Search Results for "sandbox:/mnt/data/project_plan.pod"
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Showing 6997 open source projects for "sandbox:/mnt/data/project_plan.pod"
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The AI-powered unified PSA-RMM platform for modern MSPs.SuperOps.ai is the only PSA-RMM platform powered by intelligent automation and thoughtfully crafted for the new-age MSP. The platform also helps MSPs manage their projects, clients, and IT documents from a single place.
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The full-stack observability platform that protects your dataLayer, tags and conversion dataCode-Cube.io detects issues instantly, alerts you in real time and helps you resolve them fast. No manual QA. No unreliable data. Just data you can trust and act on.
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glsl-sandbox
Shader editor and gallery
GLSL Sandbox is an in-browser playground for writing and sharing fragment shaders with instant visual feedback. It provides a minimal editor and a fullscreen WebGL viewport so your shader takes center stage, making it perfect for learning, live-coding, and showcasing visual experiments. The environment injects a small set of uniforms—time, resolution, mouse—so you can animate and interact without boilerplate. -
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OpenShell
OpenShell is the safe, private runtime for autonomous AI agents.
OpenShell is an open-source runtime designed to safely run autonomous AI agents in isolated environments. Developed by NVIDIA, it provides sandboxed execution spaces that protect system resources, credentials, and data from unauthorized access. Each agent runs inside a containerized sandbox governed by declarative YAML security policies that control network access, file permissions, and process behavior. The platform includes a gateway service that manages sandbox lifecycles and routes AI inference requests through controlled providers. OpenShell also features a privacy-aware routing system that prevents sensitive information from leaving the sandbox environment. ... -
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Azure Data Studio
A data management tool that enables working with other SQL tools
Azure Data Studio is a cross-platform database tool for data professionals who use on-premises and cloud data platforms on Windows, macOS, and Linux. Azure Data Studio offers a modern editor experience with IntelliSense, code snippets, source control integration, and an integrated terminal. It's engineered with the data platform user in mind, with the built-in charting of query result sets and customizable dashboards. -
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Laravel Data
Powerful data objects for Laravel
This package enables the creation of rich data objects which can be used in various ways. Using this package you only need to describe your data once. -
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Form-Data
A module to create readable `"multipart/form-data"` streams
A library to create readable "multipart/form-data" streams. Can be used to submit forms and file uploads to other web applications. -
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Dynamic Data
Reactive collections based on Rx.Net
...However, typical applications are much more complicated and may apply a filter, transform the original dto and apply a sort. Even with these simple everyday operations, the complexity of the code is quickly magnified. Dynamic data has been developed to remove the tedious code of dynamically maintaining collections. It has grown to become functionally very rich with at least 60 collection-based operations which amongst other things enable filtering, sorting, grouping, joining different sources, transforms, binding, pagination, data virtualization, expiration, disposal management plus more. -
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data.table
Extends base R’s data for high-performance data manipulation
data.table is an R package that extends base R’s data.frame for high-performance data manipulation. It offers concise syntax, blazing speed, and memory-efficient operations. It supports fast file reading/writing, joins, grouping, reshaping, and updates by reference. It is heavily used in large data workflows, big data in R, production pipelines, etc. Extremely efficient grouping/aggregation/summarization; can handle very large datasets (hundreds of millions to billions of rows) in memory (if available). ... -
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sq data wrangler
sq data wrangler
sq is a command line tool that provides jq-style access to structured data sources: SQL databases, or document formats like CSV or Excel. sq executes jq-like queries, or database-native SQL. It can join across sources: join a CSV file to a Postgres table, or MySQL with Excel. sq outputs to a multitude of formats including JSON, Excel, CSV, HTML, Markdown and XML, and can insert query results directly to a SQL database. sq can also inspect sources to view metadata about the source structure (tables, columns, size). ... -
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Micronaut Data
Ahead of Time Data Repositories
...The problem is worse when combined with Hibernate which maintains its own meta-model as you end up with duplicate meta-models. Micronaut Data instead moves this model into the compiler. Both GORM and Spring Data use regular expressions and pattern matching in combination with runtime generated proxies to translate a method definition on a Java interface into a query at runtime. No such runtime translation exists in Micronaut Data and this work is carried out by the Micronaut compiler at compilation time. -
Get full visibility and control over your tasks and projects with Wrike.Wrike offers world-class features that empower cross-functional, distributed, or growing teams take their projects from the initial request stage all the way to tracking work progress and reporting results.
