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"""
Lambda Deployment Helper Functions
Utilities for deploying and managing AWS Lambda functions
"""
import boto3
import json
import time
import subprocess
import zipfile
import os
from pathlib import Path
from typing import Dict, List, Optional, Any
def create_or_update_lambda_role(
iam_client,
role_name: str,
description: str = "Lambda execution role"
) -> str:
"""
Create or reuse IAM role for Lambda execution
Returns:
role_arn: ARN of the created/existing role
"""
assume_policy = {
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Principal": {"Service": "lambda.amazonaws.com"},
"Action": "sts:AssumeRole"
}
]
}
try:
role = iam_client.create_role(
RoleName=role_name,
AssumeRolePolicyDocument=json.dumps(assume_policy),
Description=description
)
print(f"✅ Created IAM role: {role_name}")
role_arn = role["Role"]["Arn"]
# Attach necessary policies
iam_client.attach_role_policy(
RoleName=role_name,
PolicyArn="arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole"
)
iam_client.attach_role_policy(
RoleName=role_name,
PolicyArn="arn:aws:iam::aws:policy/AmazonS3FullAccess"
)
# Wait for role to propagate
time.sleep(10)
except iam_client.exceptions.EntityAlreadyExistsException:
role = iam_client.get_role(RoleName=role_name)
role_arn = role["Role"]["Arn"]
print(f"ℹ️ Using existing role: {role_name}")
return role_arn
def create_deployment_package(
source_files: List[str],
requirements: List[str],
output_zip: str,
package_dir: str = "lambda_package"
) -> str:
"""
Build Lambda deployment package with dependencies
Args:
source_files: List of Python files to include
requirements: List of pip packages to install
output_zip: Name of output zip file
package_dir: Temporary directory for building package
Returns:
Path to created zip file
"""
print(f"📦 Creating deployment package: {output_zip}")
# Clean and create package directory
subprocess.run(f"rm -rf {package_dir}", shell=True)
subprocess.run(f"mkdir -p {package_dir}", shell=True)
# Install requirements
if requirements:
print(f" Installing dependencies: {', '.join(requirements)}")
req_string = " ".join(requirements)
result = subprocess.run(
f"pip install --quiet {req_string} -t {package_dir}",
shell=True,
capture_output=True,
text=True
)
if result.returncode != 0:
print(f"⚠️ Warning: Some dependencies may have failed to install")
print(result.stderr)
# Copy source files
for source_file in source_files:
print(f" Adding source: {source_file}")
subprocess.run(f"cp {source_file} {package_dir}/", shell=True)
# Create zip
print(f" Creating zip archive...")
subprocess.run(
f"cd {package_dir} && zip -r ../{output_zip} . > /dev/null 2>&1",
shell=True
)
# Cleanup
subprocess.run(f"rm -rf {package_dir}", shell=True)
# Get zip size
zip_size = os.path.getsize(output_zip) / (1024 * 1024)
print(f"✅ Package created: {output_zip} ({zip_size:.1f} MB)")
return output_zip
def deploy_lambda_function(
lambda_client,
function_name: str,
zip_file: str,
role_arn: str,
handler: str,
env_vars: Dict[str, str],
runtime: str = "python3.10",
timeout: int = 900,
memory_size: int = 3008,
architectures: List[str] = ["x86_64"]
) -> Dict:
"""
Deploy or update Lambda function
Returns:
Function configuration dict
"""
print(f"🚀 Deploying Lambda function: {function_name}")
# Read zip file
with open(zip_file, "rb") as f:
zipped_code = f.read()
try:
# Try to create new function
response = lambda_client.create_function(
FunctionName=function_name,
Runtime=runtime,
Role=role_arn,
Handler=handler,
Code={"ZipFile": zipped_code},
Timeout=timeout,
MemorySize=memory_size,
Architectures=architectures,
Environment={"Variables": env_vars},
Publish=True
)
print(f"✅ Lambda function created: {function_name}")
except lambda_client.exceptions.ResourceConflictException:
# Function exists, update it
print(f"ℹ️ Function exists, updating...")
