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Author SHA1 Message Date
Ankur Malik
7d067ca5cb Ensure application_key included in connected keys
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2025-11-26 11:39:13 -05:00
204f2d50c7 Update config.json
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2025-11-24 06:12:42 +00:00
Ankur Malik
2e162d9813 Update mlg_lookup block and schemas
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2025-11-23 23:30:21 -05:00
88b296a25a Upload files to "/"
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2025-07-11 15:10:24 +00:00
a0e78fac57 Upload files to "/"
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2025-03-25 21:12:54 +00:00
43e4c2f412 Update block.py
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2025-03-13 00:51:46 +00:00
6d94849e2d Graph lookup block
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2025-03-12 16:14:28 +00:00
9 changed files with 320 additions and 23 deletions

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**Hello world!!!** # MLG Lookup
Lookup Graph API

111
block.py
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@flowx_block import logging
def example_function(request: dict) -> dict: import json
import os
from pre_processing import process_record
from post_processing import post_processing
# Processing logic here... # Configure logging
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s [%(levelname)s] %(name)s - %(message)s",
)
logger = logging.getLogger(__name__)
return { def load_schema(path: str):
"meta_info": [ """Helper to read the JSON config file."""
{ with open(path, "r") as f:
"name": "created_date", return json.load(f)
"type": "string",
"value": "2024-11-05" def get_cluster_name(namespace: str) -> str:
} """
], Fetches the clusterName for the given namespace from config.json.
"fields": [ Expects config.json to contain a list of { "namespace": "...", "clusterName": "..." }.
{ """
"name": "", response_schema = load_schema("/app/config.json") # Update path if needed
"type": "", for item in response_schema:
"value": "" if item.get("namespace") == namespace:
} logger.info("Got the clusterName for namespace '%s'", namespace)
] return item.get("clusterName")
} logger.error("Provided Namespace '%s' not found in config.json.", namespace)
raise ValueError(f"Namespace '{namespace}' not found")
def __main__(
application_key: str,
application_timestamp: str,
deviceid: str,
fuzzydeviceid: str,
application_email_address: str,
hd_score_m1: float,
hd_score_iso_m2: float
) -> dict:
namespace = os.getenv("NAMESPACE", "staging")
base_url = "http://centurion-mlg.default.svc.cluster.local:8080/api/v1/clusters"
# base_url = "http://localhost:8080//api/v1/clusters"
cluster_name = get_cluster_name(namespace)
# cluster_name = "cluster_deviceid_email_fuzzydevice_direct_new"
url_post = f"{base_url}/{cluster_name}/records"
url_get = f"{base_url}/{cluster_name}/record"
url_get_for_graph = f"{base_url}/{cluster_name}/graph"
data = {
"application_key": application_key,
"application_timestamp": application_timestamp,
"deviceid": deviceid,
"fuzzydeviceid": fuzzydeviceid,
"application_email_address": application_email_address,
"hd_score_m1": hd_score_m1,
}
# Step 1: Pre-process the record
pre_process_output = process_record(url_post, data)
if not pre_process_output or "error" in pre_process_output:
logger.error("Pre-processing failed.")
return {"error": "Pre-processing failed"}
# Step 2: Process the record (fetch required fields)
# post_process_output = post_processing(process_output, url_get)
# is_duplicate = pre_process_output.get("record_id") in pre_process_output.get("connected_records", [])
is_duplicate = str(pre_process_output.get("is_duplicate", "false")).strip().lower() == "true"
# print(is_duplicate)
# Run the appropriate processing function
# if is_duplicate:
# process_output = processing(url_get, pre_process_output)
# post_process_output = post_processing_duplicate(process_output, url_get)
# else:
# post_process_output = post_processing(pre_process_output, url_get)
post_process_output = post_processing(pre_process_output, url_get, url_get_for_graph)
# Conditionally override the keys if they are missing or None (or the string "null")
current_app_key = post_process_output.get("application_key")
if current_app_key is None:
post_process_output["application_key"] = application_key
current_hd_score = post_process_output.get("hd_score_m1")
if current_hd_score is None:
post_process_output["hd_score_m1"] = hd_score_m1
post_process_output["hd_score_iso_m2"] = hd_score_iso_m2
logger.info("Post Processed Record")
logger.info(post_process_output)
return post_process_output

14
config.json Normal file
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[
{
"namespace": "staging",
"clusterName": "cluster_deviceid_email_fuzzydevice_direct_new"
},
{
"namespace": "production",
"clusterName": "cluster_deviceid_email_fuzzydevice_direct_new_prod"
},
{
"namespace": "production-beta",
"clusterName": "cluster_deviceid_email_fuzzydevice_direct_new_prod"
}
]

