from __future__ import print_function
import logging

import reprlib

import os
import socket
import subprocess
import textwrap
from importlib import import_module

import argparse
from builtins import input
from collections import namedtuple
from dateutil.parser import parse as parsedate
import json
from tabulate import tabulate

import daemon
from daemon.pidfile import TimeoutPIDLockFile
import signal
import sys
import threading
import traceback
import time
import psutil
import re

import airflow
from airflow import api
from airflow import jobs, settings
from airflow import configuration as conf
from airflow.exceptions import AirflowException
from airflow.executors import GetDefaultExecutor
from airflow.models import (DagModel, DagBag, TaskInstance,
                            DagPickle, DagRun, Variable, DagStat,
                            Connection, DAG)

from airflow.ti_deps.dep_context import (DepContext, SCHEDULER_DEPS)
from airflow.utils import db as db_utils
from airflow.www.app import cached_app

from sqlalchemy import func
from sqlalchemy.orm import exc

api.load_auth()
api_module = import_module(conf.get('cli', 'api_client'))
api_client = api_module.Client(api_base_url=conf.get('cli', 'endpoint_url'),
                               auth=api.api_auth.client_auth)


def sigint_handler(sig, frame):
    sys.exit(0)


def sigquit_handler(sig, frame):
    """Helps debug deadlocks by printing stacktraces when this gets a SIGQUIT
    e.g. kill -s QUIT <PID> or CTRL+\
    """
    print("Dumping stack traces for all threads in PID {}".format(os.getpid()))
    id_to_name = dict([(th.ident, th.name) for th in threading.enumerate()])
    code = []
    for thread_id, stack in sys._current_frames().items():
        code.append("\n# Thread: {}({})"
                    .format(id_to_name.get(thread_id, ""), thread_id))
        for filename, line_number, name, line in traceback.extract_stack(stack):
            code.append('File: "{}", line {}, in {}'
                        .format(filename, line_number, name))
            if line:
                code.append("  {}".format(line.strip()))
    print("\n".join(code))


def setup_logging(filename):
    root = logging.getLogger()
    handler = logging.FileHandler(filename)
    formatter = logging.Formatter(settings.SIMPLE_LOG_FORMAT)
    handler.setFormatter(formatter)
    root.addHandler(handler)
    root.setLevel(settings.LOGGING_LEVEL)

    return handler.stream


def setup_locations(process, pid=None, stdout=None, stderr=None, log=None):
    if not stderr:
        stderr = os.path.join(os.path.expanduser(settings.AIRFLOW_HOME), "airflow-{}.err".format(process))
    if not stdout:
        stdout = os.path.join(os.path.expanduser(settings.AIRFLOW_HOME), "airflow-{}.out".format(process))
    if not log:
        log = os.path.join(os.path.expanduser(settings.AIRFLOW_HOME), "airflow-{}.log".format(process))
    if not pid:
        pid = os.path.join(os.path.expanduser(settings.AIRFLOW_HOME), "airflow-{}.pid".format(process))

    return pid, stdout, stderr, log


def process_subdir(subdir):
    if subdir:
        subdir = subdir.replace('DAGS_FOLDER', settings.DAGS_FOLDER)
        subdir = os.path.abspath(os.path.expanduser(subdir))
        return subdir


def get_dag(args):
    dagbag = DagBag(process_subdir(args.subdir))
    if args.dag_id not in dagbag.dags:
        raise AirflowException(
            'dag_id could not be found: {}. Either the dag did not exist or it failed to '
            'parse.'.format(args.dag_id))
    return dagbag.dags[args.dag_id]


def get_dags(args):
    if not args.dag_regex:
        return [get_dag(args)]
    dagbag = DagBag(process_subdir(args.subdir))
    matched_dags = [dag for dag in dagbag.dags.values() if re.search(
        args.dag_id, dag.dag_id)]
    if not matched_dags:
        raise AirflowException(
            'dag_id could not be found with regex: {}. Either the dag did not exist '
            'or it failed to parse.'.format(args.dag_id))
    return matched_dags


def backfill(args, dag=None):
    logging.basicConfig(
        level=settings.LOGGING_LEVEL,
        format=settings.SIMPLE_LOG_FORMAT)

    dag = dag or get_dag(args)

    if not args.start_date and not args.end_date:
        raise AirflowException("Provide a start_date and/or end_date")

    # If only one date is passed, using same as start and end
    args.end_date = args.end_date or args.start_date
    args.start_date = args.start_date or args.end_date

    if args.task_regex:
        dag = dag.sub_dag(
            task_regex=args.task_regex,
            include_upstream=not args.ignore_dependencies)

    if args.dry_run:
        print("Dry run of DAG {0} on {1}".format(args.dag_id,
                                                 args.start_date))
        for task in dag.tasks:
            print("Task {0}".format(task.task_id))
            ti = TaskInstance(task, args.start_date)
            ti.dry_run()
    else:
        dag.run(
            start_date=args.start_date,
            end_date=args.end_date,
            mark_success=args.mark_success,
            include_adhoc=args.include_adhoc,
            local=args.local,
            donot_pickle=(args.donot_pickle or
                          conf.getboolean('core', 'donot_pickle')),
            ignore_first_depends_on_past=args.ignore_first_depends_on_past,
            ignore_task_deps=args.ignore_dependencies,
            pool=args.pool,
            delay_on_limit_secs=args.delay_on_limit)


def trigger_dag(args):
    """
    Creates a dag run for the specified dag
    :param args:
    :return:
    """
    try:
        message = api_client.trigger_dag(dag_id=args.dag_id,
                                         run_id=args.run_id,
                                         conf=args.conf,
                                         execution_date=args.exec_date)
    except IOError as err:
        logging.error(err)
        raise AirflowException(err)

    logging.info(message)


def pool(args):
    def _tabulate(pools):
        return "\n%s" % tabulate(pools, ['Pool', 'Slots', 'Description'],
                                 tablefmt="fancy_grid")

    try:
        if args.get is not None:
            pools = [api_client.get_pool(name=args.get)]
        elif args.set:
            pools = [api_client.create_pool(name=args.set[0],
                                            slots=args.set[1],
                                            description=args.set[2])]
        elif args.delete:
            pools = [api_client.delete_pool(name=args.delete)]
        else:
            pools = api_client.get_pools()
    except (AirflowException, IOError) as err:
        logging.error(err)
    else:
        logging.info(_tabulate(pools=pools))