# Update code
lambda_client.update_function_code(
FunctionName=function_name,
ZipFile=zipped_code,
Publish=True
)
print(" Code updated, waiting for deployment...")
time.sleep(10)
# Update configuration
response = lambda_client.update_function_configuration(
FunctionName=function_name,
Environment={"Variables": env_vars},
Timeout=timeout,
MemorySize=memory_size,
Handler=handler,
Runtime=runtime
)
print(f"✅ Lambda function updated: {function_name}")
return response
def setup_s3_trigger(
s3_client,
lambda_client,
bucket: str,
prefix: str,
function_name: str,
suffix: Optional[str] = None
) -> None:
"""
Configure S3 event trigger for Lambda
Args:
bucket: S3 bucket name
prefix: Folder prefix to trigger on
function_name: Lambda function to trigger
suffix: Optional file suffix filter (e.g., '.pdf')
"""
print(f"⚙️ Setting up S3 trigger: s3://{bucket}/{prefix} → {function_name}")
# Get Lambda function ARN
function_config = lambda_client.get_function(FunctionName=function_name)
function_arn = function_config["Configuration"]["FunctionArn"]
# Give S3 permission to invoke the Lambda
try:
lambda_client.add_permission(
FunctionName=function_name,
StatementId="s3invokepermission",
Action="lambda:InvokeFunction",
Principal="s3.amazonaws.com",
SourceArn=f"arn:aws:s3:::{bucket}"
)
print(f" ✅ Added invoke permission for S3")
except Exception as e:
print(f" ℹ️ Permission may already exist: {e}")
# Configure filter rules
filter_rules = [{"Name": "prefix", "Value": prefix}]
if suffix:
filter_rules.append({"Name": "suffix", "Value": suffix})
# Attach the notification configuration to S3
# Note: This replaces ALL existing Lambda notifications - use carefully
s3_client.put_bucket_notification_configuration(
Bucket=bucket,
NotificationConfiguration={
"LambdaFunctionConfigurations": [
{
"LambdaFunctionArn": function_arn,
"Events": ["s3:ObjectCreated:*"],
"Filter": {"Key": {"FilterRules": filter_rules}}
}
]
}
)
print(f"✅ S3 trigger set for s3://{bucket}/{prefix} → {function_name}")
def invoke_lambda_sync(
lambda_client,
function_name: str,
payload: Optional[Dict] = None,
show_logs: bool = True
) -> Dict:
"""
Invoke Lambda synchronously and wait for response
Args:
function_name: Name of Lambda function
payload: Optional JSON payload
show_logs: Whether to print logs
Returns:
Response from Lambda function
"""
print(f"⚡ Invoking Lambda: {function_name}")
start_time = time.time()
invoke_params = {
"FunctionName": function_name,
"InvocationType": "RequestResponse",
"LogType": "Tail" if show_logs else "None"
}
if payload:
invoke_params["Payload"] = json.dumps(payload)
response = lambda_client.invoke(**invoke_params)
# Parse response
status_code = response["StatusCode"]
if "Payload" in response:
result = json.loads(response["Payload"].read())
else:
result = {}
elapsed = time.time() - start_time
if status_code == 200:
print(f"✅ Lambda completed successfully in {elapsed:.1f} seconds")
else:
print(f"⚠️ Lambda returned status code: {status_code}")
# Show logs if requested
if show_logs and "LogResult" in response:
import base64
log_data = base64.b64decode(response["LogResult"]).decode("utf-8")
print("\n📋 Lambda Logs:")
print("-" * 60)
for line in log_data.split("\n")[-20:]: # Last 20 lines
if line.strip():
print(line)
print("-" * 60)
return result
def monitor_s3_folder(
s3_client,
bucket: str,
prefix: str,
expected_count: Optional[int] = None
) -> List[str]:
"""
Monitor S3 folder for files
Args:
bucket: S3 bucket name
prefix: Folder prefix to monitor
expected_count: Optional expected number of files
Returns:
List of file keys found
"""
print(f"📁 Monitoring s3://{bucket}/{prefix}")
response = s3_client.list_objects_v2(Bucket=bucket, Prefix=prefix)
files = []
if "Contents" in response:
for obj in response["Contents"]:
if not obj["Key"].endswith("/"):
files.append(obj["Key"])
print(f" Found {len(files)} files")
if expected_count and len(files) < expected_count:
print(f" ⏳ Waiting for {expected_count - len(files)} more files...")
return files
def upload_folder_to_s3(
s3_client,
local_folder: str,
s3_prefix: str,
bucket: str,
file_extensions: Optional[List[str]] = None,
skip_existing: bool = True
) -> int:
"""
Upload entire folder to S3
Args:
local_folder: Local folder path
s3_prefix: S3 prefix for uploads
bucket: S3 bucket name
file_extensions: Optional list of extensions to filter
skip_existing: Skip files that already exist in S3 (default True)
Returns:
Number of files uploaded
"""
print(f"📤 Uploading {local_folder} → s3://{bucket}/{s3_prefix}")
if skip_existing:
print(" (Skipping files that already exist in S3)")
uploaded = 0
skipped = 0
local_path = Path(local_folder)
if not local_path.exists():
print(f"❌ Folder not found: {local_folder}")
return 0
files = list(local_path.glob("**/*"))
for file_path in files:
if file_path.is_file():
# Check extension filter
if file_extensions and file_path.suffix.lower() not in file_extensions:
continue
# Calculate S3 key
relative_path = file_path.relative_to(local_path)
s3_key = f"{s3_prefix}{relative_path}"
# Check if file already exists in S3
if skip_existing:
try:
s3_client.head_object(Bucket=bucket, Key=s3_key)
print(f" ⏭️ Skipping (already exists): {relative_path}")
skipped += 1
continue
except s3_client.exceptions.ClientError:
# File doesn't exist, proceed with upload
pass
# Upload file
print(f" ⬆️ Uploading: {relative_path}")
s3_client.upload_file(str(file_path), bucket, s3_key)
uploaded += 1
# Summary
if skipped > 0:
print(f"✅ Uploaded {uploaded} files, skipped {skipped} existing files")
else:
print(f"✅ Uploaded {uploaded} files")
return uploaded
def monitor_lambda_processing(
logs_client,
s3_client,
bucket_name: str,
function_name: str = "ade-s3-handler",
lookback_minutes: int = 10,
output_prefix: str = "output/"
) -> Dict:
"""
Monitor Lambda processing and display results.
