Rumah > Artikel > pembangunan bahagian belakang > Memuat turun Data Pemain daripada Clash of Clans API
Adakah anda peminat Clash of Clans yang juga meminati analisis data atau pembangunan aplikasi? Dalam siaran ini, saya akan membimbing anda melalui proses memuat turun data pemain daripada Clash of Clans API menggunakan Python. Ini boleh menjadi sangat berguna untuk alatan pengurusan klan, analisis statistik pemain, atau juga membina aplikasi berkaitan Clash of Clans anda sendiri.
Sebelum kami menyelam, pastikan anda mempunyai:
Pertama, anda perlu mendaftar untuk akaun pembangun Clash of Clans:
Kami akan menggunakan beberapa perpustakaan Python untuk projek ini. Pasangnya menggunakan pip:
pip install requests pandas tqdm ratelimit
Mari pecahkan kod kepada bahagian yang boleh diurus:
import time import math import json import requests import logging import pandas as pd from concurrent.futures import ThreadPoolExecutor, as_completed from ratelimit import limits, sleep_and_retry from tqdm import tqdm
file_path = 'others/clans.json' # Function to open the file and extract tags, specifying the encoding def extract_tags_from_file(file_path): with open(file_path, 'r', encoding='utf-8') as file: # Specifying the encoding here data = json.load(file) return [item.get("tag") for item in data.get("items", [])] # Extract tags from the specified file try: extracted_tags = extract_tags_from_file(file_path) print(extracted_tags) except UnicodeDecodeError as e: print(f"Error reading the file: {e}")
# the extracted clan tags have '#' in beigning we have to replace it with URL encode '%23' def update_tags(extracted_tags): # Replace '#' with '%23' for each tag in the list updated_tags = [tag.replace('#', '%23') for tag in extracted_tags] return updated_tags # Get the updated list of tags updated_extracted_tags = update_tags(extracted_tags) # Print or return the updated list print(updated_extracted_tags)
# Replace your API_KEY api_key = 'your_api_key_here' # Base URL for the Clash of Clans API clans endpoint base_url = 'https://api.clashofclans.com/v1/clans/' # Header to include in the request headers = { 'Authorization': f'Bearer {api_key}', 'Accept': 'application/json' } # Function to get clan member list for each clan tag def get_clan_members(clan_tags): clan_members = {} # Dictionary to store clan members list by clan tag for tag in clan_tags: # Constructing the full URL for the clan members endpoint full_url = f'{base_url}{tag}/members' response = requests.get(full_url, headers=headers) if response.status_code == 200: # Successful response data = response.json() # Assuming the API returns a list of clan members directly clan_members[tag] = data.get('items', []) else: # Handle errors or unsuccessful responses print(f'Failed to fetch clan members for {tag}: HTTP {response.status_code}') return clan_members # Get clan members for each tag clan_members_lists = get_clan_members(updated_extracted_tags) # Example: print the result for the first clan first_tag = updated_extracted_tags[0] print(f'Clan members for {first_tag}:', clan_members_lists[first_tag])
# Assuming clan_members_lists is your dictionary from the modified get_clan_members function def convert_to_dataframe(clan_members_lists): # Create a list of tuples (clan_tag, player_tag) for all clans data = [(clan_tag, player_tag) for clan_tag, player_tags in clan_members_lists.items() for player_tag in player_tags] # Convert the list of tuples into a DataFrame df = pd.DataFrame(data, columns=['Clan Tag', 'Player Tag']) return df # Convert the dictionary to a DataFrame df_clan_members = convert_to_dataframe(clan_members_lists) print(df_clan_members)
def convert_to_dataframe(clan_members_lists): # Initialize an empty list to store the data data = [] # Loop through each clan tag and its corresponding list of members for clan_tag, members in clan_members_lists.items(): for member in members: # For each member, extract the clan tag and the player tag, ensuring the player tag is a string player_tag = member['tag'] # Assuming 'tag' key exists and its value is the player's tag data.append((clan_tag, player_tag)) # Convert the list of tuples into a DataFrame df = pd.DataFrame(data, columns=['Clan Tag', 'Player Tag']) # Optional: Convert clan and player tags to ensure they are URL-friendly # This step is optional and depends on whether you need to use these tags in URLs df['Clan Tag'] = df['Clan Tag'].apply(lambda x: x.replace('%23', '#')) # df['Player Tag'] = df['Player Tag'].apply(lambda x: x.replace('#', '%23')) return df # Example usage with your clan_members_lists dictionary # Make sure to replace 'clan_members_lists' with your actual dictionary variable df_clan_members = convert_to_dataframe(clan_members_lists) print(df_clan_members) df_clan_members.to_csv('datasets/clan_and_player_tags.csv', index=False)
