import requests
from requests.auth import HTTPBasicAuth
import csv
import json
import time  # Import time module to use for adding delays

# Replace with your Jira credentials and URL
JIRA_URL = "https://<instance>.atlassian.net"
API_PROJECTS_ENDPOINT = "/rest/api/3/project/search"
API_WORKFLOW_ENDPOINT = "/rest/api/3/workflowscheme/project"
USERNAME = "<email_address>"
API_TOKEN = "<API_TOKEN>"

# Delay time in seconds (customize as needed)
DELAY_TIME = 1  # 2-second delay between API calls

# Jira API headers
headers = {
    "Accept": "application/json"
}

# Function to get the workflow scheme for a project by project ID
def get_workflow_for_project(project_id):
    url = f"{JIRA_URL}{API_WORKFLOW_ENDPOINT}?projectId={project_id}"
    
    response = requests.get(url, headers=headers, auth=HTTPBasicAuth(USERNAME, API_TOKEN))
    
    if response.status_code != 200:
        print(f"Failed to fetch workflow for project ID {project_id}. Status code: {response.status_code}")
        return "N/A"
    
    data = response.json()

    # Ensure "values" exist and has at least one item
    if "values" in data and len(data['values']) > 0:
        workflow_scheme = data['values'][0].get('workflowScheme', {})
        return workflow_scheme.get('name', 'N/A')  # Get the workflow scheme name
    else:
        return "N/A"

# Function to extract issue types for a project
def get_issue_types_for_project(project):
    issue_types = project.get('issueTypes', [])
    
    # Extract the names of all issue types and join them with commas
    issue_type_names = [issue_type.get('name') for issue_type in issue_types]
    
    return ", ".join(issue_type_names) if issue_type_names else "N/A"

# Function to get paginated projects
def get_paginated_projects():
    start_at = 0
    max_results = 50  # Adjust as needed
    all_projects = []
    total_projects = None  # Initialize total projects as None initially
    
    while True:
        # Set the API URL with pagination and expand parameters
        url = f"{JIRA_URL}{API_PROJECTS_ENDPOINT}?expand=lead,insight,issueTypes&startAt={start_at}&maxResults={max_results}"
        
        # Send a GET request to the Jira API
        response = requests.get(url, headers=headers, auth=HTTPBasicAuth(USERNAME, API_TOKEN))
        
        if response.status_code != 200:
            print(f"Failed to fetch projects. Status code: {response.status_code}, Response: {response.text}")
            break
        
        # Parse the response JSON
        data = response.json()

        # Set total projects on the first API call
        if total_projects is None:
            total_projects = data['total']
            print(f"Total number of projects to fetch: {total_projects}")
        
        # Extract the required fields and fetch workflow scheme and issue types
        for project in data['values']:
            project_id = project.get('id')  # Get the project ID
            workflow_name = get_workflow_for_project(project_id)  # Get the workflow scheme for this project
            
            insight = project.get('insight', {})
            issue_types = get_issue_types_for_project(project)  # Get the issue types for this project
            
            project_info = {
                "Project Key": project.get('key'),
                "Project ID": project.get('id'),
                "Project Name": project.get('name'),
                "Project Lead": project.get('lead', {}).get('displayName', 'N/A'),
                "totalIssueCount": insight.get('totalIssueCount', 'N/A'),
                "lastIssueUpdateTime": insight.get('lastIssueUpdateTime', 'N/A'),
                "Assigned Workflow": workflow_name,  # Add the workflow scheme name
                "issueTypes": issue_types  # Add the issue types
            }
            all_projects.append(project_info)

        # Print progress after each API call
        print(f"Fetched {len(all_projects)} projects out of {total_projects} so far.")
        
        # Check if there are more results to fetch
        if len(data['values']) < max_results:
            break  # No more pages to fetch
        
        # Increment the starting index for pagination
        start_at += max_results
        
        # Add delay between consecutive API requests
        time.sleep(DELAY_TIME)  # Delay between requests

    return all_projects

# Function to export data to CSV
def export_to_csv(projects, file_name="projects_with_lead_insight_workflow_issuetypes.csv"):
    # Define the CSV file headers
    headers = ["Project Key", "Project ID", "Project Name", "Project Lead", "totalIssueCount", "lastIssueUpdateTime", "Assigned Workflow", "issueTypes"]
    
    # Write to CSV
    with open(file_name, mode='w', newline='', encoding='utf-8') as file:
        writer = csv.DictWriter(file, fieldnames=headers)
        
        # Write the header row
        writer.writeheader()
        
        # Write project data rows
        for project in projects:
            writer.writerow(project)

# Fetch all paginated projects
projects = get_paginated_projects()

# Export the data to a CSV file
export_to_csv(projects, "jira_projects_with_lead_insight_workflow_issuetypes.csv")

print(f"Exported {len(projects)} projects to 'jira_projects_with_lead_insight_workflow_issuetypes.csv'")