Release 0.10.0

.github/workflows/run-pytest.yml

@@ -12,7 +12,7 @@ jobs:
   pytest:
     strategy:
       matrix:
-        python-version: ["3.9", "3.11"]
+        python-version: ["3.9", "3.12"]
         os: [ubuntu-latest] # can't use macOS when using service containers or container jobs
     runs-on: ${{ matrix.os }}
     services:
@@ -27,21 +27,23 @@ jobs:
           - 5432:5432
           options: --health-cmd pg_isready --health-interval 10s --health-timeout 5s --health-retries 5
     steps:
-    - uses: actions/checkout@v2
-
-    - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2
+    - uses: actions/checkout@v4
+    - name: Set up Python
+      uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
 
+    - name: Install uv
+      run: pip install uv
+
     - name: Install dev dependencies
-      run: if [ -f requirements/requirements-dev.txt ]; then pip install -r requirements/requirements-dev.txt; fi
+      run: if [ -f requirements/requirements-dev.txt ]; then uv pip install -r requirements/requirements-dev.txt --system; fi
 
     - name: Install test dependencies
-      run: if [ -f requirements/requirements-test.txt ]; then pip install -r requirements/requirements-test.txt; fi
+      run: if [ -f requirements/requirements-test.txt ]; then uv pip install -r requirements/requirements-test.txt --system; fi
 
     - name: Install package
-      run: python -m pip install .
+      run: uv pip install . --system
 
     - name: Run pytest tests
       run: pytest tests -x -vv

bbconf/_version.py

@@ -1 +1 @@
-__version__ = "0.9.0"
+__version__ = "0.10.0"

bbconf/bbagent.py

@@ -1,3 +1,5 @@
+import logging
+
 from functools import cached_property
 from pathlib import Path
 from typing import List, Union
@@ -12,19 +14,26 @@
 from bbconf.modules.bedsets import BedAgentBedSet
 from bbconf.modules.objects import BBObjects
 
+from .const import PKG_NAME
+
+_LOGGER = logging.getLogger(PKG_NAME)
+
 
 class BedBaseAgent(object):
     def __init__(
         self,
         config: Union[Path, str],
+        init_ml: bool = True,
     ):
         """
-        Initialize connection to the pep_db database. You can use The basic connection parameters
+        Initialize connection to the pep_db database. You can use the basic connection parameters
         or libpq connection string.
 
+        :param config: path to the configuration file
+        :param init_ml: initialize ML models for search (default: True)
         """
 
-        self.config = BedBaseConfig(config)
+        self.config = BedBaseConfig(config, init_ml)
 
         self._bed = BedAgentBedFile(self.config, self)
         self._bedset = BedAgentBedSet(self.config)
@@ -42,6 +51,13 @@ def bedset(self) -> BedAgentBedSet:
     def objects(self) -> BBObjects:
         return self._objects
 
+    def __repr__(self) -> str:
+        repr = f"BedBaseAgent(config={self.config})"
+        repr += f"\n{self.bed}"
+        repr += f"\n{self.bedset}"
+        repr += f"\n{self.objects}"
+        return repr
+
     def get_stats(self) -> StatsReturn:
         """
         Get statistics for a bed file

bbconf/config_parser/bedbaseconfig.py

@@ -41,17 +41,38 @@
 _LOGGER = logging.getLogger(PKG_NAME)
 
 
-class BedBaseConfig:
-    def __init__(self, config: Union[Path, str]):
+class BedBaseConfig(object):
+    """
+    Class to handle BEDbase configuration file and create objects for different modules.
+    """
+
+    def __init__(self, config: Union[Path, str], init_ml: bool = True):
+        """
+        Initialize BedBaseConfig object
+
+        :param config: path to the configuration file
+        :param init_ml: initialize machine learning models used for search
+        """
+
         self.cfg_path = get_bedbase_cfg(config)
         self._config = self._read_config_file(self.cfg_path)
-
         self._db_engine = self._init_db_engine()
+
         self._qdrant_engine = self._init_qdrant_backend()
         self._qdrant_text_engine = self._init_qdrant_text_backend()
-        self._b2bsi = self._init_b2bsi_object()
-        self._r2v = self._init_r2v_object()
-        self._bivec = self._init_bivec_object()
+
+        if init_ml:
+            self._b2bsi = self._init_b2bsi_object()
+            self._r2v = self._init_r2v_object()
+            self._bivec = self._init_bivec_object()
+        else:
+            _LOGGER.info(
+                f"Skipping initialization of ML models, init_ml parameter set to False."
+            )
+
+            self._b2bsi = None
+            self._r2v = None
+            self._bivec = None
 
