Search Results for "code" - Page 16
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Showing 922 open source projects for "code"
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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... -
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WebExKit
An HTML/CSS/JavaScript editor with preview window
The Web Experimentation Kit allows you to enter HTML, CSS and JavaScript and see the results immediately in a browser frame side-by-side with the editor. If you've seen the W3Schools Tryit Editor, JSFiddle or CodePen then this should be familiar to you. The difference between WebExKit and these other applications is that WebExKit is a stand-alone application that runs on your desktop and it allows you to save (and reload) files to your own disk drive. The editor shows a properly formed... -
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UltiSnips
Snippet solution for Vim
UltiSnips is the ultimate solution for snippets in Vim. It has many features, speed being one of them. You should first expand the #! snippet, then the class snippet. The completion menu comes from YouCompleteMe, UltiSnips also integrates with deoplete, and more. You can jump through placeholders and add text while the snippet inserts text in other places automatically: when you add Animal as a base class, __init__ gets updated to call the base class constructor. When you add arguments to... -
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PyTorch Natural Language Processing
Basic Utilities for PyTorch Natural Language Processing (NLP)
...It’s open-source software, released under the BSD3 license. With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. For example, check out this example code for training on the Stanford Natural Language Inference (SNLI) Corpus. Now you've setup your pipeline, you may want to ensure that some functions run deterministically. Wrap any code that's random, with fork_rng and you'll be good to go. Now that you've computed your vocabulary, you may want to make use of pre-trained word vectors to set your embeddings. -
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Python Patterns
A collection of design patterns/idioms in Python
...Includes pattern examples for testability, delegation, flyweight, proxy, etc., plus patterns outside the classical set (registry, specification, etc.) Each pattern has readable example code, often in its own module/file, sometimes showing more than one implementation style. -
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pysourceinfo
RTTI for Python Source and Binary Files
The 'pysourceinfo' package provides source information on Python runtime objects based on 'inspect', 'sys', 'os', and 'imp'. The covered objects include packages, modules, functions, methods, scripts, and classes by two views: - File System View - packages, modules, and linenumbers - based on files and paths - Runtime Object View - callables, classes, and containers - based on in-memory RTTI / introspection The supported platforms are: - Linux, BSD, Unix, OS-X, Cygwin, and... -
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Optimized Storage for temporal Data
open Optimized Storage of time series data
Beta version. Base class for optimized storage of time series data. Uses any kind of relational database. Cross plateform with multiple languages (C++, C#, Java). Conditional storage based on value variation : DeltaValue and DeltaTime params. Get back data without losts. -
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platformids
OS and Distribution Release Enumeration
The ‘platformids‘ package provides the categorization and enumeration of OS platforms and distributions. This enables the development of portable generic code for arbitrary platforms in IT and IoT landscapes consisting of heterogeneous physical and virtual runtime environments. The introduced hierarchical bitmask vectors enable for fast and efficient platform specific code and data selection for OS and distributions with routines for specific platform releases. The supported version numbering comprise various release schemes such as classical version numbers with variable segments and optional release names, * AlpineLinux-3.8.1 * CentOS-6.10 * Debian-9.6 * Fedora31 * OS-X-10.6.8 * Ubuntu-18.04 * armbian-5.76 * cygwin-2.9.0 * opensuse-15.1 * raspbian-9.4 * slackware-14.2 * solaris-11.3 variations of numbering schemes and continous deployment * CentOS-7.6-1810 * NT-6.3.9600 * archlinux-2018.12.01 * kali-linux-2019.1 * NT-10.0.1809 -
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pythonids
Enumeration of Python implementations and releases
The ‘pythonids‘ package provides the enumeration of Python syntaxes and the categorization of Python implementations. This enables the development of fast and easy portable generic code for arbitrary platforms in IT and IoT landscapes consisting of heterogeneous physical and virtual runtime environments. The current supported syntaxes are Python2.7+ and Python3 for the Python implementations: CPython IPython (based on CPython) IronPython Jython PyPy -
Dun and Bradstreet Connect simplifies the complex burden of data managementThe amount, speed, and types of data created in today’s world can be overwhelming. With D&B Connect, you can instantly benchmark, enrich, and monitor your data against the Dun & Bradstreet Data Cloud to help ensure your systems of record have trusted data to fuel growth.
