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Find competitors near any business location using Google Maps. Enter addresses, Place IDs, or coordinates to discover nearby businesses with ratings, reviews, and rankings. Perfect for market research, site selection, and competitive analysis. Supports bulk locations and custom search terms
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.git.mise.toml.nvim.luastorage
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# pdm# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.#pdm.lock# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it# in version control.# https://pdm.fming.dev/latest/usage/project/#working-with-version-control.pdm.toml.pdm-python.pdm-build/
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# Added by Apify CLInode_modules# 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-playwright:3.13
# Second, copy just requirements.txt into the Actor image,# since it should be the only file that affects the dependency install in the next step,# in order to speed up the buildCOPY requirements.txt ./
# Install the packages specified in requirements.txt,# Print the installed Python version, pip version# and all installed packages with their versions for debuggingRUN echo "Python version:" \ && python --version \ && echo "Pip version:" \ && pip --version \ && echo "Installing dependencies:" \ && pip install -r requirements.txt \ && echo "All installed Python packages:" \ && pip freeze
# Install Playwright and its dependenciesRUN playwright install-deps && \ playwright install
# 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 . ./
# Use compileall to ensure the runnability of the Actor Python code.RUN python3 -m compileall -q src/
# Specify how to launch the source code of your Actor.# By default, the "python3 -m src" command is runCMD ["python3", "-m", "src"]1apify-client2pandas3requests4playwright{ "actorSpecification": 1, "name": "google-maps-competitor-analyzer", "title": "Google Maps Competitor Analyzer", "description": "Find competitors near any business location using Google Maps. Enter addresses, Place IDs, or coordinates to discover nearby businesses with ratings, reviews, and rankings. Perfect for market research, site selection, and competitive analysis. Supports bulk locations and custom search terms.", "version": "1.2", "buildTag": "latest", "meta": { "templateId": "python-playwright" }, "input": "./input_schema.json", "dockerfile": "../Dockerfile"}{ "title": "Google Maps Competitor Analyzer", "description": "Find competitors near any business location using Google Maps. Enter addresses, Place IDs, or coordinates to discover nearby businesses with ratings, reviews, and rankings. Perfect for market research, site selection, and competitive analysis. Supports bulk locations and custom search terms.", "type": "object", "schemaVersion": 1, "properties": { "searchQuery": { "title": "Search Niche/Keyword (e.g., Medical Spas, Mexican Restuarants, Coffee Shops)", "type": "string", "description": "What type of businesses to search for. Be specific for best results.", "default": "medical spa", "editor": "textfield", "prefill": "medical spa" }, "locations": { "title": "Business Locations- Left Side Required (Address, Place ID, or Coordinates), Right Side Optional (Business Name)", "type": "array", "description": "LEFT FIELD (REQUIRED): Enter ONE of the following: 1) Full street address (123 Main St, Beverly Hills, CA 90210), 2) Google Place ID (ChIJ2eUgeAK6j4ARbn5u_wAGqWA), or 3) GPS coordinates without spaces (34.0522,-118.2437). RIGHT FIELD (OPTIONAL): Business name to identify your location in results.", "editor": "keyValue", "prefill": [ { "key": "123 Main St, Beverly Hills, CA 90210", "value": "My Med Spa" }, { "key": "ChIJ2eUgeAK6j4ARbn5u_wAGqWA", "value": "Competitor Spa" }, { "key": "34.0522,-118.2437", "value": "" } ] }, "maxCompetitors": { "title": "Maximum Competitors per Location", "type": "integer", "description": "How many competitors to return per location. Google Maps typically shows 20-30 businesses in an area.", "default": 30, "minimum": 1, "maximum": 30, "editor": "number" }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Use residential proxies to avoid blocks. Recommended for multiple locations.", "editor": "proxy", "prefill": { "useApifyProxy": true } } }, "required": ["searchQuery", "locations"] }# Google Maps Competitor Analyzer
Find and analyze competitors for any business location using Google Maps data. Simply provide an address, Google Place ID, or coordinates, and this actor will discover nearby competing businesses with detailed information.
## 🎯 Use Cases
- **Market Research**: Analyze competition before opening a new location- **Site Selection**: Compare competitor density across multiple potential locations - **Lead Generation**: Find businesses in specific niches for B2B outreach- **Competitive Analysis**: Track ratings and reviews of competitors- **Location Scouting**: Identify market gaps and opportunities
## 📊 What You Get
For each competitor found:- Business name and Google rank- Average rating and review count- Business category- Full address- Google Place ID and CID- Identification if it's your business
## 🔧 Input
### Search QueryEnter the type of businesses to search for:- `medical spa`- `mexican restaurant`- `coffee shop`- `dental office`- etc.
### LocationsEnter locations in any of these formats:
**Full Address:**123 Main St, Beverly Hills, CA 90210
**Google Place ID:**ChIJ2eUgeAK6j4ARbn5u_wAGqWA
**GPS Coordinates:**34.0522,-118.2437
### Business Name (Optional)Add your business name to identify it in the results. The actor will mark it with `is_source_business: true` if found.
