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Showing 102 open source projects for "json-java"
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1
yq JSON
Command-line YAML, XML, TOML processor
Before using yq, you also have to install its dependency, jq. See the jq installation instructions for details and directions specific to your platform. On macOS, yq is also available on Homebrew use brew install python-yq. -
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Dataclasses JSON
Easily serialize Data Classes to and from JSON
This library provides a simple API for encoding and decoding dataclasses to and from JSON. -
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jello
CLI tool to filter JSON and JSON Lines data with Python syntax
Filter JSON and JSON Lines data with Python syntax. jello is similar to jq in that it processes JSON and JSON Lines data except jello uses standard python dict and list syntax. JSON or JSON Lines can be piped into jello via STDIN or can be loaded from a JSON file or JSON Lines files (JSON Lines are automatically slurped into a list of dictionaries). -
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jsondiff
Diff JSON and JSON-like structures in Python
Diff JSON and JSON-like structures in Python. -
MicroStation by Bentley Systems is the trusted computer-aided design (CAD) software built specifically for infrastructure design.MicroStation is the only computer-aided design software for infrastructure design, helping architects and engineers like you bring their vision to life, present their designs to their clients, and deliver their projects to the community.
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simplejson
simplejson is a simple, fast, extensible JSON encoder/decoder
simplejson is a simple, fast, complete, correct and extensible JSON <http://json.org> encoder and decoder for Python 3.3+ with legacy support for Python 2.5+. It is pure Python code with no dependencies but includes an optional C extension for a serious speed boost. simplejson is the externally maintained development version of the json library included with Python (since 2.6). This version is tested with the latest Python 3.8 and maintains backward compatibility with Python 3.3+ and the legacy Python 2.5 - Python 2.7 releases. ... -
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srsly
Modern high-performance serialization utilities for Python
This package bundles some of the best Python serialization libraries into one standalone package, with a high-level API that makes it easy to write code that's correct across platforms and Pythons. This allows us to provide all the serialization utilities we need in a single binary wheel. Currently supports JSON, JSONL, MessagePack, Pickle, and YAML. Serialization is hard, especially across Python versions and multiple platforms. After dealing with many subtle bugs over the years (encodings, locales, large files) our libraries like spaCy and Prodigy have steadily grown a number of utility functions to wrap the multiple serialization formats we need to support (especially json, msgpack and pickle). ... -
7
Remarshal
Convert between CBOR, JSON, MessagePack, TOML, and YAML
Convert between CBOR, JSON, MessagePack, TOML, and YAML. When installed, provides the command-line command remarshal as well as the short commands {cbor,json,msgpack,toml,yaml}2{cbor,json,msgpack,toml,yaml}. You can perform format conversion, reformatting, and error detection using these commands. CBOR, MessagePack, and YAML with binary fields cannot be converted to JSON or TOML. -
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granary
The social web translator
The social web translator. Fetches and converts data between social networks, HTML and JSON with microformats2, ActivityStreams/ActivityPub, Atom, JSON Feed, and more. Granary is a library and REST API that fetches and converts between a wide variety of social data sources and formats. Free yourself from silo API chaff and expose the sweet social data foodstuff inside in standard formats and protocols. -
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orjson
Fast, correct Python JSON library supporting dataclasses, datetimes
orjson is a fast, correct JSON library for Python. It benchmarks as the fastest Python library for JSON and is more correct than the standard json library or other third-party libraries. It serializes dataclass, datetime, numpy, and UUID instances natively. orjson supports CPython 3.8, 3.9, 3.10, 3.11, and 3.12. It distributes amd64/x86_64, aarch64/armv8, arm7, POWER/ppc64le, and s390x wheels for Linux, amd64 and aarch64 wheels for macOS, and amd64 and i686/x86 wheels for Windows. orjson does not support PyPy. ... -
Turn traffic into pipeline and prospects into customersDocket is an AI-powered sales enablement platform designed to unify go-to-market (GTM) data through its proprietary Sales Knowledge Lake™ and activate it with intelligent AI agents. The platform helps marketing teams increase pipeline generation by 15% by engaging website visitors in human-like conversations and qualifying leads. For sales teams, Docket improves seller efficiency by 33% by providing instant product knowledge, retrieving collateral, and creating personalized documents. Built for GTM teams, Docket integrates with over 100 tools across the revenue tech stack and offers enterprise-grade security with SOC 2 Type II, GDPR, and ISO 27001 compliance. Customers report improved win rates, shorter sales cycles, and dramatically reduced response times. Docket’s scalable, accurate, and fast AI agents deliver reliable answers with confidence scores, empowering teams to close deals faster.