def variables(args):
    if args.get:
        try:
            var = Variable.get(args.get,
                               deserialize_json=args.json,
                               default_var=args.default)
            print(var)
        except ValueError as e:
            print(e)
    if args.delete:
        session = settings.Session()
        session.query(Variable).filter_by(key=args.delete).delete()
        session.commit()
        session.close()
    if args.set:
        Variable.set(args.set[0], args.set[1])
    # Work around 'import' as a reserved keyword
    imp = getattr(args, 'import')
    if imp:
        if os.path.exists(imp):
            import_helper(imp)
        else:
            print("Missing variables file.")
    if args.export:
        export_helper(args.export)
    if not (args.set or args.get or imp or args.export or args.delete):
        # list all variables
        session = settings.Session()
        vars = session.query(Variable)
        msg = "\n".join(var.key for var in vars)
        print(msg)


def import_helper(filepath):
    with open(filepath, 'r') as varfile:
        var = varfile.read()

    try:
        d = json.loads(var)
    except Exception:
        print("Invalid variables file.")
    else:
        try:
            n = 0
            for k, v in d.items():
                if isinstance(v, dict):
                    Variable.set(k, v, serialize_json=True)
                else:
                    Variable.set(k, v)
                n += 1
        except Exception:
            pass
        finally:
            print("{} of {} variables successfully updated.".format(n, len(d)))


def export_helper(filepath):
    session = settings.Session()
    qry = session.query(Variable).all()
    session.close()

    var_dict = {}
    d = json.JSONDecoder()
    for var in qry:
        val = None
        try:
            val = d.decode(var.val)
        except Exception:
            val = var.val
        var_dict[var.key] = val

    with open(filepath, 'w') as varfile:
        varfile.write(json.dumps(var_dict, sort_keys=True, indent=4))
    print("{} variables successfully exported to {}".format(len(var_dict), filepath))


def pause(args, dag=None):
    set_is_paused(True, args, dag)


def unpause(args, dag=None):
    set_is_paused(False, args, dag)


def set_is_paused(is_paused, args, dag=None):
    dag = dag or get_dag(args)

    session = settings.Session()
    dm = session.query(DagModel).filter(
        DagModel.dag_id == dag.dag_id).first()
    dm.is_paused = is_paused
    session.commit()

    msg = "Dag: {}, paused: {}".format(dag, str(dag.is_paused))
    print(msg)


def run(args, dag=None):
    # Disable connection pooling to reduce the # of connections on the DB
    # while it's waiting for the task to finish.
    settings.configure_orm(disable_connection_pool=True)
    db_utils.pessimistic_connection_handling()
    if dag:
        args.dag_id = dag.dag_id

    # Load custom airflow config
    if args.cfg_path:
        with open(args.cfg_path, 'r') as conf_file:
            conf_dict = json.load(conf_file)

        if os.path.exists(args.cfg_path):
            os.remove(args.cfg_path)

        for section, config in conf_dict.items():
            for option, value in config.items():
                conf.set(section, option, value)
        settings.configure_vars()
        settings.configure_orm()

    if not args.pickle and not dag:
        dag = get_dag(args)
    elif not dag:
        session = settings.Session()
        logging.info('Loading pickle id {args.pickle}'.format(args=args))
        dag_pickle = session.query(
            DagPickle).filter(DagPickle.id == args.pickle).first()
        if not dag_pickle:
            raise AirflowException("Who hid the pickle!? [missing pickle]")
        dag = dag_pickle.pickle

    task = dag.get_task(task_id=args.task_id)
    ti = TaskInstance(task, args.execution_date)
    ti.refresh_from_db()

    logger = logging.getLogger('airflow.task')
    if args.raw:
        logger = logging.getLogger('airflow.task.raw')

    for handler in logger.handlers:
        try:
            handler.set_context(ti)
        except AttributeError:
            # Not all handlers need to have context passed in so we ignore
            # the error when handlers do not have set_context defined.
            pass

    hostname = socket.getfqdn()
    logging.info("Running on host {}".format(hostname))

    if args.local:
        run_job = jobs.LocalTaskJob(
            task_instance=ti,
            mark_success=args.mark_success,
            pickle_id=args.pickle,
            ignore_all_deps=args.ignore_all_dependencies,
            ignore_depends_on_past=args.ignore_depends_on_past,
            ignore_task_deps=args.ignore_dependencies,
            ignore_ti_state=args.force,
            pool=args.pool)
        run_job.run()
    elif args.raw:
        ti.run(
            mark_success=args.mark_success,
            ignore_all_deps=args.ignore_all_dependencies,
            ignore_depends_on_past=args.ignore_depends_on_past,
            ignore_task_deps=args.ignore_dependencies,
            ignore_ti_state=args.force,
            job_id=args.job_id,
            pool=args.pool,
        )
    else:
        pickle_id = None
        if args.ship_dag:
            try:
                # Running remotely, so pickling the DAG
                session = settings.Session()
                pickle = DagPickle(dag)
                session.add(pickle)
                session.commit()
                pickle_id = pickle.id
                print((
                          'Pickled dag {dag} '
                          'as pickle_id:{pickle_id}').format(**locals()))
            except Exception as e:
                print('Could not pickle the DAG')
                print(e)
                raise e

        executor = GetDefaultExecutor()
        executor.start()
        print("Sending to executor.")
        executor.queue_task_instance(
            ti,
            mark_success=args.mark_success,
            pickle_id=pickle_id,
            ignore_all_deps=args.ignore_all_dependencies,
            ignore_depends_on_past=args.ignore_depends_on_past,
            ignore_task_deps=args.ignore_dependencies,
            ignore_ti_state=args.force,
            pool=args.pool)
        executor.heartbeat()
        executor.end()

    # Child processes should not flush or upload to remote
    if args.raw:
        return

    # Force the log to flush. The flush is important because we
    # might subsequently read from the log to insert into S3 or
    # Google cloud storage. Explicitly close the handler is
    # needed in order to upload to remote storage services.
    for handler in logger.handlers:
        handler.flush()
        handler.close()


def task_failed_deps(args):
    """
    Returns the unmet dependencies for a task instance from the perspective of the
    scheduler (i.e. why a task instance doesn't get scheduled and then queued by the
    scheduler, and then run by an executor).

    >>> airflow task_failed_deps tutorial sleep 2015-01-01
    Task instance dependencies not met:
    Dagrun Running: Task instance's dagrun did not exist: Unknown reason
    Trigger Rule: Task's trigger rule 'all_success' requires all upstream tasks to have succeeded, but found 1 non-success(es).
    """
    dag = get_dag(args)
    task = dag.get_task(task_id=args.task_id)
    ti = TaskInstance(task, args.execution_date)

    dep_context = DepContext(deps=SCHEDULER_DEPS)
    failed_deps = list(ti.get_failed_dep_statuses(dep_context=dep_context))
    if failed_deps:
        print("Task instance dependencies not met:")
        for dep in failed_deps:
            print("{}: {}".format(dep.dep_name, dep.reason))
    else:
        print("Task instance dependencies are all met.")


def task_state(args):
    """
    Returns the state of a TaskInstance at the command line.

