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# to you under the Apache License, Version 2.0 (the
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"""File logging handler for tasks."""
from __future__ import annotations

import logging
import os
import warnings
from contextlib import suppress
from enum import Enum
from functools import cached_property
from pathlib import Path
from typing import TYPE_CHECKING, Any, Callable, Iterable
from urllib.parse import urljoin

import pendulum

from airflow.configuration import conf
from airflow.exceptions import RemovedInAirflow3Warning
from airflow.executors.executor_loader import ExecutorLoader
from airflow.utils.context import Context
from airflow.utils.helpers import parse_template_string, render_template_to_string
from airflow.utils.log.logging_mixin import SetContextPropagate
from airflow.utils.log.non_caching_file_handler import NonCachingFileHandler
from airflow.utils.session import create_session
from airflow.utils.state import State, TaskInstanceState

if TYPE_CHECKING:
    from airflow.models import TaskInstance

logger = logging.getLogger(__name__)


class LogType(str, Enum):
    """
    Type of service from which we retrieve logs.

    :meta private:
    """

    TRIGGER = "trigger"
    WORKER = "worker"


def _set_task_deferred_context_var():
    """
    Tell task log handler that task exited with deferral.

    This exists for the sole purpose of telling elasticsearch handler not to
    emit end_of_log mark after task deferral.

    Depending on how the task is run, we may need to set this in task command or in local task job.
    Kubernetes executor requires the local task job invocation; local executor requires the task
    command invocation.

    :meta private:
    """
    logger = logging.getLogger()
    with suppress(StopIteration):
        h = next(h for h in logger.handlers if hasattr(h, "ctx_task_deferred"))
        h.ctx_task_deferred = True


def _fetch_logs_from_service(url, log_relative_path):
    import httpx

    from airflow.utils.jwt_signer import JWTSigner

    timeout = conf.getint("webserver", "log_fetch_timeout_sec", fallback=None)
    signer = JWTSigner(
        secret_key=conf.get("webserver", "secret_key"),
        expiration_time_in_seconds=conf.getint("webserver", "log_request_clock_grace", fallback=30),
        audience="task-instance-logs",
    )
    response = httpx.get(
        url,
        timeout=timeout,
        headers={"Authorization": signer.generate_signed_token({"filename": log_relative_path})},
    )
    response.encoding = "utf-8"
    return response


_parse_timestamp = conf.getimport("logging", "interleave_timestamp_parser", fallback=None)

if not _parse_timestamp:

    def _parse_timestamp(line: str):
        timestamp_str, _ = line.split(" ", 1)
        return pendulum.parse(timestamp_str.strip("[]"))


def _parse_timestamps_in_log_file(lines: Iterable[str]):
    timestamp = None
    next_timestamp = None
    for idx, line in enumerate(lines):
        if not line:
            continue
        with suppress(Exception):
            # next_timestamp unchanged if line can't be parsed
            next_timestamp = _parse_timestamp(line)
        if next_timestamp:
            timestamp = next_timestamp
        yield timestamp, idx, line


def _interleave_logs(*logs):
    records = []
    for log in logs:
        records.extend(_parse_timestamps_in_log_file(log.splitlines()))
    last = None
    for _, _, v in sorted(
        records, key=lambda x: (x[0], x[1]) if x[0] else (pendulum.datetime(2000, 1, 1), x[1])
    ):
        if v != last:  # dedupe
            yield v
        last = v


class FileTaskHandler(logging.Handler):
    """
    FileTaskHandler is a python log handler that handles and reads task instance logs.

    It creates and delegates log handling to `logging.FileHandler` after receiving task
    instance context.  It reads logs from task instance's host machine.

    :param base_log_folder: Base log folder to place logs.
    :param filename_template: template filename string
    """

    trigger_should_wrap = True

    def __init__(self, base_log_folder: str, filename_template: str | None = None):
        super().__init__()
        self.handler: logging.Handler | None = None
        self.local_base = base_log_folder
        if filename_template is not None:
            warnings.warn(
                "Passing filename_template to a log handler is deprecated and has no effect",
                RemovedInAirflow3Warning,
                # We want to reference the stack that actually instantiates the
                # handler, not the one that calls super()__init__.
                stacklevel=(2 if type(self) == FileTaskHandler else 3),
            )
        self.maintain_propagate: bool = False
        """
        If true, overrides default behavior of setting propagate=False

        :meta private:
        """

        self.ctx_task_deferred = False
        """
        If true, task exited with deferral to trigger.

        Some handlers emit "end of log" markers, and may not wish to do so when task defers.
        """

    def set_context(self, ti: TaskInstance) -> None | SetContextPropagate:
        """
        Provide task_instance context to airflow task handler.

