#!/usr/bin/python -B
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
#
#
# asfdata.py -- Pelican plugin that processes a yaml specification of data into a setting directory
#

import os.path
import sys
import random
import json
import traceback
import operator
import pprint

import requests
import yaml
import ezt

import xml.dom.minidom

import pelican.plugins.signals
import pelican.utils


ASF_DATA = {
    'metadata': { },
    'debug': False,
}

# read the asfdata configuration in order to get data load and transformation instructions.
def read_config(config_yaml):
    with pelican.utils.pelican_open(config_yaml) as text:
        config_data = yaml.safe_load(text)
        pp = pprint.PrettyPrinter(indent=2)
        pp.pprint(config_data)
    return config_data


# load yaml and json data sources.
def load_data(path, content):
    parts = path.split('/')
    extension = os.path.splitext(parts[-1])[1]  # split off ext, keep ext
    print(f'Loading {extension} from {path}')
    if extension == '.json':
        load = json.loads(content)
    elif extension == '.yaml':
        load = yaml.safe_load(content)
    else:
        load = { }
    return load


# load data source from a url.
def url_data(url):
    return load_data( url, requests.get(url).text )


# load data source from a file.
def file_data(rel_path):
    return load_data( rel_path, open(rel_path,'r').read() )


# remove parts of a data source we don't want ro access
def remove_part(reference, part):
    for refs in reference:
        if refs == part:
            del reference[part]
            return
        elif isinstance(reference[refs], dict):
            remove_part(reference[refs], part)


# trim out parts of a data source that don't match part = True
def where_parts(reference, part):
    # currently only works on True parts
    # if we trim as we go we invalidate the iterator. Instead create a deletion list.
    filtered = [ ]
    # first find the list that needs to be trimmed.
    for refs in reference:
        if not reference[refs][part]:
            filtered.append(refs)
    # remove the parts to be trimmed.
    for refs in filtered:
        del reference[refs]


# perform alphabetation. HTTP Server is special.
def alpha_part(reference, part):
    for refs in reference:
        name = reference[refs][part]
        if name == 'HTTP Server':
            # when sorting by letter HTTPD Server is wanted first
            letter = ' '
        else:
            letter = name[0].upper()
        reference[refs]['letter'] = letter


# rotate a roster list singleton into an name and availid 
def asfid_part(reference, part):
    for refs in reference:
        fix = reference[refs][part]
        for k in fix:
            availid = k
            name = fix[k]['name']
        reference[refs][part] = name
        reference[refs]['availid'] = availid


# add logo attribute with HEAD check for existence. If nonexistent use default.
def add_logo(reference, part):
    # split between logo pattern and default.
    parts = part.split(',')
    for item in reference:
        logo = (parts[0].format(item.key_id))
        response = requests.head('https://www.apache.org/' + logo)
        if response.status_code != 200:
            logo = parts[1]
        setattr(item, 'logo', logo)
    return reference


# convert a dictionary into a sequence (list)
def sequence_dict(seq, reference):
    sequence = [ ]
    for refs in reference:
        if isinstance(reference[refs], dict):
            reference[refs]['key_id'] = refs
            for item in reference[refs]:
                if isinstance(reference[refs][item], bool):
                    reference[refs][item] = ezt.boolean(reference[refs][item])
            sequence.append(type(seq, (), reference[refs]))
    return sequence


# convert a list into a sequence. convert dictionaries items into objects.
def sequence_list(seq, reference):
    sequence = [ ]
    for refs in reference:
        if isinstance(refs, dict):
            for item in refs:
                if isinstance(refs[item], bool):
                    refs[item] = ezt.boolean(refs[item])
                elif isinstance(refs[item], list):
                    refs[item] = sequence_list(item, refs[item])
            sequence.append(type(f'{seq}', (), refs))
    return sequence


# split a list into equal sized columns. Adds back letter breaks in the alphabetical sequence.
def split_list(metadata, seq, reference, split):
    # copy sequence
    sequence = list(reference)
    # sort the copy
    sequence.sort(key=lambda x: (x.letter, x.display_name))
    # size of list
    size = len(sequence)
    # size of columns
    percol = int((size+26+split-1)/split)
    # positions
    start = nseq = nrow = 0
    letter = ' '
    for column in range(split):
        subsequence = [ ]
        end = min(size+26, start+percol)
        while nrow < end:
            if letter < sequence[nseq].letter:
                # new letter
                letter = sequence[nseq].letter
                subsequence.append(type(seq, (), { 'letter': letter, 'display_name': letter }))
            else:
                subsequence.append(sequence[nseq])
                nseq = nseq+1
            nrow = nrow+1
        # save the column sequence in the metadata
        metadata[f'{seq}_{column}'] = subsequence
        start = end
    if nseq < size:
        print(f'WARNING: {seq} not all of sequence consumed: short {size-nseq} projects')


# process sequencing transformations to the data source
def process_sequence(metadata, seq, sequence, load, debug):
    reference = load
    # has been converted to a sequence
    is_sequence = False
    # has been converted to a dictionary - won't be made into a sequence
    is_dictionary = False
    # save metadata at the end
    save_metadata = True