## 📤 Output
Results are formatted as one row per competitor, perfect for CSV export:
```json{ "input_location": "123 Main St, Beverly Hills, CA", "input_business_name": "My Med Spa", "search_query": "medical spa", "latitude": 34.0522, "longitude": -118.2437, "competitor_name": "Luxury Spa", "competitor_rank": 1, "competitor_rating": 4.8, "competitor_reviews": 245, "competitor_category": "Medical spa", "competitor_address": "456 Oak St", "is_source_business": false}⚡ Features
Bulk Processing: Analyze multiple locations in one runSmart Detection: Automatically identifies address vs Place ID vs coordinatesCSV Ready: Flattened output structure for easy Excel/CSV exportSource Identification: Marks your business if found in resultsFlexible Search: Customize search terms for any business type
🚀 Example RunInput:
Search: "coffee shops"Locations:
350 5th Ave, New York, NY | StarbucksChIJ2eUgeAK6j4ARbn5u_wAGqWA | 40.7128,-74.0060 | My Coffee Shop
Output:Up to 30 competitors per location with full details⚠️ Limitations
Maximum ~30 competitors per location (Google Maps limitation)Requires stable internet connectionBest results with specific search termsCoordinates must be in decimal format without spaces
💡 Tips
Use specific search terms for better resultsInclude business names to track your locationsTry different search terms to find all competitorsExport to CSV for easy analysis in Excel
🐛 SupportFound an issue or have a suggestion? Please create an issue on the actor page.{ "permissions": { "allow": [ "Bash(grep:*)", "Bash(echo:*)", "Bash(python:*)", "Bash(cp:*)" ], "deny": [] }}1import asyncio2import re3from urllib.parse import quote_plus4from apify import Actor5from playwright.async_api import async_playwright, TimeoutError6
7# ======================================================================8# HELPER FUNCTIONS v1.29# ======================================================================10def is_valid_business_name(name):11 if not name or len(name.strip()) < 1: return False12 if name.strip().startswith('"') and name.strip().endswith('"'): return False13 name_lower = name.strip().lower()14 if len(name_lower) > 80: return False15 # Don't reject single digits - they might be actual business names16 # But reject common UI elements17 if name_lower in ['x', '+', '-', '·', '|', '/', '\\', '^', '*']: return False18 if name_lower.startswith(('·', '$', '#', '@', 'http', 'sponsored')): return False19 # Skip if it looks like an address (starts with number and has street suffix)20 if re.match(r'^\d+\s+\w+\s+(st|street|ave|rd|dr|blvd)', name_lower, re.IGNORECASE): return False21 skip_patterns = ['google maps', 'search results', 'filter by', 'sort by', 'reviews', 'directions', 'open now', 'closed']22 if any(pattern in name_lower for pattern in skip_patterns): return False23 return True24
25def clean_business_name(name):26 if not name: return ""27 cleaned = name.strip().rstrip('&|\\').strip()28 cleanup_patterns = [29 r'\s*·.*$', r'^\s*\d+\.\s*', r'\s*\(\d+\)\s*$', r'\s*\d+\s*reviews?$',30 r'\s*\$+.*$', r'\s*Open\s*(24\s*hours?|now).*$', r'\s*Closed.*$', r'\s*Medical spa.*$'31 ]32 for pattern in cleanup_patterns:33 cleaned = re.sub(pattern, '', cleaned, flags=re.IGNORECASE)34 return cleaned.strip()35
36def extract_rating(lines):37 for line in lines:38 match = re.search(r'\b(\d\.\d)\b', line)39 if match:40 try: return float(match.group(1))41 except: continue42 return None43
44def extract_review_count(lines):45 for line in lines:46 match = re.search(r'\((\d{1,5})\)', line)47 if match:48 try: return int(match.group(1))49 except: continue50 return None51
52def extract_address(lines):53 # Try multiple patterns to find address54 address_parts = []55 found_address_start = False56 57 for i, line in enumerate(lines):58 # Skip very short lines (likely not addresses)59 if len(line) < 5:60 continue61 62 # Skip common non-address elements63 if line.lower() in ['ad', 'ads', 'sponsored', 'open', 'closed', 'open now', 'temporarily closed']:64 continue65 66 # Check if this line contains rating or review count (not part of address)67 if re.match(r'^[\d.]+$', line) or re.match(r'^\(\d+\)$', line):68 continue69 70 # Look for common address patterns71 has_street_pattern = re.search(r'\d+.*?(?:st|street|ave|avenue|rd|road|dr|drive|blvd|boulevard|way|lane|ln|pkwy|parkway|ct|court|pl|place|suite|ste|unit|apt|#)', line, re.IGNORECASE)72 has_state_zip = re.search(r'\b[A-Z]{2}\s+\d{5}\b', line)73 has_po_box = re.search(r'(p\.?o\.?\s*box|pmb)\s*\d+', line, re.IGNORECASE)74 75 if has_street_pattern or has_state_zip or has_po_box:76 # Found start of address77 found_address_start = True78 # Clean up the line79 cleaned_line = line.split('·')[-1].strip()80 # Remove common prefixes81 cleaned_line = re.sub(r'^(Open|Closed|Hours|Directions).*?·\s*', '', cleaned_line, flags=re.IGNORECASE)82 address_parts.append(cleaned_line)83 elif found_address_start and i < len(lines) - 1:84 # This might be a continuation of the address (like city, state, zip on next line)85 # Check if it's not a category or other non-address info86 if not re.search(r'(medical spa|wellness center|aesthetic|dermatology|clinic|reviews?|rating|open|closed|hours|directions|website|call)', line, re.IGNORECASE):87 # Check if it might be city/state/zip88 if re.search(r'\b[A-Z]{2}\b', line) or re.search(r'\b\d{5}\b', line) or len(line) < 50:89 address_parts.append(line.strip())90 else:91 # Probably not part of address anymore92 break93 94 # Join address parts95 if address_parts:96 # Join with comma if parts don't already have commas97 full_address = address_parts[0]98 for part in address_parts[1:]:99 if not full_address.endswith(',') and not part.startswith(','):100 full_address += ', ' + part101 else:102 full_address += ' ' + part103 return full_address.strip()104 105 return ""106
107def determine_category(lines):108 text = ' '.join(lines).lower()109 if 'dermatology' in text: return "Dermatology clinic"110 if any(x in text for x in ['wellness', 'wellness center']): return "Wellness center"111 if any(x in text for x in ['aesthetic', 'aesthetics']): return "Aesthetic clinic"112 return "Medical spa"113
