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Repository Details

Configurable and extensible validator/linter for OpenAPI documents

Build Status npm-version semantic-release Gitter Commitizen friendly CLA assistant

OpenAPI Validator

The IBM OpenAPI Validator lets you validate OpenAPI 3.0.x and OpenAPI 3.1.x documents for compliance with the OpenAPI specifications, as well as IBM-defined best practices.

Prerequisites

  • Node 16.0.0+
  • NPM 8.3.0+

Table of contents

Getting Started

The validator analyzes your API definition and reports any problems within. The validator is highly customizable, and supports OpenAPI 3.0.x and 3.1.x documents. The tool also supports a number of rules from Spectral. You can easily extend the tool with custom rules to meet your specific needs and ensure compliance to your standards.

Get started by installing the tool, then run the tool on your API definition.

Ruleset

By default, the validator will use the IBM Cloud Validation Ruleset (npm package @ibm-cloud/openapi-ruleset). However, if the validator detects the presence of any of the standard Spectral ruleset files (spectral.yaml, spectral.yml, spectral.json, or spectral.js) in the current directory (from which the validator is being run) or in any containing directory within the file system, then that ruleset file will be used instead. To explicitly specify an alternate ruleset, you can use the -r/--ruleset option (or the ruleset configuration property) to specify the name of your custom ruleset file.

If one of the standard Spectral ruleset files are present and you'd like to force the use of the IBM Cloud Validation Ruleset instead, you can use -r default or --ruleset default (or set the ruleset configuration property to the value 'default').

Details about these options are provided below in the Usage section.

Customization

You can modify the behavior of the validator for your project to meet your preferred standards. See the customization documentation for more information.

Installation

There are three ways to install the validator: using NPM, downloading a platform-specific binary, or building from source.

Install with NPM (recommended)

npm install -g ibm-openapi-validator

The -g flag installs the tool globally so that the validator can be run from anywhere in the file system. Alternatively, you can pass no flag or the --save-dev flag to add the validator as a dependency to your project and run it from your NPM scripts or JavaScript code.

Download an executable binary

Platform-specific binary files are packaged with each release for MacOS, Linux, and Windows. See the releases page to download the executable for your platform. These do not depend on Node.JS being installed.

Build from source

  1. Clone or download this repository
  2. Navigate to the root directory of this project.
  3. Install the dependencies using npm install
  4. Build the command line tool by running npm run link.

If you installed the validator using npm install -g ibm-openapi-validator, you will need to run npm uninstall -g ibm-openapi-validator before running npm run link.

Build platform-specific binaries

It is also possible to build platform specific binaries from the source code by running npm run pkg in the project root directory. The binaries (lint-openapi-macos, lint-openapi-linux, lint-openapi-windows.exe) will be in the project's packages/validator/bin directory.

Container image

Run the validator with the container image by mounting your API definition.

If it is named openapi.yaml in the current directory, then run:

docker run \
  --rm --tty \
  --volume "$PWD:/data:ro" \
  ibmdevxsdk/openapi-validator:latest \
    openapi.yaml

You should replace latest with a specific tagged version to avoid any surprises when new releases are published.

Flag and argument syntax is the same as described in Usage, but file paths are relative to /data.

To use a custom ruleset named ruleset.yaml in the current directory, run:

docker run \
  --rm --tty \
  --volume "$PWD:/data:ro" \
  ibmdevxsdk/openapi-validator:latest \
    --ruleset ruleset.yaml \
    openapi.yaml

Building your own

If the existing image doesn't suit your needs, you could extend it and build your own.

For example, to build a validator image with your own custom ruleset package installed, make a Dockerfile like this:

FROM ibmdevxsdk/openapi-validator:latest
RUN npm install -g ${your-ruleset-pkg-here}

Usage

Command Syntax

Usage: lint-openapi [options] [file...]

