"""
    utils - general utility functions for loading, saving, and manipulating data
"""

import os
from pathlib import Path
import pprint as pp
import re
import shutil  # zipfile formats
from datetime import datetime
from os.path import basename
from os.path import getsize, join

import requests
from cleantext import clean
from natsort import natsorted
from symspellpy import SymSpell
import pandas as pd
from tqdm.auto import tqdm


from contextlib import contextmanager
import sys
import os


@contextmanager
def suppress_stdout():
    """
    suppress_stdout - suppress stdout for a given block of code. credit to https://newbedev.com/how-to-suppress-console-output-in-python
    """
    with open(os.devnull, "w") as devnull:
        old_stdout = sys.stdout
        sys.stdout = devnull
        try:
            yield
        finally:
            sys.stdout = old_stdout


def remove_string_extras(mytext):
    # removes everything from a string except A-Za-z0-9 .,;
    return re.sub(r"[^A-Za-z0-9 .,;]+", "", mytext)


def corr(s):
    # adds space after period if there isn't one
    # removes extra spaces
    return re.sub(r"\.(?! )", ". ", re.sub(r" +", " ", s))


def get_timestamp():
    # get timestamp for file names
    return datetime.now().strftime("%b-%d-%Y_t-%H")


def print_spacer(n=1):
    """print_spacer - print a spacer line"""
    print("\n   --------    " * n)


def fast_scandir(dirname: str):
    """
    fast_scandir [an os.path-based means to return all subfolders in a given filepath]

    """

    subfolders = [f.path for f in os.scandir(dirname) if f.is_dir()]
    for dirname in list(subfolders):
        subfolders.extend(fast_scandir(dirname))
    return subfolders  # list


def create_folder(directory: str):
    # you will never guess what this does
    os.makedirs(directory, exist_ok=True)


def chunks(lst: list, n: int):
    """
    chunks   -  Yield successive n-sized chunks from lst
    Args:   lst (list): list to be chunked
    n (int): size of chunks

    """

    for i in range(0, len(lst), n):
        yield lst[i : i + n]


def chunky_pandas(my_df, num_chunks: int = 4):
    """
    chunky_pandas [split dataframe into `num_chunks` equal chunks, return each inside a list]

    Args:
        my_df (pd.DataFrame)
        num_chunks (int, optional): Defaults to 4.

    Returns:
        list: a list of dataframes
    """
    n = int(len(my_df) // num_chunks)
    list_df = [my_df[i : i + n] for i in range(0, my_df.shape[0], n)]

    return list_df


def load_dir_files(
    directory: str, req_extension=".txt", return_type="list", verbose=False
):
    """
    load_dir_files - an os.path based method of returning all files with extension `req_extension` in a given directory and subdirectories

    Args:


    Returns:
        list or dict: an iterable of filepaths or a dict of filepaths and their respective filenames
    """
    appr_files = []
    # r=root, d=directories, f = files
    for r, d, f in os.walk(directory):
        for prefile in f:
            if prefile.endswith(req_extension):
                fullpath = os.path.join(r, prefile)
                appr_files.append(fullpath)

    appr_files = natsorted(appr_files)

    if verbose:
        print("A list of files in the {} directory are: \n".format(directory))
        if len(appr_files) < 10:
            pp.pprint(appr_files)
        else:
            pp.pprint(appr_files[:10])
            print("\n and more. There are a total of {} files".format(len(appr_files)))

    if return_type.lower() == "list":
        return appr_files
    else:
        if verbose:
            print("returning dictionary")

        appr_file_dict = {}
        for this_file in appr_files:
            appr_file_dict[basename(this_file)] = this_file

        return appr_file_dict


def URL_string_filter(text):
    """
    URL_string_filter - filter out nonstandard "text" characters

    """
    custom_printable = (
        "0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ._"
    )

    filtered = "".join((filter(lambda i: i in custom_printable, text)))

    return filtered


def getFilename_fromCd(cd):
    """getFilename_fromCd - get the filename from a given cd str"""
    if not cd:
        return None
    fname = re.findall("filename=(.+)", cd)
    if len(fname) > 0:
        output = fname[0]
    elif cd.find("/"):
        possible_fname = cd.rsplit("/", 1)[1]
        output = URL_string_filter(possible_fname)
    else:
        output = None
    return output


def get_zip_URL(
    URLtoget: str,
    extract_loc: str = None,
    file_header: str = "dropboxexport_",
    verbose: bool = False,
):
    """get_zip_URL - download a zip file from a given URL and extract it to a given location"""

    r = requests.get(URLtoget, allow_redirects=True)
    names = getFilename_fromCd(r.headers.get("content-disposition"))
    fixed_fnames = names.split(";")  # split the multiple results
    this_filename = file_header + URL_string_filter(fixed_fnames[0])

