Search results for: Aws convert json to yaml

Below are our best 43 results for aws convert json to yaml, updated recently.

stackoverflow.com

I have been using serverless for sometime. I have been uploading images to s3 bucket. I created the s3 bucket in the aws console manually. Now, I am struggling to create s3 bucket via yaml and upload files in it due to per. I have successfully created s3 bucket via yaml using this yaml commands:

jsonformatter.org

Online JSON Formatter and Online JSON Validator provide JSON converter tools to convert JSON to XML, JSON to CSV, and JSON to YAML also JSON Editor, JSONLint, JSON Checker, and JSON Cleaner. Free JSON Formatting Online and JSON Validator Online work well in Windows, Mac, Linux, Chrome, Firefox, Safari, and Edge. JSON Example:

github.com

AWS CloudFormation Template Flip About. AWS CloudFormation Template Flip is a tool that converts AWS CloudFormation templates between JSON and YAML formats, making use of the YAML format's short function syntax where possible.. The term "Flip" is inspired by the well-known Unix command-line tool flip which converts text files between Unix, Mac, and MS-DOS …

aws.amazon.com

The Virtues of YAML CloudFormation and Using CloudFormation Designer to Convert JSON to YAML by Aaron Fagan | on ... provides the framework to define infrastructure-as-code in AWS and, until last year, this could only be written in JSON. However, in 2016, AWS added YAML 1.1 support for CloudFormation. ... Amazon Web Services, Inc. or its ...

medium.com

Note you can use the -j or -y options to specify JSON or YAML format. Output in YAML (-y) would look like this: ... You can always use the aws-cli to export your IAM Role and then tweak the JSON ...

qa.com

NOTE: I’ve got that re:Invent feeling - that as I’m writing this, someone from AWS is preparing to announce a tool that does awesome and intelligent conversions from JSON-Cfn to YAML-Cfn. Step 1: Convert the JSON to YAML. Clearly, as YAML is a super-set of JSON, there are many ways to perform the initial conversion, from online tools to ...

cftransform.com

To use, simply paste your JSON or YAML CloudFormation template into the editor and click ‘convert’. CFTransform will automatically detect the format type and convert it to the opposite format. Additionally, CFTransform will also optimize AWS specific syntax to be best practice (such as !Sub instead of Fn::Join).

newbedev.com

Imagine a Cloudformation template which creates four subnets, probably written out using copy/pasted JSON or YAML with four separate resources ("PublicSubnet0", "PublicSubnet1", and so on). The way you'd likely do that in Terraform is with aws_subnet and count = 4. Any converter that you use should be smart enough to handle that.

github.com

Any yaml parser should be able to read json out of the box because YAML is designed as a superset of json (all json is valid yaml). If you need to convert json to human readable yaml, there are many many tools you could use. Original post. Describe the bug cdk synth ignores -j option when used with -o.

codebeautify.org

This tool validates YAML after edit and before display YAML. This will help you save your time. This tool allows loading the YAML URL to Edit. Use your YAML REST URL to Edit. Click on the URL button, Enter URL and Submit. Users can also edit YAML data file by uploading the file. Editor YAML works well on Windows, MAC, Linux, Chrome, Firefox ...

aws.plainenglish.io

Parsing yaml configuration in Terraform. yamldecode — helps in formatting your yaml file into a map object that terraform can read from.. flatten — helps in restructuring nested maps into a more readable map that is easier to access by terraform functions. Creating all resources. Based on the configurations above, we can now create n sqs queues just by …

stackery.io

JavaScript Object Notation (JSON) and YAML look more similar and share design goals. While JSON is designed to be a bit easier to compile programmatically, the biggest difference for everyday use is that YAML has a method for referencing other items in the same JSON file. ... and the design goals of YAML. AWS Serverless Application Model. AWS ...

camel.apache.org

Camel DSL with YAML. For example the JSONPath can be configured to ignore JSon parsing errors. This is intended when you use a Content Based Router and want to route the message to different endpoints, but the JSon payload of the message can be in different forms; meaning that the JSonPath expressions in some cases would fail with an exceptions, and other times not.

reddit.com

Converting json to yaml in Terraform. Expected output with a additional field with random password. The files are used only on a local machine. This is what I would expect a YAML encoder to output from your supplied JSON: users: - name: john age: 23 city: barcelona - name: bob age: 29 city: london. Is that what you’re expecting?

persian.cheese.ath.cx

YAML is a markup language used in various programming languages and other software development to describe data. Converting YAML to JSON can help you save time and resources. You may now look at an introduction to YAML in Python for Beginners and JSON Tools to Parse, Format, and Validate. Want to convert JSON to Excel? Try these tools.

docs.aws.amazon.com

We recommend that you don't add # YAML comments to your templates in Designer. If your YAML template has # comments, Designer doesn't preserve those comments when editing the YAML or converting to JSON. If you edit or modify your template in Designer (for example, if you drag a resource on the canvas), your comments are lost.

Use Designer's integrated JSON and YAML editor to view and edit template details. For example, you can use the integrated editor to define the properties of a resource or to change a template parameter. The integrated editor has two views: a Components view and a Template view.

To make minor changes to a specific section of a template, use the Components view. In the Components view, the components that you can edit are divided into tabs. These tabs change depending on whether you have a resource selected.

For example, if you select a resource, Designer provides tabs to edit the resource's properties and attributes, such as an update policy or creation policy. If you haven't selected anything, Designer provides tabs for editing the template parameters, mappings, conditions, metadata, and outputs. Any changes that you make in the Components view must be valid JSON or YAML markup. If you introduce invalid JSON or YAML, Designer reverts the invalid markup to the valid markup when you leave the Components view.

To make broad changes to your template, use the Template view. In the Template view, the integrated JSON and YAML editor shows you the raw JSON or YAML of your entire template. When you want to make changes to a resource, select it in the canvas pane Designer automatically highlights that resource in the integrated JSON and YAML editor.

AWS CloudFormation Designer integrated JSON and YAML editor

Converting templates into YAML or JSON

You can convert a valid template back and forth between JSON and YAML by selecting the appropriate radio button in Choose template language. Designer can only convert valid YAML or valid JSON templates. If the conversion succeeds, the Messages pane displays a message like: Successfully converted the template to YAML.

We recommend that you don't add # YAML comments to your templates in Designer. If your YAML template has # comments, Designer doesn't preserve those comments when editing the YAML or converting to JSON. If you edit or modify your template in Designer (for example, if you drag a resource on the canvas), your comments are lost.

Once you choose a template language, any new resources you drag onto the canvas will be created in the language you have selected. To change back to another language, make sure your template is valid and then select YAML or JSON where it says Choose template language.

When you convert a template to YAML, Designer uses short form notation for functions. For example, - !GetAtt. In addition, any visual links that you draw will use short form notation in YAML mode. For more information about intrinsic functions, see Ref.

Autocomplete

The integrated JSON and YAML editor includes an auto-complete feature that helps you specify resource properties, so you don't have to remember property names. To see a list of valid properties in a JSON template, press Ctrl+Space within the Properties curly braces ({}), as shown in the following example:

For a YAML template, you can first delete the opening and closing curly braces and press Enter to go to a new line. To see a list of valid properties, press Ctrl+Space on the new line after Properties, as shown in the following example:

Keyboard shortcuts

Designer's integrated JSON and YAML editor provides the following keyboard shortcuts:

Ctrl+Space

Within the Properties key of a resource, lists all the available properties for the resource.

Ctrl+F

Searches for a specified value.

To highlight everything that matches the specified value, press Alt+Enter.

dev.to

Sometimes you have a JSON template you want to convert to YAML or vice versa, which is what I ran into today. AWS CloudFormation Template Flip is a command-line tool (and also a python library) you can use to convert a JSON template to YAML or the other way around. Tagged with aws, infrastructure, iac, cloudformation.

json2yaml.com

Convert JSON to YAML online YAML vs JSON. determine which format is right for you JSON. stands for javascript object notation records separated by commas keys & strings wrapped by double quotes good choice for data transport YAML. stands for YAML ain't markup language and is a superset of JSON ...

jsonformatter.org

JSON to YAML. JSON to YAML helps convert JSON data to YAML. It's very simple and easy way to transform and share JSON to YAML data. Best and Secure JSON to YAML works well in Windows, Mac, Linux, Chrome, Firefox, Safari and Edge.

medium.com

How to convert CloudFormation JSON to YAML. In this article, we are going to take an AWS CloudFormation file written in JSON and then convert that file to YAML format. Luckily, AWS has a way to do ...

dlt.com

18-05-2015 · I am not going to go into the holy war of the JSON vs YAML discussion. That is something that should be left to folks that have time and willingness to discuss this, just like discussions of OS X vs Windows vs Linux, or VMware vs Xen, or iOS vs Android, or …the list could continue way past this blog. But this blog is not to discuss either/or.

18-05-2015

The template is located at this address.


{ "AWSTemplateFormatVersion" : "2010-09-09", "Description" : "AWS CloudFormation Sample Template DynamoDB_Table: This template demonstrates the creation of a DynamoDB table. **WARNING** This template creates an Amazon DynamoDB table. You will be billed for the AWS resources used if you create a stack from this template.", "Parameters" : { "HaskKeyElementName" : { "Description" : "HashType PrimaryKey Name", "Type" : "String", "AllowedPattern" : "[a-zA-Z0-9]*", "MinLength": "1", "MaxLength": "2048", "ConstraintDescription" : "must contain only alphanumberic characters" }, "HaskKeyElementType" : { "Description" : "HashType PrimaryKey Type", "Type" : "String", "Default" : "S", "AllowedPattern" : "[S|N]", "MinLength": "1", "MaxLength": "1", "ConstraintDescription" : "must be either S or N" }, "ReadCapacityUnits" : { "Description" : "Provisioned read throughput", "Type" : "Number", "Default" : "5", "MinValue": "5", "MaxValue": "10000", "ConstraintDescription" : "must be between 5 and 10000" }, "WriteCapacityUnits" : { "Description" : "Provisioned write throughput", "Type" : "Number", "Default" : "10", "MinValue": "5", "MaxValue": "10000", "ConstraintDescription" : "must be between 5 and 10000" } }, "Resources" : { "myDynamoDBTable" : { "Type" : "AWS::DynamoDB::Table", "Properties" : { "AttributeDefinitions": [ { "AttributeName" : {"Ref" : "HaskKeyElementName"}, "AttributeType" : {"Ref" : "HaskKeyElementType"} } ], "KeySchema": [ { "AttributeName": {"Ref" : "HaskKeyElementName"}, "KeyType": "HASH" } ], "ProvisionedThroughput" : { "ReadCapacityUnits" : {"Ref" : "ReadCapacityUnits"}, "WriteCapacityUnits" : {"Ref" : "WriteCapacityUnits"} } } } }, "Outputs" : { "TableName" : { "Value" : {"Ref" : "myDynamoDBTable"}, "Description" : "Table name of the newly created DynamoDB table" } }
}