114def extract_place_ids(html_content: str) -> dict:115 ids = {'place_id': None, 'cid': None}116 place_id_match = re.search(r'(ChIJ[A-Za-z0-9_-]+)', html_content)117 if place_id_match:118 ids['place_id'] = place_id_match.group(1)119 cid_match = re.search(r'(0x[a-f0-9:]+)', html_content)120 if cid_match:121 ids['cid'] = cid_match.group(1)122 return ids123
124def parse_address_components(address):125 """Extract city, state, and zipcode from address string"""126 if not address:127 return {'city': '', 'state': '', 'zipcode': ''}128 129 components = {'city': '', 'state': '', 'zipcode': ''}130 original_address = address131 132 # Common Virginia cities for this data133 known_va_cities = ['Ashburn', 'Sterling', 'Leesburg', 'Herndon', 'Reston', 'Chantilly', 'Fairfax']134 135 # First, try to extract ZIP code (5 digits, optionally followed by -4 digits)136 # Look for standalone 5-digit numbers that aren't at the beginning of the address137 zip_match = re.search(r'\b(?<!\d)(\d{5})(?:-\d{4})?\b(?!\s*[A-Za-z]+\s+(?:St|Street|Ave|Avenue|Rd|Road|Dr|Drive|Blvd|Boulevard|Way|Lane|Ln|Pkwy|Parkway|Ct|Court|Pl|Place))', address)138 if zip_match:139 # Check if this 5-digit number is actually a street number by looking at what follows140 after_match = address[zip_match.end():].strip()141 # If it's followed by a street name, it's not a zip142 if not re.match(r'^[A-Za-z]+\s+(?:St|Street|Ave|Avenue|Rd|Road|Dr|Drive|Blvd|Boulevard|Way|Lane|Ln|Pkwy|Parkway|Ct|Court|Pl|Place)', after_match, re.IGNORECASE):143 components['zipcode'] = zip_match.group(1)144 address = address.replace(zip_match.group(0), '').strip().rstrip(',')145 146 # Try to extract state (2 letter abbreviation)147 state_pattern = r'\b(AL|AK|AZ|AR|CA|CO|CT|DE|FL|GA|HI|ID|IL|IN|IA|KS|KY|LA|ME|MD|MA|MI|MN|MS|MO|MT|NE|NV|NH|NJ|NM|NY|NC|ND|OH|OK|OR|PA|RI|SC|SD|TN|TX|UT|VT|VA|WA|WV|WI|WY|DC)\b'148 149 # Look for state abbreviation, preferring ones near the end150 state_matches = list(re.finditer(state_pattern, address, re.IGNORECASE))151 if state_matches:152 # Use the last state match (most likely to be the actual state)153 state_match = state_matches[-1]154 components['state'] = state_match.group(1).upper()155 # Remove state and clean up156 address = address[:state_match.start()] + address[state_match.end():]157 address = address.strip().rstrip(',').strip()158 159 # For Ashburn area addresses, if no state found but we have Ashburn, assume VA160 if not components['state'] and any(city in original_address for city in known_va_cities):161 components['state'] = 'VA'162 163 # Extract city - look for known cities first164 for known_city in known_va_cities:165 if known_city.lower() in original_address.lower():166 components['city'] = known_city167 break168 169 # If no known city found, try to extract from address structure170 if not components['city']:171 # Remove street address parts to find city172 # Split by comma and analyze parts173 parts = address.split(',')174 for part in reversed(parts): # Start from the end175 part = part.strip()176 177 # Skip if it's a street address (starts with number)178 if re.match(r'^\d+\s+', part):179 continue180 181 # Skip if it contains suite/unit/building info182 if re.search(r'\b(suite|ste|unit|apt|building|bldg|floor|fl|#)\s*[\w\d-]*\b', part, re.IGNORECASE):183 continue184 185 # Skip if it ends with street type186 if re.search(r'\b(st|street|ave|avenue|rd|road|dr|drive|blvd|boulevard|way|lane|ln|pkwy|parkway|ct|court|pl|place|plaza|plz|cir|circle|ter|terrace|commons|cmns)\s*(?:#?\d+)?$', part, re.IGNORECASE):187 continue188 189 # This might be the city190 if part and not re.match(r'^\d', part):191 components['city'] = part192 break193 194 # Special handling for specific cases195 if components['state'] == 'FL' and not components['city']:196 if 'jacksonville' in original_address.lower():197 components['city'] = 'Jacksonville'198 199 if components['state'] == 'CA' and not components['city']:200 ca_cities = ['Los Angeles', 'Santa Monica', 'Beverly Hills', 'Pasadena', 'Whittier', 201 'Encino', 'Burbank', 'Glendale', 'Hollywood', 'Sherman Oaks']202 for city in ca_cities:203 if city.lower() in original_address.lower():204 components['city'] = city205 break206 207 return components208
209def parse_location_type(location_str):210 """Determine if the location is an address, Place ID, or coordinates"""211 location_str = location_str.strip()212 213 # Check if it's a Place ID (starts with ChIJ)214 if location_str.startswith('ChIJ'):215 return 'place_id', location_str216 217 # Check if it's coordinates (format: lat,lng) - now more forgiving218 # Remove spaces around comma for better matching219 normalized = location_str.replace(' ', '')220 coord_pattern = r'^-?\d+\.?\d*,-?\d+\.?\d*$'221 if re.match(coord_pattern, normalized):222 parts = normalized.split(',')223 try:224 lat = float(parts[0])225 lng = float(parts[1])226 return 'coordinates', (lat, lng)227 except:228 pass229 230 # Otherwise, treat as address231 return 'address', location_str232
233# ======================================================================234# ACTOR SCRAPING LOGIC235# ======================================================================236async def geocode_with_address(page, address: str) -> dict:237 Actor.log.info(f"Geocoding address: {address}...")238 query = quote_plus(address)239 maps_url = f"https://www.google.com/maps/search/{query}"240 await page.goto(maps_url, wait_until='load', timeout=25000)241 await asyncio.sleep(5)242 coord_match = re.search(r'@(-?\d+\.\d+),(-?\d+\.\d+)', page.url)243 if not coord_match:244 return {'found': False, 'error': 'Could not find coordinates from address'}245 lat, lng = float(coord_match.group(1)), float(coord_match.group(2))246 html_content = await page.content()247 ids = extract_place_ids(html_content)248 return {'found': True, 'latitude': lat, 'longitude': lng, **ids}249
