{"id":943248,"date":"2024-12-26T22:33:35","date_gmt":"2024-12-26T14:33:35","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/943248.html"},"modified":"2024-12-26T22:33:37","modified_gmt":"2024-12-26T14:33:37","slug":"python%e5%a6%82%e4%bd%95%e6%89%93%e5%9c%b0%e5%90%8d","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/943248.html","title":{"rendered":"python\u5982\u4f55\u6253\u5730\u540d"},"content":{"rendered":"

\"python\u5982\u4f55\u6253\u5730\u540d\"<\/p>\n

Python\u4e2d\u6253\u5730\u540d\u7684\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528NLP\u5de5\u5177\u3001\u8c03\u7528\u5730\u7406\u6570\u636eAPI\u3001\u5229\u7528\u6b63\u5219\u8868\u8fbe\u5f0f\u3002<\/strong>\u5728\u8fd9\u4e9b\u65b9\u6cd5\u4e2d\uff0c\u4f7f\u7528NLP\u5de5\u5177\u8fdb\u884c\u6587\u672c\u5904\u7406\u662f\u6700\u4e3a\u6709\u6548\u7684\u65b9\u5f0f\u3002\u901a\u8fc7\u81ea\u7136\u8bed\u8a00\u5904\u7406\uff08NLP\uff09\u5de5\u5177\uff0c\u5982spaCy\u3001NLTK\u7b49\uff0c\u53ef\u4ee5\u8bc6\u522b\u5e76\u63d0\u53d6\u6587\u672c\u4e2d\u7684\u5730\u540d\u4fe1\u606f\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u5229\u7528NLP\u5de5\u5177\u5728Python\u4e2d\u8bc6\u522b\u548c\u63d0\u53d6\u5730\u540d\u3002<\/p>\n<\/p>\n

\u4f7f\u7528NLP\u5de5\u5177\u8fdb\u884c\u5730\u540d\u8bc6\u522b\u662f\u4e00\u4e2a\u6709\u6548\u7684\u65b9\u6cd5\uff0c\u56e0\u4e3a\u8fd9\u4e9b\u5de5\u5177\u53ef\u4ee5\u5904\u7406\u5927\u91cf\u7684\u81ea\u7136\u8bed\u8a00\u6587\u672c\uff0c\u5e76\u8bc6\u522b\u51fa\u5176\u4e2d\u7684\u547d\u540d\u5b9e\u4f53\uff0c\u5305\u62ec\u5730\u540d\u3002\u4ee5spaCy\u4e3a\u4f8b\uff0c\u5b83\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5e93\uff0c\u63d0\u4f9b\u4e86\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\uff08NER\uff09\u529f\u80fd\uff0c\u53ef\u4ee5\u7528\u4e8e\u4ece\u6587\u672c\u4e2d\u63d0\u53d6\u5730\u540d\u3002\u4f7f\u7528spaCy\u8fdb\u884c\u5730\u540d\u8bc6\u522b\u7684\u6b65\u9aa4\u5305\u62ec\uff1a\u52a0\u8f7d\u8bed\u8a00\u6a21\u578b\u3001\u5904\u7406\u6587\u672c\u4ee5\u751f\u6210\u6587\u6863\u5bf9\u8c61\u3001\u63d0\u53d6\u6587\u6863\u5bf9\u8c61\u4e2d\u7684\u547d\u540d\u5b9e\u4f53\uff0c\u5e76\u7b5b\u9009\u51fa\u5730\u540d\u5b9e\u4f53\u3002<\/p>\n<\/p>\n

\n

\u4e00\u3001NLP\u5de5\u5177\u7684\u4f7f\u7528<\/strong><\/h2>\n

1. \u4f7f\u7528spaCy\u8fdb\u884c\u5730\u540d\u8bc6\u522b<\/h2>\n<\/p>\n

spaCy\u662f\u4e00\u4e2a\u975e\u5e38\u6d41\u884c\u7684NLP\u5e93\uff0c\u5e7f\u6cdb\u7528\u4e8e\u6587\u672c\u5904\u7406\u548c\u5206\u6790\u3002\u5b83\u63d0\u4f9b\u4e86\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\u529f\u80fd\uff0c\u53ef\u4ee5\u7528\u4e8e\u8bc6\u522b\u6587\u672c\u4e2d\u7684\u5730\u540d\u3002<\/p>\n<\/p>\n