        Generally speaking returns None.  But if attr `maintain_propagate` has
        been set to propagate, then returns sentinel MAINTAIN_PROPAGATE. This
        has the effect of overriding the default behavior to set `propagate`
        to False whenever set_context is called.  At time of writing, this
        functionality is only used in unit testing.

        :param ti: task instance object
        """
        local_loc = self._init_file(ti)
        self.handler = NonCachingFileHandler(local_loc, encoding="utf-8")
        if self.formatter:
            self.handler.setFormatter(self.formatter)
        self.handler.setLevel(self.level)
        return SetContextPropagate.MAINTAIN_PROPAGATE if self.maintain_propagate else None

    @staticmethod
    def add_triggerer_suffix(full_path, job_id=None):
        """
        Derive trigger log filename from task log filename.

        E.g. given /path/to/file.log returns /path/to/file.log.trigger.123.log, where 123
        is the triggerer id.  We use the triggerer ID instead of trigger ID to distinguish
        the files because, rarely, the same trigger could get picked up by two different
        triggerer instances.
        """
        full_path = Path(full_path).as_posix()
        full_path += f".{LogType.TRIGGER.value}"
        if job_id:
            full_path += f".{job_id}.log"
        return full_path

    def emit(self, record):
        if self.handler:
            self.handler.emit(record)

    def flush(self):
        if self.handler:
            self.handler.flush()

    def close(self):
        if self.handler:
            self.handler.close()

    def _render_filename(self, ti: TaskInstance, try_number: int) -> str:
        """Return the worker log filename."""
        with create_session() as session:
            dag_run = ti.get_dagrun(session=session)
            template = dag_run.get_log_template(session=session).filename
            str_tpl, jinja_tpl = parse_template_string(template)

            if jinja_tpl:
                if hasattr(ti, "task"):
                    context = ti.get_template_context(session=session)
                else:
                    context = Context(ti=ti, ts=dag_run.logical_date.isoformat())
                context["try_number"] = try_number
                return render_template_to_string(jinja_tpl, context)

        if str_tpl:
            try:
                dag = ti.task.dag
            except AttributeError:  # ti.task is not always set.
                data_interval = (dag_run.data_interval_start, dag_run.data_interval_end)
            else:
                if TYPE_CHECKING:
                    assert dag is not None
                data_interval = dag.get_run_data_interval(dag_run)
            if data_interval[0]:
                data_interval_start = data_interval[0].isoformat()
            else:
                data_interval_start = ""
            if data_interval[1]:
                data_interval_end = data_interval[1].isoformat()
            else:
                data_interval_end = ""
            return str_tpl.format(
                dag_id=ti.dag_id,
                task_id=ti.task_id,
                run_id=ti.run_id,
                data_interval_start=data_interval_start,
                data_interval_end=data_interval_end,
                execution_date=ti.get_dagrun().logical_date.isoformat(),
                try_number=try_number,
            )
        else:
            raise RuntimeError(f"Unable to render log filename for {ti}. This should never happen")

    def _read_grouped_logs(self):
        return False

    @cached_property
    def _executor_get_task_log(self) -> Callable[[TaskInstance, int], tuple[list[str], list[str]]]:
        """This cached property avoids loading executor repeatedly."""
        executor = ExecutorLoader.get_default_executor()
        return executor.get_task_log

    def _read(
        self,
        ti: TaskInstance,
        try_number: int,
        metadata: dict[str, Any] | None = None,
    ):
        """
        Template method that contains custom logic of reading logs given the try_number.