    >>> airflow task_state tutorial sleep 2015-01-01
    success
    """
    dag = get_dag(args)
    task = dag.get_task(task_id=args.task_id)
    ti = TaskInstance(task, args.execution_date)
    print(ti.current_state())


def dag_state(args):
    """
    Returns the state of a DagRun at the command line.

    >>> airflow dag_state tutorial 2015-01-01T00:00:00.000000
    running
    """
    dag = get_dag(args)
    dr = DagRun.find(dag.dag_id, execution_date=args.execution_date)
    print(dr[0].state if len(dr) > 0 else None)


def list_dags(args):
    dagbag = DagBag(process_subdir(args.subdir))
    s = textwrap.dedent("""\n
    -------------------------------------------------------------------
    DAGS
    -------------------------------------------------------------------
    {dag_list}
    """)
    dag_list = "\n".join(sorted(dagbag.dags))
    print(s.format(dag_list=dag_list))
    if args.report:
        print(dagbag.dagbag_report())


def list_tasks(args, dag=None):
    dag = dag or get_dag(args)
    if args.tree:
        dag.tree_view()
    else:
        tasks = sorted([t.task_id for t in dag.tasks])
        print("\n".join(sorted(tasks)))


def test(args, dag=None):
    dag = dag or get_dag(args)

    task = dag.get_task(task_id=args.task_id)
    # Add CLI provided task_params to task.params
    if args.task_params:
        passed_in_params = json.loads(args.task_params)
        task.params.update(passed_in_params)
    ti = TaskInstance(task, args.execution_date)

    if args.dry_run:
        ti.dry_run()
    else:
        ti.run(ignore_task_deps=True, ignore_ti_state=True, test_mode=True)


def render(args):
    dag = get_dag(args)
    task = dag.get_task(task_id=args.task_id)
    ti = TaskInstance(task, args.execution_date)
    ti.render_templates()
    for attr in task.__class__.template_fields:
        print(textwrap.dedent("""\
        # ----------------------------------------------------------
        # property: {}
        # ----------------------------------------------------------
        {}
        """.format(attr, getattr(task, attr))))


def clear(args):
    logging.basicConfig(
        level=settings.LOGGING_LEVEL,
        format=settings.SIMPLE_LOG_FORMAT)
    dags = get_dags(args)

    if args.task_regex:
        for idx, dag in enumerate(dags):
            dags[idx] = dag.sub_dag(
                task_regex=args.task_regex,
                include_downstream=args.downstream,
                include_upstream=args.upstream)

    DAG.clear_dags(
        dags,
        start_date=args.start_date,
        end_date=args.end_date,
        only_failed=args.only_failed,
        only_running=args.only_running,
        confirm_prompt=not args.no_confirm,
        include_subdags=not args.exclude_subdags)


def restart_workers(gunicorn_master_proc, num_workers_expected):
    """
    Runs forever, monitoring the child processes of @gunicorn_master_proc and
    restarting workers occasionally.

    Each iteration of the loop traverses one edge of this state transition
    diagram, where each state (node) represents
    [ num_ready_workers_running / num_workers_running ]. We expect most time to
    be spent in [n / n]. `bs` is the setting webserver.worker_refresh_batch_size.

    The horizontal transition at ? happens after the new worker parses all the
    dags (so it could take a while!)

       V ────────────────────────────────────────────────────────────────────────┐
    [n / n] ──TTIN──> [ [n, n+bs) / n + bs ]  ────?───> [n + bs / n + bs] ──TTOU─┘
       ^                          ^───────────────┘
       │
       │      ┌────────────────v
       └──────┴────── [ [0, n) / n ] <─── start

    We change the number of workers by sending TTIN and TTOU to the gunicorn
    master process, which increases and decreases the number of child workers
    respectively. Gunicorn guarantees that on TTOU workers are terminated
    gracefully and that the oldest worker is terminated.
    """

    def wait_until_true(fn):
        """
        Sleeps until fn is true
        """
        while not fn():
            time.sleep(0.1)

    def get_num_workers_running(gunicorn_master_proc):
        workers = psutil.Process(gunicorn_master_proc.pid).children()
        return len(workers)

    def get_num_ready_workers_running(gunicorn_master_proc):
        workers = psutil.Process(gunicorn_master_proc.pid).children()
        ready_workers = [
            proc for proc in workers
            if settings.GUNICORN_WORKER_READY_PREFIX in proc.cmdline()[0]
        ]
        return len(ready_workers)

    def start_refresh(gunicorn_master_proc):
        batch_size = conf.getint('webserver', 'worker_refresh_batch_size')
        logging.debug('%s doing a refresh of %s workers',
                      state, batch_size)
        sys.stdout.flush()
        sys.stderr.flush()

        excess = 0
        for _ in range(batch_size):
            gunicorn_master_proc.send_signal(signal.SIGTTIN)
            excess += 1
            wait_until_true(lambda: num_workers_expected + excess ==
                                    get_num_workers_running(gunicorn_master_proc))

    wait_until_true(lambda: num_workers_expected ==
                            get_num_workers_running(gunicorn_master_proc))

    while True:
        num_workers_running = get_num_workers_running(gunicorn_master_proc)
        num_ready_workers_running = get_num_ready_workers_running(gunicorn_master_proc)

        state = '[{0} / {1}]'.format(num_ready_workers_running, num_workers_running)

        # Whenever some workers are not ready, wait until all workers are ready
        if num_ready_workers_running < num_workers_running:
            logging.debug('%s some workers are starting up, waiting...', state)
            sys.stdout.flush()
            time.sleep(1)

        # Kill a worker gracefully by asking gunicorn to reduce number of workers
        elif num_workers_running > num_workers_expected:
            excess = num_workers_running - num_workers_expected
            logging.debug('%s killing %s workers', state, excess)

            for _ in range(excess):
                gunicorn_master_proc.send_signal(signal.SIGTTOU)
                excess -= 1
                wait_until_true(lambda: num_workers_expected + excess ==
                                        get_num_workers_running(gunicorn_master_proc))

