Query & search registries¶
Find & access data using registries.
Setup¶
!lamin init --storage ./mydata
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💡 connected lamindb: testuser1/mydata
import lamindb as ln
ln.settings.verbosity = "info"
💡 connected lamindb: testuser1/mydata
We’ll need some toy data:
ln.Artifact(ln.core.datasets.file_jpg_paradisi05(), description="My image").save()
ln.Artifact.from_df(ln.core.datasets.df_iris(), description="The iris collection").save()
ln.Artifact(ln.core.datasets.file_fastq(), description="My fastq").save()
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❗ no run & transform get linked, consider calling ln.track()
✅ storing artifact 'fFM6DufrM8iEwnlfdQ16' at '/home/runner/work/lamindb/lamindb/docs/mydata/.lamindb/fFM6DufrM8iEwnlfdQ16.jpg'
❗ no run & transform get linked, consider calling ln.track()
✅ storing artifact 'X1Oilr0aXunbPb07S50v' at '/home/runner/work/lamindb/lamindb/docs/mydata/.lamindb/X1Oilr0aXunbPb07S50v.parquet'
❗ no run & transform get linked, consider calling ln.track()
✅ storing artifact 'nzhAAXAAC7qg23ebl5yF' at '/home/runner/work/lamindb/lamindb/docs/mydata/.lamindb/nzhAAXAAC7qg23ebl5yF.fastq.gz'
Artifact(uid='nzhAAXAAC7qg23ebl5yF', description='My fastq', suffix='.fastq.gz', size=20, hash='hi7ZmAzz8sfMd3vIQr-57Q', hash_type='md5', visibility=1, key_is_virtual=True, created_by_id=1, storage_id=1, updated_at='2024-06-05 10:45:07 UTC')
Look up metadata¶
For entities where we don’t store more than 100k records, a look up object can be a convenient way of selecting a record.
Consider the User registry:
users = ln.User.lookup(field="handle")
With auto-complete, we find a user:
user = users.testuser1
user
User(uid='DzTjkKse', handle='testuser1', name='Test User1', updated_at='2024-06-05 10:45:05 UTC')
Note
You can also auto-complete in a dictionary:
users_dict = ln.User.lookup().dict()
Filter by metadata¶
Filter for all artifacts created by a user:
ln.Artifact.filter(created_by=user).df()
| uid | version | description | key | suffix | accessor | size | hash | hash_type | n_objects | n_observations | visibility | key_is_virtual | storage_id | transform_id | run_id | created_by_id | updated_at | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||||||||
| 1 | fFM6DufrM8iEwnlfdQ16 | None | My image | None | .jpg | None | 29358 | r4tnqmKI_SjrkdLzpuWp4g | md5 | None | None | 1 | True | 1 | None | None | 1 | 2024-06-05 10:45:07.217180+00:00 |
| 2 | X1Oilr0aXunbPb07S50v | None | The iris collection | None | .parquet | DataFrame | 5629 | ah24lV9Ncc8nPL0MumEsdw | md5 | None | None | 1 | True | 1 | None | None | 1 | 2024-06-05 10:45:07.310958+00:00 |
| 3 | nzhAAXAAC7qg23ebl5yF | None | My fastq | None | .fastq.gz | None | 20 | hi7ZmAzz8sfMd3vIQr-57Q | md5 | None | None | 1 | True | 1 | None | None | 1 | 2024-06-05 10:45:07.319054+00:00 |
To access the results encoded in a filter statement, execute its return value with one of:
.df(): A pandasDataFramewith each record stored as a row..all(): An indexable djangoQuerySet..list(): A list of records..one(): Exactly one record. Will raise an error if there is none..one_or_none(): Either one record orNoneif there is no query result.
Note
The ORMs in LaminDB are Django Models and any Django query works. LaminDB extends Django’s API for data scientists.
Under the hood, any .filter() call translates into a SQL select statement.
.one() and .one_or_none() are two parts of LaminDB’s API that are borrowed from SQLAlchemy.