         self._phc = self._init_pephubclient()
         self._boto3_client = self._init_boto3_client()
@@ -182,6 +203,11 @@ def zarr_root(self) -> Union[Z_GROUP, None]:
         return zarr.group(store=cache, overwrite=False)
 
     def _init_db_engine(self) -> BaseEngine:
+        """
+        Create database engine object using credentials provided in config file
+        """
+
+        _LOGGER.info(f"Initializing database engine...")
         return BaseEngine(
             host=self._config.database.host,
             port=self._config.database.port,
@@ -197,6 +223,8 @@ def _init_qdrant_backend(self) -> QdrantBackend:
 
         :return: QdrantClient
         """
+
+        _LOGGER.info(f"Initializing qdrant engine...")
         try:
             return QdrantBackend(
                 collection=self._config.qdrant.file_collection,
@@ -210,19 +238,27 @@ def _init_qdrant_backend(self) -> QdrantBackend:
                 f"error in Connection to qdrant! skipping... Error: {err}", UserWarning
             )
 
-    def _init_qdrant_text_backend(self) -> QdrantBackend:
+    def _init_qdrant_text_backend(self) -> Union[QdrantBackend, None]:
         """
         Create qdrant client text embedding object using credentials provided in config file
 
         :return: QdrantClient
         """
 
-        return QdrantBackend(
-            dim=TEXT_EMBEDDING_DIMENSION,
-            collection=self.config.qdrant.text_collection,
-            qdrant_host=self.config.qdrant.host,
-            qdrant_api_key=self.config.qdrant.api_key,
-        )
+        _LOGGER.info(f"Initializing qdrant text engine...")
+        try:
+            return QdrantBackend(
+                dim=TEXT_EMBEDDING_DIMENSION,
+                collection=self.config.qdrant.text_collection,
+                qdrant_host=self.config.qdrant.host,
+                qdrant_api_key=self.config.qdrant.api_key,
+            )
+        except Exception as e:
+            _LOGGER.error(f"Error in Connection to qdrant text! skipping {e}")
+            warnings.warn(
+                "Error in Connection to qdrant text! skipping...", UserWarning
+            )
+            return None
 
     def _init_bivec_object(self) -> Union[BiVectorSearchInterface, None]:
         """
@@ -231,9 +267,11 @@ def _init_bivec_object(self) -> Union[BiVectorSearchInterface, None]:
         :return: BiVectorSearchInterface
         """
 
+        _LOGGER.info(f"Initializing BiVectorBackend...")
         search_backend = BiVectorBackend(
             metadata_backend=self._qdrant_text_engine, bed_backend=self._qdrant_engine
         )
+        _LOGGER.info(f"Initializing BiVectorSearchInterface...")
         search_interface = BiVectorSearchInterface(
             backend=search_backend,
             query2vec=self.config.path.text2vec,
@@ -247,6 +285,7 @@ def _init_b2bsi_object(self) -> Union[BED2BEDSearchInterface, None]:
         :return: Bed2BEDSearchInterface object
         """
         try:
+            _LOGGER.info(f"Initializing search interfaces...")
             return BED2BEDSearchInterface(
                 backend=self.qdrant_engine,
                 query2vec=BED2Vec(model=self._config.path.region2vec),
@@ -267,6 +306,7 @@ def _init_pephubclient() -> Union[PEPHubClient, None]:
         :return: PephubClient
         """
         try:
+            _LOGGER.info(f"Initializing PEPHub client...")
             return PEPHubClient()
         except Exception as e:
             _LOGGER.error(f"Error in creating PephubClient object: {e}")
@@ -298,6 +338,7 @@ def _init_r2v_object(self) -> Union[Region2VecExModel, None]:
         Create Region2VecExModel object using credentials provided in config file
         """
         try:
+            _LOGGER.info(f"Initializing R2V object...")
             return Region2VecExModel(self.config.path.region2vec)
         except Exception as e:
             _LOGGER.error(f"Error in creating Region2VecExModel object: {e}")

