diff spamr_vet_tools_v2/mlst_amrfinder_staramr.py @ 2:d7b099fbb003 draft default tip

Corrected file names and updated tool wrappers for consistency.

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/spamr_vet_tools_v2/mlst_amrfinder_staramr.py	Tue Mar 25 13:35:00 2025 +0000
@@ -0,0 +1,73 @@
+import json
+import csv
+import sys
+
+def generate_csv_from_json(json_data):
+    """
+    Parse the JSON and generate CSV files based on the analysis_software_name Abricate, AMRfinder plus and STARamr.
+    Additionally, extract and process the 'mlst_file' content into its own CSV.
+    """
+    for entry in json_data:
+        analysis_software = entry.get("analysis_software_name", "unknown")
+        results = entry.get("results", [])
+
+        if results:
+            csv_file = f"{analysis_software}_output.csv"
+            extracted_data = []
+            headers = []
+
+            for result in results:
+                if result.get("name") == "mlst_file":
+                    mlst_file_path = "mlst.csv"
+                    mlst_content = result.get("content", [])
+                    mlst_headers = ["Isolate ID", "Scheme", "Sequence Type", "Locus"]
+
+                    # Write the MLST CSV file
+                    if mlst_content:
+                        with open(mlst_file_path, "w", newline="", encoding="utf-8") as f:
+                            writer = csv.DictWriter(f, fieldnames=mlst_headers)
+                            writer.writeheader()
+                            for row in mlst_content:
+                                writer.writerow({
+                                    "Isolate ID": row.get("Isolate ID", ""),
+                                    "Scheme": row.get("Scheme", ""),
+                                    "Sequence Type": row.get("Sequence Type", ""),
+                                    "Locus": "; ".join(row.get("Locus", []))
+                                })
+
+                        print(f"MLST CSV file successfully generated: {mlst_file_path}")
+
+                if "content" in result and isinstance(result["content"], list):
+                    for content_item in result["content"]:
+                        extracted_data.append(content_item)
+                        for key in content_item.keys():
+                            if key not in headers:
+                                headers.append(key)  # Maintain the original order of the JSON keys
+
+            # Write the CSV file if there is data
+            if extracted_data:
+                with open(csv_file, "w", newline="", encoding="utf-8") as f:
+                    writer = csv.DictWriter(f, fieldnames=headers)
+                    writer.writeheader()
+                    for row in extracted_data:
+                        writer.writerow({key: row.get(key, "") for key in headers})
+
+                print(f"CSV file successfully generated: {csv_file}")
+            else:
+                print(f"No content found for {analysis_software}.")
+
+if __name__ == "__main__":
+    if len(sys.argv) != 2:
+        print("Usage: python script.py input.json")
+        sys.exit(1)
+
+    input_json_file = sys.argv[1]
+
+    try:
+        with open(input_json_file, "r", encoding="utf-8") as file:
+            json_data = json.load(file)
+        generate_csv_from_json(json_data)
+        sys.exit(0)
+    except Exception as e:
+        print(f"Error processing file: {e}")
+        sys.exit(1)