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 'ZTvbFRQrhQeF2KDyXX2u' at '/home/runner/work/lamindb/lamindb/docs/mydata/.lamindb/ZTvbFRQrhQeF2KDyXX2u.jpg'
❗ no run & transform get linked, consider calling ln.track()
✅ storing artifact '7oyPKlXi5foEtDV5gJdP' at '/home/runner/work/lamindb/lamindb/docs/mydata/.lamindb/7oyPKlXi5foEtDV5gJdP.parquet'
❗ no run & transform get linked, consider calling ln.track()
✅ storing artifact 'NrSxVowDV0zXfStQ1blW' at '/home/runner/work/lamindb/lamindb/docs/mydata/.lamindb/NrSxVowDV0zXfStQ1blW.fastq.gz'
Artifact(uid='NrSxVowDV0zXfStQ1blW', 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='2024-06-13 12:06:14 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='2024-06-13 12:06:12 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 ZTvbFRQrhQeF2KDyXX2u None My image None .jpg None 29358 r4tnqmKI_SjrkdLzpuWp4g md5 None None 1 True 1 None None 1 2024-06-13 12:06:14.650238+00:00
2 7oyPKlXi5foEtDV5gJdP None The iris collection None .parquet DataFrame 5629 ah24lV9Ncc8nPL0MumEsdw md5 None None 1 True 1 None None 1 2024-06-13 12:06:14.965248+00:00
3 NrSxVowDV0zXfStQ1blW None My fastq None .fastq.gz None 20 hi7ZmAzz8sfMd3vIQr-57Q md5 None None 1 True 1 None None 1 2024-06-13 12:06:14.973238+00:00

To access the results encoded in a filter statement, execute its return value with one of:

  • .df(): A pandas DataFrame with each record stored as a row.

  • .all(): An indexable django QuerySet.

  • .list(): A list of records.

  • .one(): Exactly one record. Will raise an error if there is none.

  • .one_or_none(): Either one record or None if there is no query result.

Note

filter() returns a QuerySet.

