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JSON vs OData: What are the differences?
1. Data Format: JSON is a data format used for data interchange, while OData is a protocol for building and consuming RESTful APIs. JSON represents data in a readable format, whereas OData provides a set of conventions for creating and consuming web services. 2. Querying Capability: JSON does not have built-in querying capabilities, whereas OData allows for querying data using a standardized URL-based query language. This enables OData to perform more advanced data operations such as filtering, sorting, and pagination. 3. Metadata: JSON does not inherently support metadata, while OData includes metadata that describes the data model and structure of the API. This metadata can be used by consumers to understand and interact with the API more effectively. 4. Standardization: JSON is a general-purpose data format with no strict guidelines or standards, while OData follows a set of industry standards and best practices for building APIs. OData provides a standardized way to expose and consume data over the web. 5. Navigation and Relationships: OData supports the ability to navigate between related entities and establish relationships in the data, whereas in JSON, managing relationships between data entities can be more challenging and requires custom implementation. 6. Payload Size: JSON tends to have smaller payload sizes compared to OData due to its simplicity and lack of additional metadata. OData payloads can be larger due to the inclusion of metadata and additional query options.
In Summary, JSON and OData differ in their fundamental data format, querying capabilities, support for metadata, standardization, navigation of relationships, and payload sizes.
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 JSON
- Simple5
- Widely supported4
Pros of OData
- Patterns for paging, sorting, filtering7
- ISO Standard5
- Query Language4
- RESTful3
- No overfetching, no underfetching3
- Get many resources in a single request2
- Self-documenting2
- Batch requests2
- Bulk requests ("array upsert")2
- Ask for what you need, get exactly that2
- Evolve your API by following the compatibility rules1
- Resource model defines conventional operations1
- Resource Modification Language1
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Cons of JSON
Cons of OData
- Overwhelming, no "baby steps" documentation1
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