Search Results for "data" - Page 14
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Showing 629 open source projects for "data"
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AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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setuplib
Extensions for setuptools - detailed information on entry points
The *setuplib* package provides core functions for the query of meta information and installation repositories of *Python* packages. It provides query and filter options on the installed packages and the available information, while displaying the result data in various formats, e.g. as table, list, or JSON, XML, YAML, CSV, etc. The provided commands and extension points integrate seamless into the standard *setuptools* and/or *distutils*. The *setuplib* is member of the group *setuplib* of extension components for the common *setup.py* installer. The targeted users are mainly developers, advanced users, and system administrators. -
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yapyutils
Utilities for platform indepentent low-level system APIs.
...These are e.g. used for extensions of the *setuptools* and *distutils*, thus reduce the package dependency and avoid circular dependencies whenever possible by using standard packages and classes only. The more complex and complete data packages are provided for higher application layer functionality. The current release contains: * *yapyutils.modules* A utility to locate and load modules by a given name and/or file system path name, based on the *sys.path* variable. * *yapyutils.files* Search and location of files, e.g. modules and configuration files... -
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platformids
OS and Distribution Release Enumeration
...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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I3D models trained on Kinetics
Convolutional neural network model for video classification
...The project provides TensorFlow and Sonnet-based implementations, pretrained checkpoints, and example scripts for evaluating or fine-tuning models. It also offers sample data, including preprocessed video frames and optical flow arrays, to demonstrate how to run inference and visualize outputs. -
99.99% Uptime for MySQL and PostgreSQL on Google CloudCloud SQL Enterprise Plus gives you a 99.99% availability SLA with near-zero downtime maintenance—typically under 10 seconds. Get 2x better read/write performance, intelligent data caching, and 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server with built-in vector search for gen AI apps. New customers get $300 in free credit.
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WALKOFF
A flexible, easy to use, automation framework
...WALKOFF puts the tools in your hands to easily automate the tedious repetitive tasks dragging your operations down. Act smarter with WALKOFF by automatically gathering data, analyzing data, or visualizing data customized to your requirements. Act faster with WALKOFF by integrating the capabilities you already own to dynamically respond on your terms to your fast-moving environment. Drag and drop workflow editor. Sharable apps and workflows. Deploy on Windows or Linux. Python 2.7 and 3.4+. Scale to your needs. ... -
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Nebula docs
Documentation repo of nebula orchestration system
Nebula is a open source distributed Docker orchestrator designed for massive scales (tens of thousands of servers/worker devices), unlike Mesos/Swarm/Kubernetes it has the ability to have workers distributed on high latency connections (such as the internet) yet have the pods(containers) be managed centrally with changes taking affect (almost) immediately, this makes Nebula ideal for managing a vast cluster of servers\devices across the globe, some example use cases are appliances\virtual appliances located at clients data centers, edge computing, and POS systems. 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? ... -
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MLBox
MLBox is a powerful Automated Machine Learning python library
MLBox is a powerful Automated Machine Learning python library. Fast reading and distributed data preprocessing/cleaning/formatting. Highly robust feature selection and leak detection. Accurate hyper-parameter optimization in high-dimensional space. State-of-the-art predictive models for classification and regression (Deep Learning, Stacking, LightGBM,...) Prediction with model interpretation. MLBox has been developed and used by many active community members. -
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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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Nebula reporter
The optional reporter container which reads nebula reports from Kafka
Nebula is an open source-distributed Docker orchestrator designed for massive scales (tens of thousands of servers/worker devices), unlike Mesos/Swarm/Kubernetes it has the ability to have workers distributed on high latency connections (such as the internet) yet have the pods(containers) be managed centrally with changes taking effect (almost) immediately, this makes Nebula ideal for managing a vast cluster of servers\devices across the globe. Ever wandered how your going to push an update... -
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Nebula worker
The worker node manager container which manages nebula nodes
Nebula is a open source distributed Docker orchestrator designed for massive scales (tens of thousands of servers/worker devices), unlike Mesos/Swarm/Kubernetes it has the ability to have workers distributed on high latency connections (such as the internet) yet have the pods(containers) be managed centrally with changes taking affect (almost) immediately, this makes Nebula ideal for managing a vast cluster of servers\devices across the globe, some example use cases are IoT devices, appliances\virtual appliances located at clients data centers, and edge computing. Nebula imposes no limits on the scale of the cluster, each component in it is designed to scale out to allow millions of workers to be managed by it. Designed to connect to devices that are spread around the globe Nebula is tolerant of network connection issues and will resync the device when it reconnects. ... -
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Django Celery
Old Celery integration project for Django
Celery is a simple, flexible, and reliable distributed system to process vast amounts of messages, while providing operations with the tools required to maintain such a system. It’s a task queue with focus on real-time processing, while also supporting task scheduling. Celery has a large and diverse community of users and contributors, you should come join us on IRC or our mailing-list. Celery is Open Source and licensed under the BSD License. A task queue’s input is a unit of work called a... -
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The Google Cloud Developer's Cheat Sheet
Cheat sheet for Google Cloud developers
...There is also a free trial that will enable you try almost everything. API platforms and ecosystems, developer and management tools, identity and security tools, gaming, networking, data and analytics tools, database, storage, gaming tools, and many more. -
