# import growth database 
import pandas as pd
from rapidfuzz import process
import requests

growth_df = pd.read_csv("../data/growth_csv/growth.csv")


def get_common_names_gbif(scientific_name: str) -> list[str]:
    """Get all common names for a scientific name via GBIF."""
    # Step 1: get GBIF taxon key
    r = requests.get(
        "https://api.gbif.org/v1/species/match",
        params={"name": scientific_name, "strict": False}
    )
    key = r.json().get("usageKey")
    if not key:
        return []

    # Step 2: get vernacular names
    r2 = requests.get(f"https://api.gbif.org/v1/species/{key}/vernacularNames")
    names = r2.json().get("results", [])
    return [n["vernacularName"].lower() for n in names if n.get("language") == "eng"]

# identify scientific name with the common name in the growth database
def find_common_name_match(scientific_name: str) -> str:
    """Find the common name for a scientific name in the growth database."""
    common_names = get_common_names_gbif(scientific_name)
    for name in common_names:
        
        # check if it matches even partially with the common name in the growth database using fuzzy matching
        match = process.extractOne(name, growth_df["Plant Name"], score_cutoff=80)
        if match:
            return match[0]  # return the matched common name from the growth database
        else:
            for word in name.split():
                print(f"  Checking if '{word}' is in growth database common names...")
                match = process.extractOne(word, growth_df["Plant Name"], score_cutoff=80)
                if match:
                    print(f"    Found a match for '{word}': '{match[0]}' with score {match[1]}")
                    return match[0]  # return the matched common name from the growth database
        
    return None

print(find_common_name_match("Circium vulgare"))  # should return "Spear Thistle"

def get_growth_info(scientific_name: str) -> dict:
    common_name = find_common_name_match(scientific_name)
    if not common_name:
        return {}
    return growth_df[growth_df["Plant Name"] == common_name].iloc[0].to_dict()