Search for metadata¶
ln.Artifact.search("iris").df()
| uid | version | description | key | suffix | accessor | size | hash | hash_type | n_objects | n_observations | visibility | key_is_virtual | storage_id | transform_id | run_id | created_by_id | updated_at | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||||||||
| 2 | X1Oilr0aXunbPb07S50v | None | The iris collection | None | .parquet | DataFrame | 5629 | ah24lV9Ncc8nPL0MumEsdw | md5 | None | None | 1 | True | 1 | None | None | 1 | 2024-06-05 10:45:07.310958+00:00 |
Let us create 500 notebook objects with fake titles and save them:
ln.save(
[
ln.Transform(name=title, type="notebook")
for title in ln.core.datasets.fake_bio_notebook_titles(n=500)
]
)
We can now search for any combination of terms:
ln.Transform.search("intestine").df().head()
| uid | version | name | key | description | type | reference | reference_type | latest_report_id | source_code_id | created_by_id | updated_at | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||
| 11 | jyXN9okUqe8rGu6G | None | Igy Oxyphil cell IgG1 intestine IgA IgG4 Mesan... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.222249+00:00 |
| 29 | xaoMypVyaXQMhVDP | None | Igg intestine study Oxyphil cell IgE Basket ce... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.225022+00:00 |
| 41 | WQ2Q52AklXJTJ2Dg | None | Blue-Sensitive Cone Cells IgG Scrotum intestine. | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.226895+00:00 |
| 42 | eprfnk8Fkqu1ndcC | None | Efficiency blue-sensitive cone cells study cla... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.227048+00:00 |
| 46 | HqoptnuzVqG8hvym | None | Iga candidate investigate IgA intestine research. | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.227658+00:00 |
Leverage relations¶
Django has a double-under-score syntax to filter based on related tables.
This syntax enables you to traverse several layers of relations:
ln.Artifact.filter(run__created_by__handle__startswith="testuse").df()
| uid | version | description | key | suffix | accessor | size | hash | hash_type | n_objects | n_observations | visibility | key_is_virtual | storage_id | transform_id | run_id | created_by_id | updated_at | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id |
The filter selects all artifacts based on the users who ran the generating notebook.
(Under the hood, in the SQL database, it’s joining the artifact table with the run and the user table.)
Beyond __startswith, Django supports about two dozen field comparators field__comparator=value.
Here are some of them.
and¶
ln.Artifact.filter(suffix=".jpg", created_by=user).df()
| uid | version | description | key | suffix | accessor | size | hash | hash_type | n_objects | n_observations | visibility | key_is_virtual | storage_id | transform_id | run_id | created_by_id | updated_at | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||||||||
| 1 | fFM6DufrM8iEwnlfdQ16 | None | My image | None | .jpg | None | 29358 | r4tnqmKI_SjrkdLzpuWp4g | md5 | None | None | 1 | True | 1 | None | None | 1 | 2024-06-05 10:45:07.217180+00:00 |
less than/ greater than¶
Or subset to artifacts greater than 10kB. Here, we can’t use keyword arguments, but need an explicit where statement.
ln.Artifact.filter(created_by=user, size__lt=1e4).df()
| uid | version | description | key | suffix | accessor | size | hash | hash_type | n_objects | n_observations | visibility | key_is_virtual | storage_id | transform_id | run_id | created_by_id | updated_at | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||||||||
| 2 | X1Oilr0aXunbPb07S50v | None | The iris collection | None | .parquet | DataFrame | 5629 | ah24lV9Ncc8nPL0MumEsdw | md5 | None | None | 1 | True | 1 | None | None | 1 | 2024-06-05 10:45:07.310958+00:00 |
| 3 | nzhAAXAAC7qg23ebl5yF | None | My fastq | None | .fastq.gz | None | 20 | hi7ZmAzz8sfMd3vIQr-57Q | md5 | None | None | 1 | True | 1 | None | None | 1 | 2024-06-05 10:45:07.319054+00:00 |
or¶
from django.db.models import Q
ln.Artifact.filter().filter(Q(suffix=".jpg") | Q(suffix=".fastq.gz")).df()
| uid | version | description | key | suffix | accessor | size | hash | hash_type | n_objects | n_observations | visibility | key_is_virtual | storage_id | transform_id | run_id | created_by_id | updated_at | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||||||||
