Open Source Python JSON Software
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Python JSON Software
View related business solutionsBrowse free open source Python JSON Software and projects below. Use the toggles on the left to filter open source Python JSON Software by OS, license, language, programming language, and project status.
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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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TOML
Tom Preston-Werner's obvious, minimal language
Tom's Obvious, Minimal Language. By Tom Preston-Werner, Pradyun Gedam, et al. TOML aims to be a minimal configuration file format that's easy to read due to obvious semantics. TOML is designed to map unambiguously to a hash table. 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). Because TOML is explicitly intended as a configuration file format, parsing it is easy, but it is not intended for serializing arbitrary data structures. -
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FreeTAKServer
Situational Awareness Server compatible with TAK clients
FTS is a Python3 implementation of a TAK Server for devices like ATAK, WinTAK, and ITAK, it is cross-platform and runs from a multi-node installation on AWS down to the Android edition. It's free and open source (released under the Eclipse Public License. FTS allows you to connect ATAK clients to share geo-information, to chat with all the connected clients, exchange files and more. It intends to support all the major use cases of the original TAK server. -
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OSCAL
Open Security Controls Assessment Language (OSCAL)
NIST is developing the Open Security Controls Assessment Language (OSCAL), a set of hierarchical, XML-, JSON-, and YAML-based formats that provide a standardized representation of information pertaining to the publication, implementation, and assessment of security controls. OSCAL is being developed through a collaborative approach with the public. Public contributions to this project are welcome. With this effort, we are stressing the agile development of a set of minimal formats that are generic enough to capture the breadth of data in scope (controls specifications), while also capable of ad-hoc tuning and extension to support peculiarities of both (industry or sector) standards and new control types. The OSCAL website provides an overview of the OSCAL project, including an XML and JSON schema reference, examples, and other resources. -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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Extract TOTP/HOTP secrets
Extract one time password (OTP) secrets from QR codes
The Python script extract_otp_secrets.py extracts one-time password (OTP) secrets from QR codes exported by two-factor authentication (2FA) apps such as "Google Authenticator". -
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TradingView Chart Data Extractor
Extract price and indicator data from TradingView charts
Ensure that you zoom/pan such that the oldest date you desire is visible on TradingView before publishing the chart. Too many indicators or too low a time resolution will increase the data points and potentially overload the free server. Avoid this by hosting/running the script on your local machine or scraping multiple times with fewer indicators and manually combining the CSV afterward. Simply append the URL of a chart/idea published on TradingView to the link below. This is not the URL of a security's chart, but the URL for a user-published chart. -
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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. Releases follow semantic versioning and serializing a new object type without an opt-in flag is considered a breaking change. -
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Canmatrix
Converting Can (Controller Area Network) Database Formats
Canmatrix is a Python package to read and write several CAN (Controller Area Network) database formats. Canmatrix implements a "Python Can Matrix Object" which describes the can-communication and the needed objects (Board units, Frames, Signals, Values, ...) Canmatrix also includes two Tools (can convert and can compare) for converting and comparing CAN databases. -
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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. -
Comet Backup - Fast, Secure Backup Software for MSPsComet is a flexible backup platform, giving you total control over your backup environment and storage destinations.
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DocArray
The data structure for multimodal data
DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. 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. 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. -
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JC
CLI tool and python library
CLI tool and python library that converts the output of popular command-line tools and file types to JSON or Dictionaries. This allows piping of output to tools like jq and simplifying automation scripts. jc JSONifies the output of many CLI tools and file types for easier parsing in scripts. This allows further command-line processing of output with tools like jq or jello by piping commands. The JC parsers can also be used as python modules. 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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SQLModel
SQL databases in Python, designed for simplicity, compatibility
SQLModel, SQL databases in Python, designed for simplicity, compatibility, and robustness. SQLModel is a library for interacting with SQL databases from Python code, with Python objects. It is designed to be intuitive, easy to use, highly compatible, and robust. SQLModel is based on Python-type annotations, and powered by Pydantic and SQLAlchemy. -
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NeuroJSON
Scalable, searchable and verifiable neuroimaging data exchange platfor
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jsondata
Modular JSON by trees and branches, pointers and patches
The 'jsondata' package provides for the modular in-memory processing of JSON data by trees, branches, pointers, and patches. The main interface classes are: - JSONData - Core for RFC7159 based data structures. Provides modular data components. - JSONDataSerializer - Core for RFC7159 based data persistence. Provides modular data serialization. - JSONPointer - RFC6901 for addressing by pointer paths. Provides pointer arithmetics. - JSON Relative Pointer - draft-handrews-relative-json-pointer/2018, contained in JSONPointer. - JSONPatch - RFC6902 for modification by patch lists. Provides the assembly of modular patch entries and the serialization of resulting patch lists. - JSONDiff - Diff utility for JSON data. - JSONSearch - Search utility JSON patterns. Online documents: https://jsondata.sourceforge.io/ -
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PersonGen
A minor Project in Python which uses the RandomUser API .
A Small Program in Python That Makes Use of RandomUser API To Generate Random Person Data. -
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ADFILT
Web filter lists for countless different topics
This is the place where I, Imre Kristoffer Eilertsen, host my web filter lists for countless different topics, for use in adblock tools and the like. GitHub was in mid-2017 by far the easiest way for laymen like me to store pure text files, which is a necessity to create subscribable lists. This is a hobby project of mine, in which I work just as much on these lists and this repo as I feel like. But don't be fooled by the appearance, as these are nevertheless some lists that I've placed lots of energy and effort into, for the enjoyment of all of us. -
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Aurora Application Server is a new Python Web Application Server and Framework. The main goal of the project is to provide the developer with a complete set of tools to speed up the application development process. See project wiki for more information.
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Awkward Array
Manipulate JSON-like data with NumPy-like idioms
Awkward Array is a library for nested, variable-sized data, including arbitrary-length lists, records, mixed types, and missing data, using NumPy-like idioms. Arrays are dynamically typed, but operations on them are compiled and fast. Their behavior coincides with NumPy when array dimensions are regular and generalizes when they're not. -
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BigchainDB Server
Meet BigchainDB. The blockchain database
BigchainDB is the blockchain database. This repository is for the BigchainDB Server. Running and testing the latest version of the BigchainDB Server is easy. Make sure you have a recent version of Docker Compose installed. -
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Python library that handles and manages communication between client and blip.pl server via blip.pl API.
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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 that it will work as you specified. We built Connexion this way in order to simplify the development process. Reduce misinterpretation about what an API is going to look like. With Connexion, you write the spec first. Connexion then calls your Python code, handling the mapping from the specification to the code. This incentivizes you to write the specification so that all of your developers can understand what your API does, even before you write a single line of code. -
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CrowdAnki
Plugin for Anki SRS designed to facilitate cooperation
CrowdAnki is a plugin for http://ankisrs.net/ that allows users to import and export decks/notes and all relevant information in a JSON format. The main purpose is to facilitate crowd-sourcing for Anki decks and notes. Starting with version 0.6 it also features a close integration with Git. Providing you with the ability to automatically maintain a history of edits for your decks. My goal here is to provide a user-friendly description of collaboration workflow. In order to do that, I looked through multiple GUI git clients. For our purposes here, I think GitHub Desktop is the best choice (as the most user-friendly client that works). There is one problem with GitHub Desktop, though - it doesn't have a Linux version. Which makes me particularly sad, as I use Linux as my main OS. -
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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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Django REST Pandas
Serves up Pandas dataframes via the Django REST Framework
Django REST Pandas (DRP) provides a simple way to generate and serve 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. These can be used to create interactive time series, scatter, and box plot charts.
