Browse free open source Python JSON Serialization Libraries and projects below. Use the toggles on the left to filter open source Python JSON Serialization Libraries by OS, license, language, programming language, and project status.

  • Auth for GenAI | Auth0 Icon
    Auth for GenAI | Auth0

    Enable AI agents to securely access tools, workflows, and data with fine-grained control and just a few lines of code.

    Easily implement secure login experiences for AI Agents - from interactive chatbots to background workers with Auth0. Auth for GenAI is now available in Developer Preview
    Try free now
  • AI-powered service management for IT and enterprise teams Icon
    AI-powered service management for IT and enterprise teams

    Enterprise-grade ITSM, for every business

    Give your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
    Try it Free
  • 1
    TOML

    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.
    Downloads: 4 This Week
    Last Update:
    See Project
  • 2
    NeuroJSON

    NeuroJSON

    Scalable, searchable and verifiable neuroimaging data exchange platfor

    Downloads: 18 This Week
    Last Update:
    See Project
  • 3
    jsondata

    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/
    Downloads: 2 This Week
    Last Update:
    See Project
  • 4
    Connexion

    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.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Build Securely on AWS with Proven Frameworks Icon
    Build Securely on AWS with Proven Frameworks

    Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.

    Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
    Download Now
  • 5
    DocArray

    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.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 6
    jsonfield

    jsonfield

    A reusable Django model field for storing ad-hoc JSON data

    jsonfield is a reusable model field that allows you to store validated JSON, automatically handling serialization to and from the database. To use, add jsonfield.JSONField to one of your models. Note: django.contrib.postgres now supports PostgreSQL's jsonb type, which includes extended querying capabilities. If you're an end user of PostgreSQL and want full-featured JSON support, then it is recommended that you use the built-in JSONField. However, jsonfield is still useful when your app needs to be database-agnostic, or when the built-in JSONField's extended querying is not being leveraged. e.g., a configuration field. JSONField is not intended to provide extended querying capabilities. That said, you may perform the same basic lookups provided by regular text fields (e.g., exact or regex lookups). Since values are stored as serialized JSON, it is highly recommended that you test your queries to ensure the expected results are returned.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
Want the latest updates on software, tech news, and AI?
Get latest updates about software, tech news, and AI from SourceForge directly in your inbox once a month.