mongo-aggregate-helper
v1.3.0
Published
A lightweight and user-friendly helper library for easily constructing and executing MongoDB aggregation pipelines. Streamline your data processing with a clean API and versatile functionality.
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Mongo Aggregate Helper
The Mongo Aggregate Helper is a lightweight and intuitive library designed to streamline the construction and execution of MongoDB aggregation pipelines. With a focus on simplicity and usability, this library empowers developers to efficiently build complex aggregation queries without the overhead of verbose code.
Table of Contents
Features
User-Friendly Interface: The library offers a straightforward API that abstracts away the complexities of MongoDB's aggregation framework, allowing developers to focus on logic rather than syntax.
Versatile Functionality: It supports a wide range of aggregation operations, including but not limited to
$group
,$match
,$project
, and more, making it suitable for various data processing tasks.Enhanced Code Readability: By promoting a clean and organized coding style, this helper facilitates maintainable and scalable projects, which is essential for both small and large applications.
Seamless Integration: Easily integrate the library into any Node.js application with minimal setup, making it a great addition for projects that rely on MongoDB for data handling.
Whether you're building data-centric applications or performing data analysis, the Mongo Aggregate Helper simplifies your MongoDB aggregation queries and enhances your development experience.
Installation
To install the package, run the following command:
npm install mongo-aggregate-helper
Methods Available
match(condition)
: Adds a$match
stage.group(grouping)
: Adds a$group
stage.sort(order)
: Adds a$sort
stageproject(fields)
: Adds a$project
stage.lookup(from, localField, foreignField, as)
: Adds a$lookup
stage.unwind(path)
: Adds a$unwind
stage.addFields(fields)
: Adds a$addFields
stage.paginate(skip, limit)
: Adds pagination using$skip
and$limit
.search(field, keyword, exactMatch)
: Adds a search capability, Allowing both exact and regex-based matching.facet(stages)
: Adds a$facet
stage.count(fieldName)
: Adds a$count
stage.execute()
: Execute the aggregation pipeline and return results.
Usage
Using MongoClient
const MongoClient = require('mongodb').MongoClient;
const Aggregator = require("mongo-aggregate-helper");
// Example MongoDB connection (replace with your connection URI)
const uri = 'mongodb://localhost:27017';
const client = new MongoClient(uri);
async function runAggregation() {
try {
await client.connect();
const database = client.db('your_database_name');
const collection = database.collection('your_collection_name');
const aggregator = new Aggregator(collection);
// Build your aggregation pipeline
const result = await aggregator
.match({ status: 'active' }) // Example match stage
.group({ _id: '$country', count: { $sum: 1 } }) // Example group stage
.execute(); // Execute the aggregation
console.log(result);
} finally {
await client.close();
}
}
runAggregation().catch(console.error);
Notes:
- Ensure that the placeholders such as
your_database_name
andyour_collection_name
in the usage example are replaced with actual values relevant to your application. - You can add any specific sections or information that you feel would enhance the usability of your package for developers.
- Make sure to include any additional dependencies or setup details that may be necessary for using your library effectively.
Using Mongoose
const mongoose = require('mongoose');
const Aggregator = require("mongo-aggregate-helper");
// Connect to your MongoDB database
mongoose.connect('mongodb://localhost:27017/your_database_name', {
useNewUrlParser: true,
useUnifiedTopology: true
});
// Define a Mongoose schema
const exampleSchema = new mongoose.Schema({
name: String,
country: String,
status: String,
});
// Create a Mongoose model
const ExampleModel = mongoose.model('Example', exampleSchema);
async function runAggregation() {
try {
// Ensure the connection is established
await mongoose.connection.once('open', () => {
console.log('Connected to MongoDB');
});
const aggregator = new Aggregator(ExampleModel); // Pass the Mongoose model
// Build your aggregation pipeline
const result = await aggregator
.match({ status: 'active' }) // Example match stage
.group({ _id: '$country', count: { $sum: 1 } }) // Example group stage
.execute(); // Execute the aggregation
console.log(result); // Output the aggregation results
} catch (error) {
console.error('Aggregation error:', error);
} finally {
await mongoose.connection.close(); // Close the connection
}
}
// Run the aggregation
runAggregation().catch(console.error);
Notes
- Replace
your_database_name
in the MongoDB connection string with the actual name of your MongoDB database. - Adjust the schema according to the fields and structure of your actual collection.
- Make sure the necessary error handling and connection management is applied as relevant for your use case.
API
Aggregator
new Aggregator(model)
Creates a new Aggregator instance.
- Parameters:
model
: The Mongoose model to aggregate.
1. match(condition)
Adds a $match
stage to filter documents based on the provided condition.
Parameters:
condition
: An object specifying the criteria to match.
