This module provides functionality for filtering and aggregating data based on MongoDB-like query syntax. It includes a set of predefined operations and the ability to extend with custom operators.
Install the module using npm:
yarn: yarn add uqry
npm: npm i uqry
module: https://unpkg.com/uqry?module
import { filter, add } from "uqry/lite";
It has extra $addFields, $unwind and $loopup stages.
import { filter, add, expression, aggregate, add } from "uqry/full";import { filter, expression, aggregate, add } from "uqry";The filter function creates a filter based on a query object.
const filter = (query) => value;const query = { age: { $gt: 25 } };
const data = { name: "Alice", age: 30 };
const result = filter(query)(data); // true
const data = [
{ name: "Alice", age: 25, city: "New York" },
{ name: "Bob", age: 30, city: "San Francisco" },
{ name: "Charlie", age: 35, city: "New York" },
];
const filterFunc = filter({ city: "New York", age: { $gt: 30 } });
const result = data.filter(filterFunc);
console.log(result); // [{ name: 'Charlie', age: 35, city: 'New York' }]
// $expr in filter function
console.log([
{ _id: 1, item: "binder", qty: parseInt("100"), price: parseFloat("12") },
{ _id: 2, item: "notebook", qty: parseInt("200"), price: parseFloat("8") },
{ _id: 3, item: "pencil", qty: parseInt("50"), price: parseFloat("6") },
{ _id: 4, item: "eraser", qty: parseInt("150"), price: parseFloat("3") },
{ _id: 5, item: "legal pad", qty: parseInt("42"), price: parseFloat("10") }
].filter(filter({
$expr: {
$lt: [
{
$cond: [
{ $gte: ["$qty", 100] },
{ $multiply: ["$price", parseFloat("0.50")] },
{ $multiply: ["$price", parseFloat("0.75")] }
]
},
5
]
}
})));const data = [
{
name: "Alice",
age: 30,
address: {
city: "New York",
zip: 10001,
},
},
{
name: "Bob",
age: 25,
address: {
city: "San Francisco",
zip: 94105,
},
},
{
name: "Charlie",
age: 35,
address: {
city: "New York",
zip: 10002,
},
},
];
const filterCriteria = {
"address.city": { $eq: "New York" },
};
const filteredData = data.filter((item) => filter(filterCriteria)(item));
console.log(filteredData);
/*
[
{
name: "Alice",
age: 30,
address: {
city: "New York",
zip: 10001
}
},
{
name: "Charlie",
age: 35,
address: {
city: "New York",
zip: 10002
}
}
]
*/
const pipelines = [
{
$group: {
_id: "$address.city",
avgAge: { $avg: "$age" },
count: { $sum: 1 },
},
},
{
$sort: { count: -1 },
},
];
const aggregatedData = aggregate(pipelines)(data);
console.log(aggregatedData);
/*
[
{
_id: "New York",
avgAge: 32.5,
count: 2
},
{
_id: "San Francisco",
avgAge: 25,
count: 1
}
]
*/The expression function evaluates an expression based on the provided context.
const expression = (expr) => context;const expr = { $add: [1, 2, 3] };
const context = {};
const result = expression(expr)(context); // 6
// More expression
const context = { a: 5, b: 10, str: "Hello World" };
console.log(expression({ $add: ["$a", "$b"] })(context)); // 15
console.log(expression({ $subtract: ["$b", "$a"] })(context)); // 5
console.log(expression({ $concat: ["$str", "!!!"] })(context)); // 'Hello World!!!'
// Test data
const data = [
{ name: "John", age: 18 },
{ name: "Alice", age: 20 },
{ name: "John", age: 25 },
{ name: "Bob", age: 15 },
{ name: "Charlie", age: 22 },
{ name: "David", age: 30 },
];
console.log(
data.filter(
expression({
$and: [{ $eq: ["$name", "John"] }, { $gt: ["$age", 18] }],
})
)
);The aggregate function processes an array of documents through a pipeline of stages.