        # Start a new worker by asking gunicorn to increase number of workers
        elif num_workers_running == num_workers_expected:
            refresh_interval = conf.getint('webserver', 'worker_refresh_interval')
            logging.debug(
                '%s sleeping for %ss starting doing a refresh...',
                state, refresh_interval
            )
            time.sleep(refresh_interval)
            start_refresh(gunicorn_master_proc)

        else:
            # num_ready_workers_running == num_workers_running < num_workers_expected
            logging.error((
                "%s some workers seem to have died and gunicorn"
                "did not restart them as expected"
            ), state)
            time.sleep(10)
            if len(
                psutil.Process(gunicorn_master_proc.pid).children()
            ) < num_workers_expected:
                start_refresh(gunicorn_master_proc)


def webserver(args):
    print(settings.HEADER)

    app = cached_app(conf)
    access_logfile = args.access_logfile or conf.get('webserver', 'access_logfile')
    error_logfile = args.error_logfile or conf.get('webserver', 'error_logfile')
    num_workers = args.workers or conf.get('webserver', 'workers')
    worker_timeout = (args.worker_timeout or
                      conf.get('webserver', 'web_server_worker_timeout'))
    ssl_cert = args.ssl_cert or conf.get('webserver', 'web_server_ssl_cert')
    ssl_key = args.ssl_key or conf.get('webserver', 'web_server_ssl_key')
    if not ssl_cert and ssl_key:
        raise AirflowException(
            'An SSL certificate must also be provided for use with ' + ssl_key)
    if ssl_cert and not ssl_key:
        raise AirflowException(
            'An SSL key must also be provided for use with ' + ssl_cert)

    if args.debug:
        print(
            "Starting the web server on port {0} and host {1}.".format(
                args.port, args.hostname))
        app.run(debug=True, port=args.port, host=args.hostname,
                ssl_context=(ssl_cert, ssl_key) if ssl_cert and ssl_key else None)
    else:
        pid, stdout, stderr, log_file = setup_locations("webserver", args.pid, args.stdout, args.stderr, args.log_file)
        if args.daemon:
            handle = setup_logging(log_file)
            stdout = open(stdout, 'w+')
            stderr = open(stderr, 'w+')

        print(
            textwrap.dedent('''\
                Running the Gunicorn Server with:
                Workers: {num_workers} {args.workerclass}
                Host: {args.hostname}:{args.port}
                Timeout: {worker_timeout}
                Logfiles: {access_logfile} {error_logfile}
                =================================================================\
            '''.format(**locals())))

        run_args = [
            'gunicorn',
            '-w', str(num_workers),
            '-k', str(args.workerclass),
            '-t', str(worker_timeout),
            '-b', args.hostname + ':' + str(args.port),
            '-n', 'airflow-webserver',
            '-p', str(pid),
            '-c', 'airflow.www.gunicorn_config'
        ]

        if args.access_logfile:
            run_args += ['--access-logfile', str(args.access_logfile)]

        if args.error_logfile:
            run_args += ['--error-logfile', str(args.error_logfile)]

        if args.daemon:
            run_args += ['-D']

        if ssl_cert:
            run_args += ['--certfile', ssl_cert, '--keyfile', ssl_key]

        run_args += ["airflow.www.app:cached_app()"]

        gunicorn_master_proc = None

        def kill_proc(dummy_signum, dummy_frame):
            gunicorn_master_proc.terminate()
            gunicorn_master_proc.wait()
            sys.exit(0)

        def monitor_gunicorn(gunicorn_master_proc):
            # These run forever until SIG{INT, TERM, KILL, ...} signal is sent
            if conf.getint('webserver', 'worker_refresh_interval') > 0:
                restart_workers(gunicorn_master_proc, num_workers)
            else:
                while True:
                    time.sleep(1)

        if args.daemon:
            base, ext = os.path.splitext(pid)
            ctx = daemon.DaemonContext(
                pidfile=TimeoutPIDLockFile(base + "-monitor" + ext, -1),
                files_preserve=[handle],
                stdout=stdout,
                stderr=stderr,
                signal_map={
                    signal.SIGINT: kill_proc,
                    signal.SIGTERM: kill_proc
                },
            )
            with ctx:
                subprocess.Popen(run_args)

                # Reading pid file directly, since Popen#pid doesn't
                # seem to return the right value with DaemonContext.
                while True:
                    try:
                        with open(pid) as f:
                            gunicorn_master_proc_pid = int(f.read())
                            break
                    except IOError:
                        logging.debug("Waiting for gunicorn's pid file to be created.")
                        time.sleep(0.1)

                gunicorn_master_proc = psutil.Process(gunicorn_master_proc_pid)
                monitor_gunicorn(gunicorn_master_proc)

            stdout.close()
            stderr.close()
        else:
            gunicorn_master_proc = subprocess.Popen(run_args)

            signal.signal(signal.SIGINT, kill_proc)
            signal.signal(signal.SIGTERM, kill_proc)

            monitor_gunicorn(gunicorn_master_proc)


def scheduler(args):
    print(settings.HEADER)
    job = jobs.SchedulerJob(
        dag_id=args.dag_id,
        subdir=process_subdir(args.subdir),
        run_duration=args.run_duration,
        num_runs=args.num_runs,
        do_pickle=args.do_pickle)

    if args.daemon:
        pid, stdout, stderr, log_file = setup_locations("scheduler", args.pid, args.stdout, args.stderr, args.log_file)
        handle = setup_logging(log_file)
        stdout = open(stdout, 'w+')
        stderr = open(stderr, 'w+')

        ctx = daemon.DaemonContext(
            pidfile=TimeoutPIDLockFile(pid, -1),
            files_preserve=[handle],
            stdout=stdout,
            stderr=stderr,
        )
        with ctx:
            job.run()

        stdout.close()
        stderr.close()
    else:
        signal.signal(signal.SIGINT, sigint_handler)
        signal.signal(signal.SIGTERM, sigint_handler)
        signal.signal(signal.SIGQUIT, sigquit_handler)
        job.run()


def serve_logs(args):
    print("Starting flask")
    import flask
    flask_app = flask.Flask(__name__)

    @flask_app.route('/log/<path:filename>')
    def serve_logs(filename):  # noqa
        log = os.path.expanduser(conf.get('core', 'BASE_LOG_FOLDER'))
        return flask.send_from_directory(
            log,
            filename,
            mimetype="application/json",
            as_attachment=False)

    WORKER_LOG_SERVER_PORT = \
        int(conf.get('celery', 'WORKER_LOG_SERVER_PORT'))
    flask_app.run(
        host='0.0.0.0', port=WORKER_LOG_SERVER_PORT)


def worker(args):
    env = os.environ.copy()
    env['AIRFLOW_HOME'] = settings.AIRFLOW_HOME