Some people have no problem reading JSON and working with it’s “large” number of curly braces. I personally prefer to no have to do that. So, after looking for information and modifying it to suite my needs, I am now able to convert the above template into the following YAML file:

---
AWSTemplateFormatVersion: '2010-09-09'
Description: 'AWS CloudFormation Sample Template DynamoDB_Table: This template demonstrates the creation of a DynamoDB table. **WARNING** This template creates an Amazon DynamoDB table. You will be billed for the AWS resources used if you create a stack from this template.'
Parameters: HaskKeyElementName: Description: HashType PrimaryKey Name Type: String AllowedPattern: "[a-zA-Z0-9]*" MinLength: '1' MaxLength: '2048' ConstraintDescription: must contain only alphanumberic characters HaskKeyElementType: Description: HashType PrimaryKey Type Type: String Default: S AllowedPattern: "[S|N]" MinLength: '1' MaxLength: '1' ConstraintDescription: must be either S or N ReadCapacityUnits: Description: Provisioned read throughput Type: Number Default: '5' MinValue: '5' MaxValue: '10000' ConstraintDescription: must be between 5 and 10000 WriteCapacityUnits: Description: Provisioned write throughput Type: Number Default: '10' MinValue: '5' MaxValue: '10000' ConstraintDescription: must be between 5 and 10000
Resources: myDynamoDBTable: Type: AWS::DynamoDB::Table Properties: AttributeDefinitions: - AttributeName: Ref: HaskKeyElementName AttributeType: Ref: HaskKeyElementType KeySchema: - AttributeName: Ref: HaskKeyElementName KeyType: HASH ProvisionedThroughput: ReadCapacityUnits: Ref: ReadCapacityUnits WriteCapacityUnits: Ref: WriteCapacityUnits
Outputs: TableName: Value: Ref: myDynamoDBTable Description: Table name of the newly created DynamoDB table

Now, in my personal opinion, the above YAML version is much easier to read than the JSON version. If you do have similar notions, please take a look at the below script. It is mostly self explanatory and also displays a bit of help if you miss something on command line. What is does though is convert one format into another and back again. This lets me work on the CloudFormation templates in YAML then convert them into proper JSON for upload into AWS.

 require 'yaml'
require 'json'
require 'optparse'
require 'ostruct'
require 'fileutils' unless ARGV.length == 3 puts "Dude, not the right number of arguments." puts "Usage: ruby YJ_Convert.rb [-j][-y] json_file.json yaml_file.yaml\n" exit
end $json_file = ARGV[1]
$yaml_file = ARGV[2] options = OpenStruct.new
OptionParser.new do |opt| opt.on('-j', '--json', 'Convert to JSON') { |o| options.json = o } opt.on('-y', '--yaml', 'Convert to YAML') { |o| options.yaml = o }
end.parse! case when options.yaml == true y_file = File.open("#{$yaml_file}", 'a') y_file.write(YAML.dump(JSON.parse(IO.read($json_file)))) y_file.close puts "Converted to YAML. Output file is #{$yaml_file}" when options.json == true j_file = YAML.load_file(File.open("#{$yaml_file}", 'r')) File.write "#{$json_file}", JSON.pretty_generate(j_file) puts "Converted to JSON. Output file is #{$json_file}"
end

Hope this helps someone with JSON to YAML to JSON conversion necessity.

markrichman.com

YAML is a superset of JSON, which means you can parse JSON with a YAML parser. Betcha didn’t know that! It is far better suited for configuration than JSON, making it the de facto configuration file format for cloud-native infrastructure tooling.

The Virtues of YAML CloudFormation and Using ...

10-11-2017 · Caution: Converting a commented YAML template to JSON will remove all comments. Comments will not re-appear if the template is toggled back to YAML. 6. Save the template in YAML format by once again choosing the File icon and choosing Save from the menu. Conclusion. In this blog post, we discussed some reasons to convert CloudFormation ...

10-11-2017

AWS CloudFormation provides the framework to define infrastructure-as-code in AWS and, until last year, this could only be written in JSON. However, in 2016, AWS added YAML 1.1 support for CloudFormation. Let’s take a look at some of the advantages of using YAML over JSON, as well as how to overcome some of the challenges in getting started writing CloudFormation in YAML.

The virtues of YAML

YAML CloudFormation fully supports all of the same features and functions as JSON CloudFormation with some additional features to reduce the length of code and increase readability. Say goodbye to the curly braces and most of the quotation marks of JSON when you use YAML. YAML uses parent nodes, child nodes, and indentation to denote hierarchy rather than curly braces and commas as in JSON.

YAML also supports comments using the # character. CloudFormation templates can get complex. Including key comments in the code can make it easier to understand, especially as teams get started with CloudFormation and develop templates together.

Let’s look at a code sample. The following YAML and JSON CloudFormation templates perform the same function, they deploy an Amazon Linux EC2 instance serving a webpage via Apache HTTP Server.

JSON template

{
    "AWSTemplateFormatVersion": "2010-09-09",
    "Parameters": {
        "SubnetID": {
            "Type": "AWS::EC2::Subnet::Id",
            "Description": "Subnet to deploy EC2 instance into"
        },
        "SecurityGroupIDs": {
            "Type": "List",
            "Description": "List of Security Groups to add to EC2 instance"
        },
        "KeyName": {
            "Type": "AWS::EC2::KeyPair::KeyName",
            "Description": "Name of an existing EC2 KeyPair to enable SSH access to the instance"
        },
        "InstanceType": {
            "Description": "EC2 instance type",
            "Type": "String",
            "Default": "t2.micro"
        }
    },
    "Mappings": {
        "AWSRegionToAMI": {
            "us-east-1": {
                "AMIID": "ami-0b33d91d"
            },
            "us-east-2": {
                "AMIID": "ami-c55673a0"
            }
        }
    },
    "Resources": {
        "EC2Instance": {
            "Type": "AWS::EC2::Instance",
            "Properties": {
                "ImageId": {
                    "Fn::FindInMap": [
                        "AWSRegionToAMI",
                        {
                            "Ref": "AWS::Region"
                        },
                        "AMIID"
                    ]
                },
                "InstanceType": {
                    "Ref": "InstanceType"
                },
                "KeyName": {
                    "Ref": "KeyName"
                },
                "SecurityGroupIds": {
                    "Ref": "SecurityGroupIDs"
                },
                "SubnetId": {
                    "Ref": "SubnetID"
                },
                "UserData": {
                    "Fn::Base64": {
                        "Fn::Sub": "#!/bin/bash -ex\nyum install -y httpd;\necho \"I love YAML CloudFormation!!\" > /var/www/html/index.html;\ncd /var/www/html;\nchmod 755 index.html;\nservice httpd start;\nchkconfig httpd on;\n"
                    }
                },
                "Tags": [
                    {
                        "Key": "Name",
                        "Value": "CloudFormation Test - YAML"
                    },
                    {
                        "Key": "Environment",
                        "Value": "Development"
                    }
                ]
            }
        }
    }
}
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YAML template

AWSTemplateFormatVersion: 2010-09-09
Parameters:
  SubnetID:
    Type: AWS::EC2::Subnet::Id
    Description: Subnet to deploy EC2 instance into
  SecurityGroupIDs:
    Type: List
    Description: List of Security Groups to add to EC2 instance
  KeyName:
    Type: AWS::EC2::KeyPair::KeyName
    Description: >-
      Name of an existing EC2 KeyPair to enable SSH access to the instance
  InstanceType:
    Description: EC2 instance type
    Type: String
    Default: t2.micro
Mappings:
  AWSRegionToAMI:
    us-east-1:
      AMIID: ami-0b33d91d
    us-east-2:
      AMIID: ami-c55673a0
Resources:
  EC2Instance:
    Type: AWS::EC2::Instance                     
    Properties:
      ImageId:
        !FindInMap                                 # This is an example of the short form YAML FindInMap function
          - AWSRegionToAMI                         # It accepts three parameters each denoted by a hyphen (-)
          - !Ref AWS::Region
          - AMIID
      InstanceType: !Ref InstanceType
      KeyName: !Ref KeyName
      SecurityGroupIds: !Ref SecurityGroupIDs
      SubnetId: !Ref SubnetID
      UserData:
        Fn::Base64:                                # YAML makes userdata much cleaner
          !Sub |
              #!/bin/bash -ex
              yum install -y httpd;
              echo "I love YAML CloudFormation!!" > /var/www/html/index.html;
              cd /var/www/html;
              chmod 755 index.html;
              service httpd start;
              chkconfig httpd on;
      Tags:                                      # Tags are an example of a sequence of mappings in YAML,
        -                                        # each key/value pair is separated by a hyphen
          Key: Name
          Value: CloudFormation Test - YAML      
        -
          Key: Environment
          Value: Development

From a readability perspective, it’s pretty clear YAML is the winner. The JSON template is 1200 characters with whitespace removed. The YAML template is 972 characters for the exact same functionality with whitespace and comments removed. Shorter templates are not only more readable and make troubleshooting errors easier, but they also allow more resources to be deployed in a single template without hitting CloudFormation limits for template body size.

Converting a JSON CloudFormation template to YAML

We’ve established there are some advantages to using YAML, but many organizations already have libraries of JSON-formatted CloudFormation templates and employees with expertise writing JSON. Additionally, many publically available code samples are written in JSON along with many AWS QuickStarts. If only there were an easy, secure way to convert JSON CloudFormation to YAML. Old JSON templates could be reused and public samples could be converted to make learning YAML easier.

Enter CloudFormation Designer

CloudFormation Designer is an easy-to-use graphical user interface to create, edit, and view CloudFormation templates. The Designer is free and is part of the AWS Management Console. One fantastic feature is the ability to convert CloudFormation templates from JSON to YAML, and back again, with the click of a button. There are other online converters out there but the Designer is part of your AWS Management Console, so the code never leaves your possession.

Let’s convert our JSON template to YAML:

1. Open the AWS Management Console and navigate to the CloudFormation service.

2. Choose the Design template button to open the Designer.

3. Open the JSON CloudFormation template by choosing the File icon, then choosing Open from the menu.

4. Select the file, either a local file on your workstation or a file in an Amazon S3 bucket. This opens the CloudFormation template in Designer. We see the familiar JSON code of our template in the bottom pane. In the upper-right pane, we see a graphical representation of the EC2 instance described in our template. Finally, in the upper-left pane, we can optionally drag and drop a variety of Resource Types onto the canvas to include them in our template.

5. In the upper right-hand corner of the code pane, note the Choose template language radio button. Choose the button next to YAML to convert the template to YAML. Just like that our JSON is perfectly formatted YAML. Choosing the JSON button will convert the template back to JSON.