Run the validator on one or more OpenAPI 3.x documents

Options:
  -c, --config <file>            use configuration stored in <file> (*.json, *.yaml, *.js)
  -e, --errors-only              include only errors in the output and skip warnings (default is false)
  -i, --ignore <file>            avoid validating <file> (e.g. -i /dir1/ignore-file1.json --ignore /dir2/ignore-file2.yaml ...) (default is []) (default: [])
  -j, --json                     produce JSON output (default is text)
  -l, --log-level <loglevel>     set the log level for one or more loggers (e.g. -l root=info -l ibm-schema-description-exists=debug ...)  (default: [])
  -n, --no-colors                disable colorizing of the output (default is false)
  -r, --ruleset <file>           use Spectral ruleset contained in `<file>` ("default" forces use of default IBM Cloud Validation Ruleset)
  -s, --summary-only             include only the summary information and skip individual errors and warnings (default is false)
  -w, --warnings-limit <number>  set warnings limit to <number> (default is -1)
  --version                      output the version number
  -h, --help                     display help for command

where [file...] is a space-separated list containing the filenames of one or more OpenAPI 3.x documents to be validated. The validator supports OpenAPI documents in either JSON or YAML format, using these supported file extensions:

.json
.yaml
.yml

Assuming your command shell supports the use of wildcards, you can use wildcards when specifying the names of files to be validated. For example, to run the validator on all .yaml files contained in the /my/apis directory, you could use this command:

lint-openapi /my/apis/*.yaml

Note that the -i/--ignore option can be particularly useful when using wildcards because it allows you to skip the validation of specific files which might otherwise be included in a validation run. For example, to validate all .yaml files in the /my/apis directory, except for /my/apis/broken-api.yaml use the command:

lint-openapi /my/apis/*.yaml -i /my/apis/broken-api.yaml

Configuration

In addition to command-line options, the validator supports the use of a configuration file containing options as well. A configuration file can be in JSON, YAML or Javascript format, using these supported extensions: .json, .yaml, .yml, and .js. Its structure must comply with this JSON schema.

You can specify the name of your configuration file with the -c/--config option. Here's an example:

lint-openapi -c my-config.yaml my-api.json

where my-config.yaml might contain the following:

errorsOnly: true
limits:
  warnings: 25
outputFormat: 'json'
summaryOnly: true

This would be equivalent to this command:

lint-openapi --errors-only --warnings-limit=25 --json --summary-only my-api.json

When using both a configuration file and various command-line options, be aware that the options specified via the command-line will take precendence and override any corresponding properties specified in the configuration file.

Configuration Properties

This section provides information about each of the properties that are supported within a configuration file.