    # Celery worker
    from airflow.executors.celery_executor import app as celery_app
    from celery.bin import worker

    worker = worker.worker(app=celery_app)
    options = {
        'optimization': 'fair',
        'O': 'fair',
        'queues': args.queues,
        'concurrency': args.concurrency,
    }

    if args.daemon:
        pid, stdout, stderr, log_file = setup_locations("worker", args.pid, args.stdout, args.stderr, args.log_file)
        handle = setup_logging(log_file)
        stdout = open(stdout, 'w+')
        stderr = open(stderr, 'w+')

        ctx = daemon.DaemonContext(
            pidfile=TimeoutPIDLockFile(pid, -1),
            files_preserve=[handle],
            stdout=stdout,
            stderr=stderr,
        )
        with ctx:
            sp = subprocess.Popen(['airflow', 'serve_logs'], env=env)
            worker.run(**options)
            sp.kill()

        stdout.close()
        stderr.close()
    else:
        signal.signal(signal.SIGINT, sigint_handler)
        signal.signal(signal.SIGTERM, sigint_handler)

        sp = subprocess.Popen(['airflow', 'serve_logs'], env=env)

        worker.run(**options)
        sp.kill()


def initdb(args):  # noqa
    print("DB: " + repr(settings.engine.url))
    db_utils.initdb()
    print("Done.")


def resetdb(args):
    print("DB: " + repr(settings.engine.url))
    if args.yes or input(
        "This will drop existing tables if they exist. "
        "Proceed? (y/n)").upper() == "Y":
        logging.basicConfig(level=settings.LOGGING_LEVEL,
                            format=settings.SIMPLE_LOG_FORMAT)
        db_utils.resetdb()
    else:
        print("Bail.")


def upgradedb(args):  # noqa
    print("DB: " + repr(settings.engine.url))
    db_utils.upgradedb()

    # Populate DagStats table
    session = settings.Session()
    ds_rows = session.query(DagStat).count()
    if not ds_rows:
        qry = (
            session.query(DagRun.dag_id, DagRun.state, func.count('*'))
                .group_by(DagRun.dag_id, DagRun.state)
        )
        for dag_id, state, count in qry:
            session.add(DagStat(dag_id=dag_id, state=state, count=count))
        session.commit()


def version(args):  # noqa
    print(settings.HEADER + "  v" + airflow.__version__)


def connections(args):
    if args.list:
        # Check that no other flags were passed to the command
        invalid_args = list()
        for arg in ['conn_id', 'conn_uri', 'conn_extra']:
            if getattr(args, arg) is not None:
                invalid_args.append(arg)
        if invalid_args:
            msg = ('\n\tThe following args are not compatible with the ' +
                   '--list flag: {invalid!r}\n')
            msg = msg.format(invalid=invalid_args)
            print(msg)
            return

        session = settings.Session()
        conns = session.query(Connection.conn_id, Connection.conn_type,
                              Connection.host, Connection.port,
                              Connection.is_encrypted,
                              Connection.is_extra_encrypted,
                              Connection.extra).all()
        conns = [map(reprlib.repr, conn) for conn in conns]
        print(tabulate(conns, ['Conn Id', 'Conn Type', 'Host', 'Port',
                               'Is Encrypted', 'Is Extra Encrypted', 'Extra'],
                       tablefmt="fancy_grid"))
        return

    if args.delete:
        # Check that only the `conn_id` arg was passed to the command
        invalid_args = list()
        for arg in ['conn_uri', 'conn_extra']:
            if getattr(args, arg) is not None:
                invalid_args.append(arg)
        if invalid_args:
            msg = ('\n\tThe following args are not compatible with the ' +
                   '--delete flag: {invalid!r}\n')
            msg = msg.format(invalid=invalid_args)
            print(msg)
            return

        if args.conn_id is None:
            print('\n\tTo delete a connection, you Must provide a value for ' +
                  'the --conn_id flag.\n')
            return

        session = settings.Session()
        try:
            to_delete = (session
                         .query(Connection)
                         .filter(Connection.conn_id == args.conn_id)
                         .one())
        except exc.NoResultFound:
            msg = '\n\tDid not find a connection with `conn_id`={conn_id}\n'
            msg = msg.format(conn_id=args.conn_id)
            print(msg)
            return
        except exc.MultipleResultsFound:
            msg = ('\n\tFound more than one connection with ' +
                   '`conn_id`={conn_id}\n')
            msg = msg.format(conn_id=args.conn_id)
            print(msg)
            return
        else:
            deleted_conn_id = to_delete.conn_id
            session.delete(to_delete)
            session.commit()
            msg = '\n\tSuccessfully deleted `conn_id`={conn_id}\n'
            msg = msg.format(conn_id=deleted_conn_id)
            print(msg)
        return

    if args.add:
        # Check that the conn_id and conn_uri args were passed to the command:
        missing_args = list()
        for arg in ['conn_id', 'conn_uri']:
            if getattr(args, arg) is None:
                missing_args.append(arg)
        if missing_args:
            msg = ('\n\tThe following args are required to add a connection:' +
                   ' {missing!r}\n'.format(missing=missing_args))
            print(msg)
            return

        new_conn = Connection(conn_id=args.conn_id, uri=args.conn_uri)
        if args.conn_extra is not None:
            new_conn.set_extra(args.conn_extra)

        session = settings.Session()
        if not (session
                    .query(Connection)
                    .filter(Connection.conn_id == new_conn.conn_id).first()):
            session.add(new_conn)
            session.commit()
            msg = '\n\tSuccessfully added `conn_id`={conn_id} : {uri}\n'
            msg = msg.format(conn_id=new_conn.conn_id, uri=args.conn_uri)
            print(msg)
        else:
            msg = '\n\tA connection with `conn_id`={conn_id} already exists\n'
            msg = msg.format(conn_id=new_conn.conn_id)
            print(msg)

        return


def flower(args):
    broka = conf.get('celery', 'BROKER_URL')
    address = '--address={}'.format(args.hostname)
    port = '--port={}'.format(args.port)
    api = ''
    if args.broker_api:
        api = '--broker_api=' + args.broker_api

    flower_conf = ''
    if args.flower_conf:
        flower_conf = '--conf=' + args.flower_conf

    if args.daemon:
        pid, stdout, stderr, log_file = setup_locations("flower", args.pid, args.stdout, args.stderr, args.log_file)
        stdout = open(stdout, 'w+')
        stderr = open(stderr, 'w+')

        ctx = daemon.DaemonContext(
            pidfile=TimeoutPIDLockFile(pid, -1),
            stdout=stdout,
            stderr=stderr,
        )

        with ctx:
            os.execvp("flower", ['flower', '-b', broka, address, port, api, flower_conf])

        stdout.close()
        stderr.close()
    else:
        signal.signal(signal.SIGINT, sigint_handler)
        signal.signal(signal.SIGTERM, sigint_handler)

        os.execvp("flower", ['flower', '-b', broka, address, port, api, flower_conf])


def kerberos(args):  # noqa
    print(settings.HEADER)
    import airflow.security.kerberos

    if args.daemon:
        pid, stdout, stderr, log_file = setup_locations("kerberos", args.pid, args.stdout, args.stderr, args.log_file)
        stdout = open(stdout, 'w+')
        stderr = open(stderr, 'w+')

        ctx = daemon.DaemonContext(
            pidfile=TimeoutPIDLockFile(pid, -1),
            stdout=stdout,
            stderr=stderr,
        )

        with ctx:
            airflow.security.kerberos.run()

        stdout.close()
        stderr.close()
    else:
        airflow.security.kerberos.run()


