js-stream-dataset-json v0.6.0
js-stream-dataset-json
js-stream-dataset-json is a TypeScript library for streaming and processing CDISC Dataset-JSON files. It provides functionalities to read data and metadata from Dataset-JSON files.
Supported Dataset-JSON versions: 1.1
Features
- Stream Dataset-JSON files
- Extract metadata from Dataset-JSON files
- Read observations as an iterable
- Get unique values from observations
- Support reading and writing using Dataset-JSON compressed format
Installation
Install the library using npm:
npm install js-stream-dataset-jsonUsage
dataset = new DatasetJSON(filePath, [options])Creating Dataset-JSON instance
import DatasetJson from 'js-stream-dataset-json';
dataset = new DatasetJSON('/path/to/dataset.json')Additional Options
isNdJson(boolean, optional): Specifies if the file is in NDJSON format. If not provided, it will be detected from the file extension.encoding(BufferEncoding, optional): Specifies the encoding of the file. Defaults to 'utf8'.isCompressed(boolean, optional): Specifies if the file is in compressed Dataset-JSON format. If not provided, it will be detected from file extension 'dsjc'.
Possible Encodings
- 'ascii'
- 'utf8'
- 'utf16le'
- 'ucs2'
- 'base64'
- 'latin1'
Example
const dataset = new DatasetJson('/path/to/dataset.ndjson', { isNdJson: true, encoding: 'utf16le' });Getting Metadata
const metadata = await dataset.getMetadata();Reading Observations
// Read first 500 records of a dataset
const data = await dataset.getData({start: 0, length: 500})Reading Observations as iterable
// Read dataset starting from position 10 (11th record in the dataset)
for await (const record of dataset.readRecords({start: 10, filterColumns: ["studyId", "uSubjId"], type: "object"})) {
console.log(record);
}Getting Unique Values
const uniqueValues = await dataset.getUniqueValues({ columns: ["studyId", "uSubjId"], limit: 100 });Applying Filters
You can apply filters to the data when reading observations using the js-array-filter package.
Example
import Filter from 'js-array-filter';
// Define a filter
const filter = new Filter('dataset-json1.1', metadata.columns, {
conditions: [
{ variable: 'AGE', operator: 'gt', value: 55 },
{ variable: 'DCDECOD', operator: 'eq', value: 'STUDY TERMINATED BY SPONSOR' }
],
connectors: ['or']
});
// Apply the filter when reading data
const filteredData = await dataset.getData({
start: 0,
filter: filter,
filterColumns: ['USUBJID', 'DCDECOD', 'AGE']
});
console.log(filteredData);Methods
getMetadata
Returns the metadata of the Dataset-JSON file.
Returns
Promise<Metadata>: A promise that resolves to the metadata of the dataset.
Example
const metadata = await dataset.getMetadata();
console.log(metadata);getData
Reads observations from the dataset.
Parameters
props(object): An object containing the following properties:start(number, optional): The starting position for reading data.length(number, optional): The number of records to read. Defaults to reading all records.type(DataType, optional): The type of the returned object ("array" or "object"). Defaults to "array".filterColumns(string[], optional): The list of columns to return when type is "object". If empty, all columns are returned.filter(Filter, optional): A Filter instance from js-array-filter package used to filter data records.
Returns
Promise<(ItemDataArray | ItemDataObject)[]>: A promise that resolves to an array of data records.
Example
const data = await dataset.getData({ start: 0, length: 500, type: "object", filterColumns: ["studyId", "uSubjId"] });
console.log(data);readRecords
Reads observations as an iterable.
Parameters
props(object, optional): An object containing the following properties:start(number, optional): The starting position for reading data. Defaults to 0.bufferLength(number, optional): The buffer length for reading data. Defaults to 1000.type(DataType, optional): The type of data to return ("array" or "object"). Defaults to "array".filterColumns(string[], optional): An array of column names to include in the returned data.
Returns
AsyncGenerator<ItemDataArray | ItemDataObject, void, undefined>: An async generator that yields data records.
Example
for await (const record of dataset.readRecords({ start: 10, filterColumns: ["studyId", "uSubjId"], type: "object" })) {
console.log(record);
}getUniqueValues
Gets unique values for variables.
Parameters
props(object): An object containing the following properties:columns(string[]): An array of column names to get unique values for.limit(number, optional): The maximum number of unique values to return for each column. Defaults to 100.bufferLength(number, optional): The buffer length for reading data. Defaults to 1000.sort(boolean, optional): Whether to sort the unique values. Defaults to true.
Returns
Promise<UniqueValues>: A promise that resolves to an object containing unique values for the specified columns.
Example
const uniqueValues = await dataset.getUniqueValues({
columns: ["studyId", "uSubjId"],
limit: 100,
bufferLength: 1000,
sort: true
});
console.log(uniqueValues);write
Writes data to a Dataset-JSON file with streaming support.
Parameters
props(object): An object containing the following properties:metadata(DatasetMetadata, optional): Dataset metadata, required for 'create' actiondata(ItemDataArray[], optional): Array of data records to writeaction('create' | 'write' | 'finalize'): The write action to performoptions(object, optional):prettify(boolean): Format JSON output with indentation. Default is false.highWaterMark(number): Sets stream buffer size in bytes. Default is 16384 (16KB).compressionLevel(number): Sets the compression level for zLib library.
Example
// Create new file with metadata
await dataset.write({
metadata: {
datasetJSONCreationDateTime: '2023-01-01T12:00:00',
datasetJSONVersion: '1.0',
records: 1000,
name: 'DM',
label: 'Demographics',
columns: [/* column definitions */]
},
action: 'create',
options: { prettify: true }
});
// Write data chunks
await dataset.write({
data: [/* array of records */],
action: 'write'
});
// Finalize the file
await dataset.write({
action: 'finalize'
});writeData
Convenience method to write a complete Dataset-JSON file in one operation.
Parameters
props(object): An object containing the following properties:metadata(DatasetMetadata): Dataset metadatadata(ItemDataArray[], optional): Array of data records to writeoptions(object, optional):prettify(boolean): Format JSON output with indentationhighWaterMark(number): Sets stream buffer size in bytes
Example
await dataset.writeData({
metadata: {
datasetJSONCreationDateTime: '2023-01-01T12:00:00',
datasetJSONVersion: '1.0',
records: 1000,
name: 'DM',
label: 'Demographics',
columns: [/* column definitions */]
},
data: [/* array of records */],
options: { prettify: true }
});Running Tests
Run the tests using Jest:
npm testLicense
This project is licensed under the MIT License. See the LICENSE file for details.
Author
Dmitry Kolosov
Contributing
Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.
For more details, refer to the source code and the documentation.
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