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 7oyPKlXi5foEtDV5gJdP None The iris collection None .parquet DataFrame 5629 ah24lV9Ncc8nPL0MumEsdw md5 None None 1 True 1 None None 1 2024-06-13 12:06:14.965248+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
4 G0V7t3TKKt6ON6MQ None Intestine Cementoblast investigate rank IgD ca... None None notebook None None None None 1 2024-06-13 12:06:19.739796+00:00
17 R0FQUvU5M1osp8fp None Bone Marrow classify Transitional epithelium B... None None notebook None None None None 1 2024-06-13 12:06:19.741853+00:00
21 F5V0SOgVmjEt365V None Igg Skin IgG3 result intestine IgD. None None notebook None None None None 1 2024-06-13 12:06:19.742474+00:00
34 EdThNWTN3DmSBC61 None Igd IgG intestine investigate IgG. None None notebook None None None None 1 2024-06-13 12:06:19.744514+00:00
35 KpLd4osfrDcvMTf9 None Candidate intestine Medulla oblongata IgG3 Med... None None notebook None None None None 1 2024-06-13 12:06:19.744668+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 ZTvbFRQrhQeF2KDyXX2u None My image None .jpg None 29358 r4tnqmKI_SjrkdLzpuWp4g md5 None None 1 True 1 None None 1 2024-06-13 12:06:14.650238+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 7oyPKlXi5foEtDV5gJdP None The iris collection None .parquet DataFrame 5629 ah24lV9Ncc8nPL0MumEsdw md5 None None 1 True 1 None None 1 2024-06-13 12:06:14.965248+00:00
3 NrSxVowDV0zXfStQ1blW None My fastq None .fastq.gz None 20 hi7ZmAzz8sfMd3vIQr-57Q md5 None None 1 True 1 None None 1 2024-06-13 12:06:14.973238+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 ZTvbFRQrhQeF2KDyXX2u None My image None .jpg None 29358 r4tnqmKI_SjrkdLzpuWp4g md5 None None 1 True 1 None None 1 2024-06-13 12:06:14.650238+00:00
3 NrSxVowDV0zXfStQ1blW None My fastq None .fastq.gz None 20 hi7ZmAzz8sfMd3vIQr-57Q md5 None None 1 True 1 None None 1 2024-06-13 12:06:14.973238+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 ZTvbFRQrhQeF2KDyXX2u None My image None .jpg None 29358 r4tnqmKI_SjrkdLzpuWp4g md5 None None 1 True 1 None None 1 2024-06-13 12:06:14.650238+00:00
3 NrSxVowDV0zXfStQ1blW None My fastq None .fastq.gz None 20 hi7ZmAzz8sfMd3vIQr-57Q md5 None None 1 True 1 None None 1 2024-06-13 12:06:14.973238+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 NrSxVowDV0zXfStQ1blW None My fastq None .fastq.gz None 20 hi7ZmAzz8sfMd3vIQr-57Q md5 None None 1 True 1 None None 1 2024-06-13 12:06:14.973238+00:00
2 7oyPKlXi5foEtDV5gJdP None The iris collection None .parquet DataFrame 5629 ah24lV9Ncc8nPL0MumEsdw md5 None None 1 True 1 None None 1 2024-06-13 12:06:14.965248+00:00
1 ZTvbFRQrhQeF2KDyXX2u None My image None .jpg None 29358 r4tnqmKI_SjrkdLzpuWp4g md5 None None 1 True 1 None None 1 2024-06-13 12:06:14.650238+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
7 Bzy9ebSVn0Qa8Rbd None Research Vagina Foveolar cell investigate visu... None None notebook None None None None 1 2024-06-13 12:06:19.740268+00:00
11 9qYEskyaofJ5YOEa None Visualize research Pineal gland Midbrain inves... None None notebook None None None None 1 2024-06-13 12:06:19.740907+00:00
33 bG1MAqUJ2D5TWpNJ None Iga research candidate efficiency IgG2 Foveola... None None notebook None None None None 1 2024-06-13 12:06:19.744359+00:00
46 KObvc4dLlRS7AYM6 None Research IgG1 Transitional epithelium IgM IgG4... None None notebook None None None None 1 2024-06-13 12:06:19.746369+00:00
55 62rUxM02zijQysGx None Outer Root Sheath intestine research. None None notebook None None None None 1 2024-06-13 12:06:19.747785+00:00
56 Swoq1oIqn9KYdoIT None Research Medullary Outer root sheath IgG4 clas... None None notebook None None None None 1 2024-06-13 12:06:19.747946+00:00
69 n1PncK4nDwa6BREr None Helper T Cell IgG2 candidate research research. None None notebook None None None None 1 2024-06-13 12:06:19.749959+00:00
70 sJEha64nq3zDGijE None Research Medullary IgM. None None notebook None None None None 1 2024-06-13 12:06:19.750113+00:00
78 TPIFTnCRu96FIiAI None Research result Medulla oblongata visualize IgG1. None None notebook None None None None 1 2024-06-13 12:06:19.754656+00:00