Arg = namedtuple(
    'Arg', ['flags', 'help', 'action', 'default', 'nargs', 'type', 'choices', 'metavar'])
Arg.__new__.__defaults__ = (None, None, None, None, None, None, None)


class CLIFactory(object):
    args = {
        # Shared
        'dag_id': Arg(("dag_id",), "The id of the dag"),
        'task_id': Arg(("task_id",), "The id of the task"),
        'execution_date': Arg(
            ("execution_date",), help="The execution date of the DAG",
            type=parsedate),
        'task_regex': Arg(
            ("-t", "--task_regex"),
            "The regex to filter specific task_ids to backfill (optional)"),
        'subdir': Arg(
            ("-sd", "--subdir"),
            "File location or directory from which to look for the dag",
            default=settings.DAGS_FOLDER),
        'start_date': Arg(
            ("-s", "--start_date"), "Override start_date YYYY-MM-DD",
            type=parsedate),
        'end_date': Arg(
            ("-e", "--end_date"), "Override end_date YYYY-MM-DD",
            type=parsedate),
        'dry_run': Arg(
            ("-dr", "--dry_run"), "Perform a dry run", "store_true"),
        'pid': Arg(
            ("--pid",), "PID file location",
            nargs='?'),
        'daemon': Arg(
            ("-D", "--daemon"), "Daemonize instead of running "
                                "in the foreground",
            "store_true"),
        'stderr': Arg(
            ("--stderr",), "Redirect stderr to this file"),
        'stdout': Arg(
            ("--stdout",), "Redirect stdout to this file"),
        'log_file': Arg(
            ("-l", "--log-file"), "Location of the log file"),