        :param ti: task instance record
        :param try_number: current try_number to read log from
        :param metadata: log metadata,
                         can be used for steaming log reading and auto-tailing.
                         Following attributes are used:
                         log_pos: (absolute) Char position to which the log
                                  which was retrieved in previous calls, this
                                  part will be skipped and only following test
                                  returned to be added to tail.
        :return: log message as a string and metadata.
                 Following attributes are used in metadata:
                 end_of_log: Boolean, True if end of log is reached or False
                             if further calls might get more log text.
                             This is determined by the status of the TaskInstance
                 log_pos: (absolute) Char position to which the log is retrieved
        """
        # Task instance here might be different from task instance when
        # initializing the handler. Thus explicitly getting log location
        # is needed to get correct log path.
        worker_log_rel_path = self._render_filename(ti, try_number)
        messages_list: list[str] = []
        remote_logs: list[str] = []
        local_logs: list[str] = []
        executor_messages: list[str] = []
        executor_logs: list[str] = []
        served_logs: list[str] = []
        is_running = ti.try_number == try_number and ti.state in (
            TaskInstanceState.RUNNING,
            TaskInstanceState.DEFERRED,
        )
        with suppress(NotImplementedError):
            remote_messages, remote_logs = self._read_remote_logs(ti, try_number, metadata)
            messages_list.extend(remote_messages)
        if ti.state == TaskInstanceState.RUNNING:
            response = self._executor_get_task_log(ti, try_number)
            if response:
                executor_messages, executor_logs = response
            if executor_messages:
                messages_list.extend(executor_messages)
        if not (remote_logs and ti.state not in State.unfinished):
            # when finished, if we have remote logs, no need to check local
            worker_log_full_path = Path(self.local_base, worker_log_rel_path)
            local_messages, local_logs = self._read_from_local(worker_log_full_path)
            messages_list.extend(local_messages)
        if is_running and not executor_messages:
            served_messages, served_logs = self._read_from_logs_server(ti, worker_log_rel_path)
            messages_list.extend(served_messages)
        elif ti.state not in State.unfinished and not (local_logs or remote_logs):
            # ordinarily we don't check served logs, with the assumption that users set up
            # remote logging or shared drive for logs for persistence, but that's not always true
            # so even if task is done, if no local logs or remote logs are found, we'll check the worker
            served_messages, served_logs = self._read_from_logs_server(ti, worker_log_rel_path)
            messages_list.extend(served_messages)

        logs = "\n".join(
            _interleave_logs(
                *local_logs,
                *remote_logs,
                *(executor_logs or []),
                *served_logs,
            )
        )
        log_pos = len(logs)
        messages = "".join([f"*** {x}\n" for x in messages_list])
        if metadata and "log_pos" in metadata:
            previous_chars = metadata["log_pos"]
            logs = logs[previous_chars:]  # Cut off previously passed log test as new tail
        out_message = logs if "log_pos" in (metadata or {}) else messages + logs
        return out_message, {"end_of_log": not is_running, "log_pos": log_pos}

    @staticmethod
    def _get_pod_namespace(ti: TaskInstance):
        pod_override = ti.executor_config.get("pod_override")
        namespace = None
        with suppress(Exception):
            namespace = pod_override.metadata.namespace
        return namespace or conf.get("kubernetes_executor", "namespace")

    def _get_log_retrieval_url(
        self, ti: TaskInstance, log_relative_path: str, log_type: LogType | None = None
    ) -> tuple[str, str]:
        """Given TI, generate URL with which to fetch logs from service log server."""
        if log_type == LogType.TRIGGER:
            if not ti.triggerer_job:
                raise RuntimeError("Could not build triggerer log URL; no triggerer job.")
            config_key = "triggerer_log_server_port"
            config_default = 8794
            hostname = ti.triggerer_job.hostname
            log_relative_path = self.add_triggerer_suffix(log_relative_path, job_id=ti.triggerer_job.id)
        else:
            hostname = ti.hostname
            config_key = "worker_log_server_port"
            config_default = 8793
        return (
            urljoin(
                f"http://{hostname}:{conf.get('logging', config_key, fallback=config_default)}/log/",
                log_relative_path,
            ),
            log_relative_path,
        )

    def read(self, task_instance, try_number=None, metadata=None):
        """
        Read logs of given task instance from local machine.

        :param task_instance: task instance object
        :param try_number: task instance try_number to read logs from. If None
                           it returns all logs separated by try_number
        :param metadata: log metadata, can be used for steaming log reading and auto-tailing.
        :return: a list of listed tuples which order log string by host
        """
        # Task instance increments its try number when it starts to run.
        # So the log for a particular task try will only show up when
        # try number gets incremented in DB, i.e logs produced the time
        # after cli run and before try_number + 1 in DB will not be displayed.
        if try_number is None:
            next_try = task_instance.next_try_number
            try_numbers = list(range(1, next_try))
        elif try_number < 1:
            logs = [
                [("default_host", f"Error fetching the logs. Try number {try_number} is invalid.")],
            ]
            return logs, [{"end_of_log": True}]
        else:
            try_numbers = [try_number]

        logs = [""] * len(try_numbers)
        metadata_array = [{}] * len(try_numbers)

        # subclasses implement _read and may not have log_type, which was added recently
        for i, try_number_element in enumerate(try_numbers):
            log, out_metadata = self._read(task_instance, try_number_element, metadata)
            # es_task_handler return logs grouped by host. wrap other handler returning log string
            # with default/ empty host so that UI can render the response in the same way
            logs[i] = log if self._read_grouped_logs() else [(task_instance.hostname, log)]
            metadata_array[i] = out_metadata

        return logs, metadata_array

    def _prepare_log_folder(self, directory: Path):
        """
        Prepare the log folder and ensure its mode is as configured.

