Search Results for "graphene"
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Showing 16 open source projects for "graphene"
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Graphene
GraphQL in Python Made Easy
Graphene is a Python library for building GraphQL APIs fast and easily, using a code-first approach. Instead of writing GraphQL Schema Definition Langauge (SDL), Python code is written to describe the data provided by your server. Graphene helps you use GraphQL effortlessly in Python, but what is GraphQL? GraphQL is a data query language developed internally by Facebook as an alternative to REST and ad-hoc webservice architectures. -
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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. -
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Graphene-SQLAlchemy
Graphene SQLAlchemy integration
A SQLAlchemy integration for Graphene. For installing Graphene, just run this command in your shell. Graphene is a powerful Python library for building GraphQL APIs, and SQLAlchemy is a popular ORM (Object-Relational Mapping) tool for working with databases. When combined, graphene-sqlalchemy allows developers to quickly and easily create a GraphQL API that seamlessly interacts with a SQLAlchemy-managed database. -
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Patched-Graphene
Magisk Patched builds of GrapheneOS (UNNOFFICIAL)
Magisk Patched builds of GrapheneOS UNNOFFICIAL -
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GQL
A GraphQL client in Python
This is a GraphQL client for Python 3.7+. Plays nicely with graphene, graphql-core, graphql-js and any other GraphQL implementation compatible with the spec. GQL architecture is inspired by React-Relay and Apollo-Client. GQL 3 is a GraphQL Client for Python 3.6+ which plays nicely with other graphql implementations compatible with the spec. Under the hood, it uses GraphQL-core which is a Python port of GraphQL.js, the JavaScript reference implementation for GraphQL. -
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AtomAI
Deep and Machine Learning for Microscopy
AtomAI is a Pytorch-based package for deep and machine-learning analysis of microscopy data that doesn't require any advanced knowledge of Python or machine learning. The intended audience is domain scientists with a basic understanding of how to use NumPy and Matplotlib. It was developed by Maxim Ziatdinov at Oak Ridge National Lab. The purpose of the AtomAI is to provide an environment that bridges the instrument-specific libraries and general physical analysis by enabling the seamless... -
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Gramine
A library OS for Linux multi-process applications
Gramine is a lightweight library-operating system (Library OS) designed to run unmodified Linux applications with minimal dependencies on the host OS, and to offer enhanced isolation and portability. It was formerly known as Graphene, but the project renamed to Gramine to avoid naming conflicts and to reflect its broader ambition beyond the original research prototype. The idea is that instead of running a full guest OS in a VM, you embed your application inside Gramine, which handles the system-call interface, process and thread management, file system, and network abstractions — everything the application expects — but strips out the overhead and complexity of a full OS stack. ... -
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Flask-GraphQL
Adds GraphQL support to your Flask application
Adds GraphQL support to your Flask application. This will add /graphql endpoint to your app and enable the GraphiQL IDE. If you are using the Schema type of Graphene library, be sure to use the graphql_schema attribute to pass as schema on the GraphQLView view. Otherwise, the GraphQLSchema from graphql-core is the way to go. The GraphQLSchema object that you want the view to execute when it gets a valid request. A value to pass as the context_value to graphql execute function. By default is set to dict with request object at key request. ... -
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Quantum Honeycomp
Interactive program to calculate electronic properties in graphene
Calculate electronic properties of graphene-like systems with a user friendly interface. The code uses the tight binding approximation and it is able to stude in a 0D, 1D and 2D geometries, orbital and magnetic fields, intrinsic and extrinsic spin-orbit coupling, sublattice imbalance, and interactions at the mean field level. The most recent version can be found in https://github.com/joselado/quantum-honeycomp Example videos https://www.youtube.com/watch? -
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graphene-like-ribbons
Calculate electronic properties of graphene-like nanoribbons
User friendly interface for calculating electronic properties in graphene-like ribbons. The programs uses the tight binding approximation and mean field Hubbard model to predict electronic properties of graphene-like nanoribbons. See Discussion to ask questions or details Update: New versions of this program will be known as quantum-honeycomp -
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GraBNES
Electronic properties of Graphene and BN
Graphene & Boron Nitride Enormous Systems -
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Graphene Dashboard
Graphene is a realtime dashboard & graphing toolkit based on D3
Graphene is a real-time dashboard and graphing toolkit built with D3.js and Backbone.js. It was originally designed to sit on top of the Graphite data model and API, enabling teams to quickly build live dashboards that show thousands of datapoints updating over time. The project provides a highly customizable and hackable client-side engine: you define “widgets” such as time series graphs, gauges or labels, hook them to data providers, and the toolkit handles ingestion, rendering and live updates. ... -
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A test project for computation of electron quantum transport properties of graphene ribbons. The computational results were published in Physical Review B 83, 245442 (2011). Fortran 90 + BLAS + LAPACK + MPI.
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xyz2eps
python command line utility to print xyz-geometry to eps file format.
xyz2eps.py is an command line utility written in Python programing language which prints the geometry from xyz-file directly to the eps-file format. Originally it was designed to study the problems related to grain boundaries in graphene. -
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ninithi 3D modelling software developed by Lanka Software Foundation can be used to visualize carbon nanotubes, fullerene, graphene and carbon nanoribbons and analyse their band structure plots.
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