Search Results for "structure"
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Showing 32 open source projects for "structure"
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1
DataSet Serialize for Delphi and Lazarus
JSON to DataSet and DataSet to JSON converter for Delphi and Lazarus
...It has features such as exporting or importing records into a DataSet, validate if JSON has all required attributes (previously entered in the DataSet), exporting or importing the structure of DataSet fields in JSON format. In addition to managing nested JSON through master detail or using TDataSetField (you choose the way that suits you best). All this using class helpers, which makes it even simpler and easier to use. -
2
REST API Response Builder for Laravel
Builds nice, normalized and easy to consume REST JSON responses
...It's lightweight, with no dependencies, extensively tested, and simple to use yet flexible and powerful, with support for on-the-fly data conversion, localization support, automatic message building, chained APIs, and (hopefully) exhaustive documentation. But that's not all! The JSON structure produced by ResponseBuilder is designed with users of your API in mind, so its structure is predictable and well-defined which makes dealing with your API using ResponseBuilder library a breeze. Simple JSON response, with a well-defined and predictable structure, easy to consume without any hassle or trickery. Your clients will love it. -
3
DocArray
The data structure for multimodal data
...It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API. Door to multimodal world: super-expressive data structure for representing complicated/mixed/nested text, image, video, audio, 3D mesh data. The foundation data structure of Jina, CLIP-as-service, DALL·E Flow, DiscoArt etc. Data science powerhouse: greatly accelerate data scientists’ work on embedding, k-NN matching, querying, visualizing, evaluating via Torch/TensorFlow/ONNX/PaddlePaddle on CPU/GPU. ... -
4
Miller
Miller is like awk, sed, cut, join, and sort for name-indexed data
...Then, on the fly, you can add new fields which are functions of existing fields, drop fields, sort, aggregate statistically, pretty-print, and more. Miller operates on key-value-pair data while the familiar Unix tools operate on integer-indexed fields: if the natural data structure for the latter is the array, then Miller's natural data structure is the insertion-ordered hash map. Miller handles a variety of data formats, including but not limited to the familiar CSV, TSV, and JSON/JSON Lines. (Miller can handle positionally-indexed data too!) -
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5
RedisJSON
RedisJSON - a JSON data type for Redis
RedisJSON is a Redis module that implements ECMA-404 The JSON Data Interchange Standard as a native data type. It allows storing, updating and fetching JSON values from Redis keys (documents). -
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Logstash Logback Encoder
Logback JSON encoder and appenders
...Originally written to support output in Logstash's JSON format, but has evolved into a highly configurable, general-purpose, structured logging mechanism for JSON and other Jackson data forms. The structure of the output, and the data it contains, is fully configurable. The general composite JSON encoders/layouts can be used to output any JSON format/data by configuring them with various JSON providers. The Logstash encoders/layouts are really just extensions of the general composite JSON encoders/layouts with a pre-defined set of providers. ... -
7
HCL
HCL is the HashiCorp configuration language
...The application defines which attribute names and nested block types are expected, and HCL parses the configuration file, verifies that it conforms to the expected structure, and returns high-level objects that the application can use for further processing. -
8
ojg
Optimized JSON for Go
Optimized JSON for Go is a high-performance parser with a variety of additional JSON tools. OjG is optimized to processing huge data sets where data does not necessarily conform to a fixed structure. -
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Vue Json Pretty
A JSON tree view component that is easy to use
A Vue component for rendering JSON data as a tree structure. The CSS file is included separately and needs to be imported manually. You can either import CSS globally in your app (if supported by your framework) or directly from the component. -
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10
go-json
Fast JSON encoder/decoder compatible with encoding/json for Go
Fast JSON encoder/decoder compatible with encoding/json for Go. -
11
Jbuilder
Generate JSON objects with a Builder-style DSL
Jbuilder gives you a simple DSL for declaring JSON structures that beats manipulating giant hash structures. This is particularly helpful when the generation process is fraught with conditionals and loops. You can either use Jbuilder stand-alone or directly as an ActionView template language. When required in Rails, you can create views à la show.json.jbuilder (the json is already yielded). Fragment caching is supported, it uses Rails.cache and works like caching in HTML templates. If your... -
12
nette Schema
Validating data structures against a given Schema
A practical library for validation and normalization of data structures against a given schema with a smart & easy-to-understand API. In variable $schema we have a validation schema (what exactly this means and how to create it we will say later) and in variable $data we have a data structure that we want to validate and normalize. This can be, for example, data sent by the user through an API, configuration file, etc. -
13
JSON Hero
JSON Hero is an open-source, beautiful JSON explorer for the web
JSON Hero is a beautiful and powerful JSON viewer designed for developers who work with large and complex JSON files. It runs as a web-based interface (and as a standalone app) that provides semantic, interactive rendering of JSON content, helping users understand the structure and meaning of data at a glance. JSON Hero automatically detects data types such as URLs, dates, colors, and base64 images, and presents them in meaningful ways. It’s designed for productivity and readability, with dark mode support, quick navigation, and collaboration features. -