\u9996\u5148\uff0c\u9700\u8981\u5b89\u88c5spaCy\u5e93\u548c\u8bed\u8a00\u6a21\u578b\u3002\u4f60\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

pip install spacy<\/p>\n
python -m spacy download en_core_web_sm<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u6765\u8bc6\u522b\u6587\u672c\u4e2d\u7684\u5730\u540d\uff1a<\/p>\n<\/p>\n
import spacy<\/p>\n
\u52a0\u8f7d\u8bed\u8a00\u6a21\u578b<\/strong><\/h2>\n
nlp = spacy.load('en_core_web_sm')<\/p>\n
\u5904\u7406\u6587\u672c<\/strong><\/h2>\n
text = "I visited New York and Los Angeles last summer."<\/p>\n
doc = nlp(text)<\/p>\n
\u63d0\u53d6\u5730\u540d<\/strong><\/h2>\n
places = [ent.text for ent in doc.ents if ent.label_ == 'GPE']<\/p>\n
print(places)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u6bb5\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u52a0\u8f7d\u4e86\u82f1\u8bed\u8bed\u8a00\u6a21\u578ben_core_web_sm<\/code>\uff0c\u7136\u540e\u5bf9\u6587\u672c\u8fdb\u884c\u5904\u7406\uff0c\u63d0\u53d6\u51fa\u547d\u540d\u5b9e\u4f53\u7c7b\u578b\u4e3aGPE<\/code>\uff08\u5730\u7406\u653f\u6cbb\u5b9e\u4f53\uff09\u7684\u5730\u540d\u3002<\/p>\n<\/p>\n
2. \u4f7f\u7528NLTK\u8fdb\u884c\u5730\u540d\u8bc6\u522b<\/h2>\n<\/p>\n
NLTK\u662f\u53e6\u4e00\u4e2a\u6d41\u884c\u7684NLP\u5e93\uff0c\u4e5f\u53ef\u4ee5\u7528\u4e8e\u5730\u540d\u8bc6\u522b\u3002\u867d\u7136NLTK\u7684NER\u529f\u80fd\u4e0d\u5982spaCy\u5f3a\u5927\uff0c\u4f46\u5b83\u4ecd\u7136\u53ef\u4ee5\u7528\u4e8e\u4e00\u4e9b\u57fa\u672c\u7684\u5730\u540d\u63d0\u53d6\u4efb\u52a1\u3002<\/p>\n<\/p>\n
\u9996\u5148\uff0c\u9700\u8981\u5b89\u88c5NLTK\u5e93\uff1a<\/p>\n<\/p>\n
pip install nltk<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7136\u540e\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u8fdb\u884c\u5730\u540d\u8bc6\u522b\uff1a<\/p>\n<\/p>\n
import nltk<\/p>\n
from nltk import ne_chunk, pos_tag, word_tokenize<\/p>\n
from nltk.tree import Tree<\/p>\n
\u4e0b\u8f7d\u5fc5\u8981\u7684NLTK\u6570\u636e\u5305<\/strong><\/h2>\n
nltk.download('punkt')<\/p>\n
nltk.download('averaged_perceptron_tagger')<\/p>\n
nltk.download('maxent_ne_chunker')<\/p>\n
nltk.download('words')<\/p>\n
\u5b9a\u4e49\u51fd\u6570\u63d0\u53d6\u5730\u540d<\/strong><\/h2>\n
def get_place_names(text):<\/p>\n
    chunked = ne_chunk(pos_tag(word_tokenize(text)))<\/p>\n
    place_names = []<\/p>\n
    for chunk in chunked:<\/p>\n
        if isinstance(chunk, Tree):<\/p>\n
            if chunk.label() == 'GPE':<\/p>\n
                place_names.append(' '.join(c[0] for c in chunk))<\/p>\n
    return place_names<\/p>\n
\u5904\u7406\u6587\u672c<\/strong><\/h2>\n
text = "I visited New York and Los Angeles last summer."<\/p>\n
places = get_place_names(text)<\/p>\n
print(places)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u6bb5\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528NLTK\u7684ne_chunk<\/code>\u51fd\u6570\u8fdb\u884c\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\uff0c\u5e76\u63d0\u53d6\u51fa\u7c7b\u578b\u4e3aGPE<\/code>\u7684\u5730\u540d\u3002<\/p>\n<\/p>\n
\n
\u4e8c\u3001\u8c03\u7528\u5730\u7406\u6570\u636eAPI<\/strong><\/h2>\n
1. \u4f7f\u7528Google Maps API\u8fdb\u884c\u5730\u540d\u8bc6\u522b<\/h2>\n<\/p>\n