Caution: Converting a commented YAML template to JSON will remove all comments. Comments will not re-appear if the template is toggled back to YAML.

6. Save the template in YAML format by once again choosing the File icon and choosing Save from the menu.

Conclusion

In this blog post, we discussed some reasons to convert CloudFormation templates from JSON to YAML format and to code in YAML. We also did a side-by-side comparison of the readability of JSON and YAML using a sample template. Finally, we walked through how to convert existing JSON CloudFormation templates to YAML using CloudFormation Designer. There’s no better time than the present to dive in and get started with CloudFormation YAML. Happy coding!

About the Author

Aaron Fagan is a Senior Cloud Infrastructure Architect on the Boston AWS Professional Services team where he works with Enterprises to accelerate and optimize their adoption of the AWS public cloud. When not coding CloudFormation in YAML, he enjoys weightlifting and cooking.

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Convert JSON to YAML - Online JSON Tools

Free online JSON to YAML converter. Just load your JSON and it will automatically get converted to YAML. There are no ads, popups or nonsense, just an awesome JSON to YAML converter.

Coming soon These json tools are on the way

Display JSON Statistics

Display detailed information about a JSON data structure.

Flatten JSON

Extract all values or keys from a JSON object as a flat list.

Extract JSON Keys

Extract all keys from all key-value JSON pairs.

Extract JSON Values

Extract all values from all key-value JSON pairs.

Find JSON Keys/Values

Find keys and/or values that interest you in a JSON file.

Obfuscate JSON

Obfuscate a JSON data structure.

Convert JSON to a HTML

Create a HTML table from keys and values of a JSON object.

Convert JSON to Properties

Convert a JSON file to properties file.

Convert Properties to JSON

Convert properties data to JSON data.

Convert JSON to TOML

Convert a JSON config to a TOML config.

Convert TOML to JSON

Convert a TOML file to a JSON file.

Convert JSON to Bencode

Convert a JSON data structure to Bencode encoding.

Convert Bencode to JSON

Convert Bencode data to JSON data.

Convert JSON to JSONL

Convert a JSON file to a JSONL file.

Convert JSONL to JSON

Convert a JSONL file to a JSON file.

Convert JSON to BSON

Convert a JSON data structure to binary BSON data.

Convert BSON to JSON

Convert binary JSON data structure (BSON) to JSON.

Convert JSON to UBJSON

Convert a JSON file to a universal binary JSON (UBJSON).

Convert UBJSON to JSON

Convert universal binary JSON (UBJSON) to regular JSON.

Convert JSON to Message Pack

Serialize JSON data to binary MessagePack format.

Convert Message Pack to JSON

Unserialize binary MessagePack to JSON struct.

Convert JSON to a LaTeX Table

Generate a LaTeX table from a JSON object.

Convert JSON to INI

Convert a JSON data file to an INI configuration file.

Convert INI to JSON

Convert an INI configuration file to JSON data file.

Truncate JSON

Loop over JSON structure and truncate all values or keys.

Find JSON Depth

Find the nesting depth of a JSON data structure.

Convert JSON to a Data URI

Convert a JSON data structure to a data URL.

Convert JSON to a PHP Array

Create a PHP data structure from a JSON data structure.

Convert a PHP array to JSON

Create a JSON data structure from a PHP data structure.

Compare Two JSON Files

Diff JSON files and show differences visually.

Sort JSON Object Keys

Lexicographically sort the order of JSON object keys.

Swap JSON Keys with Values

Exchange keys with values in a JSON file.

Create a Random JSON Array

Create a JSON array with random values.

Create a Random JSON Object

Create a JSON object with random keys and values.

Randomize a JSON Array

Randomly change the positions of array elements.

Randomize a JSON Object

Randomly change the order of key, value pairs.

Tokenize JSON

Tokenize a JSON data structure.

Run jq

Execute a jq query on a JSON data structure.

Filter JSON

Filter keys and values that match a pattern.

Damage JSON

Introduce errors in a JSON data structure.

Visualize a JSON Structure

Create an abstract visualization of JSON's complexity.

codebeautify.org

What can you do with JSON to YAML? It helps to convert your JSON data to YAML format. This tool allows loading the JSON URL, which loads JSON and converts to YAML. Click on the URL button, Enter URL and Submit. Users can also Convert JSON File to YAML by uploading the file. When you are done with JSON to YAML converting. You can download as a file or create a link …

JSON to YAML Converter Online is very easy to use utility to transform JSON to YAML data. Copy, Paste and Convert to YAML.

What can you do with JSON to YAML?

  • It helps to convert your JSON data to YAML format.
  • This tool allows loading the JSON URL, which loads JSON and converts to YAML. Click on the URL button, Enter URL and Submit.
  • Users can also Convert JSON File to YAML by uploading the file.
  • When you are done with JSON to YAML converting. You can download as a file or create a link and share.
  • JSON to YAML Transformer works well on Windows, MAC, Linux, Chrome, Firefox, Edge, and Safari.
Know more about JSON.

Example of JSON

JSON data Try it.

{
  "InsuranceCompanies": {
    "InsuranceCompany": [
      {
        "No": "1",
        "Name": "Berkshire Hathaway ( BRK.A)",
        "Market Capitalization": "7.04 billion"
      },
      {
        "No": "2",
        "Name": "LFC",
        "Market Capitalization": "0  billion"
      }
    ]
  }
}   

For Advanced Users

External URL

Load External URL in Browser URL like this https://codebeautify.org/json-to-yaml?url=external-url

https://codebeautify.org/json-to-yaml?url=https://gist.githubusercontent.com/cbmgit/852c2702d4342e7811c95f8ffc2f017f/raw/InsuranceCompanies.json
Data as Parameter

Load Data in Browser URL input like this https://codebeautify.org/json-to-yaml?input=inputdata

https://codebeautify.org/json-to-yaml?input={"InsuranceCompanies":{"InsuranceCompany":[{"No":"1","Name":"BerkshireHathaway (BRK.A)","MarketCapitalization":"7.04billion"}]}}
stackoverflow.com

8. This question does not show any research effort; it is unclear or not useful. Bookmark this question. Show activity on this post. I can't figure out how do I convert the below section of my yaml cloudformation template to a json template. Can …

onlineyamltools.com

Quickly convert JavaScript Object Notation to Yet Another Markup Language. Enter JSON in the input box on the left and you'll immediately get YAML in …

docs.aws.amazon.com

Most of the AWS Command Line Interface (AWS CLI) commands support the ability to accept all of the parameter input from a file using the --cli-input-json and --cli-input-yaml parameter s.. Those same commands helpfully provide the --generate-cli-skeleton parameter to generate a file in either JSON or YAML format with all of the parameters that you can edit and fill in.

Most of the AWS Command Line Interface (AWS CLI) commands support the ability to accept all of the parameter input from a file using the --cli-input-json and --cli-input-yaml parameters.

Those same commands helpfully provide the --generate-cli-skeleton parameter to generate a file in either JSON or YAML format with all of the parameters that you can edit and fill in. Then you can run the command with the relevant --cli-input-json or --cli-input-yaml parameter and point to the filled-in file.

Several AWS CLI commands don't map directly to individual AWS API operations, such as the aws s3 commands. Such commands don't support either the --generate-cli-skeleton or --cli-input-json and --cli-input-yaml parameters described in this topic. If you don't know whether a specific command supports these parameters, run the following command, replacing the service and command names with the ones you're interested in.

$ aws service command help

The output includes a Synopsis section that shows the parameters that the specified command supports.

$ aws iam list-users help
...
SYNOPSIS list-users ... [--cli-input-json | --cli-input-yaml]
          ...
          [--generate-cli-skeleton ]
...

The --generate-cli-skeleton parameter causes the command not to run, but instead to generate and display a parameter template that you can customize and use as input on a later command. The generated template includes all of the parameters that the command supports.

The --generate-cli-skeleton parameter accepts one of the following values:

  • input – The generated template includes all input parameters formatted as JSON. This is the default value.

  • yaml-input – The generated template includes all input parameters formatted as YAML.

  • output – The generated template includes all output parameters formatted as JSON. You can't currently request the output parameters as YAML.

Because the AWS CLI is essentially a "wrapper" around the service's API, the skeleton file expects you to reference all parameters by their underlying API parameter names. This is likely different from the AWS CLI parameter name. For example, an AWS CLI parameter named user-name might map to the AWS service's API parameter named UserName (notice the altered capitalization and missing dash). We recommend that you use the --generate-cli-skeleton option to generate the template with the "correct" parameter names to avoid errors. You can also reference the API Reference Guide for the service to see the expected parameter names. You can delete any parameters from the template that are not required and for which you don't want to supply a value.

For example, if you run the following command, it generates the parameter template for the Amazon Elastic Compute Cloud (Amazon EC2) command run-instances.

JSON

The following example shows how to generate a template formatted in JSON by using the default value (input) for the --generate-cli-skeleton parameter.

$ aws ec2 run-instances --generate-cli-skeleton
{ "DryRun": true, "ImageId": "", "MinCount": 0, "MaxCount": 0, "KeyName": "", "SecurityGroups": [ "" ], "SecurityGroupIds": [ "" ], "UserData": "", "InstanceType": "", "Placement": { "AvailabilityZone": "", "GroupName": "", "Tenancy": "" }, "KernelId": "", "RamdiskId": "", "BlockDeviceMappings": [ { "VirtualName": "", "DeviceName": "", "Ebs": { "SnapshotId": "", "VolumeSize": 0, "DeleteOnTermination": true, "VolumeType": "", "Iops": 0, "Encrypted": true }, "NoDevice": "" } ], "Monitoring": { "Enabled": true }, "SubnetId": "", "DisableApiTermination": true, "InstanceInitiatedShutdownBehavior": "", "PrivateIpAddress": "", "ClientToken": "", "AdditionalInfo": "", "NetworkInterfaces": [ { "NetworkInterfaceId": "", "DeviceIndex": 0, "SubnetId": "", "Description": "", "PrivateIpAddress": "", "Groups": [ "" ], "DeleteOnTermination": true, "PrivateIpAddresses": [ { "PrivateIpAddress": "", "Primary": true } ], "SecondaryPrivateIpAddressCount": 0, "AssociatePublicIpAddress": true } ], "IamInstanceProfile": {
        "Arn": "",
        "Name": ""
    },
    "EbsOptimized": true
}
YAML

The following example shows how to generate a template formatted in YAML by using the value yaml-input for the --generate-cli-skeleton parameter.

