Designed to be type-safe, reactive, and fast, FastUI streamlines the creation of web dashboards, admin panels, and internal tools within a FastAPI backend. -
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Raglite
RAGLite is a Python toolkit for Retrieval-Augmented Generation
Raglite is a lightweight framework for building Retrieval-Augmented Generation (RAG) pipelines with minimal configuration. It connects large language models to vector databases for context-aware responses, enabling developers to prototype and deploy RAG systems quickly. Raglite focuses on simplicity and modularity for fast experimentation. -
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Python Web
Course to learn frontend web development
This repository is a beginner-friendly template for creating Python web applications using Flask. Designed by @mouredev for learning and practice, it provides a simple, minimalistic structure for serving HTML pages and static content. Ideal for educational purposes and small-scale web projects, it also includes preconfigured files to simplify deployment and local development. -
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Helium
Lighter web automation with Python
Helium is a Python library built on top of Selenium to make browser automation more intuitive and human-friendly. It replaces verbose boilerplate code with natural language-like API calls such as click("Login") or write("hello", into="Name"). Helium manages browser setup, waits, and teardown, enabling quick development of scripts for testing, scraping, or task automation without requiring deep Selenium knowledge. -
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cmake-conan
CMake wrapper for conan C and C++ package manager
cmake-conan is a CMake wrapper for the Conan C and C++ package manager, designed to streamline the integration of Conan into CMake-based projects. It automates the process of installing and managing dependencies, allowing developers to define their requirements in Conan and have them seamlessly integrated into their CMake build process. This tool simplifies dependency management and enhances reproducibility in C++ projects. -
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Mistral Inference
Official inference library for Mistral models
Open and portable generative AI for devs and businesses. We release open-weight models for everyone to customize and deploy where they want it. Our super-efficient model Mistral Nemo is available under Apache 2.0, while Mistral Large 2 is available through both a free non-commercial license, and a commercial license. -
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AWS Deep Learning Containers
A set of Docker images for training and serving models in TensorFlow
...They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well. This project is licensed under the Apache-2.0 License. Ensure you have access to an AWS account i.e. setup your environment such that awscli can access your account via either an IAM user or an IAM role. -
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TradingAgents
Chinese Financial Trading Framework Based on Multi-Agent LLM
TradingAgents-CN is a Chinese-enhanced, multi-agent LLM framework aimed at building financial analysis and trading-oriented workflows, with an emphasis on collaboration between specialized agents rather than a single monolithic prompt. It organizes market-related tasks into roles and stages so different agents can contribute research, reasoning, aggregation, and decision support in a structured pipeline. The project is oriented toward practical usage, including a stack that can be run in a... -
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Graphene-SQLAlchemy
Graphene SQLAlchemy integration
...It is fully compatible with SQLAlchemy 1.4 and 2.0. This documentation provides detailed instructions on how to get started with graphene-sqlalchemy, including installation, setup, and usage examples. -
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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...
