|
| 1 | +import csv |
| 2 | +import os |
| 3 | +import uuid |
| 4 | +from datetime import datetime, timedelta |
| 5 | +from typing import Any, Dict, List, NamedTuple |
| 6 | + |
| 7 | +import boto3 |
| 8 | +from botocore.exceptions import ClientError |
| 9 | + |
| 10 | +SOURCE_PDF_FILE = "../source_to_copy_from.pdf" |
| 11 | + |
| 12 | + |
| 13 | +class Patient(NamedTuple): |
| 14 | + full_name: str |
| 15 | + date_of_birth: str |
| 16 | + nhs_number: str |
| 17 | + ods_code: str |
| 18 | + |
| 19 | + |
| 20 | +def get_timestamp(days_ago: int = 0) -> int: |
| 21 | + target_date = datetime.now() - timedelta(days=days_ago) |
| 22 | + return int(target_date.timestamp()) |
| 23 | + |
| 24 | + |
| 25 | +def get_patients(filename: str) -> List[Dict]: |
| 26 | + patients = [] |
| 27 | + csv_path = f"../test_patients_data/{filename}" |
| 28 | + |
| 29 | + if not os.path.exists(csv_path): |
| 30 | + print(f"Warning: {csv_path} not found.") |
| 31 | + |
| 32 | + else: |
| 33 | + with open(csv_path, mode="r", newline="") as file: |
| 34 | + reader = csv.DictReader(file) |
| 35 | + for idx, row in enumerate(reader): |
| 36 | + if idx >= 300: |
| 37 | + break |
| 38 | + patients.append(row) |
| 39 | + return patients |
| 40 | + |
| 41 | + |
| 42 | +def parse_patient_record(raw_record: dict) -> Patient: |
| 43 | + nhs_number = raw_record["NHS_NO"] |
| 44 | + name_parts = [ |
| 45 | + raw_record["GIVEN_NAME"], |
| 46 | + raw_record.get("OTHER_GIVEN_NAME", ""), |
| 47 | + raw_record["FAMILY_NAME"], |
| 48 | + ] |
| 49 | + full_name = " ".join(name_part for name_part in name_parts if name_part) |
| 50 | + date_of_birth = raw_record["DOB"].replace("/", "-") |
| 51 | + ods_code = raw_record["GPP"] |
| 52 | + return Patient(full_name, date_of_birth, nhs_number, ods_code) |
| 53 | + |
| 54 | + |
| 55 | +def build_document_review_object( |
| 56 | + patient: Patient, |
| 57 | + review_id: str, |
| 58 | + files: List[Dict[str, str]], |
| 59 | + review_status: str = "PENDING_REVIEW", |
| 60 | + review_reason: str = "General error", |
| 61 | + days_ago_uploaded: int = 1, |
| 62 | + reviewer: str | None = None, |
| 63 | + review_date: int | None = None, |
| 64 | + document_reference_id: str | None = None, |
| 65 | +) -> Dict[str, Any]: |
| 66 | + upload_timestamp = int(get_timestamp(days_ago=days_ago_uploaded)) |
| 67 | + |
| 68 | + review_obj = { |
| 69 | + "ID": review_id, |
| 70 | + "Version": 1, |
| 71 | + "Author": f"{patient.ods_code}", |
| 72 | + "Custodian": patient.ods_code, |
| 73 | + "ReviewStatus": review_status, |
| 74 | + "ReviewReason": review_reason, |
| 75 | + "UploadDate": upload_timestamp, |
| 76 | + "Files": files, |
| 77 | + "NhsNumber": patient.nhs_number, |
| 78 | + "DocumentSnomedCodeType": "16521000000101", # Lloyd George code |
| 79 | + } |
| 80 | + |
| 81 | + if reviewer: |
| 82 | + review_obj["Reviewer"] = reviewer |
| 83 | + |
| 84 | + if review_date: |
| 85 | + review_obj["ReviewDate"] = review_date |
| 86 | + |
| 87 | + if document_reference_id: |
| 88 | + review_obj["DocumentReferenceId"] = document_reference_id |
| 89 | + |
| 90 | + return review_obj |
| 91 | + |
| 92 | + |
| 93 | +def build_file_reference( |
| 94 | + upload_id, file_name: str, bucket_name: str |
| 95 | +) -> Dict[str, str]: |
| 96 | + s3_key = f"{upload_id}/{file_name}" |
| 97 | + file_location = f"s3://{bucket_name}/{s3_key}" |
