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MIT License | ||
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Copyright (c) 2018 ddio | ||
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Permission is hereby granted, free of charge, to any person obtaining a copy | ||
of this software and associated documentation files (the "Software"), to deal | ||
in the Software without restriction, including without limitation the rights | ||
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | ||
copies of the Software, and to permit persons to whom the Software is | ||
furnished to do so, subject to the following conditions: | ||
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The above copyright notice and this permission notice shall be included in all | ||
copies or substantial portions of the Software. | ||
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | ||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | ||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | ||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | ||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | ||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE | ||
SOFTWARE. |
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# TW Rental House Utility for Scrapy | ||
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This package is built for crawling Taiwanese rental house related website using [Scrapy](https://scrapy.org/). | ||
As behaviour of crawlers may differ from their goal, scale, and pipeline, this package provides only minimun feature set, which allow developer to list and decode a rental house webpage into structured data, without knowning too much about detail HTML and API structure of each website. In addition, this package is also designed for extensibility, which allow developers to insert customized callback, manipulate data, and integrate with existing crawler structure. | ||
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## Installation | ||
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## Basic Usage | ||
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## Handlers | ||
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## Contribution Guideline | ||
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Each spider class must: | ||
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1. Provide unit test | ||
2. Runnable using scrapy command | ||
3. Aviod unnecessary 3rd party dependency. |
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asn1crypto==0.24.0 | ||
attrs==19.1.0 | ||
Automat==0.7.0 | ||
cffi==1.12.3 | ||
constantly==15.1.0 | ||
cryptography==2.7 | ||
cssselect==1.0.3 | ||
hyperlink==19.0.0 | ||
idna==2.8 | ||
incremental==17.5.0 | ||
lxml==4.3.3 | ||
parsel==1.5.1 | ||
pyasn1==0.4.5 | ||
pyasn1-modules==0.2.5 | ||
pycparser==2.19 | ||
PyDispatcher==2.0.5 | ||
PyHamcrest==1.9.0 | ||
pyOpenSSL==19.0.0 | ||
queuelib==1.5.0 | ||
Scrapy==1.6.0 | ||
service-identity==18.1.0 | ||
six==1.12.0 | ||
Twisted==19.2.1 | ||
w3lib==1.20.0 | ||
zope.interface==4.6.0 |
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__pycache__ |
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name = "scrapy-tw-rental-house" |
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# -*- coding: utf-8 -*- | ||
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# Define here the models for your scraped items | ||
# | ||
# See documentation in: | ||
# https://doc.scrapy.org/en/latest/topics/items.html | ||
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from scrapy import Field, Item | ||
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class GenericHouseItem(Item): | ||
top_region = Field() | ||
sub_region = Field() | ||
deal_time = Field() | ||
deal_status = Field() | ||
n_day_deal = Field() | ||
vendor = Field() | ||
vendor_house_id = Field() | ||
vendor_house_url = Field() | ||
# price related | ||
monthly_price = Field() | ||
deposit_type = Field() | ||
n_month_deposit = Field() | ||
deposit = Field() | ||
is_require_management_fee = Field() | ||
monthly_management_fee = Field() | ||
has_parking = Field() | ||
is_require_parking_fee = Field() | ||
monthly_parking_fee = Field() | ||
per_ping_price = Field() | ||
# other basic info | ||
building_type = Field() | ||
property_type = Field() | ||
is_rooftop = Field() | ||
floor = Field() | ||
total_floor = Field() | ||
dist_to_highest_floor = Field() | ||
