Search Results for "data structure"
Sort By:
Showing 10 open source projects for "data structure"
View related business solutions-
Point of Sale. Powerful and Simple.Vibe Retail is an all-in-one retail point-of-sale and operations platform built for single-store and multi-location retailers seeking to unify inventory, sales, staff and customer data from one mobile-friendly interface. The system lets you track inventory across locations and warehouses, handle item variations (size, color, material), manage purchase orders and supplier deliveries, print custom barcodes, and transfer stock between stores in real time. On the sales side, Vibe supports multiple payment types (cards, cash, checks, gift cards, EBT), layaway workflows, serial number tracking, delivery management, loyalty programs and branded receipts. Retailers can integrate with online platforms (such as Shopify and WooCommerce), sync in-store and online sales, access 40+ real-time reports on sales, inventory and performance, set up promotions and discounts, and print receipts from mobile devices.
-
Cloud data warehouse to power your data-driven innovationBigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.
-
1
Kedro
A Python framework for creating reproducible, maintainable code
Kedro is an open sourced Python framework for creating maintainable and modular data science code. Provides the scaffolding to build more complex data and machine-learning pipelines. In addition, there's a focus on spending less time on the tedious "plumbing" required to maintain data science code; this means that you have more time to solve new problems. Standardises team workflows; the modular structure of Kedro facilitates a higher level of collaboration when teams solve problems together. ... -
2
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. Graphene Django has a number of additional features that are designed to make working with Django easy. Our primary focus in this... -
3
Pacu
The AWS exploitation framework, designed for testing security
Pacu (named after a type of Piranha in the Amazon) is a comprehensive AWS security-testing toolkit designed for offensive security practitioners. While several AWS security scanners currently serve as the proverbial “Nessus” of the cloud, Pacu is designed to be the Metasploit equivalent. Written in Python 3 with a modular architecture, Pacu has tools for every step of the pen testing process, covering the full cyber kill chain. Pacu is the aggregation of all of the exploitation experience... -
4
EasyR1
An Efficient, Scalable, Multi-Modality RL Training Framework
EasyR1 is a streamlined training framework for building “R1-style” reasoning models from open-source LLMs with minimal boilerplate. It focuses on the full reasoning stack—data preparation, supervised fine-tuning, preference or outcome-based optimization, and lightweight evaluation—so you can iterate quickly on chain-of-thought–heavy tasks. The project’s philosophy is practicality: sensible defaults, one-command recipes, and compatibility with popular base models let you stand up experiments... -
Go beyond a virtual data room with Datasite DiligenceThe data room with a view. Evolved for next-generation M&A. Built on decades of deal experience. Packed with expert tools, yet intuitive for novices. A fully mobile platform with frictionless processes. Smart AI tools that let you close more deals, faster, plus end-to-end support at all times. Do due diligence with intelligence.
-
5
CrypTen
A framework for Privacy Preserving Machine Learning
CrypTen is a research framework developed by Facebook Research for privacy-preserving machine learning built directly on top of PyTorch. It provides a secure and intuitive environment for performing computations on encrypted data using Secure Multiparty Computation (SMPC). Designed to make secure computation accessible to machine learning practitioners, CrypTen introduces a CrypTensor object that behaves like a regular PyTorch tensor, allowing users to seamlessly apply automatic differentiation and neural network operations. Its design mirrors PyTorch’s modular and library-based structure, enabling flexible experimentation, debugging, and model development. ... -
6
yapydata
Lower-Layer unified data - JSON, XML, YAML + INI, CFG, properties
The yapydata - Yet Another Python Data - provides a unified interface for the access to various data syntaxes. Therefore it encapsulates the libraries by offering a common API with the canonical internal data as JSON compatible Python in-memory structure. The application is foreseen in particular for the lower layer of the software stack including setup-tools. Thus it uses standard libraries only whenever possible. -
7
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. -
8
fooltrader
Quant framework for stock
Build a standard data schema, and then implement various connectors to import systems you are familiar with for analysis. fooltrader is a quantitative analysis trading system designed using big data technology, including data capture, cleaning, structuring, calculation, display, backtesting and trading. Its goal is to provide a unified framework for the whole market (stock, futures, bonds, foreign exchange, digital currency, macroeconomics, etc.) for research, backtesting, forecasting, and... -
9
nacho
Python micro web-framework and asynchronous networking library
...Because it encourages consistency among services, teams can spin up new microservices with a shared structure and skip repetitive setup. Though the repository may be less active than some major frameworks, it serves as a valuable jump-start for projects where speed and uniformity matter. -
Cycloid: Hybrid Cloud DevOps collaboration platformEnable your developers to do their best work and increase time-to-market speed with a leading DevOps and Hybrid Cloud platform.
-
10
This is intended to ease the development of web applications using CherryPy (web server) and Elixir (DB access) with python. It will contain structures to easily setup the database structure and populate with data, and to configure the server
- Previous
- You're on page 1
- Next
