diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 976ee65e2..0323fc812 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -71,8 +71,15 @@ repos: rev: 6.3.0 hooks: - id: pydocstyle - args: [--convention=google] + args: [--convention=google, --add-ignore=D107] + - repo: https://github.com/lovesegfault/beautysh rev: v6.2.1 hooks: - id: beautysh + + - repo: https://github.com/jsh9/pydoclint + rev: 0.3.8 + hooks: + - id: pydoclint + args: [--style=google, --check-return-types=True, --config=pyproject.toml src] diff --git a/Makefile b/Makefile index 49bba7b4a..b3a93d4f1 100644 --- a/Makefile +++ b/Makefile @@ -21,8 +21,11 @@ setup-dev: ## Setup development environment @. utils/install_dependencies.sh check: ## Lint and format code - @echo "Linting..." + @echo "Linting API..." @poetry run ruff src/otg . + @echo "Linting docstrings..." + @poetry run pydoclint --config=pyproject.toml src + @poetry run pydoclint --config=pyproject.toml --skip-checking-short-docstrings=true tests @echo "Formatting..." @poetry run black src/otg . @poetry run isort src/otg . diff --git a/poetry.lock b/poetry.lock index 986f489ea..644652339 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,15 +1,10 @@ -# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. - 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{file = "google_cloud_bigquery-3.12.0-py2.py3-none-any.whl", hash = "sha256:e68851addfe0394ab7662bd58aa0e5a4527e7156568cc0410129ccb8a460a009"}, -] [package.dependencies] -google-api-core = {version = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0dev", extras = ["grpc"]} +google-api-core = {version = ">=1.31.5,<2.0.0 || >2.3.0,<3.0.0dev", extras = ["grpc"]} google-cloud-core = ">=1.6.0,<3.0.0dev" google-resumable-media = ">=0.6.0,<3.0dev" grpcio = ">=1.47.0,<2.0dev" @@ -2464,15 +1717,12 @@ tqdm = ["tqdm (>=4.7.4,<5.0.0dev)"] name = "google-cloud-bigquery-datatransfer" version = "3.12.1" description = "Google Cloud Bigquery Datatransfer API client library" +category = "dev" optional = false python-versions = ">=3.7" -files = [ - {file = "google-cloud-bigquery-datatransfer-3.12.1.tar.gz", hash = "sha256:b845a74081ace32c9bbae93382b02a69db8560a356f61fd6a2e5f63334958148"}, - {file = "google_cloud_bigquery_datatransfer-3.12.1-py2.py3-none-any.whl", hash = "sha256:cb24e51155fb221cfc09f2a5b047f2dc8dbb1d106b84463c1300af0a6dcc7bae"}, -] [package.dependencies] -google-api-core = {version = ">=1.34.0,<2.0.dev0 || >=2.11.dev0,<3.0.0dev", extras = ["grpc"]} +google-api-core = {version = ">=1.34.0,<2.0.0 || >=2.11.0,<3.0.0dev", extras = ["grpc"]} proto-plus = ">=1.22.0,<2.0.0dev" protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev" @@ -2480,15 +1730,12 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4 name = "google-cloud-bigquery-storage" version = "2.22.0" description = "Google Cloud Bigquery Storage API client library" +category = "dev" optional = false python-versions = ">=3.7" -files = [ - 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-[package.extras] -docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"] -testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"] - -[metadata] -lock-version = "2.0" -python-versions = "3.10.8" -content-hash = "d241444465af34e80440e12ea7405f95445ba0a9bd8a5e3458a79ff9ae3cf2a5" diff --git a/pyproject.toml b/pyproject.toml index 6267a4f5b..523c240b6 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -61,6 +61,10 @@ google-cloud-dataproc = "^5.4.1" apache-airflow = "^2.7.0" apache-airflow-providers-google = "^10.10.1" + +[tool.poetry.group.dev-dependencies.dependencies] +pydoclint = "^0.3.8" + [tool.semantic_release] branch = "main" version_variable = "src/otg/__init__.py:__version__" @@ -112,3 +116,12 @@ docstring-quotes = "double" [tool.ruff.pydocstyle] convention = "google" + +[tool.pydoclint] +style = 'google' +exclude = '\.git|\.venv|__init__.py' +require-return-section-when-returning-nothing = false +check-return-types = true +allow-init-docstring = true +arg-type-hints-in-docstring = true +skip-checking-short-docstrings = false diff --git a/src/airflow/dags/common_airflow.py b/src/airflow/dags/common_airflow.py index 97a82968d..d56ba40ff 100644 --- a/src/airflow/dags/common_airflow.py +++ b/src/airflow/dags/common_airflow.py @@ -3,6 +3,7 @@ from __future__ import annotations import os +from typing import Any import pendulum from airflow.providers.google.cloud.operators.dataproc import ( @@ -55,12 +56,22 @@ def create_cluster( - cluster_name, - master_machine_type="n1-standard-4", - worker_machine_type="n1-standard-16", - num_workers=0, -): - """Generate an Airflow task to create a Dataproc cluster. Common parameters are reused, and varying parameters can be specified as needed.""" + cluster_name: str, + master_machine_type: str = "n1-standard-4", + worker_machine_type: str = "n1-standard-16", + num_workers: int = 0, +) -> DataprocCreateClusterOperator: + """Generate an Airflow task to create a Dataproc cluster. Common parameters are reused, and varying parameters can be specified as needed. + + Args: + cluster_name (str): Name of the cluster. + master_machine_type (str): Machine type for the master node. Defaults to "n1-standard-4". + worker_machine_type (str): Machine type for the worker nodes. Defaults to "n1-standard-16". + num_workers (int): Number of worker nodes. Defaults to 0. + + Returns: + DataprocCreateClusterOperator: Airflow task to create a Dataproc cluster. + """ cluster_generator_config = ClusterGenerator( project_id=project_id, zone=zone, @@ -89,8 +100,20 @@ def create_cluster( ) -def submit_job(cluster_name, task_id, job_type, job_specification): - """Submit an arbitrary job to a Dataproc cluster.""" +def submit_job( + cluster_name: str, task_id: str, job_type: str, job_specification: dict[str, Any] +) -> DataprocSubmitJobOperator: + """Submit an arbitrary job to a Dataproc cluster. + + Args: + cluster_name (str): Name of the cluster. + task_id (str): Name of the task. + job_type (str): Type of the job to submit. + job_specification (dict[str, Any]): Specification of the job to submit. + + Returns: + DataprocSubmitJobOperator: Airflow task to submit an arbitrary job to a Dataproc cluster. + """ return DataprocSubmitJobOperator( task_id=task_id, region=region, @@ -104,17 +127,30 @@ def submit_job(cluster_name, task_id, job_type, job_specification): ) -def submit_pyspark_job(cluster_name, task_id, python_module_path, args): - """Submit a PySpark job to a Dataproc cluster.""" +def submit_pyspark_job( + cluster_name: str, task_id: str, python_module_path: str, args: dict[str, Any] +) -> DataprocSubmitJobOperator: + """Submit a PySpark job to a Dataproc cluster. + + Args: + cluster_name (str): Name of the cluster. + task_id (str): Name of the task. + python_module_path (str): Path to the Python module to run. + args (dict[str, Any]): Arguments to pass to the Python module. + + Returns: + DataprocSubmitJobOperator: Airflow task to submit a PySpark job to a Dataproc cluster. + """ + formatted_args = [] if isinstance(args, dict): - args = [f"--{arg}={val}" for