colorizeOutput
Description Default
The colorizeOutput configuration property corresponds to the -n/--no-colors command-line option. If set to true, then the validator will colorize its output. true
Examples:
.yaml/.yml .json .js
colorizeOutput: false
{
  "colorizeOutput": false
}
module.exports = {
  colorizeOutput: false
};
errorsOnly
Description Default
The errorsOnly configuration property corresponds to the -e/--errors-only command-line option. If set to true, the validator will include only errors in its output, while messages of severity warning, info or hint will be skipped. false
Examples:
.yaml/.yml .json .js
errorsOnly: true
{
  "errorsOnly": true
}
module.exports = {
  errorsOnly: true
};
files
Description Default
The files configuration property corresponds to positional command-line arguments (i.e. [file...]). You can set this property to the names of the OpenAPI documents to be validated. If any filenames are also entered as positional arguments on the command-line, they will override any values specified in this configuration property. [](empty list)
Examples:
.yaml/.yml .json .js
files:
  - file1.json
  - file2.yaml
{
  "files": [
    "file1.json",
    "file2.yaml"
  ]
}
module.exports = {
  files: [
    'file1.json',
    'file2.yaml'
  ]
};
ignoreFiles
Description Default
The ignoreFiles configuration property corresponds to the -i/--ignore command-line option. Set this property to the fully-qualified filenames of OpenAPI documents to be excluded from validation. This property can be particularly useful when using wildcards for specifying the OpenAPI documents to be validated, because it allows you to skip the validation of specific files which might otherwise be included in a validation run. For example, to validate all .yaml files in the /my/apis directory, except for /my/apis/broken-api.yaml use the command:
    lint-openapi /my/apis/*.yaml --ignore /my/apis/broken-api.yaml
[](empty list)
Examples:
.yaml/.yml .json .js
ignoreFiles:
  - /my/apis/file1.yml
{
  "ignoreFiles": [
    "/my/apis/file1.yml"
  ]
}
module.exports = {
  ignoreFiles: [
    '/my/apis/file1.yml'
  ]
};
limits
Description Default
The limits configuration property corresponds to the -w/--warnings-limit command-line option. Use this property to set the warnings limit. When validating an OpenAPI document, the validator will compare the number of warnings it encounters with the warnings limit. If the number of warnings exceeds the limit, then an error will be logged and the validator will return exitCode 1, similar to if actual errors were found. If the warnings limit is set to a negative number, then no warnings limit check will be performed by the validator. { warnings: -1 }(warnings limit check disabled)
Examples:
.yaml/.yml .json .js
limits:
  warnings: 25
{
  "limits": {
    "warnings": 25
  }
}
module.exports = {
  limits: {
    warnings: 25
  }
};
logLevels
Description Default
The logLevels property is an object that specifies the logging level (error, warn, info, or debug) associated with each logger within the validator. It corresponds to the -l/--log-level command-line option. { root: 'info' }
Examples:
.yaml/.yml .json .js
logLevels:
  root: error
  ibm-schema-description-exists: debug
{
  "logLevels": {
    "root": "error",
    "ibm-schema-description-exists": "debug"
  }
}
module.exports = {
  logLevels: {
    root: 'error',
    'ibm-schema-description-exists': 'debug'
  }
};
outputFormat
Description Default
You can set the outputFormat configuration property to either text or json to indicate the type of output you want the validator to produce. This property corresponds to the -j/--json command-line option. text
Examples:
.yaml/.yml .json .js
outputFormat: json
{
  "outputFormat": "json"
}
module.exports = {
  outputFormat: 'json'
};
ruleset
Description Default
You can use the ruleset configuration property to specify a custom ruleset to be used by the validator. This corresponds to the -r/--ruleset command-line option.

By default, the validator will look for the standard Spectral ruleset files (.spectral.yaml, .spectral.yml, .spectral.json, or .spectral.js) in the current working directory and its parent directories within the filesystem. If none are found, then the IBM Cloud Validation Ruleset will be used.

If you want to force the use of the IBM Cloud Validation Ruleset even if one of the standard Spectral ruleset files are present, you can specify 'default' for the ruleset configuration property.

null, which implies that a standard Spectral ruleset file will be used (if present), otherwise the IBM Cloud Validation Ruleset will be used.
Examples:
.yaml/.yml .json .js
ruleset: my-custom-rules.yaml
{
  "ruleset": "my-custom-rules.yaml"
}
module.exports = {
  ruleset: 'my-custom-rules.yaml'
};
summaryOnly
Description Default
The summaryOnly configuration property corresponds to the -s/--summary-only command-line option. If set to true, the validator will include only the summary section in its output. false
Examples:
.yaml/.yml .json .js
summaryOnly: true
{
  "summaryOnly": true
}
module.exports = {
  summaryOnly: true
};

Validator Output

The validator can produce output in either text or JSON format. The default is text output, and this can be controlled with the -j/--json command-line option or outputFormat configuration property.

Text

Here is an example of text output:

IBM OpenAPI Validator (validator: 0.97.5; ruleset: 0.45.5), @Copyright IBM Corporation 2017, 2023.

Validation Results for /my/directory/my-api.yaml:

Errors:

  Message :   Path contains two or more consecutive path parameter references: /v1/clouds/{cloud_id}/{region_id}
  Rule    :   ibm-no-consecutive-path-parameter-segments
  Path    :   paths./v1/clouds/{cloud_id}/{region_id}
  Line    :   332

Warnings:

  Message :   Operation summaries should not have a trailing period
  Rule    :   ibm-summary-sentence-style
  Path    :   paths./v1/clouds.post.summary
  Line    :   46

  Message :   Operation summaries should not have a trailing period
  Rule    :   ibm-summary-sentence-style
  Path    :   paths./v1/clouds.get.summary
  Line    :   93

Summary:

  Total number of errors   : 1
  Total number of warnings : 2

  Errors:
   1 (100%) : Path contains two or more consecutive path parameter references

  Warnings:
   2 (100%) : Operation summaries should not have a trailing period

As you can see, any errors detected by the validator are listed first, then warnings, and finally a summary section. The -s/--summary-only command-line option or the summaryOnly configuration property can be used to request that only the summary is display. Also, the -e/--errors-only option or errorsOnly configuration property can be used to cause the validator to display only errors in the output.

