#!/usr/bin/env python
# coding: utf-8

# ## Logging in PLAMS

# PLAMS has built-in logging which aims to simplify tracking the progress and status of jobs. This consists of progress logging to stdout and a logfile, and writing job summaries to CSV files. Each of these is explained below.

# ### Progress Logger

# PLAMS writes job progress to stdout and a plain text logfile. The location of this logfile is determined by the working directory of the default job manager, and is called `logfile`.
#
# Users can also write logs to the same locations using the `log` function. This takes a `level` argument. By convention in PLAMS, the level should be between 0-7, with 0 being the most and 7 the least important logging.
#
# The level of logging that is written to stdout and the logfile can be changed through the `config.LogSettings`.

from scm.plams import Settings, AMSJob, from_smiles, log, config

counter = 0


def get_test_job():
    global counter
    s = Settings()
    s.input.ams.Task = "SinglePoint"
    s.input.dftb
    counter += 1
    return AMSJob(name=f"test{counter}", molecule=from_smiles("C"), settings=s)


config.log.stdout = 3
config.log.file = 5
config.jobmanager.hashing = None  # Force PLAMS to re-run identical test jobs


job = get_test_job()
job.run()
log("Test job finished", 5)


with open(config.default_jobmanager.logfile, "r") as f:
    print(f.read())


# Note that the logs from an AMS calculation can also be forwarded to the progress logs using the `watch = True` flag.

job = get_test_job()
job.run(watch=True)
# ### Job Summary Logger

# PLAMS also writes summaries of jobs to a CSV file, the location of which by default is also determined by the job manager. It is called `job_logfile.csv`.

jobs = [get_test_job() for _ in range(3)]
jobs[2].settings.input.ams.Task = "Not a task!"

for job in jobs:
    job.run()


# These CSVs give overall information on the status of all jobs run by a given job manager.

import csv

try:
    with open(config.default_jobmanager.job_logger.logfile, newline="") as csvfile:
        reader = csv.DictReader(csvfile)
        for row in reader:
            print(f"{row['job_name']} {row['job_status']}: {row['job_get_errormsg']}")
except AttributeError:
    pass


# ### Job Status Change Callback

# PLAMS also supports users adding a custom callback which fires when a job status changes.
#
# This is very flexible and can be used to set up custom notifications, for instance sending a desktop prompt, email or messaging app notification.

# For example, below we show how to raise a desktop notification when a job finishes. Note that this requires the external library `plyer`, which needs to be installed into your python environment.

# First we set up our notification function:

try:
    import plyer
except ImportError:
    print(
        "Install plyer into your python environment to run this example. For example, with 'pip install plyer' or 'pip install plyer[macosx]' for Mac users."
    )


def send_desktop_notification(name, path, status, at, **_):
    if status == "successful":
        plyer.notification.notify(
            title=f"PLAMS job {name}",
            message=f"Completed successfully at {at:%H:%M:%S UTC}",
            timeout=5,
        )
    elif status in ["crashed", "failed"]:
        plyer.notification.notify(
            title=f"PLAMS job {name}",
            message=f"Errored at {at:%H:%M:%S UTC}",
            timeout=5,
        )


# Then we apply it to all jobs using the global config:

config.job.on_status_change = send_desktop_notification


# When jobs are run, notifications should then be raised to the desktop.

jobs = [get_test_job() for _ in range(3)]
jobs[2].settings.input.ams.Task = "Not a task!"

for job in jobs:
    job.run()


# Note that the given callbacks will never block job execution.
#
# However, if many notifications are being sent, or there is a significant overhead to sending a notification, you may need to customize the wait time at the end of the script to allow all notifications to be sent successfully. To do this set the number of seconds for `config.atexit_timeout`:

config.atexit_timeout = 120