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CoffeeScript vs JSON: What are the differences?
**Introduction**
**1. Syntax:** CoffeeScript uses significant indentation for block structures, while JSON uses curly braces to define objects.
**2. Data Types:** CoffeeScript supports complex data structures like arrays and objects directly, unlike JSON where complex data types need to be represented as strings.
**3. Comments:** CoffeeScript allows comments using the # symbol, whereas JSON does not support comments.
**4. Functions:** CoffeeScript allows the creation of functions, with more flexibility and syntax options compared to JSON.
**5. Variables:** In CoffeeScript, variables are defined with var, let, or const keywords, while JSON does not have a concept of variables.
**6. Usage:** CoffeeScript is a programming language that compiles to JavaScript, while JSON is a lightweight data-interchange format.
In Summary, CoffeeScript has a more versatile syntax, supports complex data types directly, allows comments and functions, defines variables, and is used for programming, whereas JSON is limited to representing data in a specific format.
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?
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
- 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)
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
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.
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.
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.
Pros of CoffeeScript
- Easy to read199
- Faster to write179
- Syntactic sugar126
- Readable104
- Elegant104
- Pretty73
- Javascript the good parts53
- Open source48
- Classes44
- "it's just javascript"35
- Compact code16
- Easy15
- Simple13
- Not Javascript13
- Does the same with less code2
- I'm jobs I'm software engineer1
Pros of JSON
- Simple5
- Widely supported4
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Cons of CoffeeScript
- No ES63
- Corner cases in syntax1
- Parentheses required in 0-ary function calls1
- Unclear what will be grouped to {…}1