# Set up logging to file logging.basicConfig(filename='others/error_log.log', level=logging.ERROR, format='%(asctime)s - %(levelname)s - %(message)s') # Load the CSV file into a DataFrame df = pd.read_csv('datasets/clan_and_player_tags.csv') # Update this path to your actual CSV file location # API details api_key = 'your_api_key_here' headers = {'Authorization': 'Bearer ' + api_key} # Rate limit: 10 requests per second (adjust as needed) @sleep_and_retry @limits(calls=10, period=1) def call_api(url): response = requests.get(url, headers=headers) response.raise_for_status() return response.json() def fetch_player_details(tag): url = f'https://api.clashofclans.com/v1/players/{tag.replace("#", "%23")}' try: data = call_api(url) return { 'name': data.get('name', ''), 'role': data.get('role', ''), 'league': data.get('league', {}).get('name', ''), 'builderBaseLeague': data.get('builderBaseLeague', {}).get('name', ''), 'townHallLevel': data.get('townHallLevel', 0), 'builderHallLevel': data.get('builderHallLevel', 0), 'expLevel': data.get('expLevel', 0), 'trophies': data.get('trophies', 0), 'bestTrophies': data.get('bestTrophies', 0), 'builderBaseTrophies': data.get('builderBaseTrophies', 0), 'bestBuilderBaseTrophies': data.get('bestBuilderBaseTrophies', 0), 'attackWins': data.get('attackWins', 0), 'defenseWins': data.get('defenseWins', 0), 'warStars': data.get('warStars', 0), 'clanCapitalContributions': data.get('clanCapitalContributions', 0), 'donations': data.get('donations', 0), 'donationsReceived': data.get('donationsReceived', 0), } except requests.exceptions.RequestException as e: logging.error(f'Error fetching data for {tag}: {e}') def process_batch(batch): player_details = [] with ThreadPoolExecutor(max_workers=20) as executor: future_to_tag = {executor.submit(fetch_player_details, tag): tag for tag in batch} for future in as_completed(future_to_tag): tag = future_to_tag[future] try: details = future.result() player_details.append(details) except Exception as exc: logging.error(f'{tag} generated an exception: {exc}') return player_details def save_checkpoint(data, filename): with open(filename, 'w') as f: json.dump(data, f) def load_checkpoint(filename): try: with open(filename, 'r') as f: return json.load(f) except FileNotFoundError: return [] def main(): batch_size = 1000 checkpoint_file = 'others/player_details_checkpoint.json' # Load checkpoint if it exists player_details = load_checkpoint(checkpoint_file) start_index = len(player_details) num_batches = math.ceil((len(df) - start_index) / batch_size) for i in tqdm(range(start_index, len(df), batch_size), total=num_batches, desc="Processing batches"): batch = df['Player Tag'].iloc[i:i+batch_size].tolist() batch_details = process_batch(batch) player_details.extend(batch_details) # Save checkpoint after each batch save_checkpoint(player_details, checkpoint_file) # Filter out None values from player_details player_details = [detail for detail in player_details if detail is not None] # Create a new DataFrame with the player details details_df = pd.DataFrame(player_details) # Merge the original DataFrame with the new details DataFrame final_df = pd.concat([df, details_df], axis=1) # Save the final DataFrame to a new CSV file final_df.to_csv('datasets/player_details.csv', index=False) print("Data fetching and processing complete. Results saved to 'Clan_and_Player_Details.csv'") if __name__ == "__main__": start_time = time.time() main() end_time = time.time() print(f"Total execution time: {end_time - start_time:.2f} seconds")
Untuk menjalankan skrip:
Skrip akan memproses teg pemain dalam kelompok, mengambil butiran untuk setiap pemain dan menyimpan keputusan dalam fail CSV baharu.
Skrip ini menyediakan cara yang mantap untuk memuat turun data pemain daripada Clash of Clans API. Ia termasuk pengendalian ralat, pengehadan kadar untuk menghormati kekangan API dan menggunakan berbilang benang untuk prestasi yang lebih baik.
Ingat untuk sentiasa menghormati terma dan syarat penggunaan API. Selamat mengekod, dan teruskan bertembung!
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