"""
京东滑块验证码：打码识别 + 轨迹生成 + 拖动。
多处复用：from spiders.jd.jd_captcha import handle_jd_slider_captcha, JdCaptchaHandler
"""

import base64
import math
import random
import time
from contextlib import contextmanager

import requests
from PIL import Image

DEFAULT_CAPTCHA_TOKEN = "zPzmt1mG1ouCU6GTzsZN2Lmm8pdZypapPcLJTBRETco"
DEFAULT_SCREENSHOT_PATH = "./element_screenshot.png"
JFBYM_API_URL = "http://api.jfbym.com/api/YmServer/customApi"

CAPTCHA_MODAL_XPATH = "xpath=//div[@id='captcha_modal']"
CAPTCHA_IMG_XPATH = 'xpath://img[@id="main_img"]'
SLIDER_IMG_XPATH = "xpath://img[@class='move-img']"


@contextmanager
def pause_page_listen(page, clear=True):
    """处理验证码时暂停网络监听，避免与滑块拖动抢 CDP 资源（auto_crawl 场景）。"""
    listen = getattr(page, "listen", None)
    was_listening = bool(listen and getattr(listen, "listening", False))
    if was_listening:
        listen.pause(clear=clear)
    try:
        yield
    finally:
        if was_listening:
            listen.resume()


def simulate(target_x, seed=None):
    while 1:
        x_seq = simulate_x(target_x, seed)
        if len(x_seq) < 50 and target_x > 150:
            continue
        t_seq = _generate_t(x_seq, seed)
        y_seq = _generate_y(x_seq, t_seq, seed)
        result = []
        for x, y, t in zip(x_seq, y_seq, t_seq):
            result.append([x, y, t])
        return result


def _generate_t(x_seq, seed=None):
    if seed is not None:
        random.seed(seed + 9999)

    n = len(x_seq)
    t_seq = [0] * n

    for i in range(1, n):
        dx = x_seq[i] - x_seq[i - 1]
        is_pause = dx == 0

        if i == 1:
            t_seq[i] = random.randint(50, 95)
        elif is_pause:
            if random.random() < 0.20:
                t_seq[i] = random.choice([16, 24, 33, 40, 58, 71, 74, 90, 96, 150, 200, 264])
            else:
                t_seq[i] = random.choices([6, 7, 8, 9, 10], weights=[3, 25, 45, 22, 5])[0]
        else:
            r = random.random()
            if r < 0.90:
                t_seq[i] = random.choices([6, 7, 8, 9, 10], weights=[3, 25, 45, 22, 5])[0]
            elif r < 0.95:
                t_seq[i] = random.choice([6, 10])
            else:
                t_seq[i] = random.choice([16, 24, 25, 33, 40, 58, 71, 74, 90, 96])

    return t_seq


def _generate_y(x_seq, t_seq, seed=None):
    if seed is not None:
        random.seed(seed + 19999)

    n = len(x_seq)
    y_seq = [0] * n
    current_y = 0
    direction = 0
    dir_remaining = 0
    cooldown = 0

    for i in range(1, n):
        is_abnormal_t = t_seq[i] > 10

        if dir_remaining > 0:
            dir_remaining -= 1
            if dir_remaining == 0:
                direction = 0
                cooldown = random.randint(4, 8)
        elif cooldown > 0:
            cooldown -= 1
        else:
            triggered = False
            if is_abnormal_t and random.random() < 0.40:
                triggered = True
            elif random.random() < 0.025:
                triggered = True

            if triggered:
                if current_y >= 4:
                    direction = random.choices([-1, 1], weights=[85, 15])[0]
                elif current_y <= -4:
                    direction = random.choices([-1, 1], weights=[15, 85])[0]
                else:
                    direction = random.choice([-1, 1])
                dir_remaining = random.choices([1, 2, 3, 4], weights=[35, 35, 20, 10])[0]

        current_y += direction
        y_seq[i] = current_y

    return y_seq


def simulate_x(target_x, seed=None):
    if seed is not None:
        random.seed(seed)

    seq = [0]
    step = 1
    x = 0
    phase = "accelerating"

    accel_threshold = target_x * 0.2
    cruise_threshold = target_x * 0.5

    while x < target_x:
        remaining = target_x - x

        if phase == "accelerating":
            if step >= 9 or x >= accel_threshold:
                phase = "cruising"
                continue
        elif phase == "cruising":
            if x >= cruise_threshold:
                phase = "decelerating"
                continue
        elif phase == "decelerating":
            if remaining <= 6:
                phase = "fine_tuning"
                continue

        if phase == "accelerating":
            delta = random.choices([-1, 0, 1, 2, 3], weights=[5, 10, 30, 35, 20])[0]
            step = _clamp(step + delta, 1, 8)
        elif phase == "cruising":
            if step <= 1:
                delta = random.choices([0, 1, 2], weights=[12, 55, 33])[0]
            elif step >= 8:
                delta = random.choices([-2, -1, 0], weights=[20, 50, 30])[0]
            else:
                delta = random.choices([-2, -1, 0, 1, 2], weights=[5, 22, 50, 18, 5])[0]
            step = _clamp(step + delta, 0, 7)
        elif phase == "decelerating":
            remaining_ratio = remaining / target_x
            max_step = max(3, int(2.5 + 5.5 * remaining_ratio / 0.35))

