.actor

shopify-products-scraper-actor

Shopify Scraper Actor

.actor/actor.json

images

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

images/apify_readme_proxy.png

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

images/apify_readme_run.png

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

images/apify_readme_url.png

# configurations
.idea

# crawlee and apify storage folders
apify_storage
crawlee_storage
storage

# installed files
node_modules


.dockerignore

# First, specify the base Docker image.
# You can see the Docker images from Apify at https://hub.docker.com/r/apify/.
# You can also use any other image from Docker Hub.
FROM apify/actor-python:3.9

# Second, copy just requirements.txt into the actor image,
# since it should be the only file that affects "pip install" in the next step,
# in order to speed up the build
COPY requirements.txt ./

# Install the packages specified in requirements.txt,
# Print the installed Python version, pip version
# and all installed packages with their versions for debugging
RUN echo "Python version:" \
 && python --version \
 && echo "Pip version:" \
 && pip --version \
 && echo "Installing dependencies from requirements.txt:" \
 && pip install -r requirements.txt \
 && echo "All installed Python packages:" \
 && pip freeze

# Next, copy the remaining files and directories with the source code.
# Since we do this after installing the dependencies, quick build will be really fast
# for most source file changes.
COPY . ./

# Specify how to launch the source code of your actor.
# By default, the main.py file is run
CMD python3 main.py


Dockerfile

Select proxies to be used by your crawler.

Proxy configuration

Url to scrape

Shopify website to scrape

INPUT_SCHEMA.json

apify_readme_proxy.png

import os
from apify_client import ApifyClient
import urllib.parse
import requests
import xmltodict
import re
import json 
import logging
import requests
import time
from concurrent.futures import ThreadPoolExecutor, as_completed
from proxy import Proxy


logging.basicConfig(level=os.environ.get("LOGLEVEL", "INFO"))


THREAD_POOL = 16

session = requests.Session()
session.mount(
    'https://',
    requests.adapters.HTTPAdapter(pool_maxsize=THREAD_POOL,
                                  max_retries=3,
                                  pool_block=True)
)


def get(url, proxies=None):
    if(proxies):
        response = session.get(url, proxies=proxies)
    else:
        response = session.get(url)
    logging.info("request was completed in %s seconds [%s]", response.elapsed.total_seconds(), response.url)
    if response.status_code != 200:
        logging.error("request failed, error code %s [%s]", response.status_code, response.url)
    if 400 <= response.status_code < 600:
        # server is overloaded? give it a break
        time.sleep(15)
    return response



def download(urls):
    with ThreadPoolExecutor(max_workers=THREAD_POOL) as executor:
        # wrap in a list() to wait for all requests to complete
        for response in list(executor.map(get, urls)):
            if response.status_code == 200:
                push_product(response.content)

def push_product(content):
    content = json.loads(content)
    product = content["product"]
    productItem = {
            'min_price': get_min_price(product),
            'max_price': get_max_price(product),
            'avg_price' : get_avg_price_product(product),                
            'title' : product['title'],
            'html' : product['body_html'],
            'vendor' : product['vendor'],
            'handle' : product['handle'],
            'product_type' : product['product_type'],
            'created_at' : product['created_at'],
            'updated_at' : product['updated_at'],
            'published_at' : product['published_at'],
            'template_suffix' : product['template_suffix'],
            'published_scope' : product['published_scope'],
            'tags' : product['tags'],
            'options': get_options(product),
            'variants': [variants for variants in content["product"]["variants"]],
            'images': [images for images in content["product"]["images"]]
        }
            
    default_dataset_client.push_items([productItem])



def get_sitemap_url(url, proxies=None):
    """Infers sitemap URL from given URL."""
    parsed = urllib.parse.urlparse(url)
    if not parsed.scheme:
        raise ValueError(f"Scheme not specified in URL: {url}")
    sitemap_url = [parsed.scheme, parsed.netloc, "sitemap.xml", None, None, None]
    return urllib.parse.urlunparse(sitemap_url)

def get_products_sitemap(url,  proxies=None):
    if proxies:
        res = requests.get(url, proxies=proxies)
    else:
        res = requests.get(url)
    raw = xmltodict.parse(res.text)
    data = []
    for r in raw["sitemapindex"]["sitemap"]:
        if re.search(r"products", str(r)):
                data.append(r["loc"])
    return data

def parse_products_sitemap(urls,  proxies=None):
    products_url = []
    for url in urls:
            if proxies:
                res = requests.get(url, proxies=proxies)
            else:
                res = requests.get(url)
            raw = xmltodict.parse(res.text)
            for r in raw["urlset"]["url"]:
                    if re.search(r"/products/", r["loc"]):
                            products_url.append(r["loc"] + ".json")
    return products_url

def get_avg_price_product(product):
    i = 0
    sum_price = 0
    for variants in product["variants"]:
        i += 1
        sum_price += float(variants["price"])
    return round(sum_price / i, 2)

def get_max_price(product):
    max_price = 0
    for variants in product["variants"]:
        if float(variants["price"]) > max_price:
            max_price = float(variants["price"])
    return max_price

def get_min_price(product):
    min_price = float('inf')
    for variants in product["variants"]:
        if float(variants["price"]) < min_price:
            min_price = float(variants["price"])
    return min_price

def get_options(product):
    optionsArray = []
    for options in product["options"]:
        options.pop('id')
        options.pop('product_id')
        optionsArray.append(options)
    return optionsArray