$ aws ec2 run-instances --generate-cli-skeleton yaml-input
BlockDeviceMappings:  # The block device mapping entries.
- DeviceName: ''  # The device name (for example, /dev/sdh or xvdh).
  VirtualName: '' # The virtual device name (ephemeralN).
  Ebs: # Parameters used to automatically set up Amazon EBS volumes when the instance is launched.
    DeleteOnTermination: true  # Indicates whether the EBS volume is deleted on instance termination.
    Iops: 0 # The number of I/O operations per second (IOPS) that the volume supports.
    SnapshotId: '' # The ID of the snapshot.
    VolumeSize: 0 # The size of the volume, in GiB.
    VolumeType: st1 # The volume type. Valid values are: standard, io1, gp2, sc1, st1.
    Encrypted: true # Indicates whether the encryption state of an EBS volume is changed while being restored from a backing snapshot.
    KmsKeyId: '' # Identifier (key ID, key alias, ID ARN, or alias ARN) for a customer managed CMK under which the EBS volume is encrypted.
  NoDevice: '' # Suppresses the specified device included in the block device mapping of the AMI.
ImageId: '' # The ID of the AMI.
InstanceType: c4.4xlarge # The instance type. Valid values are: t1.micro, t2.nano, t2.micro, t2.small, t2.medium, t2.large, t2.xlarge, t2.2xlarge, t3.nano, t3.micro, t3.small, t3.medium, t3.large, t3.xlarge, t3.2xlarge, t3a.nano, t3a.micro, t3a.small, t3a.medium, t3a.large, t3a.xlarge, t3a.2xlarge, m1.small, m1.medium, m1.large, m1.xlarge, m3.medium, m3.large, m3.xlarge, m3.2xlarge, m4.large, m4.xlarge, m4.2xlarge, m4.4xlarge, m4.10xlarge, m4.16xlarge, m2.xlarge, m2.2xlarge, m2.4xlarge, cr1.8xlarge, r3.large, r3.xlarge, r3.2xlarge, r3.4xlarge, r3.8xlarge, r4.large, r4.xlarge, r4.2xlarge, r4.4xlarge, r4.8xlarge, r4.16xlarge, r5.large, r5.xlarge, r5.2xlarge, r5.4xlarge, r5.8xlarge, r5.12xlarge, r5.16xlarge, r5.24xlarge, r5.metal, r5a.large, r5a.xlarge, r5a.2xlarge, r5a.4xlarge, r5a.8xlarge, r5a.12xlarge, r5a.16xlarge, r5a.24xlarge, r5d.large, r5d.xlarge, r5d.2xlarge, r5d.4xlarge, r5d.8xlarge, r5d.12xlarge, r5d.16xlarge, r5d.24xlarge, r5d.metal, r5ad.large, r5ad.xlarge, r5ad.2xlarge, r5ad.4xlarge, r5ad.8xlarge, r5ad.12xlarge, r5ad.16xlarge, r5ad.24xlarge, x1.16xlarge, x1.32xlarge, x1e.xlarge, x1e.2xlarge, x1e.4xlarge, x1e.8xlarge, x1e.16xlarge, x1e.32xlarge, i2.xlarge, i2.2xlarge, i2.4xlarge, i2.8xlarge, i3.large, i3.xlarge, i3.2xlarge, i3.4xlarge, i3.8xlarge, i3.16xlarge, i3.metal, i3en.large, i3en.xlarge, i3en.2xlarge, i3en.3xlarge, i3en.6xlarge, i3en.12xlarge, i3en.24xlarge, i3en.metal, hi1.4xlarge, hs1.8xlarge, c1.medium, c1.xlarge, c3.large, c3.xlarge, c3.2xlarge, c3.4xlarge, c3.8xlarge, c4.large, c4.xlarge, c4.2xlarge, c4.4xlarge, c4.8xlarge, c5.large, c5.xlarge, c5.2xlarge, c5.4xlarge, c5.9xlarge, c5.12xlarge, c5.18xlarge, c5.24xlarge, c5.metal, c5d.large, c5d.xlarge, c5d.2xlarge, c5d.4xlarge, c5d.9xlarge, c5d.18xlarge, c5n.large, c5n.xlarge, c5n.2xlarge, c5n.4xlarge, c5n.9xlarge, c5n.18xlarge, cc1.4xlarge, cc2.8xlarge, g2.2xlarge, g2.8xlarge, g3.4xlarge, g3.8xlarge, g3.16xlarge, g3s.xlarge, g4dn.xlarge, g4dn.2xlarge, g4dn.4xlarge, g4dn.8xlarge, g4dn.12xlarge, g4dn.16xlarge, cg1.4xlarge, p2.xlarge, p2.8xlarge, p2.16xlarge, p3.2xlarge, p3.8xlarge, p3.16xlarge, p3dn.24xlarge, d2.xlarge, d2.2xlarge, d2.4xlarge, d2.8xlarge, f1.2xlarge, f1.4xlarge, f1.16xlarge, m5.large, m5.xlarge, m5.2xlarge, m5.4xlarge, m5.8xlarge, m5.12xlarge, m5.16xlarge, m5.24xlarge, m5.metal, m5a.large, m5a.xlarge, m5a.2xlarge, m5a.4xlarge, m5a.8xlarge, m5a.12xlarge, m5a.16xlarge, m5a.24xlarge, m5d.large, m5d.xlarge, m5d.2xlarge, m5d.4xlarge, m5d.8xlarge, m5d.12xlarge, m5d.16xlarge, m5d.24xlarge, m5d.metal, m5ad.large, m5ad.xlarge, m5ad.2xlarge, m5ad.4xlarge, m5ad.8xlarge, m5ad.12xlarge, m5ad.16xlarge, m5ad.24xlarge, h1.2xlarge, h1.4xlarge, h1.8xlarge, h1.16xlarge, z1d.large, z1d.xlarge, z1d.2xlarge, z1d.3xlarge, z1d.6xlarge, z1d.12xlarge, z1d.metal, u-6tb1.metal, u-9tb1.metal, u-12tb1.metal, u-18tb1.metal, u-24tb1.metal, a1.medium, a1.large, a1.xlarge, a1.2xlarge, a1.4xlarge, a1.metal, m5dn.large, m5dn.xlarge, m5dn.2xlarge, m5dn.4xlarge, m5dn.8xlarge, m5dn.12xlarge, m5dn.16xlarge, m5dn.24xlarge, m5n.large, m5n.xlarge, m5n.2xlarge, m5n.4xlarge, m5n.8xlarge, m5n.12xlarge, m5n.16xlarge, m5n.24xlarge, r5dn.large, r5dn.xlarge, r5dn.2xlarge, r5dn.4xlarge, r5dn.8xlarge, r5dn.12xlarge, r5dn.16xlarge, r5dn.24xlarge, r5n.large, r5n.xlarge, r5n.2xlarge, r5n.4xlarge, r5n.8xlarge, r5n.12xlarge, r5n.16xlarge, r5n.24xlarge.
Ipv6AddressCount: 0 # [EC2-VPC] The number of IPv6 addresses to associate with the primary network interface.
Ipv6Addresses: # [EC2-VPC] The IPv6 addresses from the range of the subnet to associate with the primary network interface.
- Ipv6Address: ''  # The IPv6 address.
KernelId: '' # The ID of the kernel.
KeyName: '' # The name of the key pair.
MaxCount: 0 # [REQUIRED] The maximum number of instances to launch.
MinCount: 0 # [REQUIRED] The minimum number of instances to launch.
Monitoring: # Specifies whether detailed monitoring is enabled for the instance.
  Enabled: true  # [REQUIRED] Indicates whether detailed monitoring is enabled.
Placement: # The placement for the instance.
  AvailabilityZone: ''  # The Availability Zone of the instance.
  Affinity: '' # The affinity setting for the instance on the Dedicated Host.
  GroupName: '' # The name of the placement group the instance is in.
  PartitionNumber: 0 # The number of the partition the instance is in.
  HostId: '' # The ID of the Dedicated Host on which the instance resides.
  Tenancy: dedicated # The tenancy of the instance (if the instance is running in a VPC). Valid values are: default, dedicated, host.
  SpreadDomain: '' # Reserved for future use.
RamdiskId: '' # The ID of the RAM disk to select.
SecurityGroupIds: # The IDs of the security groups.
- ''
SecurityGroups: # [EC2-Classic, default VPC] The names of the security groups.
- ''
SubnetId: '' # [EC2-VPC] The ID of the subnet to launch the instance into.
UserData: '' # The user data to make available to the instance.
AdditionalInfo: '' # Reserved.
ClientToken: '' # Unique, case-sensitive identifier you provide to ensure the idempotency of the request.
DisableApiTermination: true # If you set this parameter to true, you can't terminate the instance using the Amazon EC2 console, CLI, or API; otherwise, you can.
DryRun: true # Checks whether you have the required permissions for the action, without actually making the request, and provides an error response.
EbsOptimized: true # Indicates whether the instance is optimized for Amazon EBS I/O.
IamInstanceProfile: # The IAM instance profile.
  Arn: ''  # The Amazon Resource Name (ARN) of the instance profile.
  Name: '' # The name of the instance profile.
InstanceInitiatedShutdownBehavior: stop # Indicates whether an instance stops or terminates when you initiate shutdown from the instance (using the operating system command for system shutdown). Valid values are: stop, terminate.
NetworkInterfaces: # The network interfaces to associate with the instance.
- AssociatePublicIpAddress: true  # Indicates whether to assign a public IPv4 address to an instance you launch in a VPC.
  DeleteOnTermination: true # If set to true, the interface is deleted when the instance is terminated.
  Description: '' # The description of the network interface.
  DeviceIndex: 0 # The position of the network interface in the attachment order.
  Groups: # The IDs of the security groups for the network interface.
  - ''
  Ipv6AddressCount: 0 # A number of IPv6 addresses to assign to the network interface.
  Ipv6Addresses: # One or more IPv6 addresses to assign to the network interface.
  - Ipv6Address: ''  # The IPv6 address.
  NetworkInterfaceId: '' # The ID of the network interface.
  PrivateIpAddress: '' # The private IPv4 address of the network interface.
  PrivateIpAddresses: # One or more private IPv4 addresses to assign to the network interface.
  - Primary: true  # Indicates whether the private IPv4 address is the primary private IPv4 address.
    PrivateIpAddress: '' # The private IPv4 addresses.
  SecondaryPrivateIpAddressCount: 0 # The number of secondary private IPv4 addresses.
  SubnetId: '' # The ID of the subnet associated with the network interface.
  InterfaceType: '' # The type of network interface.
PrivateIpAddress: '' # [EC2-VPC] The primary IPv4 address.
ElasticGpuSpecification: # An elastic GPU to associate with the instance.
- Type: ''  # [REQUIRED] The type of Elastic Graphics accelerator.
ElasticInferenceAccelerators: # An elastic inference accelerator to associate with the instance.
- Type: ''  # [REQUIRED]  The type of elastic inference accelerator.
TagSpecifications: # The tags to apply to the resources during launch.
- ResourceType: network-interface  # The type of resource to tag. Valid values are: client-vpn-endpoint, customer-gateway, dedicated-host, dhcp-options, elastic-ip, fleet, fpga-image, host-reservation, image, instance, internet-gateway, launch-template, natgateway, network-acl, network-interface, reserved-instances, route-table, security-group, snapshot, spot-instances-request, subnet, traffic-mirror-filter, traffic-mirror-session, traffic-mirror-target, transit-gateway, transit-gateway-attachment, transit-gateway-route-table, volume, vpc, vpc-peering-connection, vpn-connection, vpn-gateway.
  Tags: # The tags to apply to the resource.
  - Key: ''  # The key of the tag.
    Value: '' # The value of the tag.
LaunchTemplate: # The launch template to use to launch the instances.
  LaunchTemplateId: ''  # The ID of the launch template.
  LaunchTemplateName: '' # The name of the launch template.
  Version: '' # The version number of the launch template.
InstanceMarketOptions: # The market (purchasing) option for the instances.
  MarketType: spot  # The market type. Valid values are: spot.
  SpotOptions: # The options for Spot Instances.
    MaxPrice: ''  # The maximum hourly price you're willing to pay for the Spot Instances.
    SpotInstanceType: one-time # The Spot Instance request type. Valid values are: one-time, persistent.
    BlockDurationMinutes: 0 # The required duration for the Spot Instances (also known as Spot blocks), in minutes.
    ValidUntil: 1970-01-01 00:00:00 # The end date of the request.
    InstanceInterruptionBehavior: terminate # The behavior when a Spot Instance is interrupted. Valid values are: hibernate, stop, terminate.
CreditSpecification: # The credit option for CPU usage of the T2 or T3 instance.
  CpuCredits: ''  # [REQUIRED] The credit option for CPU usage of a T2 or T3 instance.
CpuOptions: # The CPU options for the instance.
  CoreCount: 0  # The number of CPU cores for the instance.
  ThreadsPerCore: 0 # The number of threads per CPU core.
CapacityReservationSpecification: # Information about the Capacity Reservation targeting option.
  CapacityReservationPreference: none  # Indicates the instance's Capacity Reservation preferences. Valid values are: open, none.
  CapacityReservationTarget: # Information about the target Capacity Reservation.
    CapacityReservationId: ''  # The ID of the Capacity Reservation.
HibernationOptions: # Indicates whether an instance is enabled for hibernation.
  Configured: true  # If you set this parameter to true, your instance is enabled for hibernation.
LicenseSpecifications: # The license configurations.
- LicenseConfigurationArn: ''  # The Amazon Resource Name (ARN) of the license configuration.