250async def geocode_with_place_id(page, place_id: str) -> dict:251 Actor.log.info(f"Geocoding Place ID: {place_id}...")252 maps_url = f"https://www.google.com/maps/search/?api=1&query=some_text&query_place_id={place_id}"253 await page.goto(maps_url, wait_until='load', timeout=25000)254 await asyncio.sleep(5)255 coord_match = re.search(r'@(-?\d+\.\d+),(-?\d+\.\d+)', page.url)256 if not coord_match: return {'found': False, 'error': 'Could not find coordinates from Place ID'}257 lat, lng = float(coord_match.group(1)), float(coord_match.group(2))258 html_content = await page.content()259 ids = extract_place_ids(html_content)260 return {'found': True, 'latitude': lat, 'longitude': lng, 'place_id': place_id, **ids}261
262async def scrape_competitors_at_coordinates(page, source_company_name: str, lat: float, lon: float, 263 search_query: str, max_competitors: int):264 Actor.log.info(f"Scraping competitors at {lat},{lon} for '{search_query}'...")265 query = quote_plus(search_query)266 zoom_level = 11 # Wider area view to show more businesses267 url = f"https://www.google.com/maps/search/{query}/@{lat},{lon},{zoom_level}z"268 Actor.log.info(f"Using zoom level {zoom_level} for wider area coverage")269 await page.goto(url, wait_until='domcontentloaded', timeout=45000)270 271 # Always use 25% zoom for maximum results272 await page.evaluate('document.body.style.zoom="0.25"')273 await asyncio.sleep(3)274 275 selectors = ['[role="article"]', '.Nv2PK.THOPZb.CpccDe', '.lI9IFe', '.hfpxzc']276 elems = []277 for sel in selectors:278 elems = await page.query_selector_all(sel)279 if elems and len(elems) > 5: 280 Actor.log.info(f"Found {len(elems)} elements using selector: {sel}")281 break282 283 competitors = []284 cleaned_source_name = re.sub(r'[^a-z0-9]', '', source_company_name.lower()) if source_company_name else ""285 286 for element in elems[:max_competitors]:287 element_html = await element.inner_html()288 ids = extract_place_ids(element_html)289 full_text = await element.inner_text()290 lines = [ln.strip() for ln in full_text.split('\n') if ln.strip()]291 292 # Look for the actual business name, skipping numbers and UI elements293 business_name = None294 for i, line in enumerate(lines):295 # Skip single digits (likely list numbers)296 if line.strip().isdigit() and len(line.strip()) <= 2:297 continue298 # Skip common UI elements299 if line.lower() in ['ad', 'ads', 'sponsored', 'open', 'closed', 'open now']:300 continue301 # Try to validate and clean the line as a business name302 if is_valid_business_name(line):303 business_name = clean_business_name(line)304 if business_name: # Make sure cleaning didn't result in empty string305 break306 307 if not business_name or any(c['business_name'] == business_name for c in competitors): 308 continue309 310 is_source = False311 if cleaned_source_name:312 cleaned_competitor_name = re.sub(r'[^a-z0-9]', '', business_name.lower())313 is_source = cleaned_source_name in cleaned_competitor_name or cleaned_competitor_name in cleaned_source_name314 315 # Extract address and parse components316 address = extract_address(lines)317 address_components = parse_address_components(address)318 319 competitor = {320 'place_id': ids.get('place_id'),321 'business_name': business_name,322 'google_rank': len(competitors) + 1,323 'is_source_business': is_source,324 'average_rating': extract_rating(lines),325 'number_of_reviews': extract_review_count(lines),326 'main_category': determine_category(lines),327 'address': address,328 'city': address_components['city'],329 'state': address_components['state'],330 'zipcode': address_components['zipcode']331 }332 competitors.append(competitor)333 334 return competitors335
336# ======================================================================337# MAIN ACTOR FUNCTION338# ======================================================================339async def main() -> None:340 async with Actor:341 actor_input = await Actor.get_input() or {}342 343 # Parse input from new schema344 locations_data = actor_input.get('locations', [])345 search_query = actor_input.get('searchQuery', 'medical spa')346 max_competitors = actor_input.get('maxCompetitors', 30)347 proxy_configuration = actor_input.get('proxyConfiguration')348 349 # Log input for debugging350 Actor.log.info(f"Received input: {len(locations_data)} locations")351 Actor.log.info(f"Search query: {search_query}")352 Actor.log.info(f"Max competitors per location: {max_competitors}")353 354 # Convert key-value pairs to locations and business names355 locations = []356 business_names = []357 for item in locations_data:358 if isinstance(item, dict):359 locations.append(item.get('key', ''))360 business_names.append(item.get('value', ''))361 else:362 # Fallback for string input363 locations.append(str(item))364 business_names.append('')365 366 if not locations:367 Actor.log.error("No locations provided. Please add at least one location.")368 await Actor.push_data({369 'error': 'No locations provided',370 'message': 'Please provide at least one location (address, Place ID, or coordinates)'371 })372 return373 374 Actor.log.info(f"Processing {len(locations)} locations...")375 Actor.log.info(f"Search query: '{search_query}'")376 Actor.log.info(f"Max competitors: {max_competitors}")377 378 # Track total results pushed379 total_results = 0380 381 # Launch browser382 async with async_playwright() as p:383 # Handle proxy if configured384 browser_options = {"headless": True}385 386 if proxy_configuration and proxy_configuration.get('useApifyProxy'):387 try:388 # For Apify proxy, you might need to check the correct method389 # This is a placeholder - check Apify docs for your SDK version390 Actor.log.info("Proxy requested but implementation needs to be verified for your Apify SDK version")391 except Exception as e:392 Actor.log.warning(f"Could not set up proxy: {e}")393 394 Actor.log.info("Launching browser...")395 browser = await p.chromium.launch(**browser_options)396 page = await browser.new_page()397
