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scraper.py
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scraper.py
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"""
This scraper crawls OregonHikers.org for hikes, formats it as a TSV,
and then extracts useful bits of that data into a CSV.
"""
from urllib.request import Request, urlopen
from urllib.error import HTTPError
import re
import csv
import os.path
from itertools import islice
from bs4 import BeautifulSoup
import pandas as pd
BASE_URL = "http:https://www.oregonhikers.org"
HIKES_DB_FILENAME = "hikes_db"
class HikesSheet:
"""HikesSheet creates a CSV of hikes."""
def __init__(self, file_name='hikes'):
self.file_name = file_name
self.columns = [
'hike_name',
'url',
'trailhead_name',
'trailhead_lat',
'trailhead_lon',
'distance',
'time_of_year'
]
self.create_headings(self.columns)
def create_headings(self, headings_arr):
"""Creates headings in the CSV out of columns in the constructor."""
with open("{}.csv".format(self.file_name), 'w', newline='') as csvfile:
writer = csv.writer(csvfile, delimiter=',', quotechar='|', quoting=csv.QUOTE_MINIMAL)
writer.writerow(headings_arr)
def add_hike(
self, hike_name, url, \
trailhead_name, trailhead_lat, trailhead_lon, distance, time_of_year
):
"""Adds a hike with the specified fields to the CSV."""
if not trailhead_lat or not trailhead_lon:
print('Error adding hike to CSV: {}'.format(hike_name))
return
with open("{}.csv".format(self.file_name), 'a', newline='') as csvfile:
writer = csv.writer(csvfile, delimiter=',', quotechar='|', quoting=csv.QUOTE_MINIMAL)
writer.writerow([
hike_name,
url,
trailhead_name,
trailhead_lat,
trailhead_lon,
distance,
time_of_year
])
class HikesDatabase:
"""Creates a database of all hikes. Used as a sub for the live site."""
def __init__(self, file_name=HIKES_DB_FILENAME):
self.file_name = file_name
self.columns = [
'hike_url',
'hike_html',
'trailhead_url',
'trailhead_html',
]
self.create_headings(self.columns)
def create_headings(self, headings_arr):
"""Creates headings in the CSV out of columns in the constructor."""
with open("{}.tsv".format(self.file_name), 'w', newline='') as csvfile:
writer = csv.writer(csvfile, delimiter='\t', quotechar='|', quoting=csv.QUOTE_MINIMAL)
writer.writerow(headings_arr)
def add_hike(self, hike_name, hike_html, trailhead_name, trailhead_html):
"""Adds the name + html of a hike + trailhead to the CSV."""
with open("{}.tsv".format(self.file_name), 'a', newline='') as csvfile:
writer = csv.writer(csvfile, delimiter='\t', quotechar='|', quoting=csv.QUOTE_MINIMAL)
writer.writerow([
hike_name,
hike_html,
trailhead_name,
trailhead_html,
])
class HikesData:
"""Used to clean/manipulate hike data before writing to a HikesSheet."""
def __init__(self):
self.columns = [
'hike_name',
'url',
'trailhead_name',
'trailhead_lat',
'trailhead_lon',
'distance',
'time_of_year',
]
self.dataframe = pd.DataFrame([], columns=self.columns)
self.year_words = ['all', 'year', 'round', 'seasons', 'any']
self.winter_words = ['winter', 'december', 'january', 'february']
self.spring_words = ['spring', 'march', 'april', 'may', 'june', 'apr']
self.summer_words = ['summer', 'june', 'july', 'august', 'september', 'jun']
self.fall_words = ['fall', 'september', 'october', 'november', 'oct', 'nov']
self.year_round_string = "All Year "
self.winter_string = "Winter "
self.spring_string = "Spring "
self.summer_string = "Summer "
self.fall_string = "Fall "
def create_regex_from_list(self, regex_list):
"""Returns a regex that matches any item in a given list."""
return re.compile(r'\b({})'.format("|".join(regex_list)))
def add_hike(self, hike_name, url, trailhead_info, distance, time_of_year):
"""Adds a hike to the dataframe of all hikes."""
trailhead_name, trailhead_lat, trailhead_lon = trailhead_info
hike_dataframe = pd.DataFrame([[
hike_name,
url,
trailhead_name,
trailhead_lat,
trailhead_lon,
distance,
time_of_year,
]], columns=self.columns)
self.dataframe = self.dataframe.append(hike_dataframe)
def get_season_value(
self, raw_season, year_vals, \
winter_vals, spring_vals, summer_vals, fall_vals
):
"""Gets a specific season or seasons in response to a freeform season."""
new_time = ""
if raw_season in year_vals:
new_time += self.year_round_string
if raw_season in winter_vals:
new_time += self.winter_string
if raw_season in spring_vals:
new_time += self.spring_string
if raw_season in summer_vals:
new_time += self.summer_string
if raw_season in fall_vals:
new_time += self.fall_string
if new_time:
return new_time
print('Season {} not in any lists of season values'.format(raw_season))
return raw_season
def clean_time_of_year(self):
"""
Searches the `time_of_year` column for duplicates
and collapses them into a canonical phrasing.