To generate and use a parameter skeleton file

  1. Run the command with the --generate-cli-skeleton parameter to produce either JSON or YAML and direct the output to a file to save it.

    JSON
    $ aws ec2 run-instances --generate-cli-skeleton input > ec2runinst.json
    YAML
    $ aws ec2 run-instances --generate-cli-skeleton yaml-input > ec2runinst.yaml
  2. Open the parameter skeleton file in your text editor and remove any of the parameters that you don't need. For example, you might strip the template down to the following. Be sure that the file is still valid JSON or YAML after you remove the elements you don't need.

    JSON
    { "DryRun": true, "ImageId": "", "KeyName": "", "SecurityGroups": [ "" ], "InstanceType": "", "Monitoring": {
            "Enabled": true
        }
    }
    YAML
    DryRun: true
    ImageId: ''
    KeyName: ''
    SecurityGroups:
    - ''
    InstanceType:
    Monitoring: 
      Enabled: true

    In this example, we leave the DryRun parameter set to true to use the Amazon EC2 dry run feature. This feature lets you safely test the command without actually creating or modifying any resources.

  3. Fill in the remaining values with values appropriate for your scenario. In this example, we provide the instance type, key name, security group, and identifier of the Amazon Machine Image (AMI) to use. This example assumes the default AWS Region. The AMI ami-dfc39aef is a 64-bit Amazon Linux image hosted in the us-west-2 Region. If you use a different Region, you must find the correct AMI ID to use.

    JSON
    { "DryRun": true, "ImageId": "ami-dfc39aef", "KeyName": "mykey", "SecurityGroups": [ "my-sg" ], "InstanceType": "t2.micro", "Monitoring": {
            "Enabled": true
        }
    }
    YAML
    DryRun: true
    ImageId: 'ami-dfc39aef'
    KeyName: 'mykey'
    SecurityGroups:
    - 'my-sg'
    InstanceType: 't2.micro'
    Monitoring: 
      Enabled: true
  4. Run the command with the completed parameters by passing the completed template file to either the --cli-input-json or --cli-input-yaml parameter by using the file:// prefix. The AWS CLI interprets the path to be relative to your current working directory, so in the following example that displays only the file name with no path, it looks for the file directly in the current working directory.

    JSON
    $ aws ec2 run-instances --cli-input-json file://ec2runinst.json
    A client error (DryRunOperation) occurred when calling the RunInstances operation: Request would have succeeded, but DryRun flag is set.
    YAML
    $ aws ec2 run-instances --cli-input-yaml file://ec2runinst.yaml
    A client error (DryRunOperation) occurred when calling the RunInstances operation: Request would have succeeded, but DryRun flag is set.

    The dry run error indicates that the JSON or YAML is formed correctly and that the parameter values are valid. If other issues are reported in the output, fix them and repeat the previous step until the "Request would have succeeded" message is displayed.

  5. Now you can set the DryRun parameter to false to disable dry run.

    JSON
    { "DryRun": false, "ImageId": "ami-dfc39aef", "KeyName": "mykey", "SecurityGroups": [ "my-sg" ], "InstanceType": "t2.micro", "Monitoring": {
            "Enabled": true
        }
    }
    YAML
    DryRun: false
    ImageId: 'ami-dfc39aef'
    KeyName: 'mykey'
    SecurityGroups:
    - 'my-sg'
    InstanceType: 't2.micro'
    Monitoring: 
      Enabled: true
  6. Run the command, and run-instances actually launches an Amazon EC2 instance and displays the details generated by the successful launch. The format of the output is controlled by the --output parameter, separately from the format of your input parameter template.

    JSON
    $ aws ec2 run-instances --cli-input-json file://ec2runinst.json --output json
    {
        "OwnerId": "123456789012",
        "ReservationId": "r-d94a2b1",
        "Groups": [],
        "Instances": [
    ...
    YAML
    $ aws ec2 run-instances --cli-input-yaml file://ec2runinst.yaml --output yaml
    OwnerId: '123456789012'
    ReservationId: 'r-d94a2b1',
    Groups":
    - ''
    Instances:
    ...
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Json to Yaml To read in json, just pass in a json file instead of yaml, it will just work - as json is a subset of yaml. However, you will probably want to use the Style Operator or --prettyPrint/-P flag to make look more like an idiomatic yaml document.

To convert output to json, use the --output-format=json (or -o=j) flag. You can change the json output format by using the indent flag.

Given a sample.yaml file of:

yq eval -o=j sample.yaml

yq eval -o=j -I=0 sample.yaml

Each matching yaml node will be converted to json and printed out as a separate json doc. You may want to set the indent flags to 0 if you want a json doc per line.

Given a sample.yaml file of:

yq eval -o=j '.b*' sample.yaml

To read in json, just pass in a json file instead of yaml, it will just work - as json is a subset of yaml. However, you will probably want to use the Style Operator or --prettyPrint/-P flag to make look more like an idiomatic yaml document. This can be done by resetting the style of all elements.

{"a":"Easy! as one two three","b":{"c":2,"d":[3,4]}}

a: Easy! as one two three

Convert JSON to YAML Online

About JSON data conversion to YAML data. The JSON to YAML Converter was created for online transform JSON(JavaScript Object Notation) data into YAML Ain't Markup Language(YAML) data. How it Works? Just paste or upload your JSON data to the textarea above and click to the button "Convert" and you will instantly get YAML data.

The JSON to YAML Converter was created for online transform JSON(JavaScript Object Notation) data into YAML Ain't Markup Language(YAML) data.

How it Works?

Just paste or upload your JSON data to the textarea above and click to the button "Convert" and you will instantly get YAML data.

Example of JSON conversion to YAML

Before:
{
	"root":
	{
		"rows": [
		{
			"LatD": "41",
			"LatM": "5",
			"LatS": "59",
			"NS": "N",
			"LonD": "80",
			"LonM": "39",
			"LonS": "0",
			"EW": "W",
			"City": "Youngstown",
			"State": "OH"
		},
		{
			"LatD": "42",
			"LatM": "52",
			"LatS": "48",
			"NS": "N",
			"LonD": "97",
			"LonM": "23",
			"LonS": "23",
			"EW": "W",
			"City": "Yankton",
			"State": "SD"
		},
		{
			"LatD": "46",
			"LatM": "35",
			"LatS": "59",
			"NS": "N",
			"LonD": "120",
			"LonM": "30",
			"LonS": "36",
			"EW": "W",
			"City": "Yakima",
			"State": "WA"
		},
		{
			"LatD": "42",
			"LatM": "16",
			"LatS": "12",
			"NS": "N",
			"LonD": "71",
			"LonM": "48",
			"LonS": "0",
			"EW": "W",
			"City": "Worcester",
			"State": "MA"
		},
		{
			"LatD": "43",
			"LatM": "37",
			"LatS": "48",
			"NS": "N",
			"LonD": "89",
			"LonM": "46",
			"LonS": "11",
			"EW": "W",
			"City": "Wisconsin Dells",
			"State": "WI"
		}]
	}
}
After:
root:
 rows:
  -
   LatD: 41
   LatM: 5
   LatS: 59
   NS: N
   LonD: 80
   LonM: 39
   LonS: 0
   EW: W
   City: Youngstown
   State: OH
  -
   LatD: 42
   LatM: 52
   LatS: 48
   NS: N
   LonD: 97
   LonM: 23
   LonS: 23
   EW: W
   City: Yankton
   State: SD
  -
   LatD: 46
   LatM: 35
   LatS: 59
   NS: N
   LonD: 120
   LonM: 30
   LonS: 36
   EW: W
   City: Yakima
   State: WA
  -
   LatD: 42
   LatM: 16
   LatS: 12
   NS: N
   LonD: 71
   LonM: 48
   LonS: 0
   EW: W
   City: Worcester
   State: MA
  -
   LatD: 43
   LatM: 37
   LatS: 48
   NS: N
   LonD: 89
   LonM: 46
   LonS: 11
   EW: W
   City: "Wisconsin Dells"
   State: WI
After the conversion, you can apply the YAML data to your project or use it for some other purpose.
convertjson.com

Convert YAML To JSON. Use this online tool to convert YAML into JSON. Enter your data below and Press the Convert button. The output will display below the Convert button. See also JSON to YAML. Option 1 - Choose a YAML file Encoding Option 2 - Enter an URL Option 3 - …

python-json2yaml

python-json2yaml 0.1.1. pip install python-json2yaml. Copy PIP instructions. Latest version. Released: Apr 7, 2019. A simple command that turn json data to yaml format and vice versa. It can be used in Linux, MacOS and Window. Project description.