398 # Process each location399 for idx, location_str in enumerate(locations):400 # Get business name from the paired value401 business_name = business_names[idx] if idx < len(business_names) else None402 403 # Skip empty locations404 if not location_str or not location_str.strip():405 continue406 407 # Parse location type408 location_type, location_data = parse_location_type(location_str)409 410 Actor.log.info(f"\nProcessing location {idx + 1}/{len(locations)}: {location_str}")411 if business_name:412 Actor.log.info(f"Business name: {business_name}")413 414 geo = {'found': False}415 416 try:417 if location_type == 'coordinates':418 lat, lng = location_data419 Actor.log.info(f"Using provided coordinates: {lat}, {lng}")420 geo = {'found': True, 'latitude': lat, 'longitude': lng}421 elif location_type == 'place_id':422 geo = await geocode_with_place_id(page, location_data)423 else: # address424 geo = await geocode_with_address(page, location_data)425 except Exception as e:426 Actor.log.exception(f"Geocoding failed: {e}")427 geo = {'found': False, 'error': str(e)}428 429 # Scrape competitors if geocoding succeeded430 competitors_list = []431 if geo.get('found'):432 try:433 competitors_list = await scrape_competitors_at_coordinates(434 page, 435 business_name, 436 geo['latitude'], 437 geo['longitude'],438 search_query,439 max_competitors440 )441 Actor.log.info(f"Found {len(competitors_list)} competitors for {business_name or location_str}")442 except Exception as e:443 Actor.log.exception(f"Competitor scraping failed: {e}")444 else:445 Actor.log.warning(f"Skipping competitor search - geocoding failed: {geo.get('error', 'Unknown error')}")446 447 # Push results - FLATTENED for CSV448 if competitors_list:449 # One row per competitor450 for competitor in competitors_list:451 result = {452 # Competitor details in requested order453 'competitor_name': competitor['business_name'],454 'competitor_address': competitor['address'] or '',455 'competitor_city': competitor['city'] or '',456 'competitor_state': competitor['state'] or '',457 'competitor_zipcode': competitor['zipcode'] or '',458 'competitor_category': competitor['main_category'],459 'competitor_rank': competitor['google_rank'],460 'competitor_rating': competitor['average_rating'],461 'competitor_reviews': competitor['number_of_reviews'],462 'competitor_place_id': competitor['place_id'] or '',463 'latitude': geo.get('latitude'),464 'longitude': geo.get('longitude'),465 'search_query': search_query,466 # Source business info at the end467 'is_source_business': competitor['is_source_business'],468 'input_location': location_str,469 'input_business_name': business_name or ''470 }471 await Actor.push_data(result)472 total_results += 1473 else:474 # No competitors found - still push location info475 result = {476 # Empty competitor details in requested order477 'competitor_name': '',478 'competitor_address': '',479 'competitor_city': '',480 'competitor_state': '',481 'competitor_zipcode': '',482 'competitor_category': '',483 'competitor_rank': None,484 'competitor_rating': None,485 'competitor_reviews': None,486 'competitor_place_id': '',487 'latitude': geo.get('latitude'),488 'longitude': geo.get('longitude'),489 'search_query': search_query,490 # Source business info at the end491 'is_source_business': None,492 'input_location': location_str,493 'input_business_name': business_name or ''494 }495 await Actor.push_data(result)496 total_results += 1497 498 await browser.close()499 Actor.log.info(f"\nScraping completed! Processed {len(locations)} locations and found {total_results} total results.")500
501# Entry point502if __name__ == "__main__":503 asyncio.run(main())1import asyncio2import re3from urllib.parse import quote_plus4from apify import Actor5from playwright.async_api import async_playwright, TimeoutError6
7# ======================================================================8# HELPER FUNCTIONS v1.19# ======================================================================10def is_valid_business_name(name):11 if not name or len(name.strip()) < 1: return False12 if name.strip().startswith('"') and name.strip().endswith('"'): return False13 name_lower = name.strip().lower()14 if len(name_lower) > 80: return False15 # Don't reject single digits - they might be actual business names16 # But reject common UI elements17 if name_lower in ['x', '+', '-', '·', '|', '/', '\\', '^', '*']: return False18 if name_lower.startswith(('·', '$', '#', '@', 'http', 'sponsored')): return False19 # Skip if it looks like an address (starts with number and has street suffix)20 if re.match(r'^\d+\s+\w+\s+(st|street|ave|rd|dr|blvd)', name_lower, re.IGNORECASE): return False21 skip_patterns = ['google maps', 'search results', 'filter by', 'sort by', 'reviews', 'directions', 'open now', 'closed']22 if any(pattern in name_lower for pattern in skip_patterns): return False23 return True24
25def clean_business_name(name):26 if not name: return ""27 cleaned = name.strip().rstrip('&|\\').strip()28 cleanup_patterns = [29 r'\s*·.*$', r'^\s*\d+\.\s*', r'\s*\(\d+\)\s*$', r'\s*\d+\s*reviews?$',30 r'\s*\$+.*$', r'\s*Open\s*(24\s*hours?|now).*$', r'\s*Closed.*$', r'\s*Medical spa.*$'31 ]32 for pattern in cleanup_patterns:33 cleaned = re.sub(pattern, '', cleaned, flags=re.IGNORECASE)34 return cleaned.strip()35
36def extract_rating(lines):37 for line in lines:38 match = re.search(r'\b(\d\.\d)\b', line)39 if match:40 try: return float(match.group(1))41 except: continue42 return None43
44def extract_review_count(lines):45 for line in lines:46 match = re.search(r'\((\d{1,5})\)', line)47 if match:48 try: return int(match.group(1))49 except: continue50 return None51