| 1 | fFM6DufrM8iEwnlfdQ16 | None | My image | None | .jpg | None | 29358 | r4tnqmKI_SjrkdLzpuWp4g | md5 | None | None | 1 | True | 1 | None | None | 1 | 2024-06-05 10:45:07.217180+00:00 |
| 3 | nzhAAXAAC7qg23ebl5yF | None | My fastq | None | .fastq.gz | None | 20 | hi7ZmAzz8sfMd3vIQr-57Q | md5 | None | None | 1 | True | 1 | None | None | 1 | 2024-06-05 10:45:07.319054+00:00 |
in¶
ln.Artifact.filter(suffix__in=[".jpg", ".fastq.gz"]).df()
| uid | version | description | key | suffix | accessor | size | hash | hash_type | n_objects | n_observations | visibility | key_is_virtual | storage_id | transform_id | run_id | created_by_id | updated_at | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||||||||
| 1 | fFM6DufrM8iEwnlfdQ16 | None | My image | None | .jpg | None | 29358 | r4tnqmKI_SjrkdLzpuWp4g | md5 | None | None | 1 | True | 1 | None | None | 1 | 2024-06-05 10:45:07.217180+00:00 |
| 3 | nzhAAXAAC7qg23ebl5yF | None | My fastq | None | .fastq.gz | None | 20 | hi7ZmAzz8sfMd3vIQr-57Q | md5 | None | None | 1 | True | 1 | None | None | 1 | 2024-06-05 10:45:07.319054+00:00 |
order by¶
ln.Artifact.filter().order_by("-updated_at").df()
| uid | version | description | key | suffix | accessor | size | hash | hash_type | n_objects | n_observations | visibility | key_is_virtual | storage_id | transform_id | run_id | created_by_id | updated_at | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||||||||
| 3 | nzhAAXAAC7qg23ebl5yF | None | My fastq | None | .fastq.gz | None | 20 | hi7ZmAzz8sfMd3vIQr-57Q | md5 | None | None | 1 | True | 1 | None | None | 1 | 2024-06-05 10:45:07.319054+00:00 |
| 2 | X1Oilr0aXunbPb07S50v | None | The iris collection | None | .parquet | DataFrame | 5629 | ah24lV9Ncc8nPL0MumEsdw | md5 | None | None | 1 | True | 1 | None | None | 1 | 2024-06-05 10:45:07.310958+00:00 |
| 1 | fFM6DufrM8iEwnlfdQ16 | None | My image | None | .jpg | None | 29358 | r4tnqmKI_SjrkdLzpuWp4g | md5 | None | None | 1 | True | 1 | None | None | 1 | 2024-06-05 10:45:07.217180+00:00 |
contains¶
ln.Transform.filter(name__contains="search").df().head(10)
| uid | version | name | key | description | type | reference | reference_type | latest_report_id | source_code_id | created_by_id | updated_at | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||
| 5 | mrNEfBq7VLNSeBjY | None | Submandibular Glands IgD research Scrotum visu... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.221329+00:00 |
| 17 | 7ClIJZpuvBYdBW8c | None | Iga Submandibular glands research IgA Basket c... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.223168+00:00 |
| 20 | 3iT4GHOp2nQIConu | None | Cluster Submandibular glands research Oxyphil ... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.223630+00:00 |
| 22 | u7JLQqQWKkq64cyW | None | Research IgG3 Von Ebner's gland Cajal–Retzius ... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.223935+00:00 |
| 25 | Xcmb60fQ6nV8ySQl | None | Igg2 Cervix research IgA Oxyphil cell cluster ... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.224398+00:00 |
| 37 | BwGbSlLCjmrqmCjy | None | Cervix rank IgG IgE IgY IgG1 IgG3 research. | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.226279+00:00 |
| 46 | HqoptnuzVqG8hvym | None | Iga candidate investigate IgA intestine research. | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.227658+00:00 |
| 52 | 4K7BKRsDu8TaFnsL | None | Research IgE intestinal IgG4 IgA. | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.228571+00:00 |
| 57 | ZLTNdoS3xpOL6oMy | None | Ige Duodenum research IgA IgE. | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.229369+00:00 |
| 60 | 0Q7grO9QwcWd1Suf | None | Rank Cajal–Retzius cells IgG3 research researc... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.229822+00:00 |
And case-insensitive:
ln.Transform.filter(name__icontains="Search").df().head(10)
| uid | version | name | key | description | type | reference | reference_type | latest_report_id | source_code_id | created_by_id | updated_at | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||
| 5 | mrNEfBq7VLNSeBjY | None | Submandibular Glands IgD research Scrotum visu... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.221329+00:00 |
| 17 | 7ClIJZpuvBYdBW8c | None | Iga Submandibular glands research IgA Basket c... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.223168+00:00 |
| 20 | 3iT4GHOp2nQIConu | None | Cluster Submandibular glands research Oxyphil ... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.223630+00:00 |