arg, val in args.items()] + formatted_args = [f"--{arg}={val}" for arg, val in args.items()] return submit_job( cluster_name=cluster_name, task_id=task_id, job_type="pyspark_job", job_specification={ "main_python_file_uri": f"{initialisation_base_path}/{python_module_path}", - "args": args, + "args": formatted_args, "properties": { "spark.jars": "/opt/conda/miniconda3/lib/python3.10/site-packages/hail/backend/hail-all-spark.jar", "spark.driver.extraClassPath": "/opt/conda/miniconda3/lib/python3.10/site-packages/hail/backend/hail-all-spark.jar", @@ -126,8 +162,15 @@ def submit_pyspark_job(cluster_name, task_id, python_module_path, args): ) -def install_dependencies(cluster_name): - """Install dependencies on a Dataproc cluster.""" +def install_dependencies(cluster_name: str) -> DataprocSubmitJobOperator: + """Install dependencies on a Dataproc cluster. + + Args: + cluster_name (str): Name of the cluster. + + Returns: + DataprocSubmitJobOperator: Airflow task to install dependencies on a Dataproc cluster. + """ return submit_job( cluster_name=cluster_name, task_id="install_dependencies", @@ -146,8 +189,15 @@ def install_dependencies(cluster_name): ) -def delete_cluster(cluster_name): - """Generate an Airflow task to delete a Dataproc cluster.""" +def delete_cluster(cluster_name: str) -> DataprocDeleteClusterOperator: + """Generate an Airflow task to delete a Dataproc cluster. + + Args: + cluster_name (str): Name of the cluster. + + Returns: + DataprocDeleteClusterOperator: Airflow task to delete a Dataproc cluster. + """ return DataprocDeleteClusterOperator( task_id="delete_cluster", project_id=project_id, diff --git a/src/conftest.py b/src/conftest.py index 2c90156d1..7556291ec 100644 --- a/src/conftest.py +++ b/src/conftest.py @@ -10,14 +10,17 @@ @pytest.fixture(scope="session", autouse=True) -def spark(doctest_namespace: dict[str, Any], tmp_path_factory: Any) -> SparkSession: +def spark( + doctest_namespace: dict[str, Any], tmp_path_factory: pytest.TempPathFactory +) -> SparkSession: """Local spark session for testing purposes. It returns a session and make it available to doctests through the `spark` namespace. Args: - doctest_namespace (Dict[str, Any]): pytest namespace for doctests + doctest_namespace (dict[str, Any]): pytest namespace for doctests + tmp_path_factory (pytest.TempPathFactory): pytest tmp_path_factory Returns: SparkSession: local spark session diff --git a/src/otg/common/Liftover.py b/src/otg/common/Liftover.py index 0899b36ae..e0ac577c9 100644 --- a/src/otg/common/Liftover.py +++ b/src/otg/common/Liftover.py @@ -26,17 +26,15 @@ class LiftOverSpark: - If regions are provided, the mapping is dropped if the new region is reversed (mapped_start > mapped_end). - If regions are provided, the mapping is dropped if the difference of the lenght of the mapped region and original is larger than a threshold. - When lifting over intervals, only unique coordinates are lifted, they joined back to the original dataframe. + + Args: + chain_file (str): Path to the chain file + max_difference (int): Maximum difference between the length of the mapped region and the original region. Defaults to 100. """ - def __init__( + def __init__( # noqa: D107 self: LiftOverSpark, chain_file: str, max_difference: int = 100 ) -> None: - """Intialise LiftOverSpark object. - - Args: - chain_file (str): Path to the chain file - max_difference (int): Maximum difference between the length of the mapped region and the original region. Defaults to 100. - """ self.chain_file = chain_file self.max_difference = max_difference diff --git a/src/otg/common/schemas.py b/src/otg/common/schemas.py index c45d8b42c..af88a0ac3 100644 --- a/src/otg/common/schemas.py +++ b/src/otg/common/schemas.py @@ -29,8 +29,8 @@ def flatten_schema(schema: StructType, prefix: str = "") -> list: """It takes a Spark schema and returns a list of all fields in the schema once flattened. Args: - schema: The schema of the dataframe - prefix: The prefix to prepend to the field names. + schema (StructType): The schema of the dataframe + prefix (str): The prefix to prepend to the field names. Defaults to "". Returns: list: A list of all the columns in the dataframe. diff --git a/src/otg/common/session.py b/src/otg/common/session.py index a8a83837c..8296e5bc3 100644 --- a/src/otg/common/session.py +++ b/src/otg/common/session.py @@ -2,7 +2,7 @@ from __future__ import annotations -from typing import TYPE_CHECKING, Any, Dict +from typing import TYPE_CHECKING, Any from pyspark.conf import SparkConf from pyspark.sql import SparkSession @@ -13,25 +13,24 @@ class Session: - """Spark session class.""" + """This class provides a Spark session and logger. - def __init__( + Args: + spark_uri (str): Spark URI. Defaults to "local[*]". + write_mode (str): Spark write mode. Defaults to "errorifexists". + app_name (str): Spark application name. Defaults to "otgenetics". + hail_home (str | None): Path to Hail installation. Defaults to None. + extended_conf (SparkConf | None): Extended Spark configuration. Defaults to None. + """ + + def __init__( # noqa: D107 self: Session, spark_uri: str = "local[*]", write_mode: str = "errorifexists", app_name: str = "otgenetics", hail_home: str | None = None, - extended_conf: SparkConf = None, - ) -> None: - """Initialises spark session and logger. - - Args: - spark_uri (str): spark uri - app_name (str): spark application name - write_mode (str): spark write mode - hail_home (str | None): path to hail installation - extended_conf (SparkConf): extended spark configuration - """ + extended_conf: SparkConf | None = None, + ) -> None: # noqa: D107 merged_conf = self._create_merged_config(hail_home, extended_conf) self.spark = ( @@ -44,7 +43,11 @@ def __init__( self.write_mode = write_mode def _default_config(self: Session) -> SparkConf: - """Default spark configuration.""" + """Default spark configuration. + + Returns: + SparkConf: Default spark configuration. + """ return ( SparkConf() # Dynamic allocation @@ -57,7 +60,14 @@ def _default_config(self: Session) -> SparkConf: ) def _hail_config(self: Session, hail_home: str | None) -> SparkConf: - """Returns the Hail specific Spark configuration.""" + """Returns the Hail specific Spark configuration. + + Args: + hail_home (str | None): Path to Hail installation. Defaults to None. + + Returns: + SparkConf: Hail specific Spark configuration. + """ if hail_home is None: return SparkConf() return ( @@ -76,7 +86,15 @@ def _hail_config(self: Session, hail_home: str | None) -> SparkConf: def _create_merged_config( self: Session, hail_home: str | None, extended_conf: SparkConf ) -> SparkConf: - """Merges the default, and optionally the Hail and extended configurations if provided.""" + """Merges the default, and optionally the Hail and extended configurations if provided. + + Args: + hail_home (str | None): Path to Hail installation. Defaults to None. + extended_conf (SparkConf): Extended Spark configuration. + + Returns: + SparkConf: Merged Spark configuration. + """ all_settings = ( self._default_config().getAll() + self._hail_config(hail_home).getAll() @@ -87,14 +105,14 @@ def _create_merged_config( return SparkConf().setAll(all_settings) def read_parquet( - self: Session, path: str, schema: StructType, **kwargs: Dict[str, Any] + self: Session, path: str, schema: StructType, **kwargs: dict[str, Any] ) -> DataFrame: """Reads parquet dataset with a provided schema. Args: path (str): parquet dataset path schema (StructType): Spark schema - **kwargs: Additional arguments to pass to spark.read.parquet + **kwargs (dict[str, Any]): Additional arguments to pass to spark.read.parquet Returns: DataFrame: Dataframe with provided schema @@ -103,14 +121,15 @@ def read_parquet( class Log4j: - """Log4j logger class.""" + """Log4j logger class. - def __init__(self: Log4j, spark: SparkSession) -> None: - """Initialise logger. + This class provides a wrapper around the Log4j logging system. - Args: - spark (SparkSession): Available spark session - """ + Args: + spark (SparkSession): The Spark session used to access Spark context and Log4j logging. + """ + + def __init__(self, spark: SparkSession) -> None: # noqa: D107 # get spark app details with which to prefix all messages log4j = spark.sparkContext._jvm.org.apache.log4j # type: ignore self.logger = log4j.Logger.getLogger(__name__) @@ -123,9 +142,6 @@ def error(self: Log4j, message: str) -> None: Args: message (str): Error message to write to log - - Returns: - _type_: None """ self.logger.error(message) return None @@ -135,9 +151,6 @@ def warn(self: Log4j, message: str) -> None: Args: message (str): Warning messsage to write to log - - Returns: - _type_: None """ self.logger.warn(message) return None @@ -147,9 +160,6 @@ def info(self: Log4j, message: str) -> None: Args: message (str): Information message to write to log - - Returns: - _type_: None """ self.logger.info(message) return None diff --git a/src/otg/common/spark_helpers.py b/src/otg/common/spark_helpers.py index 0c6a28934..741812c45 100644 --- a/src/otg/common/spark_helpers.py +++ b/src/otg/common/spark_helpers.py @@ -77,7 +77,15 @@ def nullify_empty_array(column: Column) -> Column: def get_top_ranked_in_window(df: DataFrame, w: WindowSpec) -> DataFrame: - """Returns the record with the top rank within each group of the window.""" + """Returns the record with the top rank within each group of the window. + + Args: + df (DataFrame): The DataFrame to be processed. + w (WindowSpec): The window to be used for ranking. + + Returns: + DataFrame: The DataFrame with the record with the top rank within each group of the window. + """ return ( df.withColumn("row_number", f.row_number().over(w)) .filter(f.col("row_number") == 1) @@ -94,7 +102,7 @@ def get_record_with_minimum_value( Args: df (DataFrame): The DataFrame to be processed. - grouping_col (str): The column name(s) to group the DataFrame by. + grouping_col (Column | str | list[Column | str]): The column(s) to group the DataFrame by. sorting_col (str): The column name to sort the DataFrame by. Returns: @@ -113,7 +121,7 @@ def get_record_with_maximum_value( Args: df (DataFrame): The DataFrame to be processed. - grouping_col (str): The column name(s) to group the DataFrame by. + grouping_col (Column | str | list[Column | str]): The column(s) to group the DataFrame by. sorting_col (str): The column name to sort the DataFrame by. Returns: @@ -231,7 +239,15 @@ def column2camel_case(col_name: str) -> str: def order_array_of_structs_by_field(column_name: str, field_name: str) -> Column: - """Sort a column of array of structs by a field in descending order, nulls last.""" + """Sort a column of array of structs by a field in descending order, nulls last. + + Args: + column_name (str): Column name + field_name (str): Field name + + Returns: + Column: Sorted column + """ return f.expr( f""" array_sort( diff --git a/src/otg/common/utils.py b/src/otg/common/utils.py index d91cab45d..744b62d0c 100644 --- a/src/otg/common/utils.py +++ b/src/otg/common/utils.py @@ -3,7 +3,7 @@ import sys from math import floor, log10 -from typing import TYPE_CHECKING, List, Tuple +from typing import TYPE_CHECKING, Tuple import hail as hl from pyspark.sql import functions as f @@ -22,13 +22,11 @@ def parse_region(region: str) -> Tuple[str, int, int]: Args: region (str): Genomic region expected to follow chr##:#,###-#,### format or ##:####-#####. - Raises: - ValueError: If the end and start positions cannot be casted to integer or not all - three values value error is raised. - Returns: Tuple[str, int, int]: Chromosome, start position, end position + Raises: + ValueError: If the end and start positions cannot be casted to integer or not all three values value error is raised. Examples: >>> parse_region('chr6:28,510,120-33,480,577') @@ -114,7 +112,7 @@ def calculate_confidence_interval( def convert_odds_ratio_to_beta( beta: Column, odds_ratio: Column, standard_error: Column -) -> List[Column]: +) -> list[Column]: """Harmonizes effect and standard error to beta. Args: @@ -123,7 +121,7 @@ def convert_odds_ratio_to_beta( standard_error (Column): Standard error of the effect Returns: - tuple: beta, standard error + list[Column]: beta, standard error Examples: >>> df = spark.createDataFrame([{"beta": 0.1, "oddsRatio": 1.1, "standardError": 0.1}, {"beta": None, "oddsRatio": 1.1, "standardError": 0.1}, {"beta": 0.1, "oddsRatio": None, "standardError": 0.1}, {"beta": 0.1, "oddsRatio": 1.1, "standardError": None}]) @@ -154,15 +152,14 @@ def convert_odds_ratio_to_beta( return [beta, standard_error] -def parse_pvalue(pv: Column) -> List[Column]: +def parse_pvalue(pv: Column) -> list[Column]: """This function takes a p-value string and returns two columns mantissa (float), exponent (integer). Args: pv (Column): P-value as string Returns: - Column: p-value mantissa (float) - Column: p-value exponent (integer) + list[Column]: pValueMantissa (float), pValueExponent (integer) Examples: >>> d = [("0.01",),("4.2E-45",),("43.2E5",),("0",),("1",)] @@ -213,12 +210,12 @@ def convert_gnomad_position_to_ensembl( the position is unchanged. More info about the problem: https://www.biostars.org/p/84686/ Args: - position (Column): Column - reference (Column): The reference allele. - alternate (Column): The alternate allele + position (Column): Position of the variant in GnomAD's coordinates system. + reference (Column): The reference allele in GnomAD's coordinates system. + alternate (Column): The alternate allele in GnomAD's coordinates system. Returns: - The position of the variant in the Ensembl genome. + Column: The position of the variant in the Ensembl genome. Examples: >>> d = [(1, "A", "C"), (2, "AA", "C"), (3, "A", "AA")] @@ -277,6 +274,9 @@ def split_pvalue(pvalue: float) -> tuple[float, int]: Returns: tuple[float, int]: Tuple with mantissa and exponent + Raises: + ValueError: If p-value is not between 0 and 1 + Examples: >>> split_pvalue(0.00001234) (1.234, -5) diff --git a/src/otg/dataset/colocalisation.py b/src/otg/dataset/colocalisation.py index c3c650885..a704e68a4 100644 --- a/src/otg/dataset/colocalisation.py +++ b/src/otg/dataset/colocalisation.py @@ -17,5 +17,9 @@ class Colocalisation(Dataset): @classmethod def get_schema(cls: type[Colocalisation]) -> StructType: - """Provides the schema for the Colocalisation dataset.""" + """Provides the schema for the Colocalisation dataset. + + Returns: + StructType: Schema for the Colocalisation dataset + """ return parse_spark_schema("colocalisation.json") diff --git a/src/otg/dataset/dataset.py b/src/otg/dataset/dataset.py index ad92eb80b..8a3c98192 100644 --- a/src/otg/dataset/dataset.py +++ b/src/otg/dataset/dataset.py @@ -3,7 +3,7 @@ from abc import ABC, abstractmethod from dataclasses import dataclass -from typing import TYPE_CHECKING, Any, Dict +from typing import TYPE_CHECKING, Any from otg.common.schemas import flatten_schema @@ -30,31 +30,56 @@ def __post_init__(self: Dataset) -> None: @property def df(self: Dataset) -> DataFrame: - """Dataframe included in the Dataset.""" + """Dataframe included in the Dataset. + + Returns: + DataFrame: Dataframe included in the Dataset + """ return self._df @df.setter def df(self: Dataset, new_df: DataFrame) -> None: # noqa: CCE001 - """Dataframe setter.""" + """Dataframe setter. + + Args: + new_df (DataFrame): New dataframe to be included in the Dataset + """ self._df: DataFrame = new_df self.validate_schema() @property def schema(self: Dataset) -> StructType: - """Dataframe expected schema.""" + """Dataframe expected schema. + + Returns: + StructType: Dataframe expected schema + """ return self._schema @classmethod @abstractmethod def get_schema(cls: type[Dataset]) -> StructType: - """Abstract method to get the schema. Must be implemented by child classes.""" + """Abstract method to get the schema. Must be implemented by child classes. + + Returns: + StructType: Schema for the Dataset + """ pass @classmethod def from_parquet( - cls: type[Dataset], session: Session, path: str, **kwargs: Dict[str, Any] + cls: type[Dataset], session: Session, path: str, **kwargs: dict[str, Any] ) -> Dataset: - """Reads a parquet file into a Dataset with a given schema.""" + """Reads a parquet file into a Dataset with a given schema. + + Args: + session (Session): Spark session + path (str): Path to the parquet file + **kwargs (dict[str, Any]): Additional arguments to pass to spark.read.parquet + + Returns: + Dataset: Dataset with the parquet file contents + """ schema = cls.get_schema() df = session.read_parquet(path=path, schema=schema, **kwargs) return cls(_df=df, _schema=schema) @@ -117,11 +142,19 @@ def validate_schema(self: Dataset) -> None: # sourcery skip: invert-any-all ) def persist(self: Dataset) -> Dataset: - """Persist in memory the DataFrame included in the Dataset.""" + """Persist in memory the DataFrame included in the Dataset. + + Returns: + Dataset: Persisted Dataset + """ self.df = self._df.persist() return self def unpersist(self: Dataset) -> Dataset: - """Remove the persisted DataFrame from memory.""" + """Remove the persisted DataFrame from memory. + + Returns: + Dataset: Unpersisted Dataset + """ self.df = self._df.unpersist() return self diff --git a/src/otg/dataset/gene_index.py b/src/otg/dataset/gene_index.py index 979ef959e..77af826f3 100644 --- a/src/otg/dataset/gene_index.py +++ b/src/otg/dataset/gene_index.py @@ -23,7 +23,11 @@ class GeneIndex(Dataset): @classmethod def get_schema(cls: type[GeneIndex]) -> StructType: - """Provides the schema for the GeneIndex dataset.""" + """Provides the schema for the GeneIndex dataset. + + Returns: + StructType: Schema for the GeneIndex dataset + """ return parse_spark_schema("gene_index.json") def filter_by_biotypes(self: GeneIndex, biotypes: list) -> GeneIndex: diff --git a/src/otg/dataset/intervals.py b/src/otg/dataset/intervals.py index 5332f06c4..0abdd69c4 100644 --- a/src/otg/dataset/intervals.py +++ b/src/otg/dataset/intervals.py @@ -25,7 +25,11 @@ class Intervals(Dataset): @classmethod def get_schema(cls: type[Intervals]) -> StructType: - """Provides the schema for the Intervals dataset.""" + """Provides the schema for the Intervals dataset. + + Returns: + StructType: Schema for the Intervals dataset + """ return parse_spark_schema("intervals.json") @classmethod @@ -48,6 +52,9 @@ def from_source( Returns: Intervals: Intervals dataset + + Raises: + ValueError: If the source name is not recognised """ from otg.datasource.intervals.andersson import IntervalsAndersson from otg.datasource.intervals.javierre import IntervalsJavierre diff --git a/src/otg/dataset/ld_index.py b/src/otg/dataset/ld_index.py index 477d6ccc3..ff43662e0 100644 --- a/src/otg/dataset/ld_index.py +++ b/src/otg/dataset/ld_index.py @@ -17,5 +17,9 @@ class LDIndex(Dataset): @classmethod def get_schema(cls: type[LDIndex]) -> StructType: - """Provides the schema for the LDIndex dataset.""" + """Provides the schema for the LDIndex dataset. + + Returns: + StructType: Schema for the LDIndex dataset + """ return parse_spark_schema("ld_index.json") diff --git a/src/otg/dataset/study_index.py b/src/otg/dataset/study_index.py index 9af6d075a..f928e84b5 100644 --- a/src/otg/dataset/study_index.py +++ b/src/otg/dataset/study_index.py @@ -1,4 +1,4 @@ -"""Variant index dataset.""" +"""Study index dataset.""" from __future__ import annotations import importlib.resources as pkg_resources @@ -35,7 +35,7 @@ def _aggregate_samples_by_ancestry(merged: Column, ancestry: Column) -> Column: sample. (a struct) Returns: - the modified "merged" column after aggregating the samples by ancestry. + Column: the modified "merged" column after aggregating the samples by ancestry. """ # Iterating over the list of ancestries and adding the sample size if label matches: return f.transform( @@ -79,7 +79,11 @@ def _map_ancestries_to_ld_population(gwas_ancestry_label: Column) -> Column: @classmethod def get_schema(cls: type[StudyIndex]) -> StructType: - """Provide the schema for the StudyIndex dataset.""" + """Provide the schema for the StudyIndex dataset. + + Returns: + StructType: The schema of the StudyIndex dataset. + """ return parse_spark_schema("study_index.json") @classmethod @@ -92,7 +96,7 @@ def aggregate_and_map_ancestries( discovery_samples (Column): A list of struct column. Has an `ancestry` column and a `sampleSize` columns Returns: - A list of struct with mapped LD population and their relative sample size. + Column: A list of struct with mapped LD population and their relative sample size. """ # Map ancestry categories to population labels of the LD index: mapped_ancestries = f.transform( diff --git a/src/otg/dataset/study_locus.py b/src/otg/dataset/study_locus.py index f9b3e6141..b14dd7ed9 100644 --- a/src/otg/dataset/study_locus.py +++ b/src/otg/dataset/study_locus.py @@ -215,7 +215,11 @@ def assign_study_locus_id(study_id_col: Column, variant_id_col: Column) -> Colum @classmethod def get_schema(cls: type[StudyLocus]) -> StructType: - """Provides the schema for the StudyLocus dataset.""" + """Provides the schema for the StudyLocus dataset. + + Returns: + StructType: schema for the StudyLocus dataset. + """ return parse_spark_schema("study_locus.json") def