14
Rapid YAML
Library to parse and emit YAML, and do it fast
...(If you are looking to use your programs with a YAML tree as a configuration tree with override facilities, take a look at c4conf). ryml parses both read-only and in-situ source buffers; the resulting data nodes hold only views to sub-ranges of the source buffer. No string copies or duplications are done, and no virtual functions are used. The data tree is a flat index-based structure stored in a single array. Serialization happens only at your direct request, after parsing / before emitting. Internally, the data tree representation stores only string views and has no knowledge of types, but of course, every node can have a YAML type tag. ryml makes it easy and fast to read and modify the data tree. -
15
sq data wrangler
sq data wrangler
...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). You can use sq diff to compare tables, or entire databases. sq has commands for common database operations to copy, truncate, and drop tables. -
16
Formly
JSON powered dynamic forms for Angular
...We are building by hand with all the tools Angular gives us. NGX Formly was built as an open-source project, which you can find on GitHub. The tool lets you create forms based on a JSON structure. This makes it super easy and fast to build small and advanced forms in no time. It’s no problem when you use Angular with Material, Bootstrap, Ionic, PrimeNG, Kendo, and NativeScript. They have a plugin for all of them. We can give the select options manually to the select or via a defined enum . In order to get all the information from the enum, we have to store them in the ProductTypeNames which output an Array from the enum . -
17
ZJsonPatch
This is an implementation of RFC 6902 JSON Patch written in Java
This is an implementation of RFC 6902 JSON Patch written in Java. It can be used to avoid sending a whole document when only a part has changed, thus reducing network bandwidth requirements if data (in JSON format) is required to send across multiple systems over network or in case of multi DC transfer. -
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Ulfius HTTP Framework
Web Framework to build REST APIs, Webservices or any HTTP endpoint
HTTP Framework for REST Applications in C. Based on GNU libmicrohttpd for the backend web server, Jansson for the json manipulation library, and Libcurl for the SMTP client API. Used to facilitate the creation of web applications in C programs with a small memory footprint, as in embedded systems applications. You can create web services in HTTP or HTTPS mode, stream data, or implement server web sockets. -
19
jless
jless is a command-line JSON viewer designed for reading
...Clean syntax highlighted display of JSON data, omitting quotes around object keys, closing object and array delimiters, and trailing commas. Expand and collapse objects and arrays so you can see both the high- and low-level structure of the data. -
20
JSON-Diff
Structural diff for JSON files
json-diff is a command-line tool (and library) that computes differences between two JSON documents in a user-friendly manner. It highlights additions, deletions, and modifications in nested JSON structures, showing context so users can see where changes occurred. The output is presented in a readable diff style (text, colorized, or in various output formats) so developers can quickly understand changes between two versions of a JSON file. The tool also supports ignoring order in arrays,... -
21
SPyQL
Query data on the command line with SQL-like SELECTs powered by Python
SQL with Python in the middle. SPyQL is a query language that combines the simplicity and structure of SQL with the power and readability of Python. SPyQL offers a command-line interface that allows running SPyQL queries on top of text data (e.g. CSV, JSON). Data can come from files but also from data streams, such as as Kafka, or from databases such as PostgreSQL. Basically, data can come from any command that outputs text :-). -
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normalizr
Normalizes nested JSON according to a schema
Many APIs, public or not, return JSON data that has deeply nested objects. Using data in this kind of structure is often very difficult for JavaScript applications, especially those using Flux or Redux. Normalizr is a small, but powerful utility for taking JSON with a schema definition and returning nested entities with their IDs, gathered in dictionaries. Normalizr is built for various environments. Normalizr was originally created by Dan Abramov. -
23
JSON Form
Build forms from JSON Schema, easily template-able
...The generated HTML form includes client-side validation logic that provides direct inline feedback to the user upon form submission (provided a JSON Schema validator is available). If values are valid, the JSON Form library uses submitted values to create the JavaScript data structure that matches the data model. The layout of the generated HTML form may be entirely fine-tuned through a simple declarative mechanism. If you're more of the acting type than of the reading type, the JSON Form Playground is a simple JSON Form editor that lets you try out and extend all the examples in the doc. -
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Json Node Tree Library
Represents JSON doc as a nodes tree for transforms like XPATH & XSLT.
...The framework parses textual JSON document to nodes tree that represents JSON entity: object, array or value of primitive type. Generated tree allows to modify values of nodes and/or structure of the given JSON document. Representation of JSON object as a nodes tree allows implement an operations such as path query and transformations (like XPATH and XSLT for XML). -
25
Pikkr
JSON parser to pick up values directly without performing tokenization
...Finds values of queried fields by scanning a JSON record using the index created in the previous process and learns their logical locations (i.e. pattern of the JSON structure) in the early stages. Speculates logical locations of queried fields by using the learned result information, jumps directly to their physical locations and extracts values in the later stages. Fallbacks to basic parsing if the speculation fails.
