create db2 exporter for Prometheus .use Django as web server

 Creating a DB2 exporter for Prometheus using Python and integrating it with Django as a web server for Prometheus scraping 

```python
# Import necessary libraries
import time
from prometheus_client import start_http_server, Gauge
import ibm_db

# Constants for DB2 connection
DB2_HOST = 'your_db2_host'
DB2_PORT = 50000
DB2_DATABASE = 'your_db2_database'
DB2_USER = 'your_db2_username'
DB2_PASSWORD = 'your_db2_password'

# Connect to DB2
def connect_to_db2():
    conn_str = f"DATABASE={DB2_DATABASE};HOSTNAME={DB2_HOST};PORT={DB2_PORT};PROTOCOL=TCPIP;UID={DB2_USER};PWD={DB2_PASSWORD};"
    conn = ibm_db.connect(conn_str, '', '')
    return conn

# Query function to get metrics from DB2
def query_db2_metrics(conn):
    query = "SELECT COUNT(*) FROM your_table;"
    stmt = ibm_db.exec_immediate(conn, query)
    result = ibm_db.fetch_both(stmt)
    return result[0]

# Define Prometheus metrics
db2_metric = Gauge('db2_table_row_count', 'Number of rows in the table')

# Function to update metrics
def update_metrics():
    conn = connect_to_db2()
    row_count = query_db2_metrics(conn)
    db2_metric.set(row_count)
    ibm_db.close(conn)

# Function to run the HTTP server
def run_server():
    start_http_server(8000)
    while True:
        update_metrics()
        time.sleep(10)

# Run the server
if __name__ == '__main__':
    run_server()
```

This script does the following:

1. Connects to your DB2 database using the `ibm_db` library.
2. Queries a specified table to get the row count (you should replace `your_table` with the actual table name you want to monitor).
3. Exposes a Prometheus metric `db2_table_row_count` which represents the number of rows in the specified table.
4. Starts an HTTP server on port 8000 using `start_http_server` from `prometheus_client`.
5. Periodically updates the metric by querying the DB2 database.
6. Runs indefinitely to keep serving the metrics.

Now, for integrating with Django, you can use Django's views to expose the metrics endpoint for Prometheus scraping. Here's how you can modify the above script to integrate with Django:

```python
from django.http import HttpResponse
from prometheus_client import generate_latest, REGISTRY

# Add this function to your script
def prometheus_metrics(request):
    return HttpResponse(generate_latest(REGISTRY), content_type="text/plain")

# Modify run_server() function to run Django server
def run_server():
    # Start Django server
    from django.core.management import execute_from_command_line
    execute_from_command_line(['manage.py', 'runserver', '0.0.0.0:8000'])

# Add this line at the end of your script
urlpatterns = [path('metrics', prometheus_metrics)]

#  Django app URL configuration will need to include this urlpatterns
```

In this setup, Django is used to serve the metrics endpoint at `/metrics`, which is where Prometheus will scrape the metrics from. Make sure to include the `prometheus_metrics` view in your Django app's URL configuration.