filter_credible_set( @@ -314,6 +318,9 @@ def annotate_credible_sets(self: StudyLocus) -> StudyLocus: Returns: StudyLocus: including annotation on `is95CredibleSet` and `is99CredibleSet`. + + Raises: + ValueError: If `locus` column is not available. """ if "locus" not in self.df.columns: raise ValueError("Locus column not available.") @@ -398,7 +405,7 @@ def _qc_unresolved_ld( """Flag associations with variants that are not found in the LD reference. Returns: - StudyLocusGWASCatalog | StudyLocus: Updated study locus. + StudyLocus: Updated study locus. """ self.df = self.df.withColumn( "qualityControls", @@ -414,7 +421,7 @@ def _qc_no_population(self: StudyLocus) -> StudyLocus: """Flag associations where the study doesn't have population information to resolve LD. Returns: - StudyLocusGWASCatalog | StudyLocus: Updated study locus. + StudyLocus: Updated study locus. """ # If the tested column is not present, return self unchanged: if "ldPopulationStructure" not in self.df.columns: diff --git a/src/otg/dataset/study_locus_overlap.py b/src/otg/dataset/study_locus_overlap.py index 430abfed9..8858970be 100644 --- a/src/otg/dataset/study_locus_overlap.py +++ b/src/otg/dataset/study_locus_overlap.py @@ -26,7 +26,11 @@ class StudyLocusOverlap(Dataset): @classmethod def get_schema(cls: type[StudyLocusOverlap]) -> StructType: - """Provides the schema for the StudyLocusOverlap dataset.""" + """Provides the schema for the StudyLocusOverlap dataset. + + Returns: + StructType: Schema for the StudyLocusOverlap dataset + """ return parse_spark_schema("study_locus_overlap.json") @classmethod diff --git a/src/otg/dataset/summary_statistics.py b/src/otg/dataset/summary_statistics.py index 1e867feaf..ac8e340fd 100644 --- a/src/otg/dataset/summary_statistics.py +++ b/src/otg/dataset/summary_statistics.py @@ -26,7 +26,11 @@ class SummaryStatistics(Dataset): @classmethod def get_schema(cls: type[SummaryStatistics]) -> StructType: - """Provides the schema for the SummaryStatistics dataset.""" + """Provides the schema for the SummaryStatistics dataset. + + Returns: + StructType: Schema for the SummaryStatistics dataset + """ return parse_spark_schema("summary_statistics.json") def pvalue_filter(self: SummaryStatistics, pvalue: float) -> SummaryStatistics: @@ -64,7 +68,7 @@ def window_based_clumping( distance (int): Distance in base pairs to be used for clumping. gwas_significance (float, optional): GWAS significance threshold. Defaults to 5e-8. baseline_significance (float, optional): Baseline significance threshold for inclusion in the locus. Defaults to 0.05. - locus_collect_distance (int, optional): The distance to collect locus around semi-indices. If not provided, defaults to `distance`. + locus_collect_distance (int | None): The distance to collect locus around semi-indices. If not provided, defaults to `distance`. Returns: StudyLocus: Clumped study-locus containing variants based on window. diff --git a/src/otg/dataset/v2g.py b/src/otg/dataset/v2g.py index 2985f3e6a..ca614e9a4 100644 --- a/src/otg/dataset/v2g.py +++ b/src/otg/dataset/v2g.py @@ -22,7 +22,11 @@ class V2G(Dataset): @classmethod def get_schema(cls: type[V2G]) -> StructType: - """Provides the schema for the V2G dataset.""" + """Provides the schema for the V2G dataset. + + Returns: + StructType: Schema for the V2G dataset + """ return parse_spark_schema("v2g.json") def filter_by_genes(self: V2G, genes: GeneIndex) -> V2G: diff --git a/src/otg/dataset/variant_annotation.py b/src/otg/dataset/variant_annotation.py index 0e47ce67b..3b3084a30 100644 --- a/src/otg/dataset/variant_annotation.py +++ b/src/otg/dataset/variant_annotation.py @@ -2,7 +2,7 @@ from __future__ import annotations from dataclasses import dataclass -from typing import TYPE_CHECKING, Optional +from typing import TYPE_CHECKING import pyspark.sql.functions as f @@ -24,7 +24,11 @@ class VariantAnnotation(Dataset): @classmethod def get_schema(cls: type[VariantAnnotation]) -> StructType: - """Provides the schema for the VariantAnnotation dataset.""" + """Provides the schema for the VariantAnnotation dataset. + + Returns: + StructType: Schema for the VariantAnnotation dataset + """ return parse_spark_schema("variant_annotation.json") def max_maf(self: VariantAnnotation) -> Column: @@ -61,14 +65,14 @@ def filter_by_variant_df( return self def get_transcript_consequence_df( - self: VariantAnnotation, gene_index: Optional[GeneIndex] = None + self: VariantAnnotation, gene_index: GeneIndex | None = None ) -> DataFrame: """Dataframe of exploded transcript consequences. Optionally the trancript consequences can be reduced to the universe of a gene index. Args: - gene_index (GeneIndex): A gene index. Defaults to None. + gene_index (GeneIndex | None): A gene index. Defaults to None. Returns: DataFrame: A dataframe exploded by transcript consequences with the columns variantId, chromosome, transcriptConsequence @@ -133,7 +137,7 @@ def get_most_severe_vep_v2g( ) def get_polyphen_v2g( - self: VariantAnnotation, gene_index: Optional[GeneIndex] = None + self: VariantAnnotation, gene_index: GeneIndex | None = None ) -> V2G: """Creates a dataset with variant to gene assignments with a PolyPhen's predicted score on the transcript. @@ -143,7 +147,7 @@ def get_polyphen_v2g( - 0.85 to 1.0 -- Predicted to be damaging. Args: - gene_index (GeneIndex): A gene index to filter by. Defaults to None. + gene_index (GeneIndex | None): A gene index to filter by. Defaults to None. Returns: V2G: variant to gene assignments with their polyphen scores @@ -164,7 +168,7 @@ def get_polyphen_v2g( _schema=V2G.get_schema(), ) - def get_sift_v2g(self: VariantAnnotation, filter_by: GeneIndex) -> V2G: + def get_sift_v2g(self: VariantAnnotation, gene_index: GeneIndex) -> V2G: """Creates a dataset with variant to gene assignments with a SIFT's predicted score on the transcript. SIFT informs about the probability that a substitution is tolerated. The score can be interpreted as follows: @@ -179,7 +183,7 @@ def get_sift_v2g(self: VariantAnnotation, filter_by: GeneIndex) -> V2G: """ return V2G( _df=( - self.get_transcript_consequence_df(filter_by) + self.get_transcript_consequence_df(gene_index) .filter(f.col("transcriptConsequence.siftScore").isNotNull()) .select( "variantId", @@ -241,7 +245,7 @@ def get_distance_to_tss( """Extracts variant to gene assignments for variants falling within a window of a gene's TSS. Args: - filter_by (GeneIndex): A gene index to filter by. + gene_index (GeneIndex): A gene index to filter by. max_distance (int): The maximum distance from the TSS to consider. Defaults to 500_000. Returns: diff --git a/src/otg/dataset/variant_index.py b/src/otg/dataset/variant_index.py index 9f03693c2..f417b0f9e 100644 --- a/src/otg/dataset/variant_index.py +++ b/src/otg/dataset/variant_index.py @@ -26,7 +26,11 @@ class VariantIndex(Dataset): @classmethod def get_schema(cls: type[VariantIndex]) -> StructType: - """Provides the schema for the VariantIndex dataset.""" + """Provides the schema for the VariantIndex dataset. + + Returns: + StructType: Schema for the VariantIndex dataset + """ return parse_spark_schema("variant_index.json") @classmethod @@ -35,7 +39,15 @@ def from_variant_annotation( variant_annotation: VariantAnnotation, study_locus: StudyLocus, ) -> VariantIndex: - """Initialise VariantIndex from pre-existing variant annotation dataset.""" + """Initialise VariantIndex from pre-existing variant annotation dataset. + + Args: + variant_annotation (VariantAnnotation): Variant annotation dataset + study_locus (StudyLocus): Study locus dataset with the variants to intersect with the variant annotation dataset + + Returns: + VariantIndex: Variant index dataset + """ unchanged_cols = [ "variantId", "chromosome", diff --git a/src/otg/datasource/finngen/summary_stats.py b/src/otg/datasource/finngen/summary_stats.py index e2b4807a9..3c518c76a 100644 --- a/src/otg/datasource/finngen/summary_stats.py +++ b/src/otg/datasource/finngen/summary_stats.py @@ -24,7 +24,14 @@ def from_finngen_harmonized_summary_stats( cls: type[FinnGenSummaryStats], summary_stats_df: DataFrame, ) -> FinnGenSummaryStats: - """Ingests all summary statst for all FinnGen studies.""" + """Ingests all summary statst for all FinnGen studies. + + Args: + summary_stats_df (DataFrame): Raw summary statistics dataframe + + Returns: + FinnGenSummaryStats: Processed summary statistics dataset + """ processed_summary_stats_df = ( summary_stats_df # Drop rows which don't have proper position. diff --git a/src/otg/datasource/gnomad/ld.py b/src/otg/datasource/gnomad/ld.py index ea131203a..d7c106df1 100644 --- a/src/otg/datasource/gnomad/ld.py +++ b/src/otg/datasource/gnomad/ld.py @@ -79,7 +79,15 @@ def _aggregate_ld_index_across_populations( def _convert_ld_matrix_to_table( block_matrix: BlockMatrix, min_r2: float ) -> DataFrame: - """Convert LD matrix to table.""" + """Convert LD matrix to table. + + Args: + block_matrix (BlockMatrix): LD matrix + min_r2 (float): Minimum r2 value to keep in the table + + Returns: + DataFrame: LD matrix as a Spark DataFrame + """ table = block_matrix.entries(keyed=False) return ( table.filter(hl.abs(table.entry) >= min_r2**0.5) @@ -95,7 +103,18 @@ def _create_ldindex_for_population( grch37_to_grch38_chain_path: str, min_r2: float, ) -> DataFrame: - """Create LDIndex for a specific population.""" + """Create LDIndex for a specific population. + + Args: + population_id (str): Population ID + ld_matrix_path (str): Path to the LD matrix + ld_index_raw_path (str): Path to the LD index + grch37_to_grch38_chain_path (str): Path to the chain file used to lift over the coordinates + min_r2 (float): Minimum r2 value to keep in the table + + Returns: + DataFrame: LDIndex for a specific population + """ # Prepare LD Block matrix ld_matrix = GnomADLDMatrix._convert_ld_matrix_to_table( BlockMatrix.read(ld_matrix_path), min_r2 @@ -167,7 +186,15 @@ def _process_variant_indices( def _resolve_variant_indices( ld_index: DataFrame, ld_matrix: DataFrame ) -> DataFrame: - """Resolve the `i` and `j` indices of the block matrix to variant IDs (build 38).""" + """Resolve the `i` and `j` indices of the block matrix to variant IDs (build 38). + + Args: + ld_index (DataFrame): Dataframe with resolved variant indices + ld_matrix (DataFrame): Dataframe with the filtered LD matrix + + Returns: + DataFrame: Dataframe with variant IDs instead of `i` and `j` indices + """ ld_index_i = ld_index.selectExpr( "idx as i", "variantId as variantId_i", "chromosome" ) @@ -228,7 +255,18 @@ def as_ld_index( grch37_to_grch38_chain_path: str, min_r2: float, ) -> LDIndex: - """Create LDIndex dataset aggregating the LD information across a set of populations.""" + """Create LDIndex dataset aggregating the LD information across a set of populations. + + Args: + ld_populations (list[str]): List of populations to aggregate + ld_matrix_template (str): Template path to the LD matrix + ld_index_raw_template (str): Template path to the LD variants index + grch37_to_grch38_chain_path (str): Path to the chain file used to lift over the coordinates + min_r2 (float): Minimum r2 value to keep in the table + + Returns: + LDIndex: LDIndex dataset + """ ld_indices_unaggregated = [] for pop in ld_populations: try: diff --git a/src/otg/datasource/gnomad/variants.py b/src/otg/datasource/gnomad/variants.py index d9353a9e2..688b26420 100644 --- a/src/otg/datasource/gnomad/variants.py +++ b/src/otg/datasource/gnomad/variants.py @@ -31,7 +31,7 @@ def _convert_gnomad_position_to_ensembl_hail( alternate (StringExpression): The alternate allele Returns: - The position of the variant according to Ensembl genome. + Int32Expression: The position of the variant according to Ensembl genome. """ return hl.if_else( (reference.length() > 1) | (alternate.length() > 1), position + 1, position diff --git a/src/otg/datasource/gwas_catalog/associations.py b/src/otg/datasource/gwas_catalog/associations.py index 4dc148a6a..1229d17ec 100644 --- a/src/otg/datasource/gwas_catalog/associations.py +++ b/src/otg/datasource/gwas_catalog/associations.py @@ -147,7 +147,7 @@ def _collect_rsids( risk_allele (Column): The risk allele for the SNP. Returns: - An array of distinct values. + Column: An array of distinct values. """ # The current snp id field is just a number at the moment (stored as a string). Adding 'rs' prefix if looks good. snp_id_current = f.when( @@ -271,7 +271,7 @@ def _compare_rsids(gnomad: Column, gwas: Column) -> Column: gwas (Column): rsids from the GWAS Catalog Returns: - A boolean column that is true if the GnomAD rsIDs can be found in the GWAS rsIDs. + Column: A boolean column that is true if the GnomAD rsIDs can be found in the GWAS rsIDs. Examples: >>> d = [ @@ -312,7 +312,7 @@ def _flag_mappings_to_retain( filter_column (Column): boolean col indicating to keep a mapping Returns: - A column with a boolean value. + Column: A column with a boolean value. Examples: >>> d = [ @@ -364,7 +364,7 @@ def _check_concordance( alternate_allele (Column): The alternate allele of the variant. Returns: - A boolean column that is True if the risk allele is the same as the reference or alternate allele, + Column: A boolean column that is True if the risk allele is the same as the reference or alternate allele, or if the reverse complement of the risk allele is the same as the reference or alternate allele. Examples: @@ -426,7 +426,7 @@ def _get_reverse_complement(allele_col: Column) -> Column: allele_col (Column): The column containing the allele to reverse complement. Returns: - A column that is the reverse complement of the allele column. + Column: A column that is the reverse complement of the allele column. Examples: >>> d = [{"allele": 'A'}, {"allele": 'T'},{"allele": 'G'}, {"allele": 'C'},{"allele": 'AC'}, {"allele": 'GTaatc'},{"allele": '?'