            if remaining_ratio > 0.18:
                if step <= 1:
                    delta = random.choices([0, 1, 2], weights=[12, 50, 38])[0]
                elif step >= max_step:
                    delta = random.choices([-2, -1, 0], weights=[25, 45, 30])[0]
                else:
                    delta = random.choices([-2, -1, 0, 1, 2], weights=[8, 22, 46, 19, 5])[0]
            else:
                if step <= 0:
                    delta = random.choices([1, 2], weights=[65, 35])[0]
                elif step == 1:
                    delta = random.choices([-1, 0, 1], weights=[18, 52, 30])[0]
                elif step >= max_step:
                    delta = random.choices([-2, -1, 0], weights=[25, 45, 30])[0]
                else:
                    delta = random.choices([-2, -1, 0, 1], weights=[10, 30, 45, 15])[0]

            step = _clamp(step + delta, 0, max_step)
            if step == 0 and len(seq) >= 2 and seq[-1] == seq[-2]:
                step = 1
        elif phase == "fine_tuning":
            if remaining <= 0:
                break
            step = random.choices([0, 1, 2], weights=[10, 70, 20])[0]
            step = min(step, remaining)
            if step == 0 and len(seq) >= 2 and seq[-1] == seq[-2]:
                step = 1 if remaining >= 1 else 0

        x += step
        if x > target_x:
            x = target_x
        seq.append(x)

    return seq


def _clamp(v, lo, hi):
    return max(lo, min(hi, v))


class JdCaptchaHandler:
    """京东滑块验证码处理器，绑定 DrissionPage 的 ChromiumPage / Tab。"""

    def __init__(self, page, token=None, screenshot_path=None):
        self.page = page
        self.token = token or DEFAULT_CAPTCHA_TOKEN
        self.screenshot_path = screenshot_path or DEFAULT_SCREENSHOT_PATH

    @staticmethod
    def _safe_float(value, default=0.0):
        try:
            return float(value)
        except (TypeError, ValueError):
            return default

    def _run_js_safe(self, target, script, default=None):
        try:
            if hasattr(target, "run_js"):
                return target.run_js(script)
            if hasattr(target, "run_script"):
                return target.run_script(script)
        except Exception:
            return default
        return default

    def _get_device_pixel_ratio(self):
        ratio = self._run_js_safe(self.page, "return window.devicePixelRatio || 1;", default=1)
        ratio = self._safe_float(ratio, 1.0)
        return ratio if ratio > 0 else 1.0

    def _get_image_width(self, image_path):
        try:
            with Image.open(image_path) as img:
                return float(img.width)
        except Exception:
            return 0.0

    def _get_ele_css_width(self, ele):
        width = self._run_js_safe(ele, "return this.getBoundingClientRect().width || 0;", default=0)
        width = self._safe_float(width, 0.0)
        if width > 0:
            return width
        try:
            size = ele.rect.size
            if isinstance(size, (tuple, list)) and len(size) >= 1:
                return self._safe_float(size[0], 0.0)
        except Exception:
            pass
        return 0.0

    def _normalize_slider_distance(self, raw_distance, capt_ele, slider_ele, screenshot_path):
        distance = max(0.0, self._safe_float(raw_distance, 0.0))
        capt_css_width = self._get_ele_css_width(capt_ele)
        screenshot_width = self._get_image_width(screenshot_path)
        natural_width = self._safe_float(
            self._run_js_safe(capt_ele, "return this.naturalWidth || 0;", default=0),
            0.0,
        )

        if capt_css_width > 0 and screenshot_width > 0:
            return distance * (capt_css_width / screenshot_width)
        if capt_css_width > 0 and natural_width > 0:
            return distance * (capt_css_width / natural_width)

        dpr = self._get_device_pixel_ratio()
        if dpr > 1.0:
            return distance / dpr
        return distance

    def generate_human_track(self, distance):
        try:
            distance = float(distance)
        except (TypeError, ValueError):
            return []
        if distance <= 0 or not math.isfinite(distance):
            return []

        tracks = []
        current = 0
        mid = distance * 0.7
        t = 0.2
        v = 0
        move_points = []

        while current < mid:
            a = random.uniform(2, 4)
            v0 = v
            v = v0 + a * t
            move = v0 * t + 0.5 * a * t * t
            current += move
            move_points.append(move)

        while current < distance:
            a = -random.uniform(0.5, 1.5)
            v0 = v
            v = v0 + a * t
            if v < 0.5:
                v = 0.5
            move = v0 * t + 0.5 * a * t * t
            current += move
            move_points.append(move)

        total_points = len(move_points)
        for i, move in enumerate(move_points):
            y_offset = random.randint(-2, 2) if i % random.randint(2, 4) == 0 else 0
            if i < total_points * 0.3:
                duration = random.uniform(0.01, 0.03)
            elif i > total_points * 0.7:
                duration = random.uniform(0.03, 0.08)
            else:
                duration = random.uniform(0.02, 0.05)
            if random.random() < 0.05:
                duration += random.uniform(0.05, 0.1)
            tracks.append((move, y_offset, duration))

        if random.random() < 0.7:
            tracks.append((-random.randint(1, 3), 0, 0.05))
        return tracks

    def simulate_slider_drag(self, slider_element, target_distance):
        if target_distance <= 0:
            return
        self.page.actions.move_to(slider_element).hold()
        for offset_x, offset_y, duration in self.generate_human_track(target_distance):
            self.page.actions.move(offset_x, offset_y, duration=duration / 1000)
        self.page.actions.release()

    def verify(self, type_num, image_path=None):
        """调用云码平台：type_num=1 坐标点选，2 滑块距离。"""
        image_path = image_path or self.screenshot_path
        with open(image_path, "rb") as f:
            image_b64 = base64.b64encode(f.read()).decode()

        if type_num == 1:
            data = {
                "token": self.