Tutti Fajly Actor

1import scrapy
2import re
3
4
5class ChampionsLeagueSpider(scrapy.Spider):
6    name = 'championsleaguespider'
7    start_urls = ['https://www.uefa.com/uefachampionsleague/season=2018/clubs/']
8
9    custom_settings = {
10        'USER_AGENT': 'DDWcrawler',
11        'ROBOTSTXT_OBEY': True,
12        'DOWNLOAD_DELAY': 0.001,
13    }
14
15    # Parse statistics data of the current season
16    def parse_phase(self, fields):
17        phase = {}
18        for field in fields:
19            label = field.css('.statistics--list--label::text').extract_first()
20
21            # Passing accuracy field
22            if (label == 'passing accuracy'):
23                value = field.css('.graph-circle--additional-text::text').extract_first()
24
25            # Cards field
26            elif (label == 'Cards'):
27                cards = field.xpath('.//span[@class="statistics--list--data"]/text()').extract()
28                labels = field.css('.statistics--list--data img::attr(title)').extract()
29
30                yellow = re.findall('\d+', cards[0])
31                red = re.findall('\d+', cards[1])
32
33                value = {
34                    labels[0].lower().replace(" ", "-"): yellow[0],
35                    labels[1].lower().replace(" ", "-"): red[0],
36                }
37
38            # Passing types field
39            elif (label == 'Passing types'):
40                types = field.css('.statistics--list--data .graph-bar-container .bar-container')
41                value = {}
42
43                for type in types:
44                    pass_type = type.css('span:not(.bar)::text').extract_first()
45                    type_label = pass_type.split(' ')[1].lower()
46                    type_value = type.css('span:not(.bar) b::text').extract_first() + ' ' + \
47                                 pass_type.split(' ')[2]
48                    value[type_label] = type_value
49
50            # Goal types field
51            elif (label == 'Type of goal'):
52                types = field.css('.statistics--list--data .graph-dummy-container > div')
53                value = {}
54                for type in types:
55                    type_label = type.xpath('.//span/text()').extract()
56                    type_value = type.css('div > span::text').extract_first()
57                    value[type_label[1].lower().replace(" ", "-")] = type_value
58
59            # Standard fields
60            else:
61                value = field.css('.statistics--list--data::text').extract_first()
62
63            phase[label.lower().replace(" ", "-")] = value
64
65        return phase
66
67    # Collect statistics data and split it into phases
68    def parse_stats(self, response):
69        player = response.meta['player']
70        stats_sections = response.css('.player--statistics--list')
71        player['matches'] = {}
72
73        for section in stats_sections:
74            fields = section.css('.field')
75            phase_name = section.css('.stats-header::text').extract_first()
76
77            # Tournament phase
78            if (phase_name == 'Tournament phase'):
79                player['matches']['tournament'] = self.parse_phase(fields)
80
81            # Qualification phase
82            elif (phase_name == 'Qualifying'):
83                player['matches']['qualification'] = self.parse_phase(fields)
84
85        yield player
86
87    # Visit player's profile page, collect biography data and get a link to statistics page
88    def parse_player(self, response):
89        stats_url = response.css(
90            '.content-wrap .section--footer a[title="More statistics"]::attr(href)').extract_first()
91
92        for player in response.xpath('//div[@class="content-wrap"]'):
93            bio = {
94                'name': player.css('.player-header_name::text').extract_first(),
95                'position': player.css('.player-header_category::text').extract_first(),
96                'team': player.css('.player-header_team-name::text').extract_first(),
97                'nationality': player.css('.player-header_country::text').extract_first(),
98                'birthdate': player.css('.profile--list--data[itemprop=birthdate]::text').extract_first().split(' ')[0],
99                'height': player.css('.profile--list--data[itemprop=height]::text').extract_first(),
100                'weight': player.css('.profile--list--data[itemprop=weight]::text').extract_first(),
101            }
102
103            if (stats_url):
104                yield scrapy.Request(response.urljoin(stats_url), callback=self.parse_stats, meta={'player': bio})
105            else:
106                yield bio
107
108    # Visit page of each club and collect links to players profiles
109    def parse_clubs(self, response):
110        players = response.css('#team-data .squad--team-player')
111        players_urls = players.css('.squad--player-name > a::attr(href)').extract()
112
113        for player_url in players_urls:
114            yield scrapy.Request(response.urljoin(player_url), callback=self.parse_player)
115
116    # Get a list of clubs from the starting page
117    def parse(self, response):
118        clubs = response.css('.teams-overview_group .team > a')
119
120        clubs_tocrawl = clubs.css('::attr(href)').extract()
121
122        for club_url in clubs_tocrawl:
123            yield scrapy.Request(response.urljoin(club_url), callback=self.parse_clubs)

1const Apify = require('apify');
2const request = require('request-promise');
3
4Apify.main(async () => {
5    // Get input of your actor
6    const input = await Apify.getValue('INPUT');
7    console.log('My input:');
8    console.dir(input);
9
10    // Do something useful here
11    const html = await request('http://www.example.com');
12
13    // And then save output
14    const output = {
15        html,
16        crawledAt: new Date(),
17    };
18    console.log('My output:');
19    console.dir(output);
20    await Apify.setValue('OUTPUT', output);
21});

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2something;that;5;