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post_processing.py Normal file
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import requests
import logging
# Configure logging
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s [%(levelname)s] %(name)s - %(message)s",
)
logger = logging.getLogger(__name__)
def fetch_data(url, record_id):
"""Fetches data for a given record_id from the API."""
try:
response = requests.get(f"{url}/{record_id}", headers={"Content-Type": "application/json"})
if response.status_code == 200:
output= response.json()
return output
else:
logger.error(f"Failed to fetch {record_id}: {response.status_code}")
return None
except requests.RequestException as e:
logger.error(f"Error fetching {record_id}: {e}")
return None
def fetch_all_nodes_data(url, cluster_id):
try:
response = requests.get(f"{url}/{cluster_id}", headers={"Content-Type": "application/json"})
if response.status_code == 200:
output= response.json()
return output
else:
logger.error(f"Failed to fetch {cluster_id}: {response.status_code}")
return None
except requests.RequestException as e:
logger.error(f"Error fetching {cluster_id}: {e}")
return None
def post_processing(data, url, url_get_for_graph):
"""Main function to fetch and extract required fields."""
record_id = data.get('hd_key')
# connected_records = data.get('matches', []) + [record_id] # Matches + hd_key
cluster_id = data.get('cluster_id')
# Fetch main record data
application_key = None
hd_score_m1 = None
if record_id:
record_data = fetch_data(url, record_id)
if record_data and 'data' in record_data:
application_key = record_data['data'].get('application_key')
hd_score_m1 = record_data['data'].get('hd_score_m1')
# Fetch application_key for connected records
connected_keys = []
if cluster_id:
response_obj = fetch_all_nodes_data(url_get_for_graph, cluster_id)
if response_obj and "nodes" in response_obj:
# Extract and filter application_keys
all_keys = [
node.get('data', {}).get('application_key')
for node in response_obj['nodes']
if node.get('data') and node['data'].get('application_key') is not None
]
# Exclude the current application_key and limit to 500 entries
connected_keys = [
key for key in all_keys if key != application_key
][:500]
if application_key is not None and application_key not in connected_keys:
connected_keys.append(application_key)
return {
"application_key": application_key,
"hd_score_m1": hd_score_m1,
"connected_application_keys": connected_keys
}

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pre_processing.py Normal file
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import requests
import logging
# Configure logging
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s [%(levelname)s] %(name)s - %(message)s",
)
logger = logging.getLogger(__name__)
def process_record(url, record):
try:
response = requests.post(
url,
json={"record": record},
headers={"Content-Type": "application/json"}
)
if response.status_code == 200:
output = response.json()
logger.info(f"Pre Processed record: {record['application_key']} - Response: {output}")
return output
elif response.status_code == 404:
# Special-case handling for "CLUSTER_NOT_FOUND" (or any 404).
# Return a benign structure that includes 'hd_key' and 'matches'
# so post_processing does not fail when it does:
# record_id = data.get('hd_key')
# connected_records = data.get('matches', []) + [record_id]
logger.warning(
f"Ignoring 404 for record {record['application_key']}. "
f"Status: 404, Response: {response.text}"
)
return {
"application_key": record.get("application_key"),
"hd_key": None,
"matches": []
}
else:
logger.error(f"Failed to process record {record['application_key']}. Status: {response.status_code}, Response: {response.text}")
return {"error": response.text}
except Exception as e:
logger.error(f"Error processing record {record['application_key']}: {str(e)}")
return {"error": str(e)}

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processing.py Normal file
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import requests
import logging
# Configure logging
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s [%(levelname)s] %(name)s - %(message)s",
)
logger = logging.getLogger(__name__)
def processing(url, data):
record_id = data.get('hd_key')
try:
response = requests.get(
f"{url}/{record_id}",
headers={"Content-Type": "application/json"}
)
if response.status_code == 200:
output = response.json()
logger.info(f"Processed record: {record_id} - Response: {output}")
return output
else:
logger.error(f"Failed to process record {record_id}. Status: {response.status_code}, Response: {response.text}")
return {"error": response.text}
except Exception as e:
logger.error(f"Error processing record {record_id}: {str(e)}")
return {"error": str(e)}

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{} {
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"properties": {
"application_key": {
"type": ["string", "null"],
"description": "Unique identifier for the application."
},
"application_timestamp": {
"type": ["string", "null"],
"description": "Timestamp of the application."
},
"deviceid": {
"type": ["string", "null"],
"description": "Unique identifier for the device used in the application."
},
"fuzzydeviceid": {
"type": ["string", "null"],
"description": "Anonymized or hashed identifier for the device."
},
"application_email_address": {
"type": ["string", "null"],
"description": "Email address associated with the application."
},
"hd_score_m1": {
"type": ["number", "null"],
"description": "HD Score M1 value associated with the application."
},
"hd_score_iso_m2": {
"type": ["number", "null"],
"description": "HD Score M2 Isotonic value associated with the application."
}
},
"required": []
}

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{} requests == 2.32.3

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{} {
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"properties": {
"application_key": {
"type": ["string", "null"],
"description": "Unique identifier for the application."
},
"hd_score_m1": {
"type": ["number", "null"],
"description": "HD fraud score M1."
},
"hd_score_iso_m2": {
"type": ["number", "null"],
"description": "HD fraud score M2."
},
"connected_application_keys": {
"type": "array",
"items": {
"type": ["string", "null"]
},
"description": "List of connected application keys associated with this application."
}
},
"required": []
}