52def extract_address(lines):53 # Try multiple patterns to find address54 address_parts = []55 found_address_start = False56 57 for i, line in enumerate(lines):58 # Skip very short lines (likely not addresses)59 if len(line) < 5:60 continue61 62 # Skip common non-address elements63 if line.lower() in ['ad', 'ads', 'sponsored', 'open', 'closed', 'open now', 'temporarily closed']:64 continue65 66 # Check if this line contains rating or review count (not part of address)67 if re.match(r'^[\d.]+$', line) or re.match(r'^\(\d+\)$', line):68 continue69 70 # Look for common address patterns71 has_street_pattern = re.search(r'\d+.*?(?:st|street|ave|avenue|rd|road|dr|drive|blvd|boulevard|way|lane|ln|pkwy|parkway|ct|court|pl|place|suite|ste|unit|apt|#)', line, re.IGNORECASE)72 has_state_zip = re.search(r'\b[A-Z]{2}\s+\d{5}\b', line)73 has_po_box = re.search(r'(p\.?o\.?\s*box|pmb)\s*\d+', line, re.IGNORECASE)74 75 if has_street_pattern or has_state_zip or has_po_box:76 # Found start of address77 found_address_start = True78 # Clean up the line79 cleaned_line = line.split('·')[-1].strip()80 # Remove common prefixes81 cleaned_line = re.sub(r'^(Open|Closed|Hours|Directions).*?·\s*', '', cleaned_line, flags=re.IGNORECASE)82 address_parts.append(cleaned_line)83 elif found_address_start and i < len(lines) - 1:84 # This might be a continuation of the address (like city, state, zip on next line)85 # Check if it's not a category or other non-address info86 if not re.search(r'(medical spa|wellness center|aesthetic|dermatology|clinic|reviews?|rating|open|closed|hours|directions|website|call)', line, re.IGNORECASE):87 # Check if it might be city/state/zip88 if re.search(r'\b[A-Z]{2}\b', line) or re.search(r'\b\d{5}\b', line) or len(line) < 50:89 address_parts.append(line.strip())90 else:91 # Probably not part of address anymore92 break93 94 # Join address parts95 if address_parts:96 # Join with comma if parts don't already have commas97 full_address = address_parts[0]98 for part in address_parts[1:]:99 if not full_address.endswith(',') and not part.startswith(','):100 full_address += ', ' + part101 else:102 full_address += ' ' + part103 return full_address.strip()104 105 return ""106
107def determine_category(lines):108 text = ' '.join(lines).lower()109 if 'dermatology' in text: return "Dermatology clinic"110 if any(x in text for x in ['wellness', 'wellness center']): return "Wellness center"111 if any(x in text for x in ['aesthetic', 'aesthetics']): return "Aesthetic clinic"112 return "Medical spa"113
114def extract_place_ids(html_content: str) -> dict:115 ids = {'place_id': None, 'cid': None}116 place_id_match = re.search(r'(ChIJ[A-Za-z0-9_-]+)', html_content)117 if place_id_match:118 ids['place_id'] = place_id_match.group(1)119 cid_match = re.search(r'(0x[a-f0-9:]+)', html_content)120 if cid_match:121 ids['cid'] = cid_match.group(1)122 return ids123
124def parse_address_components(address):125 """Extract city, state, and zipcode from address string"""126 if not address:127 return {'city': '', 'state': '', 'zipcode': ''}128 129 components = {'city': '', 'state': '', 'zipcode': ''}130 original_address = address131 132 # First, try to extract ZIP code (5 digits, optionally followed by -4 digits)133 # But make sure it's not at the beginning (like a street number)134 zip_patterns = [135 r',\s*(\d{5}(?:-\d{4})?)\s*$', # ZIP at end after comma136 r'\s+(\d{5}(?:-\d{4})?)\s*$', # ZIP at end after space137 r'\b(?<!^\d)(\d{5}(?:-\d{4})?)\b(?!.*\d{5})' # Last 5-digit number that's not at start138 ]139 140 for pattern in zip_patterns:141 zip_match = re.search(pattern, address)142 if zip_match:143 components['zipcode'] = zip_match.group(1)144 address = address.replace(zip_match.group(0), '').strip().rstrip(',')145 break146 147 # Try to extract state (2 letter abbreviation)148 state_pattern = r'\b(AL|AK|AZ|AR|CA|CO|CT|DE|FL|GA|HI|ID|IL|IN|IA|KS|KY|LA|ME|MD|MA|MI|MN|MS|MO|MT|NE|NV|NH|NJ|NM|NY|NC|ND|OH|OK|OR|PA|RI|SC|SD|TN|TX|UT|VT|VA|WA|WV|WI|WY|DC)\b'149 150 # Look for state abbreviation, preferring ones near the end151 state_matches = list(re.finditer(state_pattern, address, re.IGNORECASE))152 if state_matches:153 # Use the last state match (most likely to be the actual state)154 state_match = state_matches[-1]155 components['state'] = state_match.group(1).upper()156 # Remove state and clean up157 address = address[:state_match.start()] + address[state_match.end():]158 address = address.strip().rstrip(',').strip()159 160 # Special handling for addresses that start with business name or complex location161 # e.g., "Stone Springs MedSpa by LMG, Physicians Office Building, 24430 Stone Springs Blvd Suite 100A"162 parts = address.split(',')163 164 # Remove parts that are clearly not city names165 filtered_parts = []166 for part in parts:167 part = part.strip()168 # Skip empty parts169 if not part:170 continue171 172 # Skip parts that are clearly street addresses173 if re.match(r'^\d+\s+\w+', part):174 continue175 176 # Skip suite/unit/building descriptions177 if re.search(r'\b(suite|ste|unit|apt|building|bldg|floor|fl|#)\s*[\w\d-]*\b', part, re.IGNORECASE):178 continue179 180 # Skip parts that end with street types (these are street names, not cities)181 if re.search(r'\b(st|street|ave|avenue|rd|road|dr|drive|blvd|boulevard|way|lane|ln|pkwy|parkway|ct|court|pl|place|plaza|plz|cir|circle|ter|terrace|commons|cmns)\s*(?:#?\d+)?$', part, re.IGNORECASE):182 continue183 184 filtered_parts.append(part)185 186 # Try to identify the city187 if filtered_parts:188 # The last filtered part is most likely the city189 city_candidate = filtered_parts[-1]190 191 # Clean up the city name192 # Remove any remaining suite/unit info193 city_candidate = re.sub(r'\b(suite|ste|unit|apt|#)\s*[\w\d-]+$', '', city_candidate, flags=re.IGNORECASE)194 # Remove any trailing business/building identifiers195 city_candidate = re.sub(r'\s*(building|bldg|center|ctr|office|tower|plaza|mall|complex)$', '', city_candidate, flags=re.IGNORECASE)196 city_candidate = city_candidate.strip()197 198 # Common city names in the data that we should recognize199 known_cities = ['Ashburn', 'Jacksonville', 'Santa Monica', 'Los Angeles', 'Whittier', 200 'Beverly Hills', 'Pasadena', 'Encino', 'Burbank', 'Glendale', 'Montebello',201 'Hollywood', 'Lawndale', 'Sherman Oaks', 'Sterling', 'Leesburg']202 203 # Check if any known city is in the candidate204 for known_city in known_cities:205 if known_city.lower() in city_candidate.lower():206 components['city'] = known_city207 break208 209 # If no known city found, use the candidate if it looks reasonable210 if not components['city'] and city_candidate and not re.match(r'^\d', city_candidate):211 components['city'] = city_candidate212 213 # Special case: if we have FL state but no city, and "Jacksonville" might be in original address214 if components['state'] == 'FL' and not components['city']:215 if 'jacksonville' in original_address.lower():216 components['city'] = 'Jacksonville'217 218 # Special case: if we have VA state and Ashburn-related text219 if components['state'] == 'VA' and not components['city']:220 if 'ashburn' in original_address.lower():221 components['city'] = 'Ashburn'222 223 return components224
