"""Review earnings, cash conversion, insider filing activity and short interest without collapsing different dates into one score.

Research example. Live observations can change.
"""

from datetime import UTC, datetime
from decimal import Decimal
from textwrap import fill

import matplotlib.pyplot as plt
import pandas as pd

AS_OF = datetime.now(UTC).date()
NAVY, BLUE, PINK = "#132244", "#8fb9ff", "#e7a2cc"


def fetch(qj):
    return {
        "income": qj.fmp.get_income_statement(symbol="AAPL", period="annual", limit=5),
        "cash": qj.fmp.get_cash_flow_statement(symbol="AAPL", period="annual", limit=5),
        "sec_insider": qj.sec.get_insider_transactions(symbol="AAPL", limit=100),
        "short": qj.finra.get_short_interest(symbol="AAPL"),
    }


def analyze(raw):
    statements = frame(raw["income"])[["date", "netIncome"]].merge(
        frame(raw["cash"])[["date", "operatingCashFlow"]], on="date", validate="one_to_one"
    )
    if statements.empty:
        raise ValueError("No matching earnings and cash periods")
    statements["Cash conversion %"] = [
        100 * ratio(cash, earnings)
        for cash, earnings in zip(statements["operatingCashFlow"], statements["netIncome"], strict=True)
    ]
    filings = frame(raw["sec_insider"], "filingDate")
    filings = filings.loc[(filings["form"] == "4") & (filings["filingDate"].dt.date <= AS_OF)]
    filings = filings.drop_duplicates("accessionNumber")
    if filings.empty:
        raise ValueError("No returned Form 4 filings")
    monthly = filings.set_index("filingDate").resample(pd.offsets.MonthEnd()).size().tail(12)
    short = frame(raw["short"], "settlement_date").iloc[-1]
    fig, (top, middle, bottom) = canvas("Cross-source equity evidence · AAPL", "", panels=3)
    top.bar(statements["date"].dt.year.astype(str), statements["Cash conversion %"], color=BLUE)
    top.axhline(100, color="#afc1dc", linestyle="--", lw=0.8)
    top.set_ylabel("Cash / earnings %")
    months = pd.DatetimeIndex([day.replace(day=1) for day in monthly.index])
    middle.bar(months, monthly, width=18, color=PINK)
    middle.set_ylabel("Returned Form 4 filings")
    bottom.bar(
        ["Previous", "Current"],
        [ratio(short["previous_short_position"], 1000000), ratio(short["current_short_position"], 1000000)],
        color=[BLUE, PINK],
    )
    bottom.set_ylabel("Short shares · millions")
    bottom.set_xlabel("FINRA settlement " + str(short["settlement_date"].date()))
    statements["Latest Form 4 date"] = filings["filingDate"].max()
    statements["Short settlement date"] = short["settlement_date"]
    return statements, fig


def payload(response):
    if hasattr(response, "to_dict"):
        response = response.to_dict()
    while isinstance(response, dict):
        if response.get("error") or response.get("error_code") or response.get("success") is False:
            raise ValueError("Provider request failed")
        if "data" in response:
            response = response["data"]
        elif "value" in response:
            response = response["value"]
        else:
            break
    return response


def frame(response, date="date"):
    rows = payload(response)
    if not isinstance(rows, list) or not rows:
        raise ValueError("No provider observations returned")
    result = pd.DataFrame(rows)
    if date:
        result[date] = pd.to_datetime(result[date], utc=True)
        result = result.sort_values(date)
    return result


def decimal(value):
    if pd.isna(value):
        raise ValueError("Required monetary value or quantity is missing")
    return Decimal(str(value))


def ratio(numerator, denominator):
    denominator = decimal(denominator)
    if denominator == 0:
        raise ValueError("Required denominator is zero")
    return float(decimal(numerator) / denominator)


def canvas(title, ylabel, panels=1):
    plt.rcParams.update(
        {
            "figure.facecolor": NAVY,
            "axes.facecolor": NAVY,
            "savefig.facecolor": NAVY,
            "text.color": "#e9eef8",
            "axes.labelcolor": "#afc1dc",
            "xtick.color": "#afc1dc",
            "ytick.color": "#afc1dc",
            "axes.edgecolor": "#34486b",
            "grid.color": "#34486b",
            "font.size": 10,
            "axes.prop_cycle": plt.cycler(color=[BLUE, PINK, "#ba9dea"]),
        }
    )
    fig, axes = plt.subplots(panels, 1, figsize=(9, 6.1), squeeze=False, layout="constrained")
    fig.suptitle(fill(title, width=58), fontsize=17, x=0.04, ha="left", weight="medium")
    for ax in axes.flat:
        ax.grid(axis="y", alpha=0.45)
        ax.set_axisbelow(True)
        ax.spines[["top", "right"]].set_visible(False)
    axes.flat[0].set_ylabel(ylabel)
    return fig, list(axes.flat)


def run():
    from quantjourney.sdk import QuantJourneyAPI

    qj = QuantJourneyAPI.from_env()
    raw = fetch(qj)
    table, fig = analyze(raw)
    print(table.to_string(index=False))
    fig.savefig(OUTPUT, dpi=180)
    plt.show()


OUTPUT = "sdk_equity_conviction.png"

if __name__ == "__main__":
    run()