        To handle log writing when tasks are impersonated, the log files need to
        be writable by the user that runs the Airflow command and the user
        that is impersonated. This is mainly to handle corner cases with the
        SubDagOperator. When the SubDagOperator is run, all of the operators
        run under the impersonated user and create appropriate log files
        as the impersonated user. However, if the user manually runs tasks
        of the SubDagOperator through the UI, then the log files are created
        by the user that runs the Airflow command. For example, the Airflow
        run command may be run by the `airflow_sudoable` user, but the Airflow
        tasks may be run by the `airflow` user. If the log files are not
        writable by both users, then it's possible that re-running a task
        via the UI (or vice versa) results in a permission error as the task
        tries to write to a log file created by the other user.

        We leave it up to the user to manage their permissions by exposing configuration for both
        new folders and new log files. Default is to make new log folders and files group-writeable
        to handle most common impersonation use cases. The requirement in this case will be to make
        sure that the same group is set as default group for both - impersonated user and main airflow
        user.
        """
        new_folder_permissions = int(
            conf.get("logging", "file_task_handler_new_folder_permissions", fallback="0o775"), 8
        )
        directory.mkdir(mode=new_folder_permissions, parents=True, exist_ok=True)
        if directory.stat().st_mode % 0o1000 != new_folder_permissions % 0o1000:
            print(f"Changing {directory} permission to {new_folder_permissions}")
            try:
                directory.chmod(new_folder_permissions)
            except PermissionError as e:
                # In some circumstances (depends on user and filesystem) we might not be able to
                # change the permission for the folder (when the folder was created by another user
                # before or when the filesystem does not allow to change permission). We should not
                # fail in this case but rather ignore it.
                print(f"Failed to change {directory} permission to {new_folder_permissions}: {e}")
                pass

    def _init_file(self, ti):
        """
        Create log directory and give it permissions that are configured.

        See above _prepare_log_folder method for more detailed explanation.

        :param ti: task instance object
        :return: relative log path of the given task instance
        """
        new_file_permissions = int(
            conf.get("logging", "file_task_handler_new_file_permissions", fallback="0o664"), 8
        )
        local_relative_path = self._render_filename(ti, ti.try_number)
        full_path = os.path.join(self.local_base, local_relative_path)
        if ti.is_trigger_log_context is True:
            # if this is true, we're invoked via set_context in the context of
            # setting up individual trigger logging. return trigger log path.
            full_path = self.add_triggerer_suffix(full_path=full_path, job_id=ti.triggerer_job.id)
        self._prepare_log_folder(Path(full_path).parent)

        if not os.path.exists(full_path):
            open(full_path, "a").close()
            try:
                os.chmod(full_path, new_file_permissions)
            except OSError as e:
                logging.warning("OSError while changing ownership of the log file. ", e)

        return full_path

    @staticmethod
    def _read_from_local(worker_log_path: Path) -> tuple[list[str], list[str]]:
        messages = []
        paths = sorted(worker_log_path.parent.glob(worker_log_path.name + "*"))
        if paths:
            messages.append("Found local files:")
            messages.extend(f"  * {x}" for x in paths)
        logs = [file.read_text() for file in paths]
        return messages, logs

    def _read_from_logs_server(self, ti, worker_log_rel_path) -> tuple[list[str], list[str]]:
        messages = []
        logs = []
        try:
            log_type = LogType.TRIGGER if ti.triggerer_job else LogType.WORKER
            url, rel_path = self._get_log_retrieval_url(ti, worker_log_rel_path, log_type=log_type)
            response = _fetch_logs_from_service(url, rel_path)
            if response.status_code == 403:
                messages.append(
                    "!!!! Please make sure that all your Airflow components (e.g. "
                    "schedulers, webservers, workers and triggerer) have "
                    "the same 'secret_key' configured in 'webserver' section and "
                    "time is synchronized on all your machines (for example with ntpd)\n"
                    "See more at https://airflow.apache.org/docs/apache-airflow/"
                    "stable/configurations-ref.html#secret-key"
                )
            # Check if the resource was properly fetched
            response.raise_for_status()
            if response.text:
                messages.append(f"Found logs served from host {url}")
                logs.append(response.text)
        except Exception as e:
            messages.append(f"Could not read served logs: {e}")
            logger.exception("Could not read served logs")
        return messages, logs

    def _read_remote_logs(self, ti, try_number, metadata=None) -> tuple[list[str], list[str]]:
        """
        Implement in subclasses to read from the remote service.

        This method should return two lists, messages and logs.

        * Each element in the messages list should be a single message,
          such as, "reading from x file".
        * Each element in the logs list should be the content of one file.
        """
        raise NotImplementedError