const aggregate = (pipelines) => contextArray;const pipelines = [
{ $match: { age: { $gt: 25 } } },
{ $group: { _id: "$gender", total: { $sum: 1 } } },
];
const data = [
{ name: "Alice", age: 30, gender: "female" },
{ name: "Bob", age: 20, gender: "male" },
{ name: "Charlie", age: 35, gender: "male" },
];
const result = aggregate(pipelines)(data);
// [
// { _id: 'female', total: 1 },
// { _id: 'male', total: 1 }
// ]
const data = [
{ name: "Alice", age: 30, city: "New York" },
{ name: "Bob", age: 25, city: "Los Angeles" },
{ name: "Charlie", age: 35, city: "New York" },
];
const pipeline = [
{
$project: {
name: 1,
age: { $add: ["$age", 1] }, // Add 1 to age
city: 1,
},
},
{
$match: {
age: { $gt: 30 }, // Filter for age > 30
city: "New York", // Filter for city "New York"
},
},
{
$group: {
_id: "$city", // Group by city
averageAge: { $avg: "$age" }, // Calculate average age
},
},
];
const result = aggregate(pipeline)(data);
console.log(result);
// Switch Case
console.log(
aggregate([
{
$project: {
statusDescription: {
$switch: {
branches: [
{
case: { $eq: ["$status", "A"] },
then: "Available",
},
{
case: { $eq: ["$status", "D"] },
then: "Discontinued",
},
],
default: "No status found",
},
},
},
},
])([
{ status: "A" },
{ status: "D" },
{ status: "A" },
{ status: "A" },
{ status: "D" },
{ status: "E" },
]),
);The add function allows you to dynamically add custom operators to the filtering, expression, and pipeline stages of your data processing operations. This feature is useful for extending the functionality of your data manipulation library with custom logic that can be applied to your datasets.
add(which, op, fn)-
which: A string specifying the type of operation to which the custom function should be added. Valid values are:'filter': For adding custom filter operations.'stage': For adding custom pipeline stage.'expression': For adding custom expression operations.
-
op: A string representing the name of the custom operation or stage. This will be used to reference the custom operation in your queries or pipelines. -
fn: A function implementing the custom logic for the operation. The signature of this function depends on the type of operation:- Filter Function:
(query, value) => boolean - Stage Function:
(args, context) => result - Expression Function:
(args, context) => result
- Filter Function:
To add a custom filter operation, use the add function with the 'filter' parameter.
add('filter', '$customOp', (query, value) => {
// Custom filter logic
});To add a custom pipeline stage, use the add function with the 'pipeline' parameter.
add('stage', '$customStage', (args, context) => {
// Custom pipeline stage logic
});To add a custom expression operation, use the add function with the 'expression' parameter.
add('expression', '$customAgg', (args, context) => {
// Custom expression logic
});add('filter', '$isEven', (query, value) => value % 2 === 0);
// Usage in filter
const result = data.filter(filter({ age: { $isEven: true } }));add('stage', '$addField', (args, context) => {
return { ...context, newField: 'newValue' };
});
// Usage in pipeline
const result = aggregate([{ $addField: [] }])(data);add('expression', '$sumField', (args, context) => {
return args.map(arg => expression(arg)(context)).reduce((a, b) => a + b, 0);
});
// Usage in aggregation
const result = aggregate([{ $sumField: ['field'] }])(data);- Ensure that the custom functions do not modify the original data or context unless intended.
- Custom functions should handle various edge cases and invalid inputs gracefully.
- Custom filter, pipeline, and expression operations should be tested thoroughly to ensure they behave as expected.
$eq: Equals$ne: Not equals$gt: Greater than$gte: Greater than or equal to$lt: Less than$lte: Less than or equal to$in: In array$nin: Not in array$and: Logical AND$or: Logical OR$not: Logical NOT$regex: Regexp$expr: Expression$exists: Element exists$type: Type of the value$mod: Mod$elemMatch: Array element matches$all: All elements matched in array$size: Size of an array$where: Custom function
$add: Addition$subtract: Subtraction$multiply: Multiplication$divide: Division$concat: Concatenation$min: Minimum value$max: Maximum value$avg: Average$sum: Sum$cond: Conditional$switch: Switch Case$eq: Equals$ne: Not equals$gt: Greater than$gte: Greater than or equal to$lt: Less than$lte: Less than or equal to$in: In array$nin: Not in array$and: Logical AND$or: Logical OR$not: Logical NOT
$project: Reshapes documents$match: Filters documents$group: Groups documents$sort: Sorts documents$skip: Skips documents$limit: Limits documents$count: Counts documents
This project is licensed under the MIT License.