| 22 | u7JLQqQWKkq64cyW | None | Research IgG3 Von Ebner's gland Cajal–Retzius ... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.223935+00:00 |
| 25 | Xcmb60fQ6nV8ySQl | None | Igg2 Cervix research IgA Oxyphil cell cluster ... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.224398+00:00 |
| 37 | BwGbSlLCjmrqmCjy | None | Cervix rank IgG IgE IgY IgG1 IgG3 research. | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.226279+00:00 |
| 46 | HqoptnuzVqG8hvym | None | Iga candidate investigate IgA intestine research. | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.227658+00:00 |
| 52 | 4K7BKRsDu8TaFnsL | None | Research IgE intestinal IgG4 IgA. | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.228571+00:00 |
| 57 | ZLTNdoS3xpOL6oMy | None | Ige Duodenum research IgA IgE. | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.229369+00:00 |
| 60 | 0Q7grO9QwcWd1Suf | None | Rank Cajal–Retzius cells IgG3 research researc... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.229822+00:00 |
startswith¶
ln.Transform.filter(name__startswith="Research").df()
| uid | version | name | key | description | type | reference | reference_type | latest_report_id | source_code_id | created_by_id | updated_at | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| id | ||||||||||||
| 22 | u7JLQqQWKkq64cyW | None | Research IgG3 Von Ebner's gland Cajal–Retzius ... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.223935+00:00 |
| 52 | 4K7BKRsDu8TaFnsL | None | Research IgE intestinal IgG4 IgA. | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.228571+00:00 |
| 238 | SOtR9Ha8FLmM1jQI | None | Research IgA IgG3 cluster Duodenum Basket cell... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.265100+00:00 |
| 242 | LSTJUIKegaMUFSQC | None | Research intestine IgG3 investigate IgG1. | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.265693+00:00 |
| 272 | wXIWPIzAgDqVF5X0 | None | Research IgE IgA blue-sensitive cone cells Par... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.270225+00:00 |
| 447 | BeLreE5IfjZXrIhh | None | Research IgA IgA intestinal Lymph node Chromaf... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.301056+00:00 |
| 455 | uCgTsMFrIk5PhIEF | None | Research IgG1 Submandibular glands IgG1 Von Eb... | None | None | notebook | None | None | None | None | 1 | 2024-06-05 10:45:12.302221+00:00 |
Show code cell content
# clean up test instance
!lamin delete --force mydata
!rm -r mydata
Traceback (most recent call last):
File "/opt/hostedtoolcache/Python/3.11.9/x64/bin/lamin", line 8, in <module>
sys.exit(main())
^^^^^^
File "/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/rich_click/rich_command.py", line 367, in __call__
return super().__call__(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/click/core.py", line 1157, in __call__
return self.main(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/rich_click/rich_command.py", line 152, in main
rv = self.invoke(ctx)
^^^^^^^^^^^^^^^^
File "/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/click/core.py", line 1688, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/click/core.py", line 1434, in invoke
return ctx.invoke(self.callback, **ctx.params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/click/core.py", line 783, in invoke
return __callback(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/lamin_cli/__main__.py", line 103, in delete
return delete(instance, force=force)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/lamindb_setup/_delete.py", line 98, in delete
n_objects = check_storage_is_empty(
^^^^^^^^^^^^^^^^^^^^^^^
File "/opt/hostedtoolcache/Python/3.11.9/x64/lib/python3.11/site-packages/lamindb_setup/core/upath.py", line 779, in check_storage_is_empty
raise InstanceNotEmpty(message)
lamindb_setup.core.upath.InstanceNotEmpty: Storage /home/runner/work/lamindb/lamindb/docs/mydata/.lamindb contains 3 objects ('_is_initialized' ignored) - delete them prior to deleting the instance
['/home/runner/work/lamindb/lamindb/docs/mydata/.lamindb/X1Oilr0aXunbPb07S50v.parquet', '/home/runner/work/lamindb/lamindb/docs/mydata/.lamindb/_is_initialized', '/home/runner/work/lamindb/lamindb/docs/mydata/.lamindb/fFM6DufrM8iEwnlfdQ16.jpg', '/home/runner/work/lamindb/lamindb/docs/mydata/.lamindb/nzhAAXAAC7qg23ebl5yF.fastq.gz']