Google Maps API\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u5730\u7406\u6570\u636e\u8bbf\u95ee\u529f\u80fd\uff0c\u53ef\u4ee5\u7528\u4e8e\u5730\u540d\u8bc6\u522b\u548c\u5730\u7406\u4f4d\u7f6e\u67e5\u8be2\u3002<\/p>\n<\/p>\n
\u9996\u5148\uff0c\u9700\u8981\u5728Google Cloud Platform\u4e0a\u542f\u7528Google Maps API\uff0c\u5e76\u83b7\u53d6API\u5bc6\u94a5\u3002\u7136\u540e\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u8fdb\u884c\u5730\u540d\u8bc6\u522b\uff1a<\/p>\n<\/p>\n
import requests<\/p>\n
def get_location_info(place_name, api_key):<\/p>\n
    url = f"https:\/\/maps.googleapis.com\/maps\/api\/geocode\/json?address={place_name}&key={api_key}"<\/p>\n
    response = requests.get(url)<\/p>\n
    return response.json()<\/p>\n
\u4f7f\u7528API\u83b7\u53d6\u5730\u540d\u4fe1\u606f<\/strong><\/h2>\n
api_key = 'YOUR_API_KEY'  # \u66ff\u6362\u4e3a\u4f60\u7684API\u5bc6\u94a5<\/p>\n
place_name = "New York"<\/p>\n
location_info = get_location_info(place_name, api_key)<\/p>\n
print(location_info)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u6bb5\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u901a\u8fc7Google Maps Geocoding API\u67e5\u8be2\u5730\u540d\u4fe1\u606f\u3002\u8fd4\u56de\u7684\u7ed3\u679c\u4e2d\u5305\u542b\u4e86\u5730\u540d\u7684\u8be6\u7ec6\u4fe1\u606f\u548c\u5730\u7406\u5750\u6807\u3002<\/p>\n<\/p>\n
2. \u4f7f\u7528OpenStreetMap Nominatim API<\/h2>\n<\/p>\n
OpenStreetMap\u63d0\u4f9b\u4e86\u514d\u8d39\u7684\u5730\u7406\u6570\u636eAPI\uff0cNominatim\u662f\u5176\u4e2d\u7684\u4e00\u4e2a\u5730\u7406\u7f16\u7801\u670d\u52a1\u3002<\/p>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u67e5\u8be2\u5730\u540d\u4fe1\u606f\uff1a<\/p>\n<\/p>\n
import requests<\/p>\n
def get_location_info_osm(place_name):<\/p>\n
    url = f"https:\/\/nominatim.openstreetmap.org\/search?q={place_name}&format=json&limit=1"<\/p>\n
    response = requests.get(url, headers={'User-Agent': 'Mozilla\/5.0'})<\/p>\n
    return response.json()<\/p>\n
\u4f7f\u7528API\u83b7\u53d6\u5730\u540d\u4fe1\u606f<\/strong><\/h2>\n
place_name = "New York"<\/p>\n
location_info = get_location_info_osm(place_name)<\/p>\n
print(location_info)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u6bb5\u4ee3\u7801\u901a\u8fc7OpenStreetMap Nominatim API\u67e5\u8be2\u5730\u540d\u4fe1\u606f\uff0c\u5e76\u8fd4\u56deJSON\u683c\u5f0f\u7684\u7ed3\u679c\u3002<\/p>\n<\/p>\n
\n
\u4e09\u3001\u6b63\u5219\u8868\u8fbe\u5f0f\u7684\u4f7f\u7528<\/strong><\/h2>\n
1. \u6b63\u5219\u8868\u8fbe\u5f0f\u57fa\u7840<\/h2>\n<\/p>\n
\u6b63\u5219\u8868\u8fbe\u5f0f\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u5de5\u5177\uff0c\u53ef\u4ee5\u7528\u4e8e\u6a21\u5f0f\u5339\u914d\u548c\u6587\u672c\u63d0\u53d6\u3002\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528re<\/code>\u6a21\u5757\u8fdb\u884c\u6b63\u5219\u8868\u8fbe\u5f0f\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
2. \u4f7f\u7528\u6b63\u5219\u8868\u8fbe\u5f0f\u63d0\u53d6\u5730\u540d<\/h2>\n<\/p>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a\u6587\u672c\u6587\u4ef6\uff0c\u5305\u542b\u4e86\u4e00\u4e9b\u5df2\u77e5\u683c\u5f0f\u7684\u5730\u540d\u4fe1\u606f\uff0c\u53ef\u4ee5\u4f7f\u7528\u6b63\u5219\u8868\u8fbe\u5f0f\u8fdb\u884c\u63d0\u53d6\u3002<\/p>\n<\/p>\n