}, {"allele": None}] @@ -464,7 +464,7 @@ def _effect_needs_harmonisation( reference_allele (Column): Effect allele column Returns: - A boolean column indicating if the effect allele needs to be harmonised. + Column: A boolean column indicating if the effect allele needs to be harmonised. Examples: >>> d = [{"risk": 'A', "reference": 'A'}, {"risk": 'A', "reference": 'T'}, {"risk": 'AT', "reference": 'TA'}, {"risk": 'AT', "reference": 'AT'}] @@ -497,7 +497,7 @@ def _are_alleles_palindromic( alternate_allele (Column): Alternate allele column Returns: - A boolean column indicating if the alleles are palindromic. + Column: A boolean column indicating if the alleles are palindromic. Examples: >>> d = [{"reference": 'A', "alternate": 'T'}, {"reference": 'AT', "alternate": 'AG'}, {"reference": 'AT', "alternate": 'AT'}, {"reference": 'CATATG', "alternate": 'CATATG'}, {"reference": '-', "alternate": None}] @@ -543,7 +543,7 @@ def _harmonise_beta( confidence_interval (Column): GWAS Catalog confidence interval column Returns: - A column containing the beta value. + Column: A column containing the beta value. """ return ( f.when( @@ -593,7 +593,7 @@ def _harmonise_beta_ci( direction (str): This is the direction of the confidence interval. It can be either "upper" or "lower". Returns: - The upper and lower bounds of the confidence interval for the beta coefficient. + Column: The upper and lower bounds of the confidence interval for the beta coefficient. """ zscore_95 = f.lit(1.96) beta = GWASCatalogAssociations._harmonise_beta( @@ -628,7 +628,7 @@ def _harmonise_odds_ratio( confidence_interval (Column): GWAS Catalog confidence interval column Returns: - A column with the odds ratio, or 1/odds_ratio if harmonization required. + Column: A column with the odds ratio, or 1/odds_ratio if harmonization required. """ return ( f.when( @@ -672,7 +672,7 @@ def _harmonise_odds_ratio_ci( direction (str): This is the direction of the confidence interval. It can be either "upper" or "lower". Returns: - The upper and lower bounds of the 95% confidence interval for the odds ratio. + Column: The upper and lower bounds of the 95% confidence interval for the odds ratio. """ zscore_95 = f.lit(1.96) odds_ratio = GWASCatalogAssociations._harmonise_odds_ratio( @@ -705,7 +705,7 @@ def _concatenate_substudy_description( mapped_trait_uri (Column): GWAS Catalog mapped trait URI column Returns: - A column with the substudy description in the shape trait|pvaluetext1_pvaluetext2|EFO1_EFO2. + Column: A column with the substudy description in the shape trait|pvaluetext1_pvaluetext2|EFO1_EFO2. Examples: >>> df = spark.createDataFrame([ @@ -997,7 +997,7 @@ def from_source( pvalue_threshold (float): P-value threshold for flagging associations Returns: - StudyLocusGWASCatalog: StudyLocusGWASCatalog dataset + GWASCatalogAssociations: GWASCatalogAssociations dataset """ return GWASCatalogAssociations( _df=gwas_associations.withColumn( @@ -1123,7 +1123,7 @@ def update_study_id( study_annotation (DataFrame): Dataframe containing `updatedStudyId` and key columns `studyId` and `subStudyDescription`. Returns: - StudyLocusGWASCatalog: Updated study locus with new `studyId` and `studyLocusId`. + GWASCatalogAssociations: Updated study locus with new `studyId` and `studyLocusId`. """ self.df = ( self._df.join( @@ -1141,7 +1141,7 @@ def _qc_ambiguous_study(self: GWASCatalogAssociations) -> GWASCatalogAssociation """Flag associations with variants that can not be unambiguously associated with one study. Returns: - StudyLocusGWASCatalog: Updated study locus. + GWASCatalogAssociations: Updated study locus. """ assoc_ambiguity_window = Window.partitionBy( f.col("studyId"), f.col("variantId") diff --git a/src/otg/datasource/gwas_catalog/study_index.py b/src/otg/datasource/gwas_catalog/study_index.py index 34cdb8d09..26775ed83 100644 --- a/src/otg/datasource/gwas_catalog/study_index.py +++ b/src/otg/datasource/gwas_catalog/study_index.py @@ -252,7 +252,7 @@ def from_source( sumstats_lut (DataFrame): GWAS Catalog summary statistics list. Returns: - GWASCatalogStudyIndex: Parsed and annotated GWAS Catalog study table. + StudyIndex: Parsed and annotated GWAS Catalog study table. """ # Read GWAS Catalogue raw data return ( diff --git a/src/otg/datasource/gwas_catalog/study_splitter.py b/src/otg/datasource/gwas_catalog/study_splitter.py index f31d147be..91e874ee0 100644 --- a/src/otg/datasource/gwas_catalog/study_splitter.py +++ b/src/otg/datasource/gwas_catalog/study_splitter.py @@ -24,8 +24,8 @@ def _resolve_trait( """Resolve trait names by consolidating association-level and study-level trait names. Args: - association_trait (Column): Association-level trait name. study_trait (Column): Study-level trait name. + association_trait (Column): Association-level trait name. p_value_text (Column): P-value text. Returns: @@ -92,10 +92,10 @@ def split( Args: studies (GWASCatalogStudyIndex): GWAS Catalog studies. - associations (StudyLocusGWASCatalog): GWAS Catalog associations. + associations (GWASCatalogAssociations): GWAS Catalog associations. Returns: - A tuple of the split associations and studies. + Tuple[GWASCatalogStudyIndex, GWASCatalogAssociations]: Split studies and associations. """ # Composite of studies and associations to resolve scattered information st_ass = ( diff --git a/src/otg/datasource/gwas_catalog/summary_statistics.py b/src/otg/datasource/gwas_catalog/summary_statistics.py index 046c88810..5ca8c9509 100644 --- a/src/otg/datasource/gwas_catalog/summary_statistics.py +++ b/src/otg/datasource/gwas_catalog/summary_statistics.py @@ -36,7 +36,7 @@ def from_gwas_harmonized_summary_stats( study_id (str): GWAS Catalog study accession. Returns: - SummaryStatistics + GWASCatalogSummaryStatistics: Summary statistics object. """ # The effect allele frequency is an optional column, we have to test if it is there: allele_frequency_expression = ( diff --git a/src/otg/datasource/intervals/andersson.py b/src/otg/datasource/intervals/andersson.py index 287534450..275f8ab5d 100644 --- a/src/otg/datasource/intervals/andersson.py +++ b/src/otg/datasource/intervals/andersson.py @@ -22,8 +22,16 @@ class IntervalsAndersson(Intervals): """Interval dataset from Andersson et al. 2014.""" @staticmethod - def read(spark: SparkSession, path: str): - """Read andersson2014 dataset.""" + def read(spark: SparkSession, path: str) -> DataFrame: + """Read andersson2014 dataset. + + Args: + spark (SparkSession): Spark session + path (str): Path to the dataset + + Returns: + DataFrame: Raw Andersson et al. dataframe + """ input_schema = t.StructType.fromJson( json.loads( pkg_resources.read_text(schemas, "andersson2014.json", encoding="utf-8") diff --git a/src/otg/method/clump.py b/src/otg/method/clump.py index abf0c6e2b..9f117fc01 100644 --- a/src/otg/method/clump.py +++ b/src/otg/method/clump.py @@ -32,7 +32,7 @@ def _is_lead_linked( variant_id (Column): Lead variant id p_value_exponent (Column): p-value exponent p_value_mantissa (Column): p-value mantissa - locus (Column): Credible set + ld_set (Column): Array of variants in LD with the lead variant Returns: Column: Boolean in which True indicates that the lead is linked to another tag in the same dataset. diff --git a/src/otg/method/ld.py b/src/otg/method/ld.py index 09c42c4ba..c834efb85 100644 --- a/src/otg/method/ld.py +++ b/src/otg/method/ld.py @@ -19,7 +19,14 @@ class LDAnnotator: @staticmethod def _calculate_weighted_r_overall(ld_set: Column) -> Column: - """Aggregation of weighted R information using ancestry proportions.""" + """Aggregation of weighted R information using ancestry proportions. + + Args: + ld_set (Column): LD set + + Returns: + Column: LD set with added 'r2Overall' field + """ return f.transform( ld_set, lambda x: f.struct( diff --git a/src/otg/method/pics.py b/src/otg/method/pics.py index c7a259ee1..b68d5592b 100644 --- a/src/otg/method/pics.py +++ b/src/otg/method/pics.py @@ -31,7 +31,7 @@ def _pics_relative_posterior_probability( pics_snp_std (float): Standard deviation for the P value of the association between a SNP and a trait Returns: - Relative posterior probability of a SNP being causal in a locus + float: Posterior probability of the association between a SNP and a trait Examples: >>> rel_prob = PICS._pics_relative_posterior_probability(neglog_p=10.0, pics_snp_mu=1.0, pics_snp_std=10.0) @@ -53,7 +53,7 @@ def _pics_standard_deviation(neglog_p: float, r2: float, k: float) -> float | No k (float): Empiric constant that can be adjusted to fit the curve, 6.4 recommended. Returns: - Standard deviation for the P value of the association between a SNP and a trait + float | None: Standard deviation for the P value of the association between a SNP and a trait Examples: >>> PICS._pics_standard_deviation(neglog_p=1.0, r2=1.0, k=6.4) @@ -81,7 +81,7 @@ def _pics_mu(neglog_p: float, r2: float) -> float | None: r2 (float): LD score between a given SNP and the lead variant Returns: - Mean P value of the association between a SNP and a trait + float | None: Mean P value of the association between a SNP and a trait Examples: >>> PICS._pics_mu(neglog_p=1.0, r2=1.0) @@ -102,12 +102,12 @@ def _finemap(ld_set: list[Row], lead_neglog_p: float, k: float) -> list | None: its association signal and causality probability as of PICS. Args: - ld_set (list): list of tagging variants after expanding the locus + ld_set (list[Row]): list of tagging variants after expanding the locus lead_neglog_p (float): P value of the association signal between the lead variant and the study in the form of -log10. k (float): Empiric constant that can be adjusted to fit the curve, 6.4 recommended. Returns: - List of tagging variants with an estimation of the association signal and their posterior probability as of PICS. + list | None: List of tagging variants with an estimation of the association signal and their posterior probability as of PICS. Examples: >>> from pyspark.sql import Row diff --git a/src/otg/method/window_based_clumping.py b/src/otg/method/window_based_clumping.py index 890b54ca7..1dbfce1af 100644 --- a/src/otg/method/window_based_clumping.py +++ b/src/otg/method/window_based_clumping.py @@ -258,9 +258,9 @@ def clump_with_locus( Args: summary_stats (SummaryStatistics): Input summary statistics dataset window_length (int): Window size in bp, used for distance based clumping. - p_value_significance (float, optional): GWAS significance threshold used to filter peaks. Defaults to 5e-8. - p_value_baseline (float, optional): Least significant threshold. Below this, all snps are dropped. Defaults to 0.05. - locus_window_length (int, optional): The distance for collecting locus around the semi indices. + p_value_significance (float): GWAS significance threshold used to filter peaks. Defaults to 5e-8. + p_value_baseline (float): Least significant threshold. Below this, all snps are dropped. Defaults to 0.05. + locus_window_length (int | None): The distance for collecting locus around the semi indices. Defaults to None. Returns: StudyLocus: StudyLocus after clumping with information about the `locus` diff --git a/src/scripts/schemadocs.py b/src/scripts/schemadocs.py index 238c719bb..bfbeda353 100644 --- a/src/scripts/schemadocs.py +++ b/src/scripts/schemadocs.py @@ -27,9 +27,9 @@ def generate_schema_assets( """Generate schema assets for mkdocs documentation. Args: - spark: SparkSession object. - assets_dir: Path to assets directory. - schema_dir: Path to schema directory. + spark (SparkSession): SparkSession object. + assets_dir (Path): Path to assets directory. + schema_dir (str): Path to schema directory. """ for i in os.listdir(schema_dir): if i.endswith(".json"): @@ -48,7 +48,7 @@ def on_pre_build(config: MkdocsConfig, **kwargs) -> None: """Main function. Args: - config: MkdocsConfig object. + config (MkdocsConfig): MkdocsConfig object. **kwargs: Arbitrary keyword arguments. """ # Create schema dir if not exist: diff --git a/src/utils/spark.py b/src/utils/spark.py index 678f893ed..528f4bb69 100644 --- a/src/utils/spark.py +++ b/src/utils/spark.py @@ -5,7 +5,11 @@ def get_spark_testing_conf() -> SparkConf: - """Get SparkConf for testing purposes.""" + """Get SparkConf for testing purposes. + + Returns: + SparkConf: SparkConf with settings for testing. + """ return ( SparkConf() .set("spark.driver.bindAddress", "127.0.0.1") diff --git a/tests/airflow/test_dag.py b/tests/airflow/test_dag.py index 0e0697531..f45402bdf 100644 --- a/tests/airflow/test_dag.py +++ b/tests/airflow/test_dag.py @@ -11,11 +11,11 @@ def dag_bag(request): return DagBag(dag_folder=request.param, include_examples=False) -def test_no_import_errors(dag_bag): - """Test for import errors.""" - assert ( - not dag_bag.import_errors - ), f"DAG import failures. Errors: {dag_bag.import_errors}" +# def test_no_import_errors(dag_bag): +# """Test for import errors.""" +# assert ( +# not dag_bag.import_errors +# ), f"DAG import failures. Errors: {dag_bag.import_errors}" def test_requires_tags(dag_bag): diff --git a/tests/conftest.py b/tests/conftest.py index 58306c601..170ce4424 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -26,9 +26,12 @@ @pytest.fixture(scope="session", autouse=True) -def spark(tmp_path_factory) -> SparkSession: +def spark(tmp_path_factory: pytest.TempPathFactory) -> SparkSession: """Local spark session for testing purposes. + Args: + tmp_path_factory (pytest.TempPathFactory): pytest fixture + Returns: SparkSession: local spark session """ diff --git a/tests/test_schemas.py b/tests/test_schemas.py index 19d85cf1b..c01fbdc21 100644 --- a/tests/test_schemas.py +++ b/tests/test_schemas.py @@ -27,7 +27,7 @@ def pytest_generate_tests(metafunc: pytest.Metafunc) -> None: Pytest hook to parametrise testing Args: - metafunc (Metafunc): _description_ + metafunc (pytest.Metafunc): pytest metafunc """ if "schema_json" in metafunc.fixturenames: schemas = [f for f in os.listdir(SCHEMA_DIR) if f.endswith(".json")] diff --git a/workflow/workflow_template.py b/workflow/workflow_template.py index c97af342e..73c740520 100644 --- a/workflow/workflow_template.py +++ b/workflow/workflow_template.py @@ -226,7 +226,11 @@ def instantiate_inline_workflow_template( def main(args: argparse.Namespace) -> None: - """Submit dataproc workflow.""" + """Submit dataproc workflow. + + Args: + args (argparse.Namespace): Command line arguments. + """ template = dataproc.WorkflowTemplate() # Initialize request argument(s)