| 98 | + |
| 99 | + return { |
| 100 | + "FileName": file_name, |
| 101 | + "FileLocation": file_location, |
| 102 | + } |
| 103 | + |
| 104 | + |
| 105 | +def create_test_scenarios(patients: List[Patient], bucket_name: str): |
| 106 | + |
| 107 | + review_objects = [] |
| 108 | + files_to_upload = [] |
| 109 | + |
| 110 | + def scenario_1(patient): |
| 111 | + """Pending Review with single file""" |
| 112 | + file_name = f"upload_review_{patient.nhs_number}_doc1.pdf" |
| 113 | + review_id = str(uuid.uuid4()) |
| 114 | + files = [build_file_reference(review_id, file_name, bucket_name)] |
| 115 | + review_obj = build_document_review_object( |
| 116 | + review_id=review_id, |
| 117 | + patient=patient, |
| 118 | + files=files, |
| 119 | + review_status="PENDING_REVIEW", |
| 120 | + review_reason="General error", |
| 121 | + days_ago_uploaded=1, |
| 122 | + ) |
| 123 | + return review_obj, [(patient.nhs_number, file_name, files[0]["FileLocation"])] |
| 124 | + |
| 125 | + def scenario_2(patient): |
| 126 | + """Pending Review with multiple files""" |
| 127 | + |
| 128 | + files = [] |
| 129 | + files_list = [] |
| 130 | + review_id = str(uuid.uuid4()) |
| 131 | + |
| 132 | + for i in range(3): |
| 133 | + file_name = f"upload_review_{patient.nhs_number}_doc{i+1}.pdf" |
| 134 | + file_ref = build_file_reference(review_id, file_name, bucket_name) |
| 135 | + files.append(file_ref) |
| 136 | + files_list.append((patient.nhs_number, file_name, file_ref["FileLocation"])) |
| 137 | + review_obj = build_document_review_object( |
| 138 | + review_id=review_id, |
| 139 | + patient=patient, |
| 140 | + files=files, |
| 141 | + review_status="PENDING_REVIEW", |
| 142 | + review_reason="More or less files than we expected", |
| 143 | + days_ago_uploaded=2, |
| 144 | + ) |
| 145 | + return review_obj, files_list |
| 146 | + |
| 147 | + def scenario_3(patient): |
| 148 | + """Approved review""" |
| 149 | + file_name = f"upload_review_{patient.nhs_number}_doc1.pdf" |
| 150 | + review_id = str(uuid.uuid4()) |
| 151 | + files = [build_file_reference(review_id, file_name, bucket_name)] |
| 152 | + review_obj = build_document_review_object( |
| 153 | + patient=patient, |
| 154 | + review_id=review_id, |
| 155 | + files=files, |
| 156 | + review_status="APPROVED", |
| 157 | + review_reason="Demographic mismatches", |
| 158 | + days_ago_uploaded=5, |
| 159 | + reviewer="H81109", |
| 160 | + review_date=get_timestamp(days_ago=2), |
| 161 | + document_reference_id=str(uuid.uuid4()), |
| 162 | + ) |
| 163 | + return review_obj, [(patient.nhs_number, file_name, files[0]["FileLocation"])] |
| 164 | + |
| 165 | + def scenario_4(patient): |
| 166 | + """Rejected review""" |
| 167 | + file_name = f"upload_review_{patient.nhs_number}_doc1.pdf" |
| 168 | + review_id = str(uuid.uuid4()) |
| 169 | + files = [build_file_reference(review_id, file_name, bucket_name)] |
| 170 | + review_obj = build_document_review_object( |
| 171 | + review_id=review_id, |
| 172 | + patient=patient, |
| 173 | + files=files, |
| 174 | + review_status="REJECTED", |
| 175 | + review_reason="Filename Naming convention error", |
| 176 | + days_ago_uploaded=7, |
| 177 | + reviewer="H81109", |
| 178 | + review_date=get_timestamp(days_ago=3), |
| 179 | + ) |
| 180 | + return review_obj, [(patient.nhs_number, file_name, files[0]["FileLocation"])] |