    # description
    if 'description' in sequence:
        print(f'{seq}: {sequence["description"]}')

    # select sub dictionary
    if 'path' in sequence:
        print(f'path: {sequence["path"]}')
        parts = sequence['path'].split('.')
        for part in parts:
            reference = reference[part]

    # filter dictionary by attribute value. if filter is false discard
    if 'where' in sequence:
        print(f'where: {sequence["where"]}')
        where_parts(reference, sequence['where'])

    # remove irrelevant keys
    if 'trim' in sequence:
        print(f'trim: {sequence["trim"]}')
        parts = sequence['trim'].split(',')
        for part in parts:
            remove_part(reference, part)

    # transform roster and chair patterns
    if 'asfid' in sequence:
        print(f'asfid: {sequence["asfid"]}')
        asfid_part(reference, sequence['asfid'])

    # add first letter ofr alphabetic categories
    if 'alpha' in sequence:
        print(f'alpha: {sequence["alpha"]}')
        alpha_part(reference, sequence['alpha'])

    # this dictionary is derived from sequences
    if 'dictionary' in sequence:
        print(f'dictionary: {sequence["dictionary"]}')
        reference = { }
        paths = sequence['dictionary'].split(',')
        for path in paths:
            for key in load[path]:
                reference[key] = load[path][key]
        is_dictionary = True

    # this sequence is derived from another sequence
    if 'sequence' in sequence:
        print(f'sequence: {sequence["sequence"]}')
        reference = metadata[sequence['sequence']]
        is_sequence = True

    # this sequence is a random sample of another sequence
    if 'random' in sequence:
        print(f'random: {sequence["random"]}')
        if is_sequence:
            reference = random.sample(reference, sequence['random'])
        else:
            print(f'{seq} - random requires an existing sequence to sample')

    # for a project or podling see if the logo exists w/HEAD and set the relative path.
    if 'logo' in sequence:
        print(f'logo: {sequence["logo"]}')
        if is_sequence:
            reference = add_logo(reference, sequence['logo'])
            if seq == 'featured_pods':
                # for podlings strip "Apache" from the beginning and "(incubating)" from the end.
                for item in reference:
                    setattr(item, 'name', ' '.join(item.name.split(' ')[1:-1]))
        else:
            print(f'{seq} - logo requires an existing sequence')

    # this sequence is a sorted list divided into multiple columns
    if 'split' in sequence:
        print(f'split: {sequence["split"]}')
        if is_sequence:
            split_list(metadata, seq, reference, sequence['split'])
            save_metadata = False
        else:
            print(f'{seq} - split requires an existing sequence to split')

    # convert the dictionary/list to a sequence of objects
    if not is_sequence and not is_dictionary:
        print(f'{seq}: create sequence')
        if isinstance(reference, dict):
            reference = sequence_dict(seq, reference)
        elif isinstance(reference, list):
            reference = sequence_list(seq, reference)
        else:
            print(f'{seq}: cannot proceed invalid type, must be dict or list')

    # save sequence in metadata
    if save_metadata:
        metadata[seq] = reference


# create metadata sequences and dictionaries from a data load
def process_load(metadata, value, load, debug):
    for seq in value:
        if seq not in ('url', 'file'):
            # sequence
            sequence = value[seq]
            process_sequence(metadata, seq, sequence, load, debug)


# get xml text node
def get_node_text(nodelist):
    """http://www.python.org/doc/2.5.2/lib/minidom-example.txt"""
    rc = ''
    for node in nodelist:
        if node.nodeType == node.TEXT_NODE:
            rc = rc + node.data
    return rc


# get xml element's text nodes.
def get_element_text(entry, child):
    elements = entry.getElementsByTagName(child)
    return get_node_text(elements[0].childNodes)


# retrieve blog posts from an Atom feed.
def process_blog(feed, count, debug):
    print(f'blog feed: {feed}')
    content = requests.get(feed).text
    dom = xml.dom.minidom.parseString(content)
    entries = dom.getElementsByTagName('entry')
    entries = entries[:count]
    v = [ ]
    for entry in entries:
        if debug:
            print(entry.tagName)
        v.append(
            {
                'id': get_element_text(entry, 'id'),
                'title': get_element_text(entry, 'title'),
            }
        )
    if debug:
        for s in v:
            print(s)

    return [ Blog(href=s['id'],
                  title=s['title'])
             for s in v ]


# to be updated from hidden location. (Need to discuss local.)
def twitter_auth():
    return 'AAAAAAAAAAAAAAAAAAAAACg4PgEAAAAApGfiQijpZK4EQmSvWFLqYE%2FWD%2BI%3D4F9v6SszNmT3lf8o2scY28Zlv7XilgfhMIOFdiFcUmaHfg2PwH'


# retrieve from twitter
def connect_to_endpoint(url, headers):
    response = requests.request('GET', url, headers=headers)
    if response.status_code != 200:
        raise Exception(response.status_code, response.text)
    return response.json()


