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JSON vs Markdown: What are the differences?

Markdown and JSON are both widely used in web development, but they serve different purposes and have distinct features. Here are the key differences between JSON and Markdown:

  1. Structure vs Formatting: JSON is a data interchange format used for storing and transferring structured data, while Markdown is a lightweight markup language used for formatting plain text documents. JSON focuses on representing data in a structured manner, whereas Markdown focuses on enhancing the readability and presentation of text.

  2. Data vs Text: JSON is primarily used for representing and manipulating data, often in the form of objects and arrays. It allows for complex data structures, such as nested objects and arrays, and supports key-value pairs. On the other hand, Markdown is designed for writing and formatting text, providing simple syntax for making the text bold, italic, adding headers, links, etc.

  3. Programmatically Processable vs Human-readable: JSON is designed to be easily parsed and processed by machines, making it an ideal format for transmitting data between a server and a client. It is often used with programming languages and APIs. Markdown, on the other hand, is intended to be readable by humans, allowing for easy editing and collaboration. It is commonly used for writing documentation, blog posts, and other textual content.

  4. Extensibility vs Simplicity: JSON is extensible, meaning users can define and create custom data structures and add additional properties to objects. It provides flexibility in representing complex data types. Markdown, on the other hand, follows a simple and fixed set of formatting rules. While it offers some extensions like tables and task lists, it lacks the extensibility and versatility of JSON.

  5. Strict Syntax vs Loose Syntax: JSON has a strict syntax that requires properly quoted keys and values, as well as correct placement of commas and brackets. It follows a specific set of rules and allows no room for error. Markdown, on the other hand, has a more forgiving and loose syntax. It allows for flexibility in terms of white spaces, line breaks, and formatting, making it easier to write and read.

  6. Data Validation vs Raw Text: JSON supports data validation through various schema languages like JSON Schema. It allows users to define rules and constraints for validating the structure and content of JSON data. Markdown, however, does not have built-in capabilities for data validation. It primarily focuses on the presentation of text and does not provide mechanisms for enforcing data correctness.

In summary, JSON is used for structured data representation and transfer, suitable for machine processing and data validation, while Markdown is a lightweight markup language for text formatting, focusing on human readability and simple syntax.

Advice on JSON and Markdown
Needs advice
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JSONJSON
and
PythonPython

Hi. Currently, I have a requirement where I have to create a new JSON file based on the input CSV file, validate the generated JSON file, and upload the JSON file into the application (which runs in AWS) using API. Kindly suggest the best language that can meet the above requirement. I feel Python will be better, but I am not sure with the justification of why python. Can you provide your views on this?

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Replies (3)
Recommends
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PythonPython

Python is very flexible and definitely up the job (although, in reality, any language will be able to cope with this task!). Python has some good libraries built in, and also some third party libraries that will help here. 1. Convert CSV -> JSON 2. Validate against a schema 3. Deploy to AWS

  1. The builtins include json and csv libraries, and, depending on the complexity of the csv file, it is fairly simple to convert:
import csv
import json

with open("your_input.csv", "r") as f:
    csv_as_dict = list(csv.DictReader(f))[0]

with open("your_output.json", "w") as f:
    json.dump(csv_as_dict, f)
  1. The validation part is handled nicely by this library: https://pypi.org/project/jsonschema/ It allows you to create a schema and check whether what you have created works for what you want to do. It is based on the json schema standard, allowing annotation and validation of any json

  2. It as an AWS library to automate the upload - or in fact do pretty much anything with AWS - from within your codebase: https://aws.amazon.com/sdk-for-python/ This will handle authentication to AWS and uploading / deploying the file to wherever it needs to go.

A lot depends on the last two pieces, but the converting itself is really pretty neat.

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GolangGolang

I would use Go. Since CSV files are flat (no hierarchy), you could use the encoding/csv package to read each row, and write out the values as JSON. See https://medium.com/@ankurraina/reading-a-simple-csv-in-go-36d7a269cecd. You just have to figure out in advance what the key is for each row.

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Max Musing
Founder & CEO at BaseDash · | 1 upvotes · 288.2K views
Recommends
on
Node.jsNode.js
at

This should be pretty doable in any language. Go with whatever you're most familiar with.

That being said, there's a case to be made for using Node.js since it's trivial to convert an object to JSON and vice versa.

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Pros of JSON
Pros of Markdown
  • 5
    Simple
  • 4
    Widely supported
  • 345
    Easy formatting
  • 246
    Widely adopted
  • 194
    Intuitive
  • 132
    Github integration
  • 41
    Great for note taking
  • 2
    Defacto GitHub lingo

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Cons of JSON
Cons of Markdown
    Be the first to leave a con
    • 2
      Cannot centralise (HTML code needed)
    • 1
      Inconsistend flavours eg github, reddit, mmd etc
    • 1
      Limited syntax
    • 1
      Not suitable for longer documents
    • 1
      Non-extensible
    • 1
      No right indentation
    • 1
      No underline
    • 1
      Unable to indent tables

    Sign up to add or upvote consMake informed product decisions

    What is JSON?

    JavaScript Object Notation is a lightweight data-interchange format. It is easy for humans to read and write. It is easy for machines to parse and generate. It is based on a subset of the JavaScript Programming Language.

    What is Markdown?

    Markdown is two things: (1) a plain text formatting syntax; and (2) a software tool, written in Perl, that converts the plain text formatting to HTML.

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    Blog Posts

    Aug 28 2019 at 3:10AM

    Segment

    PythonJavaAmazon S3+16
    7
    2557
    What are some alternatives to JSON and Markdown?
    YAML
    A human-readable data-serialization language. It is commonly used for configuration files, but could be used in many applications where data is being stored or transmitted.
    Protobuf
    Protocol buffers are Google's language-neutral, platform-neutral, extensible mechanism for serializing structured data – think XML, but smaller, faster, and simpler.
    Avro
    It is a row-oriented remote procedure call and data serialization framework developed within Apache's Hadoop project. It uses JSON for defining data types and protocols, and serializes data in a compact binary format.
    MongoDB
    MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
    OData
    It is an ISO/IEC approved, OASIS standard that defines a set of best practices for building and consuming RESTful APIs. It helps you focus on your business logic while building RESTful APIs without having to worry about the various approaches to define request and response headers, status codes, HTTP methods, URL conventions, media types, payload formats, query options, etc.
    See all alternatives