# -*- coding: utf-8 -*-
import contextlib
import logging
import os
import sys
from pathlib import Path

import pandas as pd
import pytz
import yaml
from pypsa.components import component_attrs, components
from pypsa.descriptors import Dict
from snakemake.utils import update_config

logger = logging.getLogger(__name__)


# Define a context manager to temporarily mute print statements
@contextlib.contextmanager
def mute_print():
    with open(os.devnull, "w") as devnull:
        with contextlib.redirect_stdout(devnull):
            yield


def override_component_attrs(directory):
    """Tell PyPSA that links can have multiple outputs by
    overriding the component_attrs. This can be done for
    as many buses as you need with format busi for i = 2,3,4,5,....
    See https://pypsa.org/doc/components.html#link-with-multiple-outputs-or-inputs

    Parameters
    ----------
    directory : string
        Folder where component attributes to override are stored
        analogous to ``pypsa/component_attrs``, e.g. `links.csv`.

    Returns
    -------
    Dictionary of overridden component attributes.
    """

    attrs = Dict({k: v.copy() for k, v in component_attrs.items()})

    for component, list_name in components.list_name.items():
        fn = f"{directory}/{list_name}.csv"
        if os.path.isfile(fn):
            overrides = pd.read_csv(fn, index_col=0, na_values="n/a")
            attrs[component] = overrides.combine_first(attrs[component])

    return attrs


# from pypsa-eur/_helpers.py
def mock_snakemake(rulename, **wildcards):
    """
    This function is expected to be executed from the 'scripts'-directory of '
    the snakemake project. It returns a snakemake.script.Snakemake object,
    based on the Snakefile.

    If a rule has wildcards, you have to specify them in **wildcards.

    Parameters
    ----------
    rulename: str
        name of the rule for which the snakemake object should be generated
    **wildcards:
        keyword arguments fixing the wildcards. Only necessary if wildcards are
        needed.
    """
    import os

    import snakemake as sm
    from packaging.version import Version, parse
    from pypsa.descriptors import Dict
    from snakemake.script import Snakemake

    script_dir = Path(__file__).parent.resolve()
    assert (
        Path.cwd().resolve() == script_dir
    ), f"mock_snakemake has to be run from the repository scripts directory {script_dir}"
    os.chdir(script_dir.parent)
    for p in sm.SNAKEFILE_CHOICES:
        if os.path.exists(p):
            snakefile = p
            break
    kwargs = dict(rerun_triggers=[]) if parse(sm.__version__) > Version("7.7.0") else {}
    workflow = sm.Workflow(snakefile, overwrite_configfiles=[], **kwargs)
    workflow.include(snakefile)
    workflow.global_resources = {}
    rule = workflow.get_rule(rulename)
    dag = sm.dag.DAG(workflow, rules=[rule])
    wc = Dict(wildcards)
    job = sm.jobs.Job(rule, dag, wc)

    def make_accessable(*ios):
        for io in ios:
            for i in range(len(io)):
                io[i] = os.path.abspath(io[i])

    make_accessable(job.input, job.output, job.log)
    snakemake = Snakemake(
        job.input,
        job.output,
        job.params,
        job.wildcards,
        job.threads,
        job.resources,
        job.log,
        job.dag.workflow.config,
        job.rule.name,
        None,
    )
    # create log and output dir if not existent
    for path in list(snakemake.log) + list(snakemake.output):
        Path(path).parent.mkdir(parents=True, exist_ok=True)

    os.chdir(script_dir)
    return snakemake


# from pypsa-eur/_helpers.py
def progress_retrieve(url, file):
    import urllib

    from progressbar import ProgressBar

    pbar = ProgressBar(0, 100)

    def dlProgress(count, blockSize, totalSize):
        pbar.update(int(count * blockSize * 100 / totalSize))

    urllib.request.urlretrieve(url, file, reporthook=dlProgress)


def generate_periodic_profiles(dt_index, nodes, weekly_profile, localize=None):
    """
    Give a 24*7 long list of weekly hourly profiles, generate this for each
    country for the period dt_index, taking account of time zones and summer
    time.
    """

    weekly_profile = pd.Series(weekly_profile, range(24 * 7))

    week_df = pd.DataFrame(index=dt_index, columns=nodes)

    for node in nodes:
        timezone = pytz.timezone(pytz.country_timezones[node[:2]][0])
        tz_dt_index = dt_index.tz_convert(timezone)
        week_df[node] = [24 * dt.weekday() + dt.hour for dt in tz_dt_index]
        week_df[node] = week_df[node].map(weekly_profile)

    week_df = week_df.tz_localize(localize)

    return week_df


def parse(l):
    if len(l) == 1:
        return yaml.safe_load(l[0])
    else:
        return {l.pop(0): parse(l)}


def update_config_with_sector_opts(config, sector_opts):
    for o in sector_opts.split("-"):
        if o.startswith("CF+"):
            l = o.split("+")[1:]
            update_config(config, parse(l))