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jsonschema
An implementation of the JSON Schema specification for Python
jsonschema is an implementation of the JSON Schema specification for Python. Full support for Draft 2020-12, Draft 2019-09, Draft 7, Draft 6, Draft 4 and Draft 3. Lazy validation that can iteratively report all validation errors. Programmatic querying of which properties or items failed validation. -
11
JC
CLI tool and python library
...In this case, the output will be a python dictionary, or a list of dictionaries, instead of JSON. Two representations of the data are available. The default representation uses a strict schema per parser and converts known numbers to int/float JSON values. Certain known values of None are converted to JSON null, known boolean values are converted, and, in some cases, additional semantic context fields are added. -
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TOML
Tom Preston-Werner's obvious, minimal language
...TOML should be easy to parse into data structures in a wide variety of languages. TOML shares traits with other file formats used for application configuration and data serialization, such as YAML and JSON. TOML and JSON both are simple and use ubiquitous data types, making them easy to code for or parse with machines. TOML and YAML both emphasize human readability features, like comments that make it easier to understand the purpose of a given line. TOML differs in combining these, allowing comments (unlike JSON) but preserving simplicity (unlike YAML). ... -
13
pyserde
Yet another serialization library on top of dataclasses
Yet another serialization library on top of data classes, inspired by serde-rs. Declare a class with pyserde's @serde decorator. -
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OSCAL
Open Security Controls Assessment Language (OSCAL)
...The OSCAL website provides an overview of the OSCAL project, including an XML and JSON schema reference, examples, and other resources. -
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Mashumaro
Fast and well tested serialization library on top of dataclasses
When using data classes, you often need to dump and load objects based on the schema you have. Mashumaro not only lets you save and load things in different ways, but it also does it super quickly. -
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ScanAPI
Automated Integration Testing and Live Documentation for your API
Given an API specification, written in YAML/JSON format, ScanAPI hits the specified endpoints, runs the test cases, and generates a detailed report of this execution - which can also be used as the API documentation itself. With almost no Python knowledge, the user can define endpoints to be hit, the expected behavior for each response and will receive a full real-time diagnostic report of the API. -
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pytablewriter
pytablewriter is a Python library to write a table in various formats
pytablewriter is a Python library to write a table in various formats: AsciiDoc / CSV / Elasticsearch / HTML / JavaScript / JSON / LaTeX / LDJSON / LTSV / Markdown / MediaWiki / NumPy / Excel / Pandas / Python / reStructuredText / SQLite / TOML / TSV / YAML. -
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Connexion
Swagger/OpenAPI First framework for Python on top of Flask
Connexion is a framework on top of Flask that automagically handles HTTP requests defined using OpenAPI (formerly known as Swagger), supporting both v2.0 and v3.0 of the specification. Connexion allows you to write these specifications, then maps the endpoints to your Python functions. This is what makes it unique from other tools that generate the specification based on your Python code. You are free to describe your REST API with as much detail as you want and then Connexion guarantees... -
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msgspec
A fast serialization and validation library, with builtin
msgspec is a fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML. -
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tmuxp
tmux session manager. built on libtmux
A session manager for tmux. Built on libtmux. -
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python-benedict
dict subclass with keylist/keypath support
python-benedict is a dict subclass with keylist/keypath/keyattr support, I/O shortcuts (base64, cli, csv, ini, json, pickle, plist, query-string, toml, xls, xml, yaml) and many utilities... for humans, obviously. -
22
HTTPie CLI
Modern, user-friendly command-line HTTP client for the API era
HTTPie (pronounced aitch-tee-tee-pie) is a command-line HTTP client. Its goal is to make CLI interaction with web services as human-friendly as possible. HTTPie is designed for testing, debugging, and generally interacting with APIs & HTTP servers. The HTTP & HTTPS commands allow for creating and sending arbitrary HTTP requests. They use simple and natural syntax and provide formatted and colorized output. -
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Cortex Analyzers
Cortex Analyzers Repository
Analyzers can be written in any programming language supported by Linux such as Python, Ruby, Perl, etc. Refer to the How to Write and Submit an Analyzer page for details on how to write and submit one. -
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SAFRS
SqlAlchemy Flask-Restful Swagger Json:API OpenAPI
SAFRS exposes SQLAlchemy database models as a JSON:API web service and generates the corresponding swagger/OpenAPI. Database objects such as the User class from the demo.py example can be extended to include relationships with other objects. The demo_relationship.py contains the following extension of the User class where a relationship with the Book class is implemented. -
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DocArray
The data structure for multimodal data
...Data science powerhouse: greatly accelerate data scientists’ work on embedding, k-NN matching, querying, visualizing, evaluating via Torch/TensorFlow/ONNX/PaddlePaddle on CPU/GPU. Data in transit: optimized for network communication, ready-to-wire at anytime with fast and compressed serialization in Protobuf, bytes, base64, JSON, CSV, DataFrame. Perfect for streaming and out-of-memory data. One-stop k-NN: Unified and consistent API for mainstream vector databases.
