feat: implement Google Batch preprocessing

src/batch/README.md

@@ -0,0 +1,17 @@
+## How to run a batch job
+
+Set up:
+```bash
+export MODULE=eqtl_catalogue
+```
+
+Run:
+```bash
+# Upload code.
+gsutil -m cp -r . gs://genetics_etl_python_playground/batch/code
+# Submit batch job.
+gcloud batch jobs submit \
+  "${MODULE//_/-}-$(date --utc +"%Y%m%d-%H%M%S")" \
+  --config <(python3 ${MODULE}.py) \
+  --location europe-west1
+```

src/batch/eqtl_catalogue.py

@@ -0,0 +1,44 @@
+"""Cloud Batch pipeline to preprocess and partition the eQTL Catalogue data."""
+
+from __future__ import annotations
+
+import sys
+
+import pandas as pd
+from batch_common import generate_job_config
+from spark_prep import SparkPrep
+
+EQTL_CATALOGUE_IMPORTED_PATH = "https://raw.githubusercontent.com/eQTL-Catalogue/eQTL-Catalogue-resources/master/tabix/tabix_ftp_paths_imported.tsv"
+EQTL_CATALOGUE_OUTPUT_BASE = (
+    "gs://genetics_etl_python_playground/1-smart-mirror/summary_stats"
+)
+
+
+if __name__ == "__main__":
+    # Are we running on Google Cloud?
+    args = sys.argv[1:]
+    if args:
+        # We are running inside Google Cloud, let's process one file.
+        batch_index = int(args[0])
+        # Read the study index and select one study.
+        df = pd.read_table(EQTL_CATALOGUE_IMPORTED_PATH)
+        record = df.loc[batch_index].to_dict()
+        # Process the study.
+        worker = SparkPrep(
+            input_uri=record["ftp_path"],
+            analysis_type="eQTL",
+            source_id="eQTL_Catalogue",
+            project_id="GTEx_V8",
+            study_id=record["qtl_group"],
+            output_base_path=EQTL_CATALOGUE_OUTPUT_BASE,
+        )
+        worker.process()
+    else:
+        # We are running locally. Let's generate the job config.
+        # For this, we only really need the total number of jobs to run.
+        number_of_tasks = len(pd.read_table(EQTL_CATALOGUE_IMPORTED_PATH))
+        print(
+            generate_job_config(
+                step_name="eqtl_catalogue", number_of_tasks=number_of_tasks
+            )
+        )