        # backfill
        'mark_success': Arg(
            ("-m", "--mark_success"),
            "Mark jobs as succeeded without running them", "store_true"),
        'local': Arg(
            ("-l", "--local"),
            "Run the task using the LocalExecutor", "store_true"),
        'donot_pickle': Arg(
            ("-x", "--donot_pickle"), (
                "Do not attempt to pickle the DAG object to send over "
                "to the workers, just tell the workers to run their version "
                "of the code."),
            "store_true"),
        'include_adhoc': Arg(
            ("-a", "--include_adhoc"),
            "Include dags with the adhoc parameter.", "store_true"),
        'bf_ignore_dependencies': Arg(
            ("-i", "--ignore_dependencies"),
            (
                "Skip upstream tasks, run only the tasks "
                "matching the regexp. Only works in conjunction "
                "with task_regex"),
            "store_true"),
        'bf_ignore_first_depends_on_past': Arg(
            ("-I", "--ignore_first_depends_on_past"),
            (
                "Ignores depends_on_past dependencies for the first "
                "set of tasks only (subsequent executions in the backfill "
                "DO respect depends_on_past)."),
            "store_true"),
        'pool': Arg(("--pool",), "Resource pool to use"),
        'delay_on_limit': Arg(
            ("--delay_on_limit",),
            help=("Amount of time in seconds to wait when the limit "
                  "on maximum active dag runs (max_active_runs) has "
                  "been reached before trying to execute a dag run "
                  "again."),
            type=float,
            default=1.0),
        # list_tasks
        'tree': Arg(("-t", "--tree"), "Tree view", "store_true"),
        # list_dags
        'report': Arg(
            ("-r", "--report"), "Show DagBag loading report", "store_true"),
        # clear
        'upstream': Arg(
            ("-u", "--upstream"), "Include upstream tasks", "store_true"),
        'only_failed': Arg(
            ("-f", "--only_failed"), "Only failed jobs", "store_true"),
        'only_running': Arg(
            ("-r", "--only_running"), "Only running jobs", "store_true"),
        'downstream': Arg(
            ("-d", "--downstream"), "Include downstream tasks", "store_true"),
        'no_confirm': Arg(
            ("-c", "--no_confirm"),
            "Do not request confirmation", "store_true"),
        'exclude_subdags': Arg(
            ("-x", "--exclude_subdags"),
            "Exclude subdags", "store_true"),
        'dag_regex': Arg(
            ("-dx", "--dag_regex"),
            "Search dag_id as regex instead of exact string", "store_true"),
        # trigger_dag
        'run_id': Arg(("-r", "--run_id"), "Helps to identify this run"),
        'conf': Arg(
            ('-c', '--conf'),
            "JSON string that gets pickled into the DagRun's conf attribute"),
        'exec_date': Arg(
            ("-e", "--exec_date"), help="The execution date of the DAG",
            type=parsedate),
        # pool
        'pool_set': Arg(
            ("-s", "--set"),
            nargs=3,
            metavar=('NAME', 'SLOT_COUNT', 'POOL_DESCRIPTION'),
            help="Set pool slot count and description, respectively"),
        'pool_get': Arg(
            ("-g", "--get"),
            metavar='NAME',
            help="Get pool info"),
        'pool_delete': Arg(
            ("-x", "--delete"),
            metavar="NAME",
            help="Delete a pool"),
        # variables
        'set': Arg(
            ("-s", "--set"),
            nargs=2,
            metavar=('KEY', 'VAL'),
            help="Set a variable"),
        'get': Arg(
            ("-g", "--get"),
            metavar='KEY',
            help="Get value of a variable"),
        'default': Arg(
            ("-d", "--default"),
            metavar="VAL",
            default=None,
            help="Default value returned if variable does not exist"),
        'json': Arg(
            ("-j", "--json"),
            help="Deserialize JSON variable",
            action="store_true"),
        'var_import': Arg(
            ("-i", "--import"),
            metavar="FILEPATH",
            help="Import variables from JSON file"),
        'var_export': Arg(
            ("-e", "--export"),
            metavar="FILEPATH",
            help="Export variables to JSON file"),
        'var_delete': Arg(
            ("-x", "--delete"),
            metavar="KEY",
            help="Delete a variable"),
        # kerberos
        'principal': Arg(
            ("principal",), "kerberos principal",
            nargs='?', default=conf.get('kerberos', 'principal')),
        'keytab': Arg(
            ("-kt", "--keytab"), "keytab",
            nargs='?', default=conf.get('kerberos', 'keytab')),
        # run
        # TODO(aoen): "force" is a poor choice of name here since it implies it overrides
        # all dependencies (not just past success), e.g. the ignore_depends_on_past
        # dependency. This flag should be deprecated and renamed to 'ignore_ti_state' and
        # the "ignore_all_dependencies" command should be called the"force" command
        # instead.
        'force': Arg(
            ("-f", "--force"),
            "Ignore previous task instance state, rerun regardless if task already "
            "succeeded/failed",
            "store_true"),
        'raw': Arg(("-r", "--raw"), argparse.SUPPRESS, "store_true"),
        'ignore_all_dependencies': Arg(
            ("-A", "--ignore_all_dependencies"),
            "Ignores all non-critical dependencies, including ignore_ti_state and "
            "ignore_task_deps",
            "store_true"),
        # TODO(aoen): ignore_dependencies is a poor choice of name here because it is too
        # vague (e.g. a task being in the appropriate state to be run is also a dependency
        # but is not ignored by this flag), the name 'ignore_task_dependencies' is
        # slightly better (as it ignores all dependencies that are specific to the task),
        # so deprecate the old command name and use this instead.
        'ignore_dependencies': Arg(
            ("-i", "--ignore_dependencies"),
            "Ignore task-specific dependencies, e.g. upstream, depends_on_past, and "
            "retry delay dependencies",
            "store_true"),
        'ignore_depends_on_past': Arg(
            ("-I", "--ignore_depends_on_past"),
            "Ignore depends_on_past dependencies (but respect "
            "upstream dependencies)",
            "store_true"),
        'ship_dag': Arg(
            ("--ship_dag",),
            "Pickles (serializes) the DAG and ships it to the worker",
            "store_true"),
        'pickle': Arg(
            ("-p", "--pickle"),
            "Serialized pickle object of the entire dag (used internally)"),
        'job_id': Arg(("-j", "--job_id"), argparse.SUPPRESS),
        'cfg_path': Arg(
            ("--cfg_path",), "Path to config file to use instead of airflow.cfg"),
        # webserver
        'port': Arg(
            ("-p", "--port"),
            default=conf.get('webserver', 'WEB_SERVER_PORT'),
            type=int,
            help="The port on which to run the server"),
        'ssl_cert': Arg(
            ("--ssl_cert",),
            default=conf.get('webserver', 'WEB_SERVER_SSL_CERT'),
            help="Path to the SSL certificate for the webserver"),
        'ssl_key': Arg(
            ("--ssl_key",),
            default=conf.get('webserver', 'WEB_SERVER_SSL_KEY'),
            help="Path to the key to use with the SSL certificate"),
        'workers': Arg(
            ("-w", "--workers"),
            default=conf.get('webserver', 'WORKERS'),
            type=int,
            help="Number of workers to run the webserver on"),
        'workerclass': Arg(
            ("-k", "--workerclass"),
            default=conf.get('webserver', 'WORKER_CLASS'),
            choices=['sync', 'eventlet', 'gevent', 'tornado'],
            help="The worker class to use for Gunicorn"),
        'worker_timeout': Arg(
            ("-t", "--worker_timeout"),
            default=conf.get('webserver', 'WEB_SERVER_WORKER_TIMEOUT'),
            type=int,
            help="The timeout for waiting on webserver workers"),
        'hostname': Arg(
            ("-hn", "--hostname"),
            default=conf.get('webserver', 'WEB_SERVER_HOST'),
            help="Set the hostname on which to run the web server"),
        'debug': Arg(
            ("-d", "--debug"),
            "Use the server that ships with Flask in debug mode",
            "store_true"),
        'access_logfile': Arg(
            ("-A", "--access_logfile"),
            default=conf.get('webserver', 'ACCESS_LOGFILE'),
            help="The logfile to store the webserver access log. Use '-' to print to "
                 "stderr."),
        'error_logfile': Arg(
            ("-E", "--error_logfile"),
            default=conf.get('webserver', 'ERROR_LOGFILE'),
            help="The logfile to store the webserver error log. Use '-' to print to "
                 "stderr."),
        # resetdb
        'yes': Arg(
            ("-y", "--yes"),
            "Do not prompt to confirm reset. Use with care!",
            "store_true",
            default=False),
        # scheduler
        'dag_id_opt': Arg(("-d", "--dag_id"), help="The id of the dag to run"),