floor_ping = Field() | ||
n_living_room = Field() | ||
n_bed_room = Field() | ||
n_bath_room = Field() | ||
n_balcony = Field() | ||
apt_feature_code = Field() | ||
rough_address = Field() | ||
# (latitude, longtitude) tuple of WGS84 coordinate | ||
rough_coordinate = Field() | ||
# boolean map | ||
# eletricity: true, water: true, gas: true, internet: true, cable_tv: true | ||
additional_fee = Field() | ||
# school, park, dept_store, conv_store, traditional_mkt, night_mkt, | ||
# hospital, police_office | ||
living_functions = Field() | ||
# subway, bus, public_bike, train, hsr | ||
transportation = Field() | ||
has_tenant_restriction = Field() | ||
has_gender_restriction = Field() | ||
gender_restriction = Field() | ||
can_cook = Field() | ||
allow_pet = Field() | ||
has_perperty_registration = Field() | ||
# undermined for now | ||
facilities = Field() | ||
contact = Field() | ||
author = Field() | ||
agent_org = Field() | ||
imgs = Field() | ||
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class RawHouseItem(Item): | ||
house_id = Field() | ||
vendor = Field() | ||
is_list = Field() | ||
raw = Field() | ||
dict = Field() |
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# This package will contain the spiders of your Scrapy project | ||
# | ||
# Please refer to the documentation for information on how to create and manage | ||
# your spiders. |
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scrapy-package/scrapy-tw-rental-house/spiders/all_591_cities.py
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all_591_cities = [ | ||
{ | ||
"city": "台北市", | ||
"id": "1" | ||
}, | ||
{ | ||
"city": "新北市", | ||
"id": "3" | ||
}, | ||
{ | ||
"city": "桃園市", | ||
"id": "6" | ||
}, | ||
{ | ||
"city": "新竹市", | ||
"id": "4" | ||
}, | ||
{ | ||
"city": "新竹縣", | ||
"id": "5" | ||
}, | ||
{ | ||
"city": "基隆市", | ||
"id": "2" | ||
}, | ||
{ | ||
"city": "宜蘭縣", | ||
"id": "21" | ||
}, | ||
{ | ||
"city": "台中市", | ||
"id": "8" | ||
}, | ||
{ | ||
"city": "彰化縣", | ||
"id": "10" | ||
}, | ||
{ | ||
"city": "苗栗縣", | ||
"id": "7" | ||
}, | ||
{ | ||
"city": "雲林縣", | ||
"id": "14" | ||
}, | ||
{ | ||
"city": "南投縣", | ||
"id": "11" | ||
}, | ||
{ | ||
"city": "高雄市", | ||
"id": "17" | ||
}, | ||
{ | ||
"city": "台南市", | ||
"id": "15" | ||
}, | ||
{ | ||
"city": "嘉義市", | ||
"id": "12" | ||
}, | ||
{ | ||
"city": "屏東縣", | ||
"id": "19" | ||
}, | ||
{ | ||
"city": "嘉義縣", | ||
"id": "13" | ||
}, | ||
{ | ||
"city": "花蓮縣", | ||
"id": "23" | ||
}, | ||
{ | ||
"city": "台東縣", | ||
"id": "22" | ||
}, | ||
{ | ||
"city": "金門縣", | ||
"id": "25" | ||
}, | ||
{ | ||
"city": "澎湖縣", | ||
"id": "24" | ||
} | ||
] |
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from enum import IntEnum | ||
from os import path | ||
import json | ||
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class DealStatusType(IntEnum): | ||
OPENED = 0 | ||
NOT_FOUND = 1 | ||
DEAL = 2 | ||
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UNKNOWN_ENUM = 0xffff | ||
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BuildingType = IntEnum('BuildingType', [ | ||
('公寓', 0), | ||
('透天', 1), | ||
('電梯大樓', 2), | ||
('華廈', 3), | ||
('辦公商業大樓', 4), | ||
('倉庫', 5), | ||
('店面(店鋪)', 6), | ||
('廠辦', 7), | ||
('工廠', 8), | ||
('農舍', 9) | ||
]) | ||
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class PropertyType(IntEnum): | ||
整層住家 = 0 | ||
獨立套房 = 1 | ||
分租套房 = 2 | ||
雅房 = 3 | ||
車位 = 4 | ||
其他 = 5 | ||
倉庫 = 6 | ||
場地 = 7 | ||
攤位 = 8 | ||
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class ContactType(IntEnum): | ||
屋主 = 0 | ||
代理人 = 1 | ||
房仲 = 2 | ||
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class DepositType(IntEnum): | ||
月 = 0 | ||
定額 = 1 | ||
面議 = 2 | ||
其他 = 3 | ||
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class GenderType(IntEnum): | ||
不限 = 0 | ||
女 = 1 | ||
男 = 2 | ||
其他 = 3 | ||
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tw_regions_path = '{}/data/tw_regions.json'.format( | ||
path.dirname(path.realpath(__file__))) | ||
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with open(tw_regions_path) as regions_file: | ||
tw_regions = json.load(regions_file) | ||
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TopRegionType = IntEnum('TopRegionType', tw_regions['top_region']) | ||
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SubRegionType = IntEnum('SubRegionType', tw_regions['sub_region']) |
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