Returns: The current Aggregator
instance.
2. group(grouping)
Adds a $group
stage to group documents based on specified keys.
Parameters:
grouping
: An object defining the grouping criteria.
Returns: The current Aggregator
instance.
3. sort(order)
Adds a $sort
stage to sort documents.
Parameters:
order
: An object specifying the sort order (e.g.,{ field: 1 }
for ascending).
Returns: The current Aggregator
instance.
4. project(fields)
Adds a $project
stage to specify which fields to include or exclude.
Parameters:
fields
: An object defining fields to include or exclude from documents.
Returns: The current Aggregator
instance.
5. lookup(from, localField, foreignField, as)
Adds a $lookup
stage to perform a left outer join with another collection.
Parameters:
from
: The collection to join.localField
: The field from the input documents.foreignField
: The field from the documents of thefrom
collection.as
: The name for the new array field to add to the input documents.
Returns: The current Aggregator
instance.
6. unwind(path)
Adds a $unwind
stage to deconstruct an array field to generate a separate document for each element.
Parameters:
path
: The path to the array field to unwind.
Returns: The current Aggregator
instance.
7. addFields(fields)
Adds a $addFields
stage to add new fields to documents.
Parameters:
fields
: An object defining the fields to add.
Returns: The current Aggregator
instance.
8. paginate(skip = 0, limit)
Adds pagination with $skip
and optional $limit
.
Parameters:
skip
: Number of documents to skip (default is0
).limit
: Maximum number of documents to return. Ifundefined
ornull
, the$limit
stage is not added.
Returns: The current Aggregator
instance.
9. search(field, keyword, exactMatch = false)
Adds a text or regex search stage.
Parameters:
field
: The field to search.keyword
: The search keyword.exactMatch
: Boolean indicating whether to match exactly (default isfalse
).
Returns: The current Aggregator
instance.
10. facet(stages)
Adds a $facet
stage for multi-faceted results.
Parameters:
stages
: An object specifying multiple aggregation pipelines.
Returns: The current Aggregator
instance.
11. count(fieldName = "totalCount")
Adds a $count
stage to get the total count of documents.
Parameters:
fieldName
: Name of the field to store the count (default is"totalCount"
).
Returns: The current Aggregator
instance.
12. execute()
Executes the aggregation pipeline and returns the results.
Returns: A Promise that resolves with the results of the aggregation.
Example
Here's an example demonstrating the use of the API:
const Aggregator = require("mongo-aggregate-helper");
const aggregator = new Aggregator(YourModel);
const results = await aggregator
.match({ status: "active" })
.group({ _id: "$country", count: { $sum: 1 } })
.sort({ count: -1 })
.project({ country: "$_id", count: 1 })
.execute();
console.log(results);
Notes
- The
Aggregator
class is designed to simplify the construction of MongoDB aggregation pipelines using Mongoose models. - Each method returns the
Aggregator
instance, allowing for method chaining to build complex queries easily. - Make sure to handle errors accordingly when executing the pipeline with
.execute()
, as it returns a promise that may reject on failure. - You can use any combination of the provided methods to tailor your aggregation query to your specific needs.
- Refer to the official MongoDB Aggregation Framework documentation for more details on aggregation stages and their usage.
Contributing
We welcome contributions to enhance the Aggregator
class and improve overall functionality. To get started, please follow these guidelines:
How to Contribute
Fork the Repository
- Click on the "Fork" button at the top right corner of the repository page to create your own copy of the project.
Clone Your Fork
Clone your forked repository to your local machine:
git clone https://github.com/Mongo-Aggregate-Helper/mongo-aggregate-helper.git
Create a Branch
Create a new branch for your feature or bug fix:
git checkout -b feature/your-feature-name
Make Your Changes
- Implement your changes or improvements in your local branch.
Run Tests
Ensure that all existing and new tests pass by running the test suite:
npm test
Commit Your Changes
Stage your changes and commit them with a clear message:
git add . git commit -m "Add a brief description of your changes"
Push to Your Fork
Push your changes back to your forked repository:
git push origin feature/your-feature-name
Open a Pull Request
- Navigate to the original repository and submit a pull request. Provide a clear description of your changes and why they are beneficial.
Guidelines
- Ensure that your code follows the project's coding style and conventions.
- Write tests for any new functionality or fixes you add.
- Document any changes you make in the code or the README file.
Issues
If you encounter any bugs or have feature requests, feel free to open an issue in the repository. Please provide clear details about the problem or suggestion to help us address it effectively.
Thank you for considering contributing to this project! Your contributions are greatly appreciated.
License
This project is licensed under the MIT License
.
Summary of the MIT License
The MIT License is a permissive free software license that allows users to do almost anything with your project, as long as they include a copy of the original MIT License and copyright notice with it.