# Run the main function of the script, if the script is executed directly
if __name__ == '__main__':
    # Initialize the main ApifyClient instance
    client = ApifyClient(os.environ['APIFY_TOKEN'], api_url=os.environ['APIFY_API_BASE_URL'])

    # Get the resource subclient for working with the default key-value store of the actor
    default_kv_store_client = client.key_value_store(os.environ['APIFY_DEFAULT_KEY_VALUE_STORE_ID'])

    # Get the value of the actor input and print it
    print('Loading input')
    actor_input = default_kv_store_client.get_record(os.environ['APIFY_INPUT_KEY'])['value']

    proxies = None
    if "proxy" in actor_input.keys() and os.environ["APIFY_IS_AT_HOME"] and os.environ["APIFY_PROXY_PASSWORD"] and os.environ["APIFY_TOKEN"]:
        proxies = Proxy().get_proxy()
    
    # Structure of input is defined in INPUT_SCHEMA.json
    print(f'Enter url: {actor_input["url"]}')

    sitemap_url = get_sitemap_url(actor_input["url"], proxies=proxies)
    sitemaps_url = get_products_sitemap(sitemap_url, proxies=proxies)
    products_url = parse_products_sitemap(sitemaps_url, proxies=proxies)

    default_dataset_client = client.dataset(os.environ['APIFY_DEFAULT_DATASET_ID'])

    download(products_url)
#    for product in products_url:
#        req = requests.get(product, proxies=proxies)
#        content = json.loads(req.text)
#        product = content["product"]

#        productItem = {
#                'min_price': get_min_price(product),
#                'max_price': get_max_price(product),
#                'avg_price' : get_avg_price_product(product),                
#                'title' : product['title'],
#                'html' : product['body_html'],
#                'vendor' : product['vendor'],
#                'handle' : product['handle'],
#                'product_type' : product['product_type'],
#                'created_at' : product['created_at'],
#                'updated_at' : product['updated_at'],
#                'published_at' : product['published_at'],
#                'template_suffix' : product['template_suffix'],
#                'published_scope' : product['published_scope'],
#                'tags' : product['tags'],
#                'options': get_options(product),
#                'variants': [variants for variants in content["product"]["variants"]],
#                'images': [images for images in content["product"]["images"]]
#            }
#                
#        default_dataset_client.push_items([productItem])

    # Get the resource subclient for working with the default dataset of the actor
    #default_dataset_client = client.dataset(os.environ['APIFY_DEFAULT_DATASET_ID'])

    # Structure of output is defined in .actor/actor.json
    #default_dataset_client.push_items([
    #    {
    #        'first_number': actor_input["first_number"],
    #        'second_number': actor_input["second_number"],
    #        'sum': result
    #    },
    #])


main.py

from typing import TypedDict, List
from dotenv import load_dotenv
from os import environ
import requests

load_dotenv()

class ProxyConfig(TypedDict):
    countryCode: str
    groups: List[str]

proxy_info = {
    'countryCode': 'US',
    'groups': ['SHADER', 'RESIDENTIAL'],
}

token = environ.get('APIFY_TOKEN')

class Proxy():

    def get_proxy():
        return get_proxy_url(proxy_info, token)
    
    def get_proxy_password(self, token: str):
        # attempt to pull the password from env. this will work
        from_env = environ.get('APIFY_PROXY_PASSWORD')
        if from_env:
            return from_env

        # otherwise, get it from the API
        user_data = requests.get(f'https://api.apify.com/v2/users/me?token={token}').json()
        password = user_data['data']['proxy']['password']
        return password

    def get_proxy_url(self, config: ProxyConfig, token: str):
        groups = '' if not 'groups' in config.keys() or not len(config['groups']) else f'''groups-{'+'.join(config['groups'])}'''
        country = '' if not 'countryCode' in config.keys() or not len(config['countryCode']) else f'''country-{config['countryCode']}'''
        username = 'auto' if not len(groups) and not len(country) else ','.join([groups, country])
        password = get_proxy_password(token)
        hostname = environ.get('APIFY_PROXY_HOSTNAME') or 'proxy.apify.com'
        port = environ.get('APIFY_PROXY_PORT') or '8000'

        return f'''http://{username}:{password}@{hostname}:{port}'''

proxy.py

# Add your dependencies here.
# See https://pip.pypa.io/en/latest/cli/pip_install/#requirements-file-format
# for how to format them
xmltodict==0.13.0
urllib3==1.26.5
requests==2.25.1
python-dotenv==0.21.0

requirements.txt

Our shopify website scraper is the perfect tool for anyone looking to get information on shopify websites. Use it to get products from any concurrent including price, images, variants

Shopify Products Scraper

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