225def parse_location_type(location_str):226 """Determine if the location is an address, Place ID, or coordinates"""227 location_str = location_str.strip()228 229 # Check if it's a Place ID (starts with ChIJ)230 if location_str.startswith('ChIJ'):231 return 'place_id', location_str232 233 # Check if it's coordinates (format: lat,lng) - now more forgiving234 # Remove spaces around comma for better matching235 normalized = location_str.replace(' ', '')236 coord_pattern = r'^-?\d+\.?\d*,-?\d+\.?\d*$'237 if re.match(coord_pattern, normalized):238 parts = normalized.split(',')239 try:240 lat = float(parts[0])241 lng = float(parts[1])242 return 'coordinates', (lat, lng)243 except:244 pass245 246 # Otherwise, treat as address247 return 'address', location_str248
249# ======================================================================250# ACTOR SCRAPING LOGIC251# ======================================================================252async def geocode_with_address(page, address: str) -> dict:253 Actor.log.info(f"Geocoding address: {address}...")254 query = quote_plus(address)255 maps_url = f"https://www.google.com/maps/search/{query}"256 await page.goto(maps_url, wait_until='load', timeout=25000)257 await asyncio.sleep(5)258 coord_match = re.search(r'@(-?\d+\.\d+),(-?\d+\.\d+)', page.url)259 if not coord_match:260 return {'found': False, 'error': 'Could not find coordinates from address'}261 lat, lng = float(coord_match.group(1)), float(coord_match.group(2))262 html_content = await page.content()263 ids = extract_place_ids(html_content)264 return {'found': True, 'latitude': lat, 'longitude': lng, **ids}265
266async def geocode_with_place_id(page, place_id: str) -> dict:267 Actor.log.info(f"Geocoding Place ID: {place_id}...")268 maps_url = f"https://www.google.com/maps/search/?api=1&query=some_text&query_place_id={place_id}"269 await page.goto(maps_url, wait_until='load', timeout=25000)270 await asyncio.sleep(5)271 coord_match = re.search(r'@(-?\d+\.\d+),(-?\d+\.\d+)', page.url)272 if not coord_match: return {'found': False, 'error': 'Could not find coordinates from Place ID'}273 lat, lng = float(coord_match.group(1)), float(coord_match.group(2))274 html_content = await page.content()275 ids = extract_place_ids(html_content)276 return {'found': True, 'latitude': lat, 'longitude': lng, 'place_id': place_id, **ids}277
278async def scrape_competitors_at_coordinates(page, source_company_name: str, lat: float, lon: float, 279 search_query: str, max_competitors: int):280 Actor.log.info(f"Scraping competitors at {lat},{lon} for '{search_query}'...")281 query = quote_plus(search_query)282 zoom_level = 11 # Wider area view to show more businesses283 url = f"https://www.google.com/maps/search/{query}/@{lat},{lon},{zoom_level}z"284 Actor.log.info(f"Using zoom level {zoom_level} for wider area coverage")285 await page.goto(url, wait_until='domcontentloaded', timeout=45000)286 287 # Always use 25% zoom for maximum results288 await page.evaluate('document.body.style.zoom="0.25"')289 await asyncio.sleep(3)290 291 selectors = ['[role="article"]', '.Nv2PK.THOPZb.CpccDe', '.lI9IFe', '.hfpxzc']292 elems = []293 for sel in selectors:294 elems = await page.query_selector_all(sel)295 if elems and len(elems) > 5: 296 Actor.log.info(f"Found {len(elems)} elements using selector: {sel}")297 break298 299 competitors = []300 cleaned_source_name = re.sub(r'[^a-z0-9]', '', source_company_name.lower()) if source_company_name else ""301 302 for element in elems[:max_competitors]:303 element_html = await element.inner_html()304 ids = extract_place_ids(element_html)305 full_text = await element.inner_text()306 lines = [ln.strip() for ln in full_text.split('\n') if ln.strip()]307 308 # Look for the actual business name, skipping numbers and UI elements309 business_name = None310 for i, line in enumerate(lines):311 # Skip single digits (likely list numbers)312 if line.strip().isdigit() and len(line.strip()) <= 2:313 continue314 # Skip common UI elements315 if line.lower() in ['ad', 'ads', 'sponsored', 'open', 'closed', 'open now']:316 continue317 # Try to validate and clean the line as a business name318 if is_valid_business_name(line):319 business_name = clean_business_name(line)320 if business_name: # Make sure cleaning didn't result in empty string321 break322 323 if not business_name or any(c['business_name'] == business_name for c in competitors): 324 continue325 326 is_source = False327 if cleaned_source_name:328 cleaned_competitor_name = re.sub(r'[^a-z0-9]', '', business_name.lower())329 is_source = cleaned_source_name in cleaned_competitor_name or cleaned_competitor_name in cleaned_source_name330 331 # Extract address and parse components332 address = extract_address(lines)333 address_components = parse_address_components(address)334 335 competitor = {336 'place_id': ids.get('place_id'),337 'business_name': business_name,338 'google_rank': len(competitors) + 1,339 'is_source_business': is_source,340 'average_rating': extract_rating(lines),341 'number_of_reviews': extract_review_count(lines),342 'main_category': determine_category(lines),343 'address': address,344 'city': address_components['city'],345 'state': address_components['state'],346 'zipcode': address_components['zipcode']347 }348 competitors.append(competitor)349 350 return competitors351