# retrieve the last count recent tweets from the handle.
def process_twitter(handle, count):
    print(f'-----\ntwitter feed: {handle}')
    bearer_token = twitter_auth()
    query = f'from:{handle}'
    tweet_fields = 'tweet.fields=author_id'
    url = f'https://api.twitter.com/2/tweets/search/recent?query={query}&{tweet_fields}'
    headers = {'Authorization': f'Bearer {bearer_token}'}
    load = connect_to_endpoint(url, headers)
    reference = sequence_list('twitter', load['data'])
    if load['meta']['result_count'] < count:
        v = reference
    else:
        v = reference[:count]
    return v


# create sequence of sequences of ASF ECCN data.
def process_eccn(fname):
    print('-----\nECCN:', fname)
    j = yaml.safe_load(open(fname))

    def make_sources(sources):
        return [ Source(href=s['href'],
                        manufacturer=s['manufacturer'],
                        why=s['why'])
                 for s in sources ]

    def make_versions(vsns):
        return [ Version(version=v['version'],
                         eccn=v['eccn'],
                         source=make_sources(v.get('source', [ ])),
                         )
                 for v in sorted(vsns,
                                 key=operator.itemgetter('version')) ]

    def make_products(prods):
        return [ Product(name=p['name'],
                         versions=make_versions(p['versions']),
                         )
                 for p in sorted(prods,
                                 key=operator.itemgetter('name')) ]

    #print('PROJs:', [p['name'] for p in j['eccnmatrix']])
    return [ Project(name=proj['name'],
                     href=proj['href'],
                     contact=proj['contact'],
                     product=make_products(proj['product']))
             for proj in sorted(j['eccnmatrix'],
                                key=operator.itemgetter('name')) ]


# object wrappers
class wrapper:
    def __init__(self, **kw):
        vars(self).update(kw)

# Improve the names when failures occur.
class Source(wrapper): pass
class Version(wrapper): pass
class Product(wrapper): pass
class Project(wrapper): pass
class Blog(wrapper): pass


# create metadata according to instructions.
def config_read_data(pel_ob):
    print('-----\nasfdata')

    asf_data = pel_ob.settings.get('ASF_DATA')

    if not asf_data:
        print('This Pelican installation is not using ASF_DATA')
        return

    for key in asf_data:
        print(f'config: [{key}] = {asf_data[key]}')

    debug = asf_data['debug']
    
    # This must be present in ASF_DATA. It contains data for use
    # by our plugins, and possibly where we load/inject data from
    # other sources.
    metadata = asf_data['metadata']

    # Lift data from ASF_DATA['data'] into METADATA
    if 'data' in asf_data:
        print(f'Processing {asf_data["data"]}')
        config_data = read_config(asf_data['data'])
        for key in config_data:
            # first check for data that is a singleton with special handling
            if key == 'eccn':
                # process eccn data
                fname = config_data[key]['file']
                metadata[key] = v = process_eccn(fname)
                if debug:
                    print('ECCN V:', v)
                continue

            if key == 'twitter':
                # process twitter data (if we decide to have multiple twitter feeds available then move next to blog'
                handle = config_data[key]['handle']
                count = config_data[key]['count']
                metadata[key] = v = process_twitter(handle, count)
                if debug:
                    print('TWITTER V:', v)
                continue

            value = config_data[key]
            if isinstance(value, dict):
                # dictionaries are complex data sources
                print(f'-----\n{key} creates one or more sequences')
                if debug:
                    print(value)
                # special cases that are multiple are processed first
                if 'blog' in value:
                    # process blog feed
                    feed = config_data[key]['blog']
                    count = config_data[key]['count']
                    metadata[key] = v = process_blog(feed, count, debug)
                    if debug:
                        print('BLOG V:', v)
                    continue

                elif 'url' in value:
                    # process a url based data source
                    load = url_data(value['url'])
                    process_load(metadata, value, load, debug)

                elif 'file' in value:
                    # process a file from within the site tree
                    load = file_data(value['file'])
                    process_load(metadata, value, load, debug)

                else:
                    # should probably be an error.
                    metadata[key] = value
            else:
                # simple metadata values
                print(f'{key} = {value}')
                metadata[key] = value

    # display asfdata metadata.
    print('-----')
    for key in metadata:
        if debug:
            print(f'metadata[{key}] =')
            print(metadata[key])
            print('-----')
        elif isinstance(metadata[key], str):
            print(f'metadata[{key}] = "{metadata[key]}"')
        elif isinstance(metadata[key], int):
            print(f'metadata[{key}] = {metadata[key]}')
        elif isinstance(metadata[key], list):
            print(f'metadata[{key}] is a sequence.')
        elif isinstance(metadata[key], dict):
            print(f'metadata[{key}] is a dictionary.')
        else:
            keytype = type(metadata[key])
            print(f'metadata[{key}] is a {keytype}')


def tb_initialized(pel_ob):
    """ Print any exception, before Pelican chews it into nothingness."""
    try:
        config_read_data(pel_ob)
    except:
        print('-----', file=sys.stderr)
        traceback.print_exc()
        raise


def register():
    # Hook the "initialized" signal, to load our custom data.
    pelican.plugins.signals.initialized.connect(tb_initialized)