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What is a JSON procedure?
In its simplest form, the JSON procedure allows the user to take a SAS® data set and create a JSON output file from the data. The user can also customize the JSON output by using a variety of options. In addition to that, the user can create their own JSON separate from the SAS® data set using the procedure.

Is JSON a programming language?
JSON is a lightweight, text-based, language-independent syntax for defining data interchange formats. It was derived from the ECMAScript programming language, but is programming language independent. JSON defines a small set of structuring rules for the portable representation of structured data.

Why is JSON a popular Data Interchange Format?
JSON is continuing to grow as the preferred data interchange format due to its simplicity and versatility. The JSON procedure gives SAS® users the ability to export SAS® data sets in JSON, as well as the ability to create custom JSON output.

How does jsonlite work?
The implementation is based on the mapping described in the vignette (Ooms, 2014). In addition to converting JSON data from/to R objects, 'jsonlite' contains functions to stream, validate, and prettify JSON data.

[PDF File]The JSON Data Interchange Syntax - ECMAScript
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The JSON Data Interchange Syntax 1 Scope JSON is a lightweight, text-based, language-independent syntax for defining data interchange formats. It was derived from the ECMAScript programming language, but is programming language independent. JSON defines a small set of structuring rules for the portable representation of structured data.

[PDF File]Creating and Controlling JSON Output with PROC JSON - SAS
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ABSTRACT JSON is continuing to grow as the preferred data interchange format due to its simplicity and versatility. The JSON procedure gives SAS® users the ability to export SAS® data sets in JSON, as well as the ability to create custom JSON output.

[PDF File]Intelligent REST API Data Fuzzing - GitHub Pages
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ABSTRACT The cloud runs on REST APIs. In this paper, we study how to in- telligently generate data payloads embedded in REST API requests in order to find data-processing bugs in cloud services. We discuss how to leverage REST API specifications, which, by definition, con- tain data schemas for API request bodies.

[PDF File]A Tool for JSON Schema Witness Generation - OpenProceedings
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Consider the following schema. { "type": "object", "properties": { "x": { "type": "integer" } }, "required": [ "x" ] } This schema declares that all instances are JSON objects, and that each object has a mandatory member whose name is x and whose type is inteдer.

[PDF File]jsonlite: A Simple and Robust JSON Parser and Generator for R
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Wrapper to generate and parse gzipped JSON, in order to save some disk or network space. This is mainly effective for larger json objects with many repeated keys, as is common in serialized data frames. Usage as_gzjson_raw(x, ...) as_gzjson_b64(x, ...) parse_gzjson_raw(buf, ...) parse_gzjson_b64(b64, ...) Arguments x R data object to be ...

[PDF File]Understanding JSON Schema - GSU
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Understanding JSON Schema, Release 7.0 JSON Schema is a powerful tool for validating the structure of JSON data. However, learning to use it by reading its speciﬁcation is like learning to drive a car by looking at its blueprints. You don’t need to know how an electric motor ﬁts together if all you want to do is pick up the groceries.

Generate json schema from data