JSON

When displaying JSON output, the validator will produce a JSON object which complies with this JSON schema. Here is an example of JSON output:

{
  "error": {
    "results": [
      {
        "message": "Path contains two or more consecutive path parameter references: /v1/clouds/{cloud_id}/{region_id}",
        "path": [
          "paths",
          "/v1/clouds/{cloud_id}/{region_id}"
        ],
        "rule": "ibm-consecutive-path-segments",
        "line": 332
      }
    ],
    "summary": {
      "total": 1,
      "entries": [
        {
          "generalizedMessage": "Path contains two or more consecutive path parameter references",
          "count": 1,
          "percentage": 100
        }
      ]
    }
  },
  "warning": {
    "results": [
      {
        "message": "Operation summaries should not have a trailing period",
        "path": [
          "paths",
          "/v1/clouds",
          "post",
          "summary"
        ],
        "rule": "ibm-summary-sentence-style",
        "line": 46
      },
      {
        "message": "Operation summaries should not have a trailing period",
        "path": [
          "paths",
          "/v1/clouds",
          "get",
          "summary"
        ],
        "rule": "ibm-summary-sentence-style",
        "line": 93
      }
    ],
    "summary": {
      "total": 2,
      "entries": [
        {
          "generalizedMessage": "Operation summaries should not have a trailing period",
          "count": 2,
          "percentage": 100
        }
      ]
    }
  },
  "info": {
    "results": [],
    "summary": {
      "total": 0,
      "entries": []
    }
  },
  "hint": {
    "results": [],
    "summary": {
      "total": 0,
      "entries": []
    }
  },
  "hasResults": true
}

The JSON output is also affected by the -s/--summary-only and -e/--errors-only options as well as the summaryOnly and errorsOnly configuration properties.

Logging

The validator uses a logger for displaying messages on the console. The core validator uses a single logger named root, while each of the rules contained in the IBM Cloud Validation Ruleset uses their own unique logger whose name will match the rule's id (e.g. ibm-accept-header, ibm-schema-description-exists, etc.).

Each logger has a logging level associated with it: error, warn, info, and debug. Each of these levels implicitly includes the levels that precede it in the list. For example, if you set the logging level of a logger to info, then all messages of type info, warn, and error will be displayed, but debug messages will not.

To set the level of the root logger to info, you could use this option: --log-level root=info.

To set the level of the logger used by the ibm-accept-header rule to debug, you could use this option: -l ibm-accept-header=debug.

You can also use a glob-like value for a logger name to set the level on multiple loggers. For example, to set the level for all loggers whose name starts with ibm-property, try this: -l ibm-property*=debug.

Enabling debug logging for a specific rule might be useful in a situation where the rule is reporting violations which seem to be inexplicable. In this case, additional debug information might be helpful in determining why the violations are occurring, and could possibly lead to a solution. For example, suppose the ibm-pagination-style rule is reporting several violations, but yet at first glance it's not obvious why these violations are occurring. To enable debug logging for this rule, use a command like this:

lint_openapi -l ibm-pagination-style=debug my-new-api.yaml

The default log level for the root logger is info, while the default log level for rule-specific loggers is warn.

Contributing

See CONTRIBUTING.

License

This project is licensed under Apache 2.0. Full license text is available in LICENSE.

