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import pandas as pd | |
from pandas import DataFrame | |
from typing import Optional | |
from src.utils import extract_before_parenthesis | |
class Restaurants: | |
def __init__(self, path="/home/user/app/database/restaurants/clean_restaurant_2022.csv"): | |
self.path = path | |
self.data = pd.read_csv(self.path).dropna()[['Name','Average Cost','Cuisines','Aggregate Rating','City']] | |
print("Restaurants loaded.") | |
def load_db(self): | |
self.data = pd.read_csv(self.path).dropna() | |
def run(self, | |
city: str, | |
) -> DataFrame: | |
"""Search for restaurant .""" | |
results = self.data[self.data["City"] == city] | |
# results = results[results["date"] == date] | |
# if price_order == "asc": | |
# results = results.sort_values(by=["Average Cost"], ascending=True) | |
# elif price_order == "desc": | |
# results = results.sort_values(by=["Average Cost"], ascending=False) | |
# if rating_order == "asc": | |
# results = results.sort_values(by=["Aggregate Rating"], ascending=True) | |
# elif rating_order == "desc": | |
# results = results.sort_values(by=["Aggregate Rating"], ascending=False) | |
if len(results) == 0: | |
return "There is no restaurant in this city." | |
return results | |
def run_for_annotation(self, | |
city: str, | |
) -> DataFrame: | |
"""Search for restaurant .""" | |
results = self.data[self.data["City"] == extract_before_parenthesis(city)] | |
# results = results[results["date"] == date] | |
# if price_order == "asc": | |
# results = results.sort_values(by=["Average Cost"], ascending=True) | |
# elif price_order == "desc": | |
# results = results.sort_values(by=["Average Cost"], ascending=False) | |
# if rating_order == "asc": | |
# results = results.sort_values(by=["Aggregate Rating"], ascending=True) | |
# elif rating_order == "desc": | |
# results = results.sort_values(by=["Aggregate Rating"], ascending=False) | |
return results |