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CTS Surveyor
Foot traffic and facial analytics for your business and home
Surveyor is a software solution that monitors its environment via camera and gathers demographic information about the public in the surrounding area, providing important statistics such as number of people passing by as well as providing facial analytics to classify the pedestrians based on their age and gender. The statistical data is stored in a local database and is made available via RESTful API’s, and easy integration with other applications can be accomplished via a WebSocket interface that provides live notifications about people in the camera’s field of view At the moment, the solutions is available for Windows only, with Linux version coming soon – please see our User Guide at http://caerustech-solutions.com/demo/User_Guide.pdf Sample Python client: https://github.com/CaerustechSolutions/cts-surveyor-pyclient Contact Us: http://caerustech-solutions.com/contact-us/ -
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captcha_break
Identification codes
This project will use Keras to build a deep convolutional neural network to identify the captcha verification code. It is recommended to use a graphics card to run the project. The following visualization codes are jupyter notebookall done in . If you want to write a python script, you can run it normally with a little modification. Of course, you can also remove these visualization codes. captcha is a library written in python to generate verification codes. It supports image verification... -
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TGAN
Generative adversarial training for generating synthetic tabular data
We are happy to announce that our new model for synthetic data called CTGAN is open-sourced. The new model is simpler and gives better performance on many datasets. TGAN is a tabular data synthesizer. It can generate fully synthetic data from real data. Currently, TGAN can generate numerical columns and categorical columns. TGAN has been developed and runs on Python 3.5, 3.6 and 3.7. 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. ... -
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Active Learning
Framework and examples for active learning with machine learning model
...It provides modular tools for running reproducible experiments across different datasets, sampling strategies, and machine learning models. 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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data-science-ipython-notebooks
Data science Python notebooks: Deep learning
Data Science IPython Notebooks is a broad, curated set of Jupyter notebooks covering Python, data wrangling, visualization, machine learning, deep learning, and big data tools. It aims to be a practical map of the ecosystem, showing hands-on examples with libraries such as NumPy, pandas, matplotlib, scikit-learn, and others. Many notebooks introduce concepts step by step, then apply them to real datasets so readers can see techniques in action. -
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Django REST Pandas
Serves up Pandas dataframes via the Django REST Framework
...The resulting API can serve up CSV (and a number of other formats for consumption by a client-side visualization tool like d3.js. The design philosophy of DRP enforces a strict separation between data and presentation. 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. ... -
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django-rest-auth
This app makes it extremely easy to build Django powered SPA's
This app makes it extremely easy to build Django powered SPA's (Single Page App) or Mobile apps exposing all registration and authentication-related functionality as CBV's (Class Base View) and REST (JSON). Tivix rebuilt a NATO software system to organize and coordinate rescue missions for submarines in distress across the globe. The United Nations Partner Portal (UNPP) is a web application built for a group of UN agencies to simplify their business processes and streamline collaboration... -
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Invenio
Invenio digital library framework
Invenio is a highly customizable open-source framework for building large-scale digital repositories and research data platforms. Developed by CERN, it is designed to manage, index, and provide access to metadata-rich content such as publications, datasets, and multimedia files. Invenio provides a modular architecture, making it suitable for libraries, archives, and research institutions. -
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ShadowSocksShare
Python ShadowSocks framework
This project obtains the shared ss(r) account from the ss(r) shared website crawler, redistributes the account and generates a subscription link by parsing and verifying the account connectivity. Since Google plus will be closed on April 2, 2019, almost all the available accounts crawled before come from Google plus. So if you are building your own website, please keep an eye on the updates of this project and redeploy using the latest source code. -
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Pipelines
An experimental programming language for data flow
Pipelines is a language and runtime for crafting massively parallel pipelines. Unlike other languages for defining data flow, the Pipeline language requires the implementation of components to be defined separately in the Python scripting language. This allows the details of implementations to be separated from the structure of the pipeline while providing access to thousands of active libraries for machine learning, data analysis, and processing. -
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Trigger Happy
Automate the exchanges of the data between applications
Automate the exchanges of the data between the applications and services you use on the web. Make Twitter talk to Mastodon, make Github talk to Mattermost, store your favorite tweets by creating notes in Evernote, follow RSS feeds and post each news in Wallabag, Pocket or Evernote. The possibilities are too numerous to name all of them, but with that project you won't have to raise your little finger at all: automate everything and make your life easier. -
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django-dynamic-scraper
Creating Scrapy scrapers via the Django admin interface
...Since it simplifies things DDS is not usable for all kinds of scrapers, but it is well suited for the relatively common case of regularly scraping a website with a list of updated items (e.g. news, events, etc.) and then dig into the detail page to scrape some more infos for each item. Django Dynamic Scraper tries to keep its data structure in the database as separated as possible from the models in your app, so it comes with its own Django model classes for defining scrapers, runtime information related to your scraper runs and classes. -
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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. It favors clarity over micro-optimizations so learners can grasp the idea before worrying about edge performance. ...
