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Showing 10 open source projects for "linux full install"
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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. -
2
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. -
3
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. -
4
jsondiff
Diff JSON and JSON-like structures in Python
Diff JSON and JSON-like structures in Python. -
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5
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). Once loaded, the data is available as a python list or dictionary object named '_'. Processed data can be output as JSON, JSON Lines, bash array... -
6
Python JSONPath Next-Generation
JSONPath implementation for Python that aims to be standard compliant
A final implementation of JSONPath for Python that aims to be standard compliant, including arithmetic and binary comparison operators, as defined in the original JSONPath proposal. This package merges both jsonpath-rw and jsonpath-rw-ext and provides several AST API enhancements, such as the ability to update or remove nodes in the tree. This library provides a robust and significantly extended implementation of JSONPath for Python. It is tested with CPython 3.7 and higher. This library... -
7
crossplane
Quick and reliable way to convert NGINX configurations into JSON
Reliable and fast NGINX configuration file parser and builder. Since crossplane is usually used to create payloads that are sent to different servers, it's important to keep security in mind. For that reason, the --ignore option was added. It can be used to keep certain sensitive directives out of the payload output entirely. -
8
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... -
9
hyperjson
Python module for reading/writing JSON data using Rust's serde-json
A hyper-fast, safe Python module to read and write JSON data. Works as a drop-in replacement for Python's built-in json module. This is alpha software and there will be bugs, so maybe don't deploy to production just yet. -
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10
Full Stack FastAPI Couchbase
Full stack, modern web application generator
Full stack, modern web application generator. Using FastAPI, Couchbase as a database, Docker, automatic HTTPS, and more. Couchbase has a great set of features that is not easily or commonly found in alternatives. REST backend tests based on Pytest, integrated with Docker, so you can test the full API interaction, independent on the database. As it runs in Docker, it can build a new data store from scratch each time (so you can use ElasticSearch, MongoDB, or whatever you want, and just test...
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