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Haskell vs JSON: What are the differences?
What is Haskell? An advanced purely-functional programming language. .
What is JSON? A lightweight data-interchange format. 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.
Haskell and JSON can be categorized as "Languages" tools.
According to the StackShare community, JSON has a broader approval, being mentioned in 20 company stacks & 104 developers stacks; compared to Haskell, which is listed in 33 company stacks and 47 developer stacks.
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 Haskell
- Purely-functional programming90
- Statically typed66
- Type-safe59
- Open source39
- Great community38
- Built-in concurrency31
- Built-in parallelism30
- Composable30
- Referentially transparent24
- Generics20
- Type inference15
- Intellectual satisfaction15
- If it compiles, it's correct12
- Flexible8
- Monads8
- Great type system5
- Proposition testing with QuickCheck4
- One of the most powerful languages *(see blub paradox)*4
- Purely-functional Programming4
- Highly expressive, type-safe, fast development time3
- Pattern matching and completeness checking3
- Great maintainability of the code3
- Fun3
- Reliable3
- Best in class thinking tool2
- Kind system2
- Better type-safe than sorry2
- Type classes2
- Predictable1
- Orthogonality1
Pros of JSON
- Simple5
- Widely supported4
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Cons of Haskell
- Too much distraction in language extensions9
- Error messages can be very confusing8
- Libraries have poor documentation5
- No good ABI3
- No best practices3
- Poor packaging for apps written in it for Linux distros2
- Sometimes performance is unpredictable2
- Slow compilation1
- Monads are hard to understand1