"""
time_of_year_data = self.dataframe['time_of_year'].unique().tolist()
year_round_regex = self.create_regex_from_list(self.year_words)
winter_regex = self.create_regex_from_list(self.winter_words)
spring_regex = self.create_regex_from_list(self.spring_words)
summer_regex = self.create_regex_from_list(self.summer_words)
fall_regex = self.create_regex_from_list(self.fall_words)
year_round_values = [
val for val in time_of_year_data if val and year_round_regex.search(val.lower())
]
winter_values = [
val for val in time_of_year_data if val and winter_regex.search(val.lower())
]
spring_values = [
val for val in time_of_year_data if val and spring_regex.search(val.lower())
]
summer_values = [
val for val in time_of_year_data if val and summer_regex.search(val.lower())
]
fall_values = [
val for val in time_of_year_data if val and fall_regex.search(val.lower())
]
# then double back to see if any seasons were "skipped" the first time through.
skipped_spring_values = [
val for val in winter_values if val in summer_values and val not in spring_values
]
skipped_summer_values = [
val for val in spring_values if val in fall_values and val not in summer_values
]
skipped_fall_values = [
val for val in summer_values if val in winter_values and val not in fall_values
]
# a trail is PROBABLY not open Fall-Spring without being open year-round.
spring_values += skipped_spring_values
summer_values += skipped_summer_values
fall_values += skipped_fall_values
# loop back over dataframe values to replace with canonical value of that season
temp_dataframe = pd.DataFrame([], columns=self.columns)
for row in self.dataframe.iterrows():
time_of_year = self.get_season_value(
row[1]['time_of_year'],
year_round_values,
winter_values,
spring_values,
summer_values,
fall_values,
)
hike_df = pd.DataFrame([[
row[1]['hike_name'],
row[1]['url'],
row[1]['trailhead_name'],
row[1]['trailhead_lat'],
row[1]['trailhead_lon'],
row[1]['distance'],
time_of_year,
]], columns=self.columns)
temp_dataframe = temp_dataframe.append(hike_df)
self.dataframe = temp_dataframe
def make_request(url):
"""Create a Request object."""
return Request(url, headers={'User-Agent': 'Mozilla/5.0'})
def make_soup(url):
"""Reads a Request object and parses its HTML."""
return BeautifulSoup(urlopen(make_request(url)), features="html.parser")
def make_soup_from_html(html):
"""Reads in HTML and returns a parsed bs4 tree."""
return BeautifulSoup(html, features="html.parser")
def get_hike_name(content):
"""From bs4-parsed HTML, extract the hike name."""
return content.find('h1').string
def get_hike_distance(content):
"""From bs4-parsed HTML, extract the hike distance."""
try:
return content.find('ul') \
.find(text=re.compile(r'Distance: ')) \
.split(': ')[1] \
.split('\n')[0] \
.split(' miles')[0]
except AttributeError:
return None
def get_hike_time_of_year(content):
"""From bs4-parsed HTML, extract the hike time of year."""
try:
return content.find('ul') \
.find(text=re.compile(r'Seasons:')) \
.split(':')[1] \
.split('\n')[0]
except AttributeError:
return None
def find_all_result_pages(url, arr):
"""
Given a base Search URL,
hit the Next button repeatedly and return all pages findable this way.
"""
result_pages = arr
result_pages.append(url)
html = make_soup(url)
content = html.find(id='mw-content-text')
results_counter = content.find('b')
next_link = results_counter.next_sibling.next_sibling
if next_link.name == 'a':
return find_all_result_pages("{}{}".format(BASE_URL, next_link.get('href')), result_pages)
return result_pages
def find_all_result_links(url):
"""Given a page of results, find all the links to hike pages."""
result_pages = find_all_result_pages(url, [])
links = []
for result_page in result_pages:
html = make_soup(result_page)
wrapper = html.find_all('p')[0]
links += wrapper.find_all('a')
return links
def get_raw_hike_data(url):
"""Intakes a hike URL and gets the HTML for that hike and the URL + HTML for the trailhead."""