import re<\/p>\n
text = "I visited New York, Los Angeles, and San Francisco last summer."<\/p>\n
\u5b9a\u4e49\u6b63\u5219\u8868\u8fbe\u5f0f\u6a21\u5f0f<\/strong><\/h2>\n
pattern = r"\\b(New York|Los Angeles|San Francisco)\\b"<\/p>\n
\u4f7f\u7528\u6b63\u5219\u8868\u8fbe\u5f0f\u63d0\u53d6\u5730\u540d<\/strong><\/h2>\n
places = re.findall(pattern, text)<\/p>\n
print(places)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u8fd9\u6bb5\u4ee3\u7801\u4e2d\uff0c\u6211\u4eec\u5b9a\u4e49\u4e86\u4e00\u4e2a\u6b63\u5219\u8868\u8fbe\u5f0f\u6a21\u5f0f\uff0c\u7528\u4e8e\u5339\u914d\u6587\u672c\u4e2d\u7684\u5730\u540d\u3002re.findall<\/code>\u51fd\u6570\u8fd4\u56de\u6240\u6709\u5339\u914d\u7684\u7ed3\u679c\u3002<\/p>\n<\/p>\n
3. \u52a8\u6001\u6784\u5efa\u6b63\u5219\u8868\u8fbe\u5f0f<\/h2>\n<\/p>\n
\u5982\u679c\u6709\u4e00\u4e2a\u5730\u540d\u5217\u8868\uff0c\u53ef\u4ee5\u52a8\u6001\u6784\u5efa\u6b63\u5219\u8868\u8fbe\u5f0f\u4ee5\u5339\u914d\u6587\u672c\u4e2d\u7684\u5730\u540d\u3002<\/p>\n<\/p>\n
import re<\/p>\n
text = "I visited New York, Los Angeles, and San Francisco last summer."<\/p>\n
known_places = ["New York", "Los Angeles", "San Francisco"]<\/p>\n
\u52a8\u6001\u6784\u5efa\u6b63\u5219\u8868\u8fbe\u5f0f\u6a21\u5f0f<\/strong><\/h2>\n
pattern = r"\\b(" + "|".join(map(re.escape, known_places)) + r")\\b"<\/p>\n
\u4f7f\u7528\u6b63\u5219\u8868\u8fbe\u5f0f\u63d0\u53d6\u5730\u540d<\/strong><\/h2>\n
places = re.findall(pattern, text)<\/p>\n
print(places)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u6bb5\u4ee3\u7801\u5c55\u793a\u4e86\u5982\u4f55\u4f7f\u7528\u5df2\u77e5\u5730\u540d\u5217\u8868\u52a8\u6001\u6784\u5efa\u6b63\u5219\u8868\u8fbe\u5f0f\uff0c\u5e76\u4ece\u6587\u672c\u4e2d\u63d0\u53d6\u5730\u540d\u3002<\/p>\n<\/p>\n
\n
\u603b\u7ed3\u6765\u8bf4\uff0cPython\u4e2d\u8bc6\u522b\u548c\u63d0\u53d6\u5730\u540d\u7684\u65b9\u6cd5\u591a\u79cd\u591a\u6837\uff0c\u5305\u62ec\u4f7f\u7528NLP\u5de5\u5177\uff08\u5982spaCy\u548cNLTK\uff09\u3001\u8c03\u7528\u5730\u7406\u6570\u636eAPI\uff08\u5982Google Maps\u548cOpenStreetMap Nominatim\uff09\u4ee5\u53ca\u5229\u7528\u6b63\u5219\u8868\u8fbe\u5f0f\u8fdb\u884c\u6587\u672c\u5339\u914d\u3002\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u72ec\u7279\u7684\u4f18\u70b9\uff0c\u9009\u62e9\u9002\u5408\u7684\u5de5\u5177\u548c\u65b9\u6cd5\u53ef\u4ee5\u6709\u6548\u63d0\u5347\u5730\u540d\u8bc6\u522b\u7684\u51c6\u786e\u6027\u548c\u6548\u7387\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u4f7f\u7528Python\u5904\u7406\u5730\u540d\u6570\u636e\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u591a\u4e2a\u5e93\u6765\u5904\u7406\u5730\u540d\u6570\u636e\u3002\u4f8b\u5982\uff0cgeopy<\/code>\u5e93\u53ef\u4ee5\u5e2e\u52a9\u4f60\u8fdb\u884c\u5730\u7406\u7f16\u7801\uff0c\u5c06\u5730\u540d\u8f6c\u6362\u4e3a\u7ecf\u7eac\u5ea6\u5750\u6807\u3002\u4f7f\u7528geopy<\/code>\u65f6\uff0c\u4f60\u53ef\u4ee5\u901a\u8fc7\u7b80\u5355\u7684API\u8c03\u7528\u83b7\u53d6\u5730\u540d\u7684\u8be6\u7ec6\u4fe1\u606f\uff0c\u6bd4\u5982\u56fd\u5bb6\u3001\u57ce\u5e02\u548c\u8857\u9053\u7b49\u3002<\/p>\n
\u5728Python\u4e2d\u5982\u4f55\u83b7\u53d6\u5730\u540d\u7684\u7ecf\u7eac\u5ea6\uff1f<\/strong>
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