bbconf/db_utils.py

@@ -130,6 +130,9 @@ class Bed(Base):
     ref_classifier: Mapped["GenomeRefStats"] = relationship(
         "GenomeRefStats", back_populates="bed", cascade="all, delete-orphan"
     )
+    processed: Mapped[bool] = mapped_column(
+        default=False, comment="Whether the bed file was processed"
+    )
 
 
 class BedMetadata(Base):
@@ -255,6 +258,11 @@ class Files(Base):
     bedfile: Mapped["Bed"] = relationship("Bed", back_populates="files")
     bedset: Mapped["BedSets"] = relationship("BedSets", back_populates="files")
 
+    __table_args__ = (
+        UniqueConstraint("name", "bedfile_id"),
+        UniqueConstraint("name", "bedset_id"),
+    )
+
 
 class BedFileBedSetRelation(Base):
     __tablename__ = "bedfile_bedset_relation"
@@ -303,6 +311,10 @@ class BedSets(Base):
     author: Mapped[str] = mapped_column(nullable=True, comment="Author of the bedset")
     source: Mapped[str] = mapped_column(nullable=True, comment="Source of the bedset")
 
+    processed: Mapped[bool] = mapped_column(
+        default=False, comment="Whether the bedset was processed"
+    )
+
 
 class Universes(Base):
     __tablename__ = "universes"
@@ -339,7 +351,7 @@ class TokenizedBed(Base):
         nullable=False,
     )
     universe_id: Mapped[str] = mapped_column(
-        ForeignKey("universes.id", ondelete="CASCADE", passive_deletes=True),
+        ForeignKey("universes.id", ondelete="CASCADE"),
         primary_key=True,
         index=True,
         nullable=False,
@@ -352,7 +364,7 @@ class TokenizedBed(Base):
     universe: Mapped["Universes"] = relationship(
         "Universes",
         back_populates="tokenized",
-        passive_deletes=True,
+        passive_deletes="all",
     )
 
 

bbconf/exceptions.py

@@ -83,3 +83,9 @@ class QdrantInstanceNotInitializedError(BedBaseConfError):
     """Error type for missing qdrant instance"""
 
     pass
+
+
+class BedSetTrackHubLimitError(BedBaseConfError):
+    """Limit for visualizing trackhub exceeded"""
+
+    pass

bbconf/helpers.py

@@ -22,6 +22,8 @@ def get_bedbase_cfg(cfg: str = None) -> str:
         Optional, the $BEDBASE config env var will be used if not provided
     :return str: absolute configuration file path
     """
+
+    _LOGGER.info(f"Loading configuration file: {cfg}")
     selected_cfg = select_config(config_filepath=cfg, config_env_vars=CFG_ENV_VARS)
     if not selected_cfg:
         raise BedBaseConnectionError(

bbconf/models/bed_models.py

@@ -75,7 +75,7 @@ class BedStatsModel(BaseModel):
 
 
 class BedPEPHub(BaseModel):
-    sample_name: str
+    sample_name: str = ""
     genome: str = ""
     organism: str = ""
     species_id: str = ""
@@ -192,8 +192,8 @@ class BedListResult(BaseModel):
 
 class QdrantSearchResult(BaseModel):
     id: str
-    payload: dict
-    score: float
+    payload: dict = None
+    score: float = None
     metadata: Union[BedMetadataBasic, None] = None
 
 
@@ -233,3 +233,9 @@ class RefGenValidModel(BaseModel):
     tier_ranking: int
 
     model_config = ConfigDict(extra="forbid")
+
+
+class RefGenValidReturnModel(BaseModel):
+    id: str
+    provided_genome: Union[str, None] = None
+    compared_genome: List[RefGenValidModel]