try:
html = make_soup(url)
except HTTPError:
print('Error getting hike: {}'.format(url))
return None
hike_html = html.find(id='mainContent')
try:
trailhead_url = '{}{}'.format(
BASE_URL,
hike_html.find('ul').find(text=re.compile(r'Start')).next_sibling.get('href')
)
except AttributeError:
print('Error getting trailhead for hike: {}'.format(url))
return None
try:
trailhead_html = make_soup(trailhead_url)
except HTTPError:
print('Error getting trailhead for hike: {}'.format(url))
return None
return(url, hike_html, trailhead_url, trailhead_html)
def add_hikes_to_database():
"""Scrapes the live OH.org and adds hikes to the database file."""
db = HikesDatabase() #pylint: disable=C0103
start_url = "http:https://www.oregonhikers.org/w/index.php?title=Special:Ask&limit=500&q=%5B%5BDistance%3A%3A%3E0+miles%5D%5D&p=format%3Dlist%2Flink%3Dall%2Fheaders%3Dshow%2Fsearchlabel%3D%E2%80%A6-20further-20results&sort=&order=ASC&eq=yes" #pylint: disable=C0301
links = find_all_result_links(start_url)
total_links = len(links)
curr_link = 1
for link in links:
print('Processing {} of {}'.format(curr_link, total_links))
data = get_raw_hike_data('{}{}'.format(BASE_URL, link.get('href')))
curr_link += 1
if data:
url, html, t_url, t_html = data
db.add_hike(url, html, t_url, t_html)
def get_trailhead_lat(content):
"""From bs4-parsed HTML, extract the trailhead lat."""
lat = content.find(id='mw-content-text').find('ul').find(text=re.compile(r'Latitude: '))
try:
lat = lat.split(": ")[1].split("\n")[0]
except AttributeError:
print("Trailhead no lat.")
return None
return lat
def get_trailhead_lon(content):
"""From bs4-parsed HTML, extract the trailhead lon."""
lon = content.find(id='mw-content-text').find('ul').find(text=re.compile(r'Longitude: '))
try:
lon = lon.split(": ")[1].split("\n")[0]
except AttributeError:
print("Trailhead no lon.")
return None
return lon
def get_trailhead_name(content):
"""From bs4-parsed HTML, extract the trailhead name."""
try:
return content.find('h1').string
except AttributeError:
print("Could not find trailhead name.")
return None
def get_hike_data(row):
"""
This function gets hike data from a row of a CSV of:
hike URL, hike HTML, trailhead URL, trailhead HTML.
"""
hike_url = row[0]
hike_html = make_soup_from_html(row[1])
hike_name = get_hike_name(hike_html)
hike_distance = get_hike_distance(hike_html)
hike_time_of_year = get_hike_time_of_year(hike_html)
trailhead_html = make_soup_from_html(row[3])
trailhead_name = get_trailhead_name(trailhead_html)
trailhead_lat = get_trailhead_lat(trailhead_html)
trailhead_lon = get_trailhead_lon(trailhead_html)
return(
hike_name,
hike_url,
(trailhead_name, trailhead_lat, trailhead_lon),
hike_distance,
hike_time_of_year
)
def scrape():
"""
Scrape OregonHikers starting from a results page
and create a CSV of hike info found that way.
"""
if not os.path.isfile('{}.tsv'.format(HIKES_DB_FILENAME)):
# if a local copy doesn't already exist,
# create it, populate it, and then run the whole program again.
print('Local copy of data does not exist. Downloading...')
add_hikes_to_database()
print('Done adding hike to database!')
with open("{}.tsv".format(HIKES_DB_FILENAME), 'r', newline='') as file:
reader = csv.reader(file, delimiter='\t', quotechar='|', quoting=csv.QUOTE_MINIMAL)
total_hikes = sum(1 for row in reader) - 1
file.seek(0)
data_frame = HikesData()
curr_row = 1
for row in islice(reader, 1, None):
print('Adding hike {} / {}'.format(curr_row, total_hikes))
curr_row += 1
hike_data = get_hike_data(row)
hike_name, url, trailhead_info, distance, time_of_year = hike_data
data_frame.add_hike(hike_name, url, trailhead_info, distance, time_of_year)
data_frame.clean_time_of_year()
sheet = HikesSheet()
for row in data_frame.dataframe.iterrows():
hike_name, url, trailhead_name, \
trailhead_lat, trailhead_lon, distance, time_of_year = row[1]
sheet.add_hike(
hike_name, url, \
trailhead_name, trailhead_lat, trailhead_lon, distance, time_of_year
)
print('Done!')
exit(1)
scrape()