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Apache Thrift vs JSON: What are the differences?
Introduction
Apache Thrift and JSON are both popular data serialization formats used in web development. However, they have several key differences that differentiate them in terms of features and usage.
Schema Definition: Apache Thrift requires a separate schema definition language to define the structure of the data being serialized and deserialized. This schema definition is used to generate code in various programming languages for data serialization and deserialization. On the other hand, JSON does not require a separate schema definition and can be used directly as a lightweight data interchange format.
Data Types: Apache Thrift provides a wider range of primitive data types compared to JSON. It includes basic types like integers, floats, and booleans, as well as more complex types like enums, lists, and maps. JSON, on the other hand, supports only a limited set of data types including strings, numbers, booleans, arrays, and objects.
Binary Protocol: Apache Thrift supports a binary protocol, which is a compact and efficient way of serializing data. This binary protocol reduces the size of the data being transmitted over the network and provides better performance compared to JSON. JSON, on the other hand, uses a plain-text format, which is less compact and efficient compared to the binary protocol.
Code Generation: Apache Thrift generates code in multiple programming languages based on the provided schema definition. This generated code can be used to serialize and deserialize data in a language-specific manner. JSON, on the other hand, does not require any code generation as it can be directly parsed and serialized using built-in language features.
Compatibility: Apache Thrift provides language-specific libraries for various programming languages, ensuring compatibility and seamless integration with different systems. JSON, on the other hand, has native support in almost all modern programming languages, making it highly compatible and widely used.
Extensibility: Apache Thrift allows developers to define custom data types and functions as extensions to the core protocol. This extensibility feature provides flexibility in handling complex data structures and protocols. JSON, on the other hand, does not have a built-in extensibility mechanism and relies on external conventions or standards for handling complex data structures.
In summary, Apache Thrift offers a powerful and efficient data serialization framework with a separate schema definition language, binary protocol support, and code generation capabilities. JSON, on the other hand, is a lightweight and widely supported data interchange format that does not require a separate schema definition and can be used with minimal overhead.
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.
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