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GeoJSON vs JSON: What are the differences?
GeoJSON and JSON are both widely used formats for representing data. While they share similarities, there are key differences between these two formats that are important to understand.
Data Structure: The main difference between GeoJSON and JSON lies in their data structure. JSON is a general-purpose data interchange format that can represent any type of data. On the other hand, GeoJSON is a subset of JSON that is specifically designed for representing geographic data. GeoJSON introduces additional properties and data types to support the representation of geographical features such as points, lines, and polygons.
Geographical Specificity: Another important difference between GeoJSON and JSON is their level of geographical specificity. While JSON can represent any type of data without any geographical context, GeoJSON is specifically designed to store and exchange geographical information. It provides a standardized way to represent geographical features and their properties, making it easier to work with spatial data.
Coordinate System: GeoJSON introduces a standardized coordinate system for representing geographical features. It uses the WGS84 coordinate system, which is commonly used in GPS and mapping applications. This allows for accurate spatial representation and interoperability between different systems that support GeoJSON.
Geometric Shapes: GeoJSON supports the representation of different geometric shapes such as points, lines, and polygons, along with their associated properties. These shapes are defined using coordinates, allowing for precise spatial representation and analysis. JSON, on the other hand, does not have built-in support for representing geometric shapes and requires additional processing to handle spatial data.
Compatibility: While JSON is a widely supported format and can be used with any programming language or framework that supports data interchange, GeoJSON has specific support for geographic data in systems and libraries that are designed for working with spatial data. This makes GeoJSON a more suitable choice for applications that deal with geographic data and require spatial processing capabilities.
Serialization: When it comes to serialization, JSON can be easily serialized and deserialized using standard libraries in most programming languages. GeoJSON, being a subset of JSON, can also be serialized and deserialized using these libraries. However, GeoJSON introduces additional rules and constraints specific to geographic data, which may require specialized libraries or functions for serialization and deserialization.
In summary, GeoJSON expands on JSON with features specifically tailored for geographical data. Choose GeoJSON for precise spatial representation, standardized formats, and seamless integration with spatial data systems. Use JSON for general data exchange whenever geographical specificity is not crucial.
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 GeoJSON
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