mongo-pipebuilder 0.2.1

Type-safe, fluent MongoDB aggregation pipeline builder

mongo-pipebuilder

Type-safe, fluent MongoDB aggregation pipeline builder for Python.

Overview

mongo-pipebuilder provides a clean, type-safe way to build MongoDB aggregation pipelines using the Builder Pattern with a fluent interface for maximum readability and safety.

Features

• ✅ Type-safe: Full type hints support with IDE autocomplete
• ✅ Fluent interface: Chain methods for readable, maintainable code
• ✅ Zero dependencies: Pure Python, lightweight package
• ✅ Extensible: Easy to add custom stages via add_stage()
• ✅ Well tested: Comprehensive test suite with 96%+ coverage

Installation

pip install mongo-pipebuilder

Quick Start

from mongo_pipebuilder import PipelineBuilder

# Build a pipeline
pipeline = (
    PipelineBuilder()
    .match({"status": "active"})
    .lookup(
        from_collection="users",
        local_field="userId",
        foreign_field="_id",
        as_field="user"
    )
    .project({"name": 1, "user.email": 1})
    .sort({"name": 1})
    .limit(10)
    .build()
)

# Use with pymongo
from pymongo import MongoClient
client = MongoClient()
collection = client.db.my_collection
results = collection.aggregate(pipeline)

API Reference

PipelineBuilder

Main class for building aggregation pipelines.

Methods

match(conditions: Dict[str, Any]) -> Self

Adds a $match stage to filter documents.

.match({"status": "active", "age": {"$gte": 18}})

lookup(from_collection: str, local_field: str, foreign_field: str, as_field: str, pipeline: Optional[List[Dict[str, Any]]] = None) -> Self

Adds a $lookup stage to join with another collection.

.lookup(
    from_collection="users",
    local_field="userId",
    foreign_field="_id",
    as_field="user",
    pipeline=[{"$match": {"active": True}}]  # Optional nested pipeline
)

add_fields(fields: Dict[str, Any]) -> Self

Adds a $addFields stage to add or modify fields.

.add_fields({"fullName": {"$concat": ["$firstName", " ", "$lastName"]}})

project(fields: Dict[str, Any]) -> Self

Adds a $project stage to reshape documents.

.project({"name": 1, "email": 1, "_id": 0})

group(group_by: Dict[str, Any], accumulators: Dict[str, Any]) -> Self

Adds a $group stage to group documents.

.group(
    group_by={"category": "$category"},
    accumulators={"total": {"$sum": "$amount"}}
)

unwind(path: str, preserve_null_and_empty_arrays: bool = False, include_array_index: Optional[str] = None) -> Self

Adds a $unwind stage to deconstruct arrays.

.unwind("tags", preserve_null_and_empty_arrays=True)
.unwind("items", include_array_index="itemIndex")

sort(fields: Dict[str, int]) -> Self

Adds a $sort stage.

.sort({"createdAt": -1, "name": 1})

limit(limit: int) -> Self

Adds a $limit stage.

.limit(10)

skip(skip: int) -> Self

Adds a $skip stage.

.skip(20)

unset(fields: Union[str, List[str]]) -> Self

Adds a $unset stage to remove fields from documents.

.unset("temp_field")
.unset(["field1", "field2", "field3"])

replace_root(new_root: Dict[str, Any]) -> Self

Adds a $replaceRoot stage to replace the root document.

.replace_root({"newRoot": "$embedded"})
.replace_root({"newRoot": {"$mergeObjects": ["$doc1", "$doc2"]}})

replace_with(replacement: Any) -> Self

Adds a $replaceWith stage (alias for $replaceRoot in MongoDB 4.2+).

.replace_with("$embedded")
.replace_with({"$mergeObjects": ["$doc1", "$doc2"]})

facet(facets: Dict[str, List[Dict[str, Any]]]) -> Self

Adds a $facet stage for parallel execution of multiple sub-pipelines.