81 uNGvTyG3hCkI0swB None Skin IgE research Medullary IgG Foveolar cell ... None None notebook None None None None 1 2024-06-13 12:06:19.755113+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
7 Bzy9ebSVn0Qa8Rbd None Research Vagina Foveolar cell investigate visu... None None notebook None None None None 1 2024-06-13 12:06:19.740268+00:00
11 9qYEskyaofJ5YOEa None Visualize research Pineal gland Midbrain inves... None None notebook None None None None 1 2024-06-13 12:06:19.740907+00:00
33 bG1MAqUJ2D5TWpNJ None Iga research candidate efficiency IgG2 Foveola... None None notebook None None None None 1 2024-06-13 12:06:19.744359+00:00
46 KObvc4dLlRS7AYM6 None Research IgG1 Transitional epithelium IgM IgG4... None None notebook None None None None 1 2024-06-13 12:06:19.746369+00:00
55 62rUxM02zijQysGx None Outer Root Sheath intestine research. None None notebook None None None None 1 2024-06-13 12:06:19.747785+00:00
56 Swoq1oIqn9KYdoIT None Research Medullary Outer root sheath IgG4 clas... None None notebook None None None None 1 2024-06-13 12:06:19.747946+00:00
69 n1PncK4nDwa6BREr None Helper T Cell IgG2 candidate research research. None None notebook None None None None 1 2024-06-13 12:06:19.749959+00:00
70 sJEha64nq3zDGijE None Research Medullary IgM. None None notebook None None None None 1 2024-06-13 12:06:19.750113+00:00
78 TPIFTnCRu96FIiAI None Research result Medulla oblongata visualize IgG1. None None notebook None None None None 1 2024-06-13 12:06:19.754656+00:00
81 uNGvTyG3hCkI0swB None Skin IgE research Medullary IgG Foveolar cell ... None None notebook None None None None 1 2024-06-13 12:06:19.755113+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
7 Bzy9ebSVn0Qa8Rbd None Research Vagina Foveolar cell investigate visu... None None notebook None None None None 1 2024-06-13 12:06:19.740268+00:00
46 KObvc4dLlRS7AYM6 None Research IgG1 Transitional epithelium IgM IgG4... None None notebook None None None None 1 2024-06-13 12:06:19.746369+00:00
56 Swoq1oIqn9KYdoIT None Research Medullary Outer root sheath IgG4 clas... None None notebook None None None None 1 2024-06-13 12:06:19.747946+00:00
70 sJEha64nq3zDGijE None Research Medullary IgM. None None notebook None None None None 1 2024-06-13 12:06:19.750113+00:00
78 TPIFTnCRu96FIiAI None Research result Medulla oblongata visualize IgG1. None None notebook None None None None 1 2024-06-13 12:06:19.754656+00:00
110 7WK6LtTMLfNLAoJH None Research visualize IgM Midbrain IgG3 Midbrain ... None None notebook None None None None 1 2024-06-13 12:06:19.759551+00:00
120 D3xGpnFQkyhQlFVI None Research Skin Pineal gland study. None None notebook None None None None 1 2024-06-13 12:06:19.761024+00:00
169 NXMqCsuItc6YOReh None Research Spermatocyte IgD Cementoblast Helper ... None None notebook None None None None 1 2024-06-13 12:06:19.771042+00:00
214 KZQnSYw9FVacDGkj None Research Pineal gland study IgG2 Medullary Tra... None None notebook None None None None 1 2024-06-13 12:06:19.777707+00:00
225 MBszcF3Dv2cC4Ouc None Research IgD Spermatocyte classify Medulla obl... None None notebook None None None None 1 2024-06-13 12:06:19.779374+00:00
250 FDsEeQsq6f3FKDUO None Research cluster efficiency Vagina Medullary e... None None notebook None None None None 1 2024-06-13 12:06:19.785723+00:00
285 W6TWfNGmqw36PY4e None Research IgG IgD IgG3 IgG4 IgG4. None None notebook None None None None 1 2024-06-13 12:06:19.790872+00:00
324 TWfDDHrzyx1ig4xY None Research visualize IgG2 IgG4 classify Medulla ... None None notebook None None None None 1 2024-06-13 12:06:19.799247+00:00
469 22gI3AKhiaezPUYu None Research Outer pillar cells of organ of Corti ... None None notebook None None None None 1 2024-06-13 12:06:19.899530+00:00
Hide 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/7oyPKlXi5foEtDV5gJdP.parquet', '/home/runner/work/lamindb/lamindb/docs/mydata/.lamindb/NrSxVowDV0zXfStQ1blW.fastq.gz', '/home/runner/work/lamindb/lamindb/docs/mydata/.lamindb/ZTvbFRQrhQeF2KDyXX2u.jpg', '/home/runner/work/lamindb/lamindb/docs/mydata/.lamindb/_is_initialized']