Args:
logs_client: Boto3 CloudWatch Logs client
s3_client: Boto3 S3 client
bucket_name: S3 bucket name
function_name: Lambda function name to monitor
lookback_minutes: How many minutes back to look in logs
output_prefix: S3 prefix for output files
Returns:
Dict with processing statistics
"""
import time
log_group = f"/aws/lambda/{function_name}"
print(f"⏳ Monitoring Lambda processing...")
print(" To stop monitoring, press esc followed by double clicking i\n")
# Track processed files
processed_files = set()
processing_files = set()
skipped_files = set()
error_files = set()
start_time = int((time.time() - (lookback_minutes * 60)) * 1000)
try:
while True:
resp = logs_client.filter_log_events(logGroupName=log_group, startTime=start_time)
events = resp.get("events", [])
for event in events:
message = event["message"].strip()
# Track successful completions
if "🎉 Completed pipeline for" in message:
file_name = message.split("Completed pipeline for ")[1].split(" →")[0]
if file_name not in processed_files:
processed_files.add(file_name)
print(f"✅ Processed: {file_name}")
# Track files being processed (but don't print)
elif "🤖 Starting ADE parsing for" in message:
file_name = message.split("parsing for ")[1].split(" (")[0]
processing_files.add(file_name)
# Track skipped files
elif "⏭️ Skipping" in message and "already processed" in message:
file_name = message.split("Skipping ")[1].split(" -")[0]
if file_name not in skipped_files:
skipped_files.add(file_name)
print(f"⏭️ Skipped (already exists): {file_name}")
# Show errors
elif "❌ Error processing" in message:
print(f" {message}")
try:
file_name = message.split("Error processing ")[1].split(":")[0]
error_files.add(file_name)
except:
pass
start_time = max(start_time, event["timestamp"] + 1)
time.sleep(5)
except KeyboardInterrupt:
print(f"\n⛔ Monitoring stopped by user")
# Show summary from logs
print(f"\n📊 Lambda Processing Summary:")
print(f" Processed: {len(processed_files)} files")
print(f" Skipped: {len(skipped_files)} files")
print(f" Errors: {len(error_files)} files")
if processed_files:
print("\n Files processed in this session:")
for f in sorted(processed_files):
print(f" - {f}")
# Check what's actually in the output folder
print(f"\n📁 Checking S3 {output_prefix} folder...")
response = s3_client.list_objects_v2(
Bucket=bucket_name,
Prefix=output_prefix,
MaxKeys=1000 # Get all files
)
output_files = []
if "Contents" in response:
output_files = [obj["Key"] for obj in response["Contents"] if not obj["Key"].endswith("/")]
print(f" Total files in {output_prefix}: {len(output_files)}")
# Organize by folder
folders = {}
for key in output_files:
parts = key.split("/")
if len(parts) > 2: # Has subfolder
folder = parts[1]
if folder not in folders:
folders[folder] = []
folders[folder].append(key)
elif len(parts) == 2: # Direct in output/
if "root" not in folders:
folders["root"] = []
folders["root"].append(key)
# Display organized summary
if folders:
print(f"\n Files by folder:")
for folder, files in sorted(folders.items()):
if folder == "root":
print(f" {output_prefix} (root): {len(files)} files")
else:
print(f" {output_prefix}{folder}/: {len(files)} files")
# Option to show all files
show_all = input("\n Show all output files? (y/n): ").lower() == 'y'
if show_all:
print("\n All output files:")
for key in sorted(output_files):
print(f" - {key}")
else:
print(f" No files found in {output_prefix} yet")
return {
"processed": len(processed_files),
"skipped": len(skipped_files),
"errors": len(error_files),
"total_output_files": len(output_files),
"processed_files": list(processed_files),
"output_files": output_files
}