import requests
import pandas as pd
import numpy as np
from pyproj import Transformer

# create transformer once (faster if used repeatedly)
_transformer = Transformer.from_crs("EPSG:4326", "EPSG:3857", always_xy=True)


def main(lat, lon, radius_m,
                              n_vertices=15,
                              page_size=10000,
                              species_summary=False):
    """
    Fetch Artsdatabanken observations inside a semicircular polygon.

    Parameters
    ----------
    lat : float
    lon : float
    radius_m : float
        Radius in meters
    n_vertices : int
        Polygon vertices approximating the circle
    page_size : int
    species_summary : bool
        If True, also return species counts

    Returns
    -------
    pandas.DataFrame
    (optional) pandas.Series with species counts
    """

    # -------------------
    # Build polygon
    # -------------------

    cx, cy = _transformer.transform(lon, lat)

    angles = np.linspace(0, 2*np.pi, n_vertices, endpoint=False)

    x = np.float32(cx + radius_m * np.cos(angles))
    y = np.float32(cy + radius_m * np.sin(angles))

    points = [f"{xi}+{yi}" for xi, yi in zip(x, y)]
    points.append(points[0])  # close polygon

    polygon = "POLYGON((" + ",".join(points) + "))"

    # -------------------
    # API request
    # -------------------

    url = (
        "https://artskart.artsdatabanken.no/publicapi/api/observations/list/"
        f"?gmWktPolygon={polygon}&page=0&pageSize={page_size}"
    )

    r = requests.get(url)
    r.raise_for_status()

    data = r.json()

    if "Observations" not in data:
        return pd.DataFrame()

    # -------------------
    # Dataframe creation
    # -------------------

    df = pd.json_normalize(data["Observations"])[
        ["Latitude", "Longitude", "Notes", "ScientificName", "ScientificNameId"]
    ]

    df["Latitude"] = df["Latitude"].str.replace(",", ".").astype(float)
    df["Longitude"] = df["Longitude"].str.replace(",", ".").astype(float)

    if species_summary:
        return df, df["ScientificName"].value_counts()

    return df