.facet({
    "items": [{"$skip": 10}, {"$limit": 20}],
    "meta": [{"$count": "total"}]
})

count(field_name: str = "count") -> Self

Adds a $count stage to count documents.

.match({"status": "active"}).count("active_count")

set_field(fields: Dict[str, Any]) -> Self

Adds a $set stage (alias for $addFields in MongoDB 3.4+).

.set_field({"status": "active", "updatedAt": "$$NOW"})

add_stage(stage: Dict[str, Any]) -> Self

Adds a custom stage for advanced use cases.

.add_stage({"$facet": {
    "categories": [{"$group": {"_id": "$category"}}],
    "total": [{"$count": "count"}]
}})

prepend(stage: Dict[str, Any]) -> Self

Adds a stage at the beginning of the pipeline.

builder.match({"status": "active"})
builder.prepend({"$match": {"deleted": False}})
# Pipeline: [{"$match": {"deleted": False}}, {"$match": {"status": "active"}}]

insert_at(position: int, stage: Dict[str, Any]) -> Self

Inserts a stage at a specific position (0-based index) in the pipeline.

builder.match({"status": "active"}).group({"_id": "$category"}, {"count": {"$sum": 1}})
builder.insert_at(1, {"$sort": {"name": 1}})
# Pipeline: [{"$match": {...}}, {"$sort": {...}}, {"$group": {...}}]

Note: For inserting before a specific stage type, combine with get_stage_types():

stage_types = builder.get_stage_types()
group_index = stage_types.index("$group")
builder.insert_at(group_index, {"$addFields": {"x": 1}})

validate() -> bool

Validates the pipeline before execution. Checks that:

• Pipeline is not empty
• $out and $merge stages are the last stages (critical MongoDB rule)
• $out and $merge are not used together

builder = PipelineBuilder()
builder.match({"status": "active"}).validate()  # Returns True

# Invalid: $out not last
builder.add_stage({"$out": "output"}).match({"status": "active"})
builder.validate()  # Raises ValueError: $out stage must be the last stage

build() -> List[Dict[str, Any]]

Returns the complete pipeline as a list of stage dictionaries.

Examples

Complex Pipeline with Nested Lookup

pipeline = (
    PipelineBuilder()
    .match({"status": "published"})
    .lookup(
        from_collection="authors",
        local_field="authorId",
        foreign_field="_id",
        as_field="author"
    )
    .unwind("author", preserve_null_and_empty_arrays=True)
    .lookup(
        from_collection="categories",
        local_field="categoryId",
        foreign_field="_id",
        as_field="category",
        pipeline=[
            {"$match": {"active": True}},
            {"$project": {"name": 1, "slug": 1}}
        ]
    )
    .unwind("category")
    .add_fields({
        "authorName": "$author.name",
        "categoryName": "$category.name"
    })
    .project({
        "title": 1,
        "authorName": 1,
        "categoryName": 1,
        "publishedAt": 1
    })
    .sort({"publishedAt": -1})
    .limit(20)
    .build()
)

Aggregation with Grouping

pipeline = (
    PipelineBuilder()
    .match({"date": {"$gte": "2024-01-01"}})
    .group(
        group_by={"month": {"$dateToString": {"format": "%Y-%m", "date": "$date"}}},
        accumulators={
            "totalSales": {"$sum": "$amount"},
            "avgAmount": {"$avg": "$amount"},
            "count": {"$sum": 1}
        }
    )
    .sort({"month": 1})
    .build()
)

Development

Project Structure

mongo-pipebuilder/
├── src/
│   └── mongo_pipebuilder/
│       ├── __init__.py
│       └── builder.py
├── tests/
│   └── test_builder.py
├── examples/
│   └── examples.py
├── pyproject.toml
├── README.md
└── LICENSE

Running Tests

pytest tests/

Contributing

See DEVELOPMENT.md for development guidelines.

License

MIT License - see LICENSE file for details.