Updated ncbi api processing to require api key

Updated merge function to not attempt to run if both input files do not exist
Updated apiWorker to use v2 api instead of v2alpha

Author: christopher-mangion

dataSources/ncbi/llib/apiWorker.py

@@ -44,7 +44,7 @@ def apiWorker(queue: Queue, id: int, apiKey: str, recordsPerCall: int, accession
 
     try:
         for string in accessionStrings:
-            url = f"https://api.ncbi.nlm.nih.gov/datasets/v2alpha/genome/accession/{string}/dataset_report"
+            url = f"https://api.ncbi.nlm.nih.gov/datasets/v2/genome/accession/{string}/dataset_report"
             response = session.get(url, headers=headers, params=params)
             data = response.json()
             records = data.get("reports", [])

dataSources/ncbi/llib/sharedProcessing.py

@@ -13,15 +13,12 @@
 
 def getStats(summaryFile: DataFile, outputPath: Path):
     apiKey = secrets.ncbi.key
+    if not isinstance(apiKey, str):
+        logging.error("No API key found in secrets file, and is required to access NCBI api. Please update 'secrets.toml' with 'key' field under 'ncbi'.")
+        return
+    
+    logging.info("Found API key")
     processes = 10
-    if apiKey is None:
-        apiKey = "" # Use empty string
-        processes = 3 # Reduce processes count due to reduced api call rate
-        logging.info("No API key found")
-
-    else:
-        logging.info("Found API key")
-
     recordsPerCall = 200
     recordsPerSubsection = 30000
     accessionCol = "#assembly_accession"
@@ -68,6 +65,14 @@ def getStats(summaryFile: DataFile, outputPath: Path):
     writer.combine(False, index=False)
 
 def merge(summaryFile: DataFile, statsFilePath: Path, outputPath: Path) -> None:
+    if not summaryFile.exists():
+        logging.error("Unable to merge files as summary file doesn't exist")
+        return
+    
+    if not statsFilePath.exists():
+        logging.error("Unable to merge files as stats file doesn't exist")
+        return
+
     df = summaryFile.read(low_memory=False)
     df2 = pd.read_csv(statsFilePath, low_memory=False)
     df = df.merge(df2, how="outer", left_on="#assembly_accession", right_on="current_accession")