AtlasQ
AtlasQ allows the usage of AtlasSearch keeping the MongoEngine syntax.
Structure
The package tries to follow the MongoEngine structure;
the major differences reside in the transform.py and queryset.py files.
Transform
Like in MongoEngine, a step in the pipeline is the creation of a query from a Q object:
we have to find a correspondence between the MongoEngine common syntax and what AtlasSearch allows.
For doing this, we had to find some compromises.
Not every keyword is supported at the moment: if you have an actual use case that you would like to support, please be free to open an issue or a PR at any moment.
QuerySet
There are probably a thousand of better implementation, if you actually knew MongoEngine and above all PyMongo. Unfortunately, our knowledge is limited, so here we go. If you find a solution that works better, again, feel free to open an issue or a PR.
The main idea, is that the filter should work like an aggregation.
For doing so, and with keeping the compatibility on how MongoEngine works (i.e. the filter should return a queryset of Document) we had to do some work.
Calling .aggregate instead has to work as MongoEngine expect, meaning a list of dictionaries.
Usage
Now the most important part: how do you use this package?
from mongoengine import Document, fields
from atlasq import AtlasManager, AtlasQ, AtlasQuerySet
index_name = str("my_index")
class MyDocument(Document):
name = fields.StringField(required=True)
surname = fields.StringField(required=True)
atlas = AtlasManager(index_name)
obj = MyDocument.objects.create(name="value", surname="value2")
qs = MyDocument.atlas.filter(name="value")
assert isinstance(qs, AtlasQuerySet)
obj_from_atlas = qs.first()
assert obj == obj_from_atlas
obj2_from_atlas = MyDocument.atlas.get(AtlasQ(name="value") & AtlasQ(surname="value2"))
assert obj == obj2_from_atlas
obj3_from_atlas = MyDocument.atlas.get(AtlasQ(wrong_field="value"))
assert obj3_from_atlas is None
Extended Features
Validation
We also decided to have, optionally, a validation of the index. Two things are checked:
- The index actually exists (If you query a non-existing index, Atlas as default behaviour will not raise any error).
- The fields that you are querying are actually indexed(If you query a field that is not indexed, Atlas as default behaviour will not raise any error, and will return an empty list).
To make these check, you need to call the function
ensure_indexon the queryset.
from mongoengine import Document, fields
from atlasq import AtlasManager, AtlasQ
index_name = str("my_index")
class MyDocument(Document):
name = fields.StringField(required=True)
surname = fields.StringField(required=True)
atlas = AtlasManager(index_name)
result = MyDocument.atlas.ensure_index("user", "pwd", "group", "cluster")
assert result is True
obj1_from_atlas = MyDocument.atlas.get(AtlasQ(name="value"))
obj2_from_atlas = MyDocument.atlas.get(AtlasQ(wrong_field="value")) # raises AtlasIndexFieldError
EmbeddedDocuments
Embedded documents are queried in two different ways, depending on how you created your Search Index.
Remember to ensure the index so that AtlasQ can know how your index is defined
If you used the embeddedDocuments type, AtlasQ will use the embeddedDocument query syntax.
Otherwise, if you used the document type, or you did not ensure the index, a normal text search with the . syntax will be used.
Upload index
It is possible to upload directly the Search index using AtlasQ, calling the function upload_index on the queryset. Syntax checks on the index itself are performed.
If the _id is not present but pk or id was specified, it will be automatically added, allowing valid text query on the
primary key.
from mongoengine import Document, fields
from atlasq import AtlasManager
index_name = str("my_index")
index = {
"analyzer": "lucene.keyword",
"mappings": {
"dynamic": False,
"fields": {
"_id": {
"type": "objectId"
},
"name": {
"type": "string"
},
"surname": {
"type": "string"
},
}
}
}
class MyDocument(Document):
name = fields.StringField(required=True)
surname = fields.StringField(required=True)
atlas = AtlasManager(index_name)
result = MyDocument.atlas.ensure_index("user", "pwd", "group", "cluster")
assert result is False
MyDocument.atlas.upload_index(index, "user", "pwd", "group", "cluster")
result = MyDocument.atlas.ensure_index("user", "pwd", "group", "cluster")
assert result is True
Sort
On the 10th of July 2023, the Sort functionality was released for Atlas search.
AtlasQ, from version 0.12.0, will support this feature inside the order_by function.
To have the old behaviour of the order_by (useful if you want to sort after aggregations and not after the search stage), you can set the kwarg as_aggregation as True.
Release files for atlasq 0.15.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| atlasq-0.15.0.tar.gz | 39.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| atlasq-0.15.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 55.3 kB
Release files / atlasq-0.15.0.tar.gz
| Download URL | atlasq-0.15.0.tar.gz |
|---|---|
| Size | 39.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Uploaded via |
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|
Release files / atlasq-0.15.0-py3-none-any.whl
| Download URL | atlasq-0.15.0-py3-none-any.whl |
|---|---|
| Size | 16.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.12.6
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