| 181 | + |
| 182 | + def scenario_5(patient): |
| 183 | + """Approved with multiple files and document reference""" |
| 184 | + |
| 185 | + files = [] |
| 186 | + files_list = [] |
| 187 | + review_id = str(uuid.uuid4()) |
| 188 | + |
| 189 | + for i in range(2): |
| 190 | + file_name = f"upload_review_{patient.nhs_number}_doc{i+1}.pdf" |
| 191 | + file_ref = build_file_reference(review_id, file_name, bucket_name) |
| 192 | + files.append(file_ref) |
| 193 | + files_list.append((patient.nhs_number, file_name, file_ref["FileLocation"])) |
| 194 | + |
| 195 | + review_obj = build_document_review_object( |
| 196 | + review_id=review_id, |
| 197 | + patient=patient, |
| 198 | + files=files, |
| 199 | + review_status="APPROVED", |
| 200 | + review_reason="Duplicate records error", |
| 201 | + days_ago_uploaded=10, |
| 202 | + reviewer="H81109", |
| 203 | + review_date=get_timestamp(days_ago=5), |
| 204 | + document_reference_id=str(uuid.uuid4()), |
| 205 | + ) |
| 206 | + return review_obj, files_list |
| 207 | + |
| 208 | + |
| 209 | + def scenario_6(patient): |
| 210 | + """random document type review""" |
| 211 | + |
| 212 | + file_name = f"random_upload_{patient.nhs_number}.txt" |
| 213 | + review_id = str(uuid.uuid4()) |
| 214 | + files = [build_file_reference(review_id, file_name, bucket_name)] |
| 215 | + review_obj = build_document_review_object( |
| 216 | + review_id=review_id, |
| 217 | + patient=patient, |
| 218 | + files=files, |
| 219 | + review_status="PENDING_REVIEW", |
| 220 | + review_reason="Unknown NHS number", |
| 221 | + days_ago_uploaded=3, |
| 222 | + ) |
| 223 | + review_obj["DocumentSnomedCodeType"] = "734163000" |
| 224 | + return review_obj, [(patient.nhs_number, file_name, files[0]["FileLocation"])] |
| 225 | + |
| 226 | + def scenario_7(patient): |
| 227 | + """Multiple versions: NEVER_REVIEWED (v1) and PENDING_REVIEW (v2) with different custodians""" |
| 228 | + |
| 229 | + review_id = str(uuid.uuid4()) |
| 230 | + file_name = f"upload_review_{patient.nhs_number}_doc1.pdf" |
| 231 | + |
| 232 | + files = [build_file_reference(review_id, file_name, bucket_name)] |
| 233 | + |
| 234 | + review_obj_v1 = build_document_review_object( |
| 235 | + review_id=review_id, |
| 236 | + patient=patient, |
| 237 | + files=files, |
| 238 | + review_status="NEVER_REVIEWED", |
| 239 | + review_reason="General error", |
| 240 | + review_date=get_timestamp(days_ago=1), |
| 241 | + days_ago_uploaded=15, |
| 242 | + ) |
| 243 | + review_obj_v1["Version"] = 1 |
| 244 | + review_obj_v1["Author"] = "A12345" |
| 245 | + review_obj_v1["Reviewer"] = "A12345" |
| 246 | + |
| 247 | + review_obj_v2 = build_document_review_object( |
| 248 | + review_id=review_id, |
| 249 | + patient=patient, |
| 250 | + files=files, |
| 251 | + review_status="PENDING_REVIEW", |
| 252 | + review_reason="General error", |
| 253 | + days_ago_uploaded=15, |
| 254 | + ) |
| 255 | + review_obj_v2["Version"] = 2 |
| 256 | + review_obj_v1["Author"] = "A12345" |
| 257 | + review_obj_v2["Custodian"] = "H81109" |
| 258 | + |
| 259 | + files_list = [ |
| 260 | + (patient.nhs_number, file_name, files[0]["FileLocation"]) |
| 261 | + ] |
| 262 | + |
| 263 | + return [review_obj_v1, review_obj_v2], files_list |
| 264 | + |
| 265 | + scenarios = [ |
| 266 | + scenario_1, |