  • Project description
  • Project details
  • Release history
  • Download files
https://travis-ci.org/appstore-zencore/python-json2yaml.svg?branch=master

A simple command that turn json data to yaml format and vice versa. It can be used in Linux, MacOS and Window.

pip install python-json2yaml

Commands

E:\code\zencore-json2yaml\test>json2yaml --help
Usage: json2yaml [OPTIONS] [SRC] [DST]

Options:
--help  Show this message and exit.

E:\code\zencore-json2yaml\test>yaml2json --help
Usage: yaml2json [OPTIONS] [SRC] [DST]

Options:
--help  Show this message and exit.
  1. Read json text from stdin and print yaml text to stdout
cat a.json | json2yaml
  1. Read json text from stdin and print yaml text to a file
cat a.json | json2yaml - a.txt
  1. Read json text from a file and print yaml text to another file
json2yaml a.json a.txt

Project details


Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for python-json2yaml, version 0.1.1
Filename, size File type Python version Upload date Hashes
Filename, size python-json2yaml-0.1.1.tar.gz (2.1 kB) File type Source Python version None Upload date Hashes View
textcompare.org

How to convert JSON to YAML? Enter JSON in input textarea or choose and upload .json file. Choose options like indentation, size etc. Click on Show Output button to get YAML output.

How to Convert YAML to JSON [Python, PowerShell, Go]

20-04-2021 · Using PowerShell to Convert YAML to JSON. PowerShell is capable of modifying text files and converting objects to several formats in including JSON. Because PowerShell is extensible, you can use PowerShell to convert YAML to JSON format with the right module. Adding YAML Support to PowerShell

20-04-2021

Many modern tools, particularly in configuration management and Infrastructure as Code (IaC) spaces, use JSON or YAML files to store configuration data. If you need to convert data from YAML to JSON format, then this article is for you.

In this article, you will learn several ways to convert data YAML to JSON format, including scripting in Python, PowerShell, and Go.

Prerequisites

If you’d like to follow along with examples in this tutorial, be sure you have

  • A code editor. This article will use Visual Studio Code version 1.55.1. Feel free to use any code editor you want.
  • To get started with converting YAML to JSON, you need a sample YAML content. Copy the content below into a new file called operating-systems.yml. Save the YAML file in your working directory.
operating-systems.yml
Windows 10: 100
Windows Server 2019: 50
Windows Server 2022: 1
MacOS: 3
CentOS: 75
Photon: 12

Using Python to Convert YAML to JSON

Python is an excellent language to use for automation. But did you know you can extend Python’s capabilities and use it to convert documents from YAML to JSON? And you only need to perform a few steps and start converting YAML to JSON in no time.

The example in this section requires you to have installed Python 3.9 and PIP (the latest version as of this writing is 21.0.1).

Adding YAML Support to Python

Python does not have out-of-the-box support for YAML. Meaning, Python cannot read or interpret YAML documents by default. To add YAML support to Python, you have first to install the PyYAML module.

To install the PyYAML module, you’ll need to run the pip command, which is the package installer for Python. To do so, follow these steps.

First, open your preferred command interpreter, such as the command prompt or PowerShell. The pip command should work in either one. This example uses PowerShell.

Next, run the command below in PowerShell. This command installs the PyYAML module.

pip install pyyaml

As you can see in the screenshot below, pip installed the latest version of PyYAML (5.4.1 as of this writing).

Installing the PyYAML module
Installing the PyYAML module

Writing the Conversion Script

Now that you’ve installed the required module (PyYAML), you’re ready to write your conversion script. To create the YAML to JSON Python script, follow these steps.

1. Open your code editor and create a new file called convert-os.py in your working directory. This file is your script.

2. Copy the code below and paste it into your blank convert-os.py file. This script will read the YAML content of operating-systems.yml, convert the content to JSON format, and write the JSON output to the python_operating-systems.json file.

## convert-os.py
## Import the modules to handle JSON & YAML
import yaml
import json ## Create a variable to hold the data to import
os_list = {} ## Read the YAML file
with open("c:\temp\operating-systems.yml") as infile:     # Marshall the YAML into the variable defined above os_list = yaml.load(infile, Loader=yaml.FullLoader)     # Print the List to the console. print(os_list) Open a file to write the JSON output. The 'w' makes the file writable with open("c:\temp\python_operating-systems.json", 'w') as outfile:     # Marshall the JSON, setting "indent" makes the file more readable json.dump(os_list, outfile, indent=4) print("JSON file written.")

3. Save the convert-os.py script.

Running the Conversion Script

After creating the conversion script, it’s time to put it to the test. To execute the YAML to JSON Python script, proceed as follows:

1. Open a terminal window. This article uses PowerShell, but the command prompt (CMD) would work just as well.

2. Copy the command below, paste it in PowerShell, and press Enter. This command runs the Python executable program to invoke the convert-os.py script you created in the previous section.

python c:\temp\convert-os.py

After running the command, you should see a similar output like the image below. As you can see, the command displayed the JSON output on the screen and saved the same output to the c:\temp\python_operating-systems.json file.

Running the YAML to JSON conversion script using Python
Running the YAML to JSON conversion script using Python

3. Lastly, open the JSON file called python_operating-systems.json that the convert-os.py Python script should have created. In this example, to open the file in notepad, run the command below in PowerShell.

notepad C:\temp\python_operating-systems.json
Viewing the python_operating-systems.json file in notepad
Viewing the python_operating-systems.json file in notepad

Using PowerShell to Convert YAML to JSON

PowerShell is capable of modifying text files and converting objects to several formats in including JSON. Because PowerShell is extensible, you can use PowerShell to convert YAML to JSON format with the right module.

Adding YAML Support to PowerShell

PowerShell has built-in support for handling JSON content, but not for YAML. Fortunately, there is a module that extends PowerShell to support YAML files. This module is called PowerShell-yaml, and the latest version as of this writing is 0.4.2. Follow these steps to install the module.

1. On your computer, open a PowerShell session.

2. Copy the command below, paste it in PowerShell, and press Enter. This command uses the Install-Module cmdlet to install the PowerShell-yaml module.

Install-Module PowerShell-yaml

3. After installing the module, two new cmdlets will become available in PowerShell as part of the PowerShell-yaml module. These new cmdlets are:

ConvertFrom-Yaml – the cmdlet to convert YAML data to a hash table.

ConvertTo-Yaml – the cmdlet to convert hash table objects to YAML data.

To confirm both cmdlets are available in PowerShell, run the command below in PowerShell.

Get-Command -Module PowerShell-yaml

As you can see below, the Get-Command cmdlet listed the cmdlets from the PowerShell-yaml module.

Getting the PowerShell-yaml cmdlets
Getting the PowerShell-yaml cmdlets

Writing the Conversion Script

To create the YAML to JSON conversion PowerShell script, follow these instructions.

1. Open your code editor and create a new file called convert-os.ps1 in your working directory.

2. Copy code below and paste in the blank convert-os.ps1 file. The code snippet below reads the operating-systems.yml file and converts it to JSON. Once in JSON, it then stores the JSON in the file PowerShell_operating-systems.json.

#convert-os.ps1
 #Read the YAML file using Get-Content and convert the data to a hashtable using ConvertFrom-Yaml. The $os_list variable stores the hashtable object.
 $os_list = (Get-Content -Path "C:\temp\operating-systems.yml" | ConvertFrom-Yaml)
 #Convert the hashtable object in the $os_list variable to JSON format using ConvertTo-Json. Once in JSON, save the save to C:\temp\PowerShell_operating-systems.json file using Set-Content.
 Set-Content -Path "C:\temp\PowerShell_operating-systems.json" -Value ($os_list | ConvertTo-Json)

3. Save the convert-os.ps1 file.

Running the Conversion Script

Now that you’ve created your conversion script, the next step is to run it to convert YAML to JSON. To execute the PowerShell conversion script, follow these steps.

  1. Open a PowerShell window if you don’t have one opened yet.

2. Copy the command below, paste it in PowerShell, and press Enter. This command invokes the convert-os.ps1 script you’ve created in the previous section.

c:\temp\convert-os.ps1

3. After running the script, open the JSON output file C:\temp\PowerShell_operating-systems.json that the convert-os.ps1 script created in the previous step. To do so, run the command below in PowerShell to open the PowerShell_operating-systems.json in notepad.

notepad C:\temp\PowerShell_operating-systems.json
Viewing the content of the PowerShell_operating-systems.json file
Viewing the content of the PowerShell_operating-systems.json file

Using Go to Convert YAML to JSON

Python and PowerShell are both high-level languages. Being high-level makes writing scripts easier but also takes away a little bit of control. On the other hand, Go is a low-level language, which makes importing YAML data more complex.

The example in this section will be using Go. The latest version as of this writing is go1.16.3. If you don’t have Go yet, refer to the download and install page to install it on your computer.

Adding YAML Support to Go

Like PowerShell and Python, JSON support is part of Go’s core libraries, but YAML is not. To add YAML support in Go, you need to install the YAML.v3 package first using the go get command. To install the YAML.v3 package:

First, on your computer, open the command shell you want to use, such as the command prompt or PowerShell. This example uses PowerShell.

Next, copy the command below and run it in PowerShell. This command will download and install the package name gopkg.in/yaml.v3.

go get gopkg.in/yaml.v3
Installing the yaml.v3 package in Go
Installing the yaml.v3 package in Go

Writing the Conversion Script

To create the YAML to JSON conversion Go script, follow these instructions.

1. Open your code editor and create a new file called convert-os.go in your working directory.

2. Copy the code below and paste in the blank convert-os.go file. The code imports the required packages, defines some memory structures, imports the YAML file, and converts to JSON before writing to a JSON file called c:\temp\go_operating-systems.json.