352# ======================================================================353# MAIN ACTOR FUNCTION354# ======================================================================355async def main() -> None:356 async with Actor:357 actor_input = await Actor.get_input() or {}358 359 # Parse input from new schema360 locations_data = actor_input.get('locations', [])361 search_query = actor_input.get('searchQuery', 'medical spa')362 max_competitors = actor_input.get('maxCompetitors', 30)363 proxy_configuration = actor_input.get('proxyConfiguration')364 365 # Log input for debugging366 Actor.log.info(f"Received input: {len(locations_data)} locations")367 Actor.log.info(f"Search query: {search_query}")368 Actor.log.info(f"Max competitors per location: {max_competitors}")369 370 # Convert key-value pairs to locations and business names371 locations = []372 business_names = []373 for item in locations_data:374 if isinstance(item, dict):375 locations.append(item.get('key', ''))376 business_names.append(item.get('value', ''))377 else:378 # Fallback for string input379 locations.append(str(item))380 business_names.append('')381 382 if not locations:383 Actor.log.error("No locations provided. Please add at least one location.")384 await Actor.push_data({385 'error': 'No locations provided',386 'message': 'Please provide at least one location (address, Place ID, or coordinates)'387 })388 return389 390 Actor.log.info(f"Processing {len(locations)} locations...")391 Actor.log.info(f"Search query: '{search_query}'")392 Actor.log.info(f"Max competitors: {max_competitors}")393 394 # Track total results pushed395 total_results = 0396 397 # Launch browser398 async with async_playwright() as p:399 # Handle proxy if configured400 browser_options = {"headless": True}401 402 if proxy_configuration and proxy_configuration.get('useApifyProxy'):403 try:404 # For Apify proxy, you might need to check the correct method405 # This is a placeholder - check Apify docs for your SDK version406 Actor.log.info("Proxy requested but implementation needs to be verified for your Apify SDK version")407 except Exception as e:408 Actor.log.warning(f"Could not set up proxy: {e}")409 410 Actor.log.info("Launching browser...")411 browser = await p.chromium.launch(**browser_options)412 page = await browser.new_page()413
414 # Process each location415 for idx, location_str in enumerate(locations):416 # Get business name from the paired value417 business_name = business_names[idx] if idx < len(business_names) else None418 419 # Skip empty locations420 if not location_str or not location_str.strip():421 continue422 423 # Parse location type424 location_type, location_data = parse_location_type(location_str)425 426 Actor.log.info(f"\nProcessing location {idx + 1}/{len(locations)}: {location_str}")427 if business_name:428 Actor.log.info(f"Business name: {business_name}")429 430 geo = {'found': False}431 432 try:433 if location_type == 'coordinates':434 lat, lng = location_data435 Actor.log.info(f"Using provided coordinates: {lat}, {lng}")436 geo = {'found': True, 'latitude': lat, 'longitude': lng}437 elif location_type == 'place_id':438 geo = await geocode_with_place_id(page, location_data)439 else: # address440 geo = await geocode_with_address(page, location_data)441 except Exception as e:442 Actor.log.exception(f"Geocoding failed: {e}")443 geo = {'found': False, 'error': str(e)}444 445 # Scrape competitors if geocoding succeeded446 competitors_list = []447 if geo.get('found'):448 try:449 competitors_list = await scrape_competitors_at_coordinates(450 page, 451 business_name, 452 geo['latitude'], 453 geo['longitude'],454 search_query,455 max_competitors456 )457 Actor.log.info(f"Found {len(competitors_list)} competitors for {business_name or location_str}")458 except Exception as e:459 Actor.log.exception(f"Competitor scraping failed: {e}")460 else:461 Actor.log.warning(f"Skipping competitor search - geocoding failed: {geo.get('error', 'Unknown error')}")462 463 # Push results - FLATTENED for CSV464 if competitors_list:465 # One row per competitor466 for competitor in competitors_list:467 result = {468 # Competitor details in requested order469 'competitor_name': competitor['business_name'],470 'competitor_address': competitor['address'] or '',471 'competitor_city': competitor['city'] or '',472 'competitor_state': competitor['state'] or '',473 'competitor_zipcode': competitor['zipcode'] or '',474 'competitor_category': competitor['main_category'],475 'competitor_rank': competitor['google_rank'],476 'competitor_rating': competitor['average_rating'],477 'competitor_reviews': competitor['number_of_reviews'],478 'competitor_place_id': competitor['place_id'] or '',479 'latitude': geo.get('latitude'),480 'longitude': geo.get('longitude'),481 'search_query': search_query,482 # Source business info at the end483 'is_source_business': competitor['is_source_business'],484 'input_location': location_str,485 'input_business_name': business_name or ''486 }487 await Actor.push_data(result)488 total_results += 1489 else:490 # No competitors found - still push location info491 result = {492 # Empty competitor details in requested order493 'competitor_name': '',494 'competitor_address': '',495 'competitor_city': '',496 'competitor_state': '',497 'competitor_zipcode': '',498 'competitor_category': '',499 'competitor_rank': None,500 'competitor_rating': None,501 'competitor_reviews': None,502 'competitor_place_id': '',503 'latitude': geo.get('latitude'),504 'longitude': geo.get('longitude'),505 'search_query': search_query,506 # Source business info at the end507 'is_source_business': None,508 'input_location': location_str,509 'input_business_name': business_name or ''510 }511 await Actor.push_data(result)512 total_results += 1513 514 await browser.close()515 Actor.log.info(f"\nScraping completed! Processed {len(locations)} locations and found {total_results} total results.")516# Entry point517if __name__ == "__main__":518 asyncio.run(main())
1
1import asyncio2
3from .main import main4
5# Execute the Actor entry point.6asyncio.run(main())