| 267 | + scenario_2, |
| 268 | + scenario_3, |
| 269 | + scenario_4, |
| 270 | + scenario_5, |
| 271 | + scenario_6, |
| 272 | + scenario_7, |
| 273 | + ] |
| 274 | + |
| 275 | + for idx, patient in enumerate(patients): |
| 276 | + scenario_func = scenarios[idx % len(scenarios)] |
| 277 | + result = scenario_func(patient) |
| 278 | + review_obj, patient_files = result |
| 279 | + |
| 280 | + if isinstance(review_obj, list): |
| 281 | + review_objects.extend(review_obj) |
| 282 | + else: |
| 283 | + review_objects.append(review_obj) |
| 284 | + |
| 285 | + files_to_upload.extend(patient_files) |
| 286 | + |
| 287 | + return review_objects, files_to_upload |
| 288 | + |
| 289 | + |
| 290 | +def upload_files_to_s3(files_to_upload: List[tuple], source_pdf: str): |
| 291 | + s3_client = boto3.client("s3") |
| 292 | + |
| 293 | + for nhs_number, file_name, file_location in files_to_upload: |
| 294 | + s3_location = file_location.replace("s3://", "") |
| 295 | + bucket_name, s3_key = s3_location.split("/", 1) |
| 296 | + |
| 297 | + try: |
| 298 | + s3_client.upload_file( |
| 299 | + Filename=source_pdf, |
| 300 | + Bucket=bucket_name, |
| 301 | + Key=s3_key, |
| 302 | + ExtraArgs={"ContentType": "application/pdf"}, |
| 303 | + ) |
| 304 | + except FileNotFoundError: |
| 305 | + print(f"Source file not found: {source_pdf}") |
| 306 | + except ClientError as e: |
| 307 | + print(f"Error uploading {file_name}: {e}") |
| 308 | + |
| 309 | + |
| 310 | +def write_to_dynamodb(review_objects: List[Dict[str, Any]], table_name: str): |
| 311 | + dynamodb = boto3.resource("dynamodb") |
| 312 | + table = dynamodb.Table(table_name) |
| 313 | + |
| 314 | + try: |
| 315 | + with table.batch_writer() as batch: |
| 316 | + for review_obj in review_objects: |
| 317 | + batch.put_item(Item=review_obj) |
| 318 | + print(f"\nSuccessfully wrote {len(review_objects)} review objects to DynamoDB") |
| 319 | + except ClientError as e: |
| 320 | + print(f"Error writing to DynamoDB: {e.response['Error']['Message']}") |
| 321 | + raise |
| 322 | + |
| 323 | + |
| 324 | +def main(): |
| 325 | + environment = os.environ.get("ENVIRONMENT", "ndr-dev") |
| 326 | + bucket_name = f"{environment}-document-pending-review-store" |
| 327 | + table_name = f"{environment}_DocumentUploadReview" |
| 328 | + patient_file = os.environ.get("PATIENT_DATA_FILE", "ODS_Code_H81109.csv") |
| 329 | + |
| 330 | + try: |
| 331 | + patients_data = get_patients(patient_file) |
| 332 | + patients = [parse_patient_record(record) for record in patients_data] |
| 333 | + print(f"Loaded {len(patients)} patients") |
| 334 | + except Exception as e: |
| 335 | + print(f"Error loading patients: {e}") |
| 336 | + return |
| 337 | + |
| 338 | + review_objects, files_to_upload = create_test_scenarios(patients, bucket_name) |
| 339 | + print(f"Created {len(review_objects)} review objects with {len(files_to_upload)} files") |
| 340 | + |
| 341 | + print("\nUploading files to S3...") |
| 342 | + upload_files_to_s3(files_to_upload, SOURCE_PDF_FILE) |
| 343 | + |
| 344 | + print("\nWriting to DynamoDB...") |
| 345 | + write_to_dynamodb(review_objects, table_name) |
| 346 | + |
| 347 | + print("SETUP COMPLETE") |
| 348 | + |
| 349 | + |
| 350 | +if __name__ == "__main__": |
| 351 | + main() |
| 352 | + |
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