        'run_duration': Arg(
            ("-r", "--run-duration"),
            default=None, type=int,
            help="Set number of seconds to execute before exiting"),
        'num_runs': Arg(
            ("-n", "--num_runs"),
            default=-1, type=int,
            help="Set the number of runs to execute before exiting"),
        # worker
        'do_pickle': Arg(
            ("-p", "--do_pickle"),
            default=False,
            help=(
                "Attempt to pickle the DAG object to send over "
                "to the workers, instead of letting workers run their version "
                "of the code."),
            action="store_true"),
        'queues': Arg(
            ("-q", "--queues"),
            help="Comma delimited list of queues to serve",
            default=conf.get('celery', 'DEFAULT_QUEUE')),
        'concurrency': Arg(
            ("-c", "--concurrency"),
            type=int,
            help="The number of worker processes",
            default=conf.get('celery', 'celeryd_concurrency')),
        # flower
        'broker_api': Arg(("-a", "--broker_api"), help="Broker api"),
        'flower_hostname': Arg(
            ("-hn", "--hostname"),
            default=conf.get('celery', 'FLOWER_HOST'),
            help="Set the hostname on which to run the server"),
        'flower_port': Arg(
            ("-p", "--port"),
            default=conf.get('celery', 'FLOWER_PORT'),
            type=int,
            help="The port on which to run the server"),
        'flower_conf': Arg(
            ("-fc", "--flower_conf"),
            help="Configuration file for flower"),
        'task_params': Arg(
            ("-tp", "--task_params"),
            help="Sends a JSON params dict to the task"),
        # connections
        'list_connections': Arg(
            ('-l', '--list'),
            help='List all connections',
            action='store_true'),
        'add_connection': Arg(
            ('-a', '--add'),
            help='Add a connection',
            action='store_true'),
        'delete_connection': Arg(
            ('-d', '--delete'),
            help='Delete a connection',
            action='store_true'),
        'conn_id': Arg(
            ('--conn_id',),
            help='Connection id, required to add/delete a connection',
            type=str),
        'conn_uri': Arg(
            ('--conn_uri',),
            help='Connection URI, required to add a connection',
            type=str),
        'conn_extra': Arg(
            ('--conn_extra',),
            help='Connection `Extra` field, optional when adding a connection',
            type=str),
    }
    subparsers = (
        {
            'func': backfill,
            'help': "Run subsections of a DAG for a specified date range",
            'args': (
                'dag_id', 'task_regex', 'start_date', 'end_date',
                'mark_success', 'local', 'donot_pickle', 'include_adhoc',
                'bf_ignore_dependencies', 'bf_ignore_first_depends_on_past',
                'subdir', 'pool', 'delay_on_limit', 'dry_run')
        }, {
            'func': list_tasks,
            'help': "List the tasks within a DAG",
            'args': ('dag_id', 'tree', 'subdir'),
        }, {
            'func': clear,
            'help': "Clear a set of task instance, as if they never ran",
            'args': (
                'dag_id', 'task_regex', 'start_date', 'end_date', 'subdir',
                'upstream', 'downstream', 'no_confirm', 'only_failed',
                'only_running', 'exclude_subdags', 'dag_regex'),
        }, {
            'func': pause,
            'help': "Pause a DAG",
            'args': ('dag_id', 'subdir'),
        }, {
            'func': unpause,
            'help': "Resume a paused DAG",
            'args': ('dag_id', 'subdir'),
        }, {
            'func': trigger_dag,
            'help': "Trigger a DAG run",
            'args': ('dag_id', 'subdir', 'run_id', 'conf', 'exec_date'),
        }, {
            'func': pool,
            'help': "CRUD operations on pools",
            "args": ('pool_set', 'pool_get', 'pool_delete'),
        }, {
            'func': variables,
            'help': "CRUD operations on variables",
            "args": ('set', 'get', 'json', 'default', 'var_import', 'var_export', 'var_delete'),
        }, {
            'func': kerberos,
            'help': "Start a kerberos ticket renewer",
            'args': ('principal', 'keytab', 'pid',
                     'daemon', 'stdout', 'stderr', 'log_file'),
        }, {
            'func': render,
            'help': "Render a task instance's template(s)",
            'args': ('dag_id', 'task_id', 'execution_date', 'subdir'),
        }, {
            'func': run,
            'help': "Run a single task instance",
            'args': (
                'dag_id', 'task_id', 'execution_date', 'subdir',
                'mark_success', 'force', 'pool', 'cfg_path',
                'local', 'raw', 'ignore_all_dependencies', 'ignore_dependencies',
                'ignore_depends_on_past', 'ship_dag', 'pickle', 'job_id'),
        }, {
            'func': initdb,
            'help': "Initialize the metadata database",
            'args': tuple(),
        }, {
            'func': list_dags,
            'help': "List all the DAGs",
            'args': ('subdir', 'report'),
        }, {
            'func': dag_state,
            'help': "Get the status of a dag run",
            'args': ('dag_id', 'execution_date', 'subdir'),
        }, {
            'func': task_failed_deps,
            'help': (
                "Returns the unmet dependencies for a task instance from the perspective "
                "of the scheduler. In other words, why a task instance doesn't get "
                "scheduled and then queued by the scheduler, and then run by an "
                "executor)."),
            'args': ('dag_id', 'task_id', 'execution_date', 'subdir'),
        }, {
            'func': task_state,
            'help': "Get the status of a task instance",
            'args': ('dag_id', 'task_id', 'execution_date', 'subdir'),
        }, {
            'func': serve_logs,
            'help': "Serve logs generate by worker",
            'args': tuple(),
        }, {
            'func': test,
            'help': (
                "Test a task instance. This will run a task without checking for "
                "dependencies or recording it's state in the database."),
            'args': (
                'dag_id', 'task_id', 'execution_date', 'subdir', 'dry_run',
                'task_params'),
        }, {
            'func': webserver,
            'help': "Start a Airflow webserver instance",
            'args': ('port', 'workers', 'workerclass', 'worker_timeout', 'hostname',
                     'pid', 'daemon', 'stdout', 'stderr', 'access_logfile',
                     'error_logfile', 'log_file', 'ssl_cert', 'ssl_key', 'debug'),
        }, {
            'func': resetdb,
            'help': "Burn down and rebuild the metadata database",
            'args': ('yes',),
        }, {
            'func': upgradedb,
            'help': "Upgrade the metadata database to latest version",
            'args': tuple(),
        }, {
            'func': scheduler,
            'help': "Start a scheduler instance",
            'args': ('dag_id_opt', 'subdir', 'run_duration', 'num_runs',
                     'do_pickle', 'pid', 'daemon', 'stdout', 'stderr',
                     'log_file'),
        }, {
            'func': worker,
            'help': "Start a Celery worker node",
            'args': ('do_pickle', 'queues', 'concurrency',
                     'pid', 'daemon', 'stdout', 'stderr', 'log_file'),
        }, {
            'func': flower,
            'help': "Start a Celery Flower",
            'args': ('flower_hostname', 'flower_port', 'flower_conf', 'broker_api',
                     'pid', 'daemon', 'stdout', 'stderr', 'log_file'),
        }, {
            'func': version,
            'help': "Show the version",
            'args': tuple(),
        }, {
            'func': connections,
            'help': "List/Add/Delete connections",
            'args': ('list_connections', 'add_connection', 'delete_connection',
                     'conn_id', 'conn_uri', 'conn_extra'),
        },
    )
    subparsers_dict = {sp['func'].__name__: sp for sp in subparsers}
    dag_subparsers = (
        'list_tasks', 'backfill', 'test', 'run', 'pause', 'unpause')

    @classmethod
    def get_parser(cls, dag_parser=False):
        parser = argparse.ArgumentParser()
        subparsers = parser.add_subparsers(
            help='sub-command help', dest='subcommand')
        subparsers.required = True

        subparser_list = cls.dag_subparsers if dag_parser else cls.subparsers_dict.keys()
        for sub in subparser_list:
            sub = cls.subparsers_dict[sub]
            sp = subparsers.add_parser(sub['func'].__name__, help=sub['help'])
            for arg in sub['args']:
                if 'dag_id' in arg and dag_parser:
                    continue
                arg = cls.args[arg]
                kwargs = {
                    f: getattr(arg, f)
                    for f in arg._fields if f != 'flags' and getattr(arg, f)}
                sp.add_argument(*arg.flags, **kwargs)
            sp.set_defaults(func=sub['func'])
        return parser


def get_parser():
    return CLIFactory.get_parser()