    # define paths and save the zip file
    if extract_loc is None:
        extract_loc = "dropbox_dl"
    dl_place = join(os.getcwd(), extract_loc)
    create_folder(dl_place)
    save_loc = join(os.getcwd(), this_filename)
    open(save_loc, "wb").write(r.content)
    if verbose:
        print("downloaded file size was {} MB".format(getsize(save_loc) / 1000000))

    # unpack the archive
    shutil.unpack_archive(save_loc, extract_dir=dl_place)
    if verbose:
        print("extracted zip file - ", datetime.now())
        x = load_dir_files(dl_place, req_extension="", verbose=verbose)

    # remove original
    try:
        os.remove(save_loc)
        del save_loc
    except Exception:
        print("unable to delete original zipfile - check if exists", datetime.now())

    print("finished extracting zip - ", datetime.now())

    return dl_place


def merge_dataframes(data_dir: str, ext=".xlsx", verbose=False):
    """
    merge_dataframes - given a filepath, loads and attempts to merge all files as dataframes

    Args:
        data_dir (str): [root directory to search in]
        ext (str, optional): [anticipate file extension for the dataframes ]. Defaults to '.xlsx'.

    Returns:
        pd.DataFrame(): merged dataframe of all files
    """

    src = Path(data_dir)
    src_str = str(src.resolve())
    mrg_df = pd.DataFrame()

    all_reports = load_dir_files(directory=src_str, req_extension=ext, verbose=verbose)

    failed = []

    for df_path in tqdm(all_reports, total=len(all_reports), desc="joining data..."):

        try:
            this_df = pd.read_excel(df_path).convert_dtypes()

            mrg_df = pd.concat([mrg_df, this_df], axis=0)
        except Exception:
            short_p = os.path.basename(df_path)
            print(
                f"WARNING - file with extension {ext} and name {short_p} could not be read."
            )
            failed.append(short_p)

    if len(failed) > 0:
        print("failed to merge {} files, investigate as needed")

    if verbose:
        pp.pprint(mrg_df.info(True))

    return mrg_df


def download_URL(url: str, file=None, dlpath=None, verbose=False):
    """
    download_URL - download a file from a URL and show progress bar

    Parameters
    ----------
    url : str
        URL to download
    file : [type], optional
        [description], by default None
    dlpath : [type], optional
        [description], by default None
    verbose : bool, optional
        [description], by default False

    Returns
    -------
    str - path to the downloaded file
    """

    if file is None:
        if "?dl=" in url:
            # is a dropbox link
            prefile = url.split("/")[-1]
            filename = str(prefile).split("?dl=")[0]
        else:
            filename = url.split("/")[-1]

        file = clean(filename)
    if dlpath is None:
        dlpath = Path.cwd()  # save to current working directory
    else:
        dlpath = Path(dlpath)  # make a path object

    r = requests.get(url, stream=True, allow_redirects=True)
    total_size = int(r.headers.get("content-length"))
    initial_pos = 0
    dl_loc = dlpath / file
    with open(str(dl_loc.resolve()), "wb") as f:
        with tqdm(
            total=total_size,
            unit="B",
            unit_scale=True,
            desc=file,
            initial=initial_pos,
            ascii=True,
        ) as pbar:
            for ch in r.iter_content(chunk_size=1024):
                if ch:
                    f.write(ch)
                    pbar.update(len(ch))

    if verbose:
        print(f"\ndownloaded {file} to {dlpath}\n")

    return str(dl_loc.resolve())


def dl_extract_zip(
    URLtoget: str,
    extract_loc: str = None,
    file_header: str = "TEMP_archive_dl_",
    verbose: bool = False,
):
    """
    dl_extract_zip - generic function to download a zip file and extract it

    Parameters
    ----------
    URLtoget : str
        zip file URL to download
    extract_loc : str, optional
        directory to extract zip to , by default None
    file_header : str, optional
        [description], by default "TEMP_archive_dl_"
    verbose : bool, optional
        [description], by default False

    Returns
    -------
    str - path to the downloaded and extracted folder
    """

    extract_loc = Path(extract_loc)
    extract_loc.mkdir(parents=True, exist_ok=True)

    save_loc = download_URL(
        url=URLtoget, file=f"{file_header}.zip", dlpath=None, verbose=verbose
    )

    shutil.unpack_archive(save_loc, extract_dir=extract_loc)

    if verbose:
        print("extracted zip file - ", datetime.now())
        x = load_dir_files(extract_loc, req_extension="", verbose=verbose)

    # remove original
    try:
        os.remove(save_loc)
        del save_loc
    except Exception:
        print("unable to delete original zipfile - check if exists", datetime.now())

    if verbose:
        print("finished extracting zip - ", datetime.now())

    return extract_loc


def cleantxt_wrap(ugly_text, all_lower=False):
    """
    cleantxt_wrap - applies the clean function to a string.

    Args:
        ugly_text (str): [string to be cleaned]

    Returns:
        [str]: [cleaned string]
    """
    if isinstance(ugly_text, str) and len(ugly_text) > 0:
        return clean(ugly_text, lower=all_lower)
    else:
        return ugly_text