// This tells go which function to load. package main // Import packages: import ( // JSON module "encoding/json" // For writing output to the screen "fmt" // For reading and wiritng files "io/ioutil" // YAML module "gopkg.in/yaml.v3" ) // Define two "Structs" these are data structures in memory, and match // The form of the YAML and JSON files. type operatingSystems struct { Windows10 int yaml:"Windows 10" WindowsServer2019 int yaml:"Windows Server 2019" WindowsServer2022 int yaml:"Windows Server 2022" MacOS int yaml:"MacOS" CentOS int yaml:"CentOS" Photon int yaml:"Photon" } type operatingSystemsjson struct { Windows10 int json:"Windows 10" WindowsServer2019 int json:"Windows Server 2019" WindowsServer2022 int json:"Windows Server 2022" MacOS int json:"MacOS" CentOS int json:"CentOS" Photon int json:"Photon" } func main() { // Let the user know the process has started fmt.Println("Parsing YAML file") // Define the path to the input file var fileName string = "c:\temp\operating-systems.yml" // Load the YAML from the file. Go requires error handling for this step. yamlFile, err := ioutil.ReadFile(fileName) if err != nil { fmt.Printf("Error reading YAML file: %s\n", err) return } // Extract the YAML into your Struct var oses operatingSystems yaml.Unmarshal(yamlFile, &oses) //Create the JSON Struct, using the data from the YAML Struct var osesjson = operatingSystemsjson{ Windows10: oses.Windows10, WindowsServer2019: oses.WindowsServer2019, WindowsServer2022: oses.WindowsServer2022, MacOS: oses.MacOS, CentOS: oses.CentOS, Photon: oses.Photon, } // Create a string to output in JSON format. jsonOutput, err := json.Marshal(osesjson) // Print the result to screen. Notice that the % v means that // the variable name gets printed with the data. This is why // there are no spaces in the output Kay names. fmt.Printf("Result: % v\n", osesjson) //write the JSON file
 err = ioutil.WriteFile("c:\temp\Go_operating-systems.json", jsonOutput, 0644)
 }

3. Save the convert-os.go file.

Running the Conversion Script

Running Go scripts uses the go run command followed by the script’s filename. To run the YAML to JSON conversion Go script, proceed as follows.

1. On your computer, open the command shell you want to use. On Windows, the go will work on either the command prompt or PowerShell. This example uses PowerShell to run go.

2. Once you’re in PowerShell, copy the command below and run it in PowerShell. This command will invoke the go run command to run the c:\temp\convert-os.go script.

go run c:\temp\convert-os.go
Running Convert-os Go script.
Running Convert-os Go script.

3. After running the script, open the output file C:\temp\Go_operating-systems.json that the convert-os.go script created in the previous step. This example opens the Go_operating-systems.json in notepad.

Viewing the Go_operating-systems.json in notepad
Viewing the Go_operating-systems.json in notepad

Conclusion

In this article, you’ve learned how to convert YAML data and files to JSON using scripts in Python, PowerShell, and Go. Now that you’ve learned different ways to convert YAML to JSON, which way do you think you will use more?

Convert To AWS SSM - Visual Studio Marketplace

Convert To AWS SSM. Convert Powershell and/or Shell scripts to AWS SSM documents. Features. This plugin is capable of generating both JSON and YAML AWS SSM Documents from PowerShell and/or Shell scripts. It is also capable of retrieving the script back from an SSM document. It does not support SSM documents with multiple steps. Usage

Convert Powershell and/or Shell scripts to AWS SSM documents.

Features

This plugin is capable of generating both JSON and YAML AWS SSM Documents from PowerShell and/or Shell scripts. It is also capable of retrieving the script back from an SSM document. It does not support SSM documents with multiple steps.

Usage

  1. Open a PowerShell or Shell script of your choice
  2. Open the Command Palette (F1 or CMD/CTRL Shift P or "View" > "Command Palette...")
  3. Search for "ConvertTo-SSM", and two options will appear
    • "ConvertTo-SSM: Create JSON document"
    • "ConvertTo-SSM: Create YAML document"
    • "ConvertTo-SSM: Get script from AWS SSM document"
  4. Click desired conversion option

Configurations

  • EnableAutoCopyToClipboard

    • When enabled, the SSM document output is automatically copied to the clipboard
  • EnableCopyRunCommandOnly

    • When enabled alongside EnableAutoCopyToClipboard, it copies the 'RunCommand' section of the SSM command only (supported only on conversions from a script to SSM document)

Instructions

PowerShell To JSON SSM Documnet

PowerShell to Json

Shell script To JSON SSM Documnet

Shell to Json

PowerShell to YAML SSM document

PowerShell to Json

Shell script to YAML SSM document

Shell to Json

Known Issues

N/A

Release Notes

CHANGELOG

onlineyamltools.com

Quickly convert Yet Another Markup Language to JavaScript Object Notation. Enter YAML in the input box on the left and you'll immediately get JSON in …

pypi.org

json2yaml 1.2.0. pip install json2yaml. Copy PIP instructions. Latest version. Released: Oct 19, 2021. Convert JSON to YAML or vice versa, while preserving the order of associative arrays. Project description. Project details. Release history.

convertjson.com

Use this tool to convert JSON into YAML format. New-JSONLines format supported. Enter your data below and Press the Convert button. The output will display below the Convert button. See also YAML to JSON

jlordiales.me

23-05-0000 · It will detect the input’s type and, in the case of YAML, convert to JSON before applying jq and then convert the result back to YAML. Note that since YAML is actually a superset of JSON this will only work for those YAML files that can be correctly converted to JSON. You can see the code here and the docker image here. Usage

23-05-0000

If you’ve ever had to parse JSON from your terminal you probably know about jq. It’s basically sed for JSON and it works wonderfully well. If you’ve had to parse YAML from your terminal however, the problem becomes a bit harder. You can either go for some super obscure 15 lines sed and awk combination that has the advantage of being pure bash, or go with a higher level language (ruby or python comes to mind) to actually do the parsing and outputting the result to stdout. In this post I’ll show jyparser, a simple tool (packaged as a nice docker image) that allows you to use a jq-like syntax to parse and also update JSON and YAML files from your terminal using exactly the same commands.

The problem

So imagine you have your app and different JSON files for the different environments your app will be deployed to, with each file containing things like the environment name, the build version currently deployed, etc. Maybe something like:

~ cat my_app.json { "app_name" : "awesome app", "build_version" : 1, "tags" : ["myTeam", "myCompany"]
}

Now as part of your deployment process you want to read the build_version variable from the JSON file, increase it by 1 and then update the original JSON with the new value.

This would not be super hard to do with plain jq:

~ version=$(cat my_app.json | jq '.build_version')
~ echo $version
1 ~ new_version=$((version 1))
~ echo $new_version
2 ~ cat my_app.json | jq --arg value $new_version '.build_version |= $value'
{ "app_name": "awesome app", "build_version": "2", "tags": [ "myTeam", "myCompany" ]
}

It’s not too hard but it’s not straightforward either, specially the update part. You have to know about jq update operator (|=) and how you can pass env variables using --arg.

Now imagine you decide to switch to YAML instead of JSON because either you started using a different tool that only accepts YAML or the same tool accepts both and you prefer it over JSON.

~ cat my_app.yml app_name: awesome app
build_version: 1
tags:
- myTeam
- myCompany

You still want to accomplish the same thing, bump the build_version of your YAML. But your previous deployment bash script with your fancy jq query obviously doesn’t work anymore. Now you need to figure out how you’re going to parse and update that YAML, which like I mentioned in the beginning is not trivial (or at least I didn’t find a nice and easy way to do it).

Wouldn’t it be nice if you could somehow say: cat my_app.{yml, json} | get .build_version to read the value you are interested in and cat my_app.{yml, json} | set .build_version to update it? That is, use exactly the same command regardless of where the input is coming from (JSON or YAML). Enter jyparser

jyparser

jyparser stands for JSON/YAML Parser (I know, not very original but I always sucked at names) and it was created specifically for the use case I described above. Getting a single value from a JSON or YAML, doing something with it (if needed) and then setting a new value for it on the original input. Of course reading/updating entire objects/arrays in JSON or entire hashes/lists in YAML is also supported.

At its hearth jyparser is a simple wrapper around jq and 2 python 1 liners to convert from JSON to YAML and vice versa. It will detect the input’s type and, in the case of YAML, convert to JSON before applying jq and then convert the result back to YAML. Note that since YAML is actually a superset of JSON this will only work for those YAML files that can be correctly converted to JSON.

You can see the code here and the docker image here.

Usage

Let’s look at some examples of how you would usually use the tool.

The image’s entry point accepts 2 operations: get and set. It can take its inputs from stdin or read from a file if this is passed as the first parameter.

Read

The get command takes an arbitrary jq filter. If the result is a simple value (number, string or boolean) then that value is returned. Otherwise, the resulting JSON or YAML is returned (depending on what the input was).

Given the following JSON file:

~ cat test.json {"menu": { "id": "file", "value": "File", "popup": { "menuitem": [ {"value": "New", "onclick": "CreateNewDoc()"}, {"value": "Open", "onclick": "OpenDoc()"}, {"value": "Close", "onclick": "CloseDoc()"} ] }
}}

If you wanted to get the value of the id property you could use:

~ cat test.json | docker run -i --rm jlordiales/jyparser get .menu.id "file"

The JSON is passed via stdin, which is useful if you get that from something like curl. If you have an actual file that you want to use as input then you can pass it directly as the first parameter to the script:

~ docker run -i --rm -v `pwd`:/jyparser:ro jlordiales/jyparser test.json get ".menu.id" "file"

The example above mounts the current dir with the file into /jyparser (which is the default WORKDIR for the docker image) and then uses that file as input.

Exactly the same command works for YAML as well. Given the equivalent YAML file:

~ cat test.yml
menu: id: file value: File popup: menuitem: - onclick: CreateNewDoc() value: New - onclick: OpenDoc() value: Open - onclick: CloseDoc()
      value: Close

We can get the id property with:

~ cat test.yml | docker run -i --rm jlordiales/jyparser get .menu.id "file"

If the result from running the jq filter is not a simple value, then the corresponding JSON or YAML is returned:

~ cat test.json | docker run -i --rm jlordiales/jyparser get ".menu.popup.menuitem[1]" { "value": "Open", "onclick": "OpenDoc()"
} ~ cat test.yml | docker run -i --rm jlordiales/jyparser get ".menu.popup.menuitem[1]" onclick: OpenDoc()
value: Open

The jq filter that is passed as parameter is sent as is to the tool, so you are not limited so simple filters. Anything that is valid for jq is valid for jyparser as well.

Similarly to the get operation, there’s a set one. This operation takes 2 parameters: a jq filter to select a specific element of the input and a new value to update that element to. The result is the original input with the value updated.