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IBM Gantt Chart Component, integrable in Vanilla, jQuery, or React Framework.
JavaScript
193
star
69

api-samples

Samples code that uses QRadar API's
Python
192
star
70

cdfsl-benchmark

(ECCV 2020) Cross-Domain Few-Shot Learning Benchmarking System
Python
190
star
71

kube101

Kubernetes 101 workshop (https://ibm.github.io/kube101/)
Shell
181
star
72

CrossViT

Official implementation of CrossViT. https://arxiv.org/abs/2103.14899
Python
180
star
73

rl-testbed-for-energyplus

Reinforcement Learning Testbed for Power Consumption Optimization using EnergyPlus
Python
180
star
74

browser-functions

A lightweight serverless platform that uses Web Browsers as execution engines
JavaScript
180
star
75

pwa-lit-template

A template for building Progressive Web Applications using Lit and Vaadin Router.
TypeScript
178
star
76

fastfit

FastFit ⚑ When LLMs are Unfit Use FastFit ⚑ Fast and Effective Text Classification with Many Classes
Python
174
star
77

AMLSim

The AMLSim project is intended to provide a multi-agent based simulator that generates synthetic banking transaction data together with a set of known money laundering patterns - mainly for the purpose of testing machine learning models and graph algorithms. We welcome you to enhance this effort since the data set related to money laundering is critical to advance detection capabilities of money laundering activities.
Python
170
star
78

socket-io

A Socket.IO client for C#
C#
169
star
79

tfjs-web-app

A TensorFlow.js Progressive Web App for Offline Visual Recognition
JavaScript
164
star
80

spark-tpc-ds-performance-test

Use the TPC-DS benchmark to test Spark SQL performance
TSQL
160
star
81

simulai

A toolkit with data-driven pipelines for physics-informed machine learning.
Python
157
star
82

watson-online-store

Learn how to use Watson Assistant and Watson Discovery. This application demonstrates a simple abstraction of a chatbot interacting with a Cloudant NoSQL database, using a Slack UI.
HTML
156
star
83

unitxt

πŸ¦„ Unitxt: a python library for getting data fired up and set for training and evaluation
Python
155
star
84

istio101

Istio 101 workshop (https://ibm.github.io/istio101/)
Shell
154
star
85

Medical-Blockchain

A healthcare data management platform built on blockchain that stores medical data off-chain
Vue
150
star
86

terratorch

a Python toolkit for fine-tuning Geospatial Foundation Models (GFMs).
Python
148
star
87

node-odbc

ODBC bindings for node
JavaScript
146
star
88

taxinomitis

Source code for Machine Learning for Kids site
JavaScript
143
star
89

watson-assistant-slots-intro

A Chatbot for ordering a pizza that demonstrates how using the IBM Watson Assistant Slots feature, one can fill out an order, form, or profile.
JavaScript
143
star
90

tsfm

Foundation Models for Time Series
Jupyter Notebook
143
star
91

SALMON

Self-Alignment with Principle-Following Reward Models
Python
142
star
92

ipfs-social-proof

IPFS Social Proof: A decentralized identity and social proof system
JavaScript
142
star
93

kgi-slot-filling

This is the code for our KILT leaderboard submissions (KGI + Re2G models).
Python
141
star
94

etcd-java

Alternative etcd3 java client
Java
141
star
95

regression-transformer

Regression Transformer (2023; Nature Machine Intelligence)
Python
140
star
96

deploy-react-kubernetes

Built for developers who are interested in learning how to deploy a React application on Kubernetes, this pattern uses the React and Redux framework and calls the OMDb API to look up movie information based on user input. This pattern can be built and run on both Docker and Kubernetes.
JavaScript
139
star
97

probabilistic-federated-neural-matching

Bayesian Nonparametric Federated Learning of Neural Networks
Python
137
star
98

innovate-digital-bank

This repository contains instructions to build a digital bank composed of a set of microservices that communicate with each other. Using Nodejs, Express, MongoDB and deployed to a Kubernetes cluster on IBM Cloud.
JavaScript
137
star
99

core-dump-handler

Save core dumps from a Kubernetes Service or RedHat OpenShift to an S3 protocol compatible object store
Rust
136
star
100

KubeflowDojo

Repository to hold code, instructions, demos and pointers to presentation assets for Kubeflow Dojo
Jupyter Notebook
133
star