<jupyter_start><jupyter_text>First steps1. google cloud2. Create project inside google cloud3. Activate our API Services -> Geocoding Api & Places API4. Get API Key & restrict<jupyter_code>api_key = "<KEY>"<jupyter_output><empty_output><jupyter_text>Client1. Google Maps API Docs2. Geocoding API3. Places API<jupyter_code>from urllib.parse import urlencode
data_type = 'json'
endpoint = f"https://maps.googleapis.com/maps/api/geocode/{data_type}"
params = {"address" :  "1600 Amphitheatre Parkway, Mountain+View, CA", "key": api_key}
url_params = urlencode(params)

sample = "https://maps.googleapis.com/maps/api/geocode/json?address=1600+Amphitheatre+Parkway,+Mountain+View,+CA&key=YOUR_API_KEY"<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.128099173553719, 'fraction_numerical': 0.02066115702479339, 'mean_word_length': 7.35632183908046, 'pattern_counts': {'":': 1, '<': 10, '<?xml version=': 0, '>': 11, 'https://': 2, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '584362', 'license': 'MIT', 'n_tokens_mistral': 273, 'n_tokens_neox': 256, 'n_words': 50, 'path': 'Python/Day 20/.ipynb_checkpoints/Geo-coding and Places AP with Google Maps-checkpoint.ipynb', 'repo_name': 'georgethedeveloper77/30DAYS-of-Python', 'size': '760'}