Pymongo based python client with data definition layer.
Project description
Mongomancy
Description
Project contains abstraction of pymongo
driver for automatic reconnect on master switch in remote MongoDB cluster. It
also provides data definition layer.
Core of mongo_driver
is the Engine
class, handling queries reconnection with notification to registered reconnect
hooks.
Database
creates Collection
s by their definitions. Database hooks itself to engine reconnect event, so it can switch
internal state of database's collections instances.
classDiagram
Executor <|-- Engine : implements
Database o-- Executor
Database *-- Collection
Database o-- CollectionDefinition
Collection o-- Executor
CollectionDefinition *-- Index
CollectionDefinition *-- Document
class Executor{
<<abstract>>
reconnect()
register_hook(reconnect_hook_func)
find_one(collection: pymongo.collection.Collection, ...)
other_collection_methods(collection: pymongo.collection.Collection, ...)
}
class Engine{
+client: MongoClient
-_retry_command(collection, command, ...)
dispose()
reconnect()
register_hook(reconnect_hook_func)
find_one(collection: pymongo.collection.Collection, ...)
other_collection_methods(collection: pymongo.collection.Collection, ...)
}
class Collection{
+dialect_entity: pymongo.collection.Collection
+engine: Executor
+find_one(...)
other_collection_methods()
}
class Document{
+unique_key: Optional[BsonDict]
+data: BsonDict
}
class CollectionDefinition{
+name: str
+indices: Sequence[Index]
+default_docs: Sequence[Document]
}
class Index{
+fields: OrderedDictType[str, Union[str, int]]
+name: Optional[str]
+unique: Optional[bool]
field_for_mongo() -> List[Tuple[str, Union[str, int]]]
}
class Database{
+engine: Executor
+topology: List[types.CollectionDefinition]
-_database: pymongo.database.Database
-_collections: Dict[str, Collection]
invalidate_cache_hook(source: Engine)
get_collection(name: str) -> Collection
extend(*new_definitions: types.CollectionDefinition)
create_all(skip_existing: bool)
ping() -> bool
}
Installation
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Usage
import logging
from mongomancy import Engine, Database, CollectionDefinition, Index
engine = Engine("localhost", 27017)
logger = logging.getLogger(__name__)
db = Database(engine=engine, logger=logger)
game = CollectionDefinition(name="game", indices=[Index(fields={"genre": 1})])
player = CollectionDefinition(name="player", indices=[Index(fields={"player_id": 1}, unique=True)])
db.add_collection(game)
db.add_collection(player)
db.create_all()
db["game"].find({"genre": "adventure"})
Tests
You can run tests with coverage tracing:
python -m coverage run -m unittest tests/test_* -v
To generate coverage report:
python -m coverage html
Build
Clone repo and set up your pypi repo account credentials on build for build environment.
-
Move to package repo:
cd ~/git/mongomancy
-
Install requirements:
python -m pip install -Ur requirements.txt
-
Clean old build fragments:
rm -rf ./dist ./build ./mongomancy/mongomancy.egg-info
-
Build new package:
python -m build
-
Upload new package:
python -m twine upload dist/*
Project details
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