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Valet
Valet lets you securely store data in the iOS, tvOS, or macOS Keychain
Valet lets you securely store data in the iOS, tvOS, watchOS, or macOS Keychain without knowing a thing about how the Keychain works. It’s easy. The identifier you choose for your Valet is used to create a sandbox for the data your Valet writes to the keychain. Two Valets of the same type created via the same initializer, accessibility value, and identifier will be able to read and write the same key:value pairs; Valets with different identifiers each have their own sandbox. ... -
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Pythonic Data Structures and Algorithms
Minimal examples of data structures and algorithms in Python
The Pythonic Data Structures and Algorithms repository by keon is a hands-on collection of implementations of classical data structures and algorithms written in Python. It offers working, often well-commented code for many standard algorithmic problems — from sorting/searching to graph algorithms, dynamic programming, data structures, and more — making it a valuable resource for learning and reference. -
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WasmEdge
Extensible WebAssembly runtime for cloud native applications
WasmEdge is a lightweight, high-performance, and extensible WebAssembly runtime. It is the fastest Wasm VM today. WasmEdge is an official sandbox project hosted by the CNCF. Its use cases include modern web application architectures (Isomorphic & Jamstack applications), microservices on the edge cloud, serverless SaaS APIs, embedded functions, smart contracts, and smart devices. The WasmEdge Runtime provides a well-defined execution sandbox for its contained WebAssembly bytecode program. ... -
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WSLGit
Use Git installed in Bash on Windows/Windows Subsystem for Linux (WSL)
...Use Git installed in Bash on Windows/Windows Subsystem for Linux (WSL) from Windows and Visual Studio Code (VSCode) The primary reason for this tool is to make the Git plugin in Visual Studio Code (VSCode) work with the git command installed in WSL. For these two to interoperate, this tool translates paths between the Windows (C:\Foo\Bar) and Linux (/mnt/c/Foo/Bar) representations. The install.bat script creates a folder structure similar to the one used by Git For Windows, and creates some useful symbolic links in the wslgit\cmd and wslgit\bin folders. VSCode will find the git executable automatically if the two optional installation steps were taken. -
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Spring Data Neo4j
Provide support to increase developer productivity in Java
...The template programming model is equivalent to other Spring templates and builds the basis for interaction with the graph and is also used for the Spring Data repository support. Spring Data Neo4j is a core part of the Spring Data project which aims to provide convenient data access for NoSQL databases. Spring Data builds on Spring Framework, check the spring.io web-site for a wealth of reference documentation. If you are just starting out with Spring, try one of the guides. -
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Spring Data REST
Simplifies building hypermedia-driven REST web services
Spring Data REST is part of the umbrella Spring Data project and makes it easy to build hypermedia-driven REST web services on top of Spring Data repositories. Spring Data REST builds on top of Spring Data repositories, analyzes your application’s domain model and exposes hypermedia-driven HTTP resources for aggregates contained in the model. -
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Spring Data MongoDB
Provide support to increase developer productivity in Java
The primary goal of the Spring Data project is to make it easier to build Spring-powered applications that use new data access technologies such as non-relational databases, map-reduce frameworks, and cloud-based data services. The Spring Data MongoDB project aims to provide a familiar and consistent Spring-based programming model for new datastores while retaining store-specific features and capabilities. -
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The Data Engineering Handbook
Links to everything you'd ever want to learn about data engineering
The Data Engineering Handbook is a comprehensive, community-curated repository that aggregates essential learning resources for anyone interested in becoming a professional data engineer. Rather than being a code project itself, it’s a learning handbook that links to books, articles, tutorials, community groups, boot camps, and real-world project examples that collectively form a roadmap to mastering data engineering skills. -
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Spring Data Redis
Provides support to increase developer productivity in Java
Provides support to increase developer productivity in Java when using Redis, a key-value store. Uses familiar Spring concepts such as a template class for core API usage and lightweight repository-style data access. The primary goal of the Spring Data project is to make it easier to build Spring-powered applications that use new data access technologies such as non-relational databases, map-reduce frameworks, and cloud-based data services. Connection package as low-level abstraction across multiple Redis drivers (Lettuce and Jedis). Exception translation to Spring’s portable Data Access exception hierarchy for Redis driver exceptions. ... -
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NYC Taxi Data
Import public NYC taxi and for-hire vehicle (Uber, Lyft)
The nyc-taxi-data repository is a rich dataset and exploratory project around New York City taxi trip records. It collects and preprocesses large-scale trip datasets (fares, pickup/dropoff, timestamps, locations, passenger counts) to enable data analysis, modeling, and visualization efforts. The project includes scripts and notebooks for cleaning and filtering the raw data, memory-efficient processing for large CSV/Parquet files, and aggregation workflows (e.g. trips per hour, heatmaps of pickups/dropoffs). ... -
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Spring Data JPA
Simplifies the development of creating a JPA-based data access layer
Spring Data JPA, part of the larger Spring Data family, makes it easy to easily implement JPA-based repositories. This module deals with enhanced support for JPA-based data access layers. It makes it easier to build Spring-powered applications that use data access technologies. Implementing a data access layer of an application has been cumbersome for quite a while. -
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Synthetic Data Kit
Tool for generating high quality Synthetic datasets
Synthetic Data Kit is a CLI-centric toolkit for generating high-quality synthetic datasets to fine-tune Llama models, with an emphasis on producing reasoning traces and QA pairs that line up with modern instruction-tuning formats. It ships an opinionated, modular workflow that covers ingesting heterogeneous sources (documents, transcripts), prompting models to create labeled examples, and exporting to fine-tuning schemas with minimal glue code. -
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Victory
React components for building interactive data visualizations
...Check out the docs to see how you can get started building interactive data visualizations. Fully contained, reusable data visualization elements are responsible for their own styles and behaviors. Extend the Victory experience on Android and iOS platforms with an identical API. -
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The CUE Data Constraint Language
The home of the CUE language. Validate and define text-based config
CUE is an open source data constraint language which aims to simplify tasks involving defining and using data. CUE merges the notion of schema and data. The same CUE definition can simultaneously be used for validating data and act as a template to reduce boilerplate. Schema definition is enriched with fine-grained value definitions and default values. At the same time, data can be simplified by removing values implied by such detailed definitions. ... -
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Synthetic Data Vault (SDV)
Synthetic Data Generation for tabular, relational and time series data
The Synthetic Data Vault (SDV) is a Synthetic Data Generation ecosystem of libraries that allows users to easily learn single-table, multi-table and timeseries datasets to later on generate new Synthetic Data that has the same format and statistical properties as the original dataset. Synthetic data can then be used to supplement, augment and in some cases replace real data when training Machine Learning models. -
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Countries, Languages & Continents data
Countries, Languages & Continents data (capital and currency)
...Languages list only contains languages used in Countries data. Full list of known languages is exported as languagesAll from ./dist/languages.all.json.