~ cat test.json | docker run -i --rm jlordiales/jyparser set ".menu.id" \"new_id\"
{ "menu": { "id": "new_id", "value": "File", "popup": { "menuitem": [ { "value": "New", "onclick": "CreateNewDoc()" }, { "value": "Open", "onclick": "OpenDoc()" }, { "value": "Close", "onclick": "CloseDoc()" } ] } }
}

Important: given the way bash scripts handle quotes on parameters passed to them, if the new value you want to set for the property is a string you need to explicitly escape the quotes as in the example. Otherwise, jq will complain that the value is not valid (rightfully so). This is not needed for numbers or booleans. So the following works as expected:

~ cat test.json | docker run -i --rm jlordiales/jyparser set ".menu.id" 15
{ "menu": { "id": 15, "value": "File", "popup": { "menuitem": [ { "value": "New", "onclick": "CreateNewDoc()" }, { "value": "Open", "onclick": "OpenDoc()" }, { "value": "Close", "onclick": "CloseDoc()" } ] } }
}

This way of updating the JSON is arguably a lot easier to read and use than the jq version we saw at the beginning. It’s just set and, best of all, the same works for YAML:

~ cat test.yml | docker run -i --rm jlordiales/jyparser set ".menu.id" \"new_id\" menu: id: new_id popup: menuitem: - onclick: CreateNewDoc() value: New - onclick: OpenDoc() value: Open - onclick: CloseDoc()
      value: Close
  value: File

As with the get operation, set can take the input both from stdin and a file if passed as first argument.

Conclusion

If you are doing regular parsing/updating of JSON and/or YAML and you don’t want to have hugely complex combinations of jq with sed and awk but instead have a simple interface to work with both types then give jyparser a try. It was created for a very specific use case but it might be able to adapt to yours as well.

jyparser was heavily inspired by y2j, so make sure to check it out as well.

Top 12 Handy YAML to JSON Converter Tools

25-02-2022 · Aconvert is also a great and secure place to convert YAML input to JSON output. Here are the steps to use this tool-. Click the “Choose Files” button to choose multiple files from your computer. Or, use the dropdown to select an online file from URLs, Google Drive, or Dropbox. Choose a target document format.

25-02-2022

Many online tools convert from one language to another without knowing anything about either one. This article will discuss some of the best tools available for converting from YAML to JSON and vice versa.

YAML is a human-readable data serialization language used to represent structured data in text format. In many programming languages, YAML is used as the default schema language. It uses indentation instead of curly braces and spaces instead of semicolons.

A subset of YAML known as JSON (JavaScript Object Notation) is commonly used to transmit data structures between programs. However, YAML isn’t supported by every programming language, and it cannot store objects in arrays or coerce strings into numbers, for example.

What is YAML Language?

YAML is a data serialization language commonly employed to write configuration files. It is a matter of opinion, YAML stands for Yet Another Markup Language, or YAML isn’t a markup language. It emphasizes the fact that YAML is a data-oriented language and not documents.

YAML is a well-known programming language since it is simple to comprehend and readable by the human eye. It is also a good choice alongside other programming languages.

Because YAML is a superset of JSON, it can parse JSON using a YAML parser. The extensions that are part of YAML include .yaml as well as .yml. YAML specifications allow users to define their data types and specific data typing. The most popular data types used in YAML are numbers, strings, null values. Boolean, Dates and timestamps, Sequences, and Nested values.

What is JSON Format?

JSON (JavaScript Object Notation) is a language-independent, human-readable language used for its simplicity and is mainly used in web-based applications.

JSON includes a feature that allows you that encodes six different types of data, including objects, array, strings, null, numbers, and Boolean. JSON is far easier for computers to comprehend and is remarkably flexible compared to YAML, which permits encoding of Python data, but it has vulnerabilities when decoding. That is why YAML is challenging to interpret.

The most used format for data transmission between programs is JSON. This article will discuss some of the best tools available for converting from YAML to JSON and vice versa.

Convert quickly Another Markup Language to JavaScript with Online YAML Tools. Enter YAML into the input field to the left side, and you’ll see JSON displayed within the output field to the right. Enter YAML, get JSON. There aren’t downloads or ads, and everything works within your browser.

A YAML converter converts YAML configurations and documents into JSON configurations and files. It does not have any additional configuration options. Only one thing that you can alter is JSON’s output. You have three choices: indent JSON using spaces or indent JSON using tabs and reduce JSON output.

JSON formatter

JSON formatter is another free website that allows you to transform JSON into YAML online for no cost. Like all the other sites in this post, you can upload a YAML file or copy the YAML code onto it; after that, it converts the input YAML into JSON and displays the output.

After receiving an output formatted in JSON, you can choose to save it to your clipboard. You can also save the JSON output into a text file. But, there aren’t any other tools or additional features available on the website to use. Just send the YAML, and you will receive your JSON output. It’s as easy as that.

JSON-Formatter

Visit it by clicking on the URL and then copying the YAML data into its interface to access this tool. Make sure you insert the YAML data into the pane to your left. When you have pasted the input data from YAML, it will instantly display the JSON output, which you can download to your personal computer. You can also save the JSON code and apply it to any place you like.

Beautify Code

Beautify Code converter transforms the YAML text into an actual JSON object. It is accomplished by taking each part of the YAML file and translating it into a valid JSON property.

JSON to YAML

JSON to YAML tool is equipped with two panes where you can enter the YAML data into one and obtain the result in JSON in the other. This tool can be used for both conversions: YAML to JSON and JSON into YAML. To perform this YAML conversion to JSON conversion, all you have to do is copy the YAML code into its interface. In just a few seconds, you will get the JSON output.

JSON-to-YAML

To use this tool online, visit the homepage using the above URL. After that, copy and paste the YAML code into the upper right-hand pane. After that, it will automatically display what’s in the JSON details in the bottom pane.

You can copy the JSON data and save it in the form of a file on your personal computer. It supports the reverse conversion too. So, regardless of whether you’re looking to change YAML into JSON and JSON to YAML, it will be able to accomplish this quickly.

Code Beautify

Code Beautify is a straightforward YAML into JSON converter site that you can test at no cost. It can take the YAML code directly, or you can upload a YAML file to it. After receiving your YAML inputs, the program instantly will return its JSON output.

Not only that, but if you own a YAML file stored elsewhere, it is possible to enter the URL of that file to retrieve the YAML data and transform it into JSON. Then it is possible to save JSON data as a file on your computer and perform whatever you wish.

Code-Beautify

To begin using this tool, visit its website using the link above. Then, you can copy the YAML code or upload a YAML file on your computer. You can also specify an URL for your “.yml” file to fetch the YAML information.

After the YAML file specification, press “YAML to JSON” or the “YAML to JSON” button to begin the conversion. The conversion will instantly show the JSON output you can save to your personal computer. It’s as simple as that.

ConvertJSON

ConvertJSON is among the most popular websites that allow you to change YAML data into JSON in just a blink. It extracts your “.yml” file from you and outputs the data in JSON format. It is possible to directly insert the YAML code into its interface and get JSON output.

In addition to YAML in JSON change, you could also select alternatives. It allows you to specify what line ends you would like to see to be included in your JSON file.

Convert-JSON

If you want to convert YAML to JSON via this website to access the tool, go to the URL above. Once you have that, you can either upload the YAML file to your computer or copy the YAML code into the pane to the left. Once you’ve done that, you’ll need to select the type of line endings at the lower part on the next pane. Then, begin the conversion.

ConvertSimple

ConvertSimple is another online tool that lets you easily convert YAML to JSON. You just have to copy your YAML entry into the input box on the left, and it will convert it to JSON. The JSON output is in the box to the left.

If there’s a problem in the YAML file and the converter isn’t in a position to complete the conversion, the error message will show up in the output box, letting you know where the error was discovered inside the YAML. Utilize the control box to select the options that alter the conversion.

ConvertSimple

The YAML data is protected. ConvertSimple’s converter doesn’t send any of your YAML details to the servers they use for conversion. The process is entirely done in your browser. That’s why ConvertSimple’s converter is the most secure and efficient converter available.

WTools make it easy to convert YAML documents online into the appropriate JSON format. The tool can convert YAML The Ain’t Markup Language (YAML) documents into JSON (JavaScript Obj Notation) documents, and it’s an entirely free conversion. There is no need to download any software to convert.

How does it Work?

Paste your YAML into the text area above. Click on “Convert,” and you will be able to access JSON data in the following text area. After conversion, you can add this JSON into your application or any other reason.

Browserling

With Browserling, you can upload the YAML file or paste the YAML code into it. After that, it converts the input YAML into JSON and displays the output to you.

Once you’ve received your output as JSON, it is possible to copy it to your clipboard. You can also convert the JSON output into a text file. But, there are no other tools or additional features available on the site that you can utilize. Submit the YAML, and you will receive a JSON output. It’s as easy as that.

Browserling

To access this tool, access it by clicking on the URL and then copying the YAML data into its interface. Make sure you copy the YAML data into the lower left-hand pane. When you have pasted the input data in the YAML format, it will provide you with the JSON output, which you can download to your personal computer. Additionally, you can take a copy of the JSON code and apply it to any place you like.

Conversion Tools is yet another YAML to JSON convertor. You can choose from a variety of plans and use its services even without any registration. It also offers custom convertor development for businesses and professionals to transform files and process data.

Conversion Tools

Here are the steps to use this tool-

  • Choose your options and then click the ‘Run Conversion’ button.
  • Drag and drop the file onto the “Browse” button or Click “Browse” to select the file.
  • Use a single archive or file (zip 7z, rar, zip, the xz) to convert the batch.
  • Choose No. of spaces to be indented.
  • Click the button to start the conversion.
  • Run conversion.

There are restrictions set on how many conversions can be performed and the file size for each conversion. The Conversion Plan determines the limits that you select. For users who aren’t registered, there is a limit of 10 conversions per day, 10 MB per uploaded file—just register and upgrade for free.

Tutorial Works

Tutorial Works is a free tool to convert YAML files to JSON. All the YAML that you input here is not transmitted to the server or stored at any time. Your personal information is protected.

Copy the YAML you would like to convert, then click the Convert button. You will get the desired output in the bottom field.

Tutorial Works

Aconvert

Aconvert is also a great and secure place to convert YAML input to JSON output. Here are the steps to use this tool-

  • Click the “Choose Files” button to choose multiple files from your computer. Or, use the dropdown to select an online file from URLs, Google Drive, or Dropbox. 
  • Choose a target document format. The target format for documents could be PDF or DOC or DOCX and XLS. Other formats include XLS, PPT HTML, PPTX, HTML CSV, TXT RTF, ODT, ODS, ODP, XPS or OXPS. Selecting a format for the target will show which formats from the source can be converted into the destination format.
  • Click the “Convert Now!” button to begin the batch conversion. The converted files are shown under the “Conversion Results” section “Conversion Results” section. Click the icon to display the QR Code for the file or save the files to online storage services. 
AConvert

Conclusion

JSON is a lightweight, text-based data interchange format becoming increasingly popular. YAML is a markup language used in various programming languages and other software development to describe data. Converting YAML to JSON can help you save time and resources.

You may now look at an introduction to YAML in Python for Beginners and JSON Tools to Parse, Format, and Validate. Want to convert JSON to Excel? Try these tools.

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