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Showing 120 open source projects for "main"
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restless
A lightweight REST miniframework for Python
...Works great with Django, Flask, Pyramid & Tornado, but should be useful for many other Python web frameworks. Based on the lessons learned from Tastypie & other REST libraries. Restless tries to be RESTful by default, but flexible enough. The main Resource class has data methods (that you implement) for all the main RESTful actions. It also uses HTTP status codes as correctly as possible. Restless is BYOD (bring your own data) and hence, works with almost any ORM/data source. If you can import a module to work with the data & can represent it as JSON, Restless can work with it. ... -
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Paperless-ng
A supercharged version of paperless, scan, index and archive docs
...Paperless-ng is a fork of the original paperless project. It changes many things both on the surface and under the hood. Paperless-ng was created because I feel that these changes are too big to be pushed into the main repository right away. -
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workshops_project
Workshops is an open source, simple, dead-lightweight LMS
Workshops is an open source, simple, dead-lightweight LMS (Learning Management System) application programmed in Python (version 3.8.x) with Django (version 2.2.x) web framework which main purpose is to make a standarized way to share knowledge via courses in a slide-based view in browser powered by remark javascript library, easy to create, edit, delete and show your courses using simple markdown and html if necessary. Inspired on an old project in my social labours to help share knowledge in an easy way. -
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PyTorch SimCLR
PyTorch implementation of SimCLR: A Simple Framework
For quite some time now, we know about the benefits of transfer learning in Computer Vision (CV) applications. Nowadays, pre-trained Deep Convolution Neural Networks (DCNNs) are the first go-to pre-solutions to learn a new task. These large models are trained on huge supervised corpora, like the ImageNet. And most important, their features are known to adapt well to new problems. This is particularly interesting when annotated training data is scarce. In situations like this, we take the... -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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nginx ui
Nginx UI allows you to access and modify the nginx configurations
...If you feel the same way I wish you a lot of fun with the application and I am looking forward to your feedback, change requests or even a star. Containerization is now state of the art and therefore the application is delivered in a container. With the menu item Main Config the Nginx specific configuration files can be extracted and updated. These are dynamically read from the Nginx directory. If a file has been added manually, it is immediately integrated into the Nginx UI Main Config menu item. -
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Jeffy
Serverless Application Framework for Python AWS Lambda
Jeffy is a Serverless "Application" Framework for Python consisting of a suite of Utilities for Lambda functions that make developing serverless applications easy. There are three main things that Jeffy is focused on: 1. Logging - Jeffy provides easy to see JSON format logging. All events, responses and errors are captured and you can make configurations for any additional attributes you'd like to see on the logs. 2. Decorators - Jeffy has an extensive range of decorators/ event handlers for implementing common things for Lambda functions. 3. ... -
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Kopf
A Python framework to write Kubernetes operators
Kopf —Kubernetes Operator Pythonic Framework, is a framework and a library to make Kubernetes operator's development easier, just in a few lines of Python code. The main goal is to bring the Domain-Driven Design to the infrastructure level, with Kubernetes being an orchestrator/database of the domain objects (custom resources), and the operators containing the domain logic (with no or minimal infrastructure logic). -
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layman is the Gentoo overlay manager and allows to integrate experimental software packages into the main distribution. It can also be used as a manager for version control repositories.
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Baselines
High-quality implementations of reinforcement learning algorithms
Unlike the other two, openai/baselines is not currently a maintained or prominent repo in the OpenAI organization (and I found no strong reference in OpenAI’s main GitHub). Historically, “baselines” repositories are often used for baseline implementations of reinforcement learning algorithms or reference models (e.g. in the RL domain). If there was an OpenAI “baselines” repo, it might have contained reference implementations for reinforcement learning or model policy baselines to compare new work against. ... -
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10
Miasm
Reverse engineering framework in Python
...Miasm is not the first tool to implement this feature. But, well, as the tool already had everything needed to implement DSE, it was just a matter of time before these features landed in the main branch. -
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RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
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Olex2 is visualisation software for small-molecule crystallography developed at Durham University/EPSRC. It provides comprehensive tools for crystallographic model manipulation for the end user and an extensible development framework for programmers. The project has been supported by Olexsys Ltd since 2010.
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Coach
Enables easy experimentation with state of the art algorithms
...Coach collects statistics from the training process and supports advanced visualization techniques for debugging the agent being trained. Coach supports many state-of-the-art reinforcement learning algorithms, which are separated into three main classes - value optimization, policy optimization, and imitation learning. Coach supports a large number of environments which can be solved using reinforcement learning. -
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TestLink-API-Python-client
Python XML-RPC client for TestLink
TestLink-API-Python-client is a Python XML-RPC client for TestLink Initially based on James Stock testlink-api-python-client R7 and Olivier Renault JinFeng idea - an interaction of TestLink, Robot Framework and Jenkins. TestLink-API-Python-client delivers two main classes - TestlinkAPIGeneric - Implements the Testlink API methods as generic PY methods with error handling - TestlinkAPIClient - Inherits from TestlinkAPIGeneric and defines service methods like "copyTCnewVersion" and the helper class - TestLinkHelper - search connection parameter from environment variables and command line arguments -
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Active Learning
Framework and examples for active learning with machine learning model
...The system allows researchers to study how models can improve labeling efficiency by selectively querying the most informative data points rather than relying on uniformly sampled training sets. The main experiment runner (run_experiment.py) supports a wide range of configurations, including batch sizes, dataset subsets, model selection, and data preprocessing options. It includes several established active learning strategies such as uncertainty sampling, k-center greedy selection, and bandit-based methods, while also allowing for custom algorithm implementations. ... -
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Madara
Middleware for distributed applications
...MADARA was originally developed as an agent-based middleware specifically for real-time, distributed artificial intelligence, but is now more general purpose for distributed timing, control, knowledge and reasoning, and quality-of-service. MADARA is composed of several tools and middleware, and the main entry point into the system is the Knowledge and Reasoning Language (KaRL) Engine, which provides a real-time scripting language for nanosecond execution times hooked into a flexible transport layer for distributed reasoning. The KaRL engine also supports object-oriented C++, Java, and Python programming through Containers, classes that provide abstractions and references for variable location within the KaRL Knowledge Base. ... -
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jsondata
Modular JSON by trees and branches, pointers and patches
The 'jsondata' package provides for the modular in-memory processing of JSON data by trees, branches, pointers, and patches. The main interface classes are: - JSONData - Core for RFC7159 based data structures. Provides modular data components. - JSONDataSerializer - Core for RFC7159 based data persistence. Provides modular data serialization. - JSONPointer - RFC6901 for addressing by pointer paths. Provides pointer arithmetics. - JSON Relative Pointer - draft-handrews-relative-json-pointer/2018, contained in JSONPointer... -
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PyTorch Book
PyTorch tutorials and fun projects including neural talk
...But in theory there shouldn't be too many problems on python2 and CPU. The basic part (the first five chapters) explains the content of PyTorch. This part introduces the main modules in PyTorch and some tools commonly used in deep learning. For this part of the content, Jupyter Notebook is used as a teaching tool here, and readers can modify and run with notebooks and repeat experiments. -
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TensorFlow World
Simple and ready-to-use tutorials for TensorFlow
This repository aims to provide simple and ready-to-use tutorials for TensorFlow. The explanations are present in the wiki associated with this repository. There are different motivations for this open source project. TensorFlow (as we write this document) is one of / the best deep learning frameworks available. The question that should be asked is why has this repository been created when there are so many other tutorials about TensorFlow available on the web? Deep Learning is in very high... -
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mds-utils
General purpose utilities for C++ and Python developers
...Amongst them, some type traits for detecting different uBLAS matrix types. 3. some useful classes that allow to treat the old C FILE pointer as a C++ stream. 4. C++ wrappers of the main Python objects, independent of those in Boost Python. Wrappers are provided also for NumPy arrays. 5. C++ classes that help on treating Python file objects as C++ streams. 6. a review and refactor of the indexing support in Python extensions. Now access in write mode is supported too. More details on the Doxygen documentation. ... -
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Py2Bin
compile python script file to standeloune binary file (MacOs 10.6 + )
Py2Bin is an application for MacOs X 10.6 or later, this application compile and bluid a standeloune executable binary file from a .py python script file. The result of the compilation can be execute without the python programe This application is submite under GPL pulic licence If you need som information of if ou have a problem with this application please wrtite to m.houbad@gmail.com Py2Bin use Pyinstaller as compiler -
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radiustest
Radius client written in python
This is a flexible radius client. The main idea is to have a client which could be easily used to test different Radius servers. Client supports: - Radius PAP authentication - Multi thread (sniffing separated from sending) - Several Attribute Value Pairs (AVP) supported (nas-ip-address, service-type, nas-port-type, calling-station-id, called-station-id) - We can add new AVP easily - Flooding mode (performance/stress testing) - Accounting messages Client uses scapy library to send/receive packets. ... -
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Platform Course
Opensource framework for creation bussiness web applications
Platform Course 5.0.0 is opensource framework for easy development of original solutions for unique business process. Main advantages: cross-domain auth, LDAP integration, cross-browser GWT-based UI, big tables handling, chart and geo maps, input forms on XForms. Tested with MSSQL, PostgreSQL and Oracle. Actual SVN Repository for this product is located at https://share.curs.ru/svn/showcase/branches/stable/ Login: reader Password: reader If you wish to know further details or participate in platform development, fell free to contact us via info@curs.ru Wiki page of the Platform: https://share.curs.ru/wiki -
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ElastAlert
Easy and flexible alerting with ElasticSearch
We designed ElastAlert to be reliable, highly modular, and easy to set up and configure. It works by combining Elasticsearch with two types of components, rule types and alerts. Elasticsearch is periodically queried and the data is passed to the rule type, which determines when a match is found. When a match occurs, it is given to one or more alerts, which take action based on the match. This is configured by a set of rules, each of which defines a query, a rule type, and a set of alerts.... -
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Flask-RESTful
Simple framework for creating REST APIs
Flask-RESTful is an extension for Flask that adds support for quickly building REST APIs. It is a lightweight abstraction that works with your existing ORM/libraries. Flask-RESTful encourages best practices with minimal setup. If you are familiar with Flask, Flask-RESTful should be easy to pick up. Flask-RESTful provides an extension to Flask for building REST APIs. Flask-RESTful was initially developed as an internal project at Twilio, built to power their public and internal APIs....