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abu
Abu quantitative trading system (stocks, options, futures, bitcoin)
Abu Quantitative Integrated AI Big Data System, K-Line Pattern System, Classic Indicator System, Trend Analysis System, Time Series Dimension System, Statistical Probability System, and Traditional Moving Average System conduct in-depth quantitative analysis of investment varieties, completely crossing the user's complex code quantification stage, more suitable for ordinary people to use, towards the era of vectorization 2.0. The above system combines hundreds of seed quantitative models, such as financial time series loss model, deep pattern quality assessment model, long and short pattern combination evaluation model, long pattern stop-loss strategy model, short pattern covering strategy model, big data K-line pattern Historical portfolio fitting model, trading position mentality model, dopamine quantification model, inertial residual resistance support model, long-short swap revenge probability model, strong and weak confrontation model, trend angle change rate model, etc. -
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I3D models trained on Kinetics
Convolutional neural network model for video classification
Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with both RGB and optical flow input streams. ... -
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hug
Embrace the APIs of the future. For developing APIs
...As a result, it drastically simplifies Python API development. Make developing a Python-driven API as succinct as a written definition. The framework should encourage code that self-documents. It should be fast. A developer should never feel the need to look somewhere else for performance reasons. Writing tests for APIs written on-top of hug should be easy and intuitive. Magic done once, in an API framework, is better than pushing the problem set to the user of the API framework. Be the basis for next-generation Python APIs, embracing the latest technology. -
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Nebula docs
Documentation repo of nebula orchestration system
...Ever wandered how your going to push an update to that smart fridge your company is working on as it's thousands of devices around the globe? wish you could have the assurance that your service will always use the latest code\envvars\etc in all of it's edge locations? want the ability to stop\start a globally distributed service with a single command? Nebula was designed from the ground up to answer all of this needs. -
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MMF
A modular framework for vision & language multimodal research
...MMF contains reference implementations of state-of-the-art vision and language models and has powered multiple research projects at Facebook AI Research. MMF is designed from ground up to let you focus on what matters, your model, by providing boilerplate code for distributed training, common datasets and state-of-the-art pre-trained baselines out-of-the-box. MMF is built on top of PyTorch that brings all of its power in your hands. MMF is not strongly opinionated. So you can use all of your PyTorch knowledge here. MMF is created to be easily extensible and composable. Through our modular design, you can use specific components from MMF that you care about. ... -
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Nebula reporter
The optional reporter container which reads nebula reports from Kafka
...Ever wandered how your going to push an update to that smart fridge your company is working on as it's thousands of devices around the globe? wish you could have the assurance that your service will always use the latest code\envvars\etc in all of its edge locations? want the ability to stop\start a globally distributed service with a single command? Nebula was designed from the ground up to answer all of these needs and much more, refer to the documentation if your interested in seeing how to use it. -
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captcha_break
Identification codes
...It supports image verification codes and voice verification codes. We use its function of generating image verification codes. First, we set our verification code format to numbers and capital letters, and generate a string of verification codes. It is well known that tensorflow occupies all video memory by default, which is not conducive to us conducting multiple experiments at the same time, so we can use the following code when tensorflow uses the video memory it needs instead of directly occupying all video memory. -
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Embed Prolog directly in your Python, C# or Javascript program using the yield keyword. There is no API standing between your code and Yield Prolog, so you can use all language features, including arrays, file I/O, user interaction and your own classes.
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Platformer 2D Godot Game
Test project with a 2D platform game developing in Godot 3.1
Test project with a 2D platform game developing in Godot 3.1, reusable mechanics for: State Machine, basics AI, Android Games. -
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UniCC LALR(1) Parser Generator
Parser generator, targetting C, C++, Python, JavaScript, JSON and XML
UniCC (UNIversal Compiler-Compiler) compiles an augmented grammar definition into a program source code that parses the described grammar. Because UniCC is intended to be target-language independent, it can be configured via template definition files to emit parsers in almost any programming language. UniCC comes with out of the box support for the programming languages C, C++, Python (both 2.x and 3.x) and JavaScript. Parsers can also be generated into JSON and XML. -
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TGAN
Generative adversarial training for generating synthetic tabular data
...Also, although it is not strictly required, the usage of a virtualenv is highly recommended in order to avoid interfering with other software installed in the system where TGAN is run. For development, you can use make install-develop instead in order to install all the required dependencies for testing and code listing. In order to be able to sample new synthetic data, TGAN first needs to be fitted to existing data. -
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Walle 2.0
Walle 2.0 web
...Get through server management, grayscale release. Advanced gitlab-like user management mode. Online order application, review, grayscale release, real-time websocket. Walle allows users to release code and finally can not only choose jenkins! Support various web code releases, release and rollback of php, java, python, go and other codes can be completed with one click through the web. walle is a freely configurable project, more user-friendly, high-value, an open source online deployment system that supports git, multi-user, multi-language, multi-project, and multi-environment simultaneous deployment. -
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porttree
Show dependences of a FreeBSD port as a pseudo graphic tree
For a given FreeBSD port, determine its dependences using any combination of the FETCH_, EXTRACT_, PATCH_, BUILD_, LIB_, RUN_ and TEST_DEPENDS, and show them as a pseudo graphical tree. Use back references for cross-connections. -
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Code Catalog in Python
Algorithms and data structures for review for coding interview
code-catalog-python serves as a grab-bag of small, readable Python examples that illustrate common algorithms, data structures, and utility patterns. Each snippet aims to be self-contained and easy to study, with clear inputs, outputs, and the essential logic on display. The catalog format lets you scan for an example, copy it, and adapt it to your use case without wading through a large framework. -
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django-rest-auth
This app makes it extremely easy to build Django powered SPA's
...Tivix specializes in backend web development for Fortune 500 enterprises, venture-backed startups and NGOs. We reduce development risk by using sprint methodology and standards-based code to get applications to market quickly. A well-built backend will result in a seamless user experience that scales as you grow. A poorly-built backend causes bugs, glitches and potential security issues. -
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Django REST Pandas
Serves up Pandas dataframes via the Django REST Framework
...This keeps the implementation simple, but also has the nice side effect of making it trivial to provide the source data for your visualizations. This capability can often be leveraged by sending users to the same URL that your visualization code uses internally to load the data. While DRP is primarily a data API, it also provides a default collection of interactive visualizations through the @wq/chart library, and a @wq/pandas loader to facilitate custom JavaScript charts that work well with CSV output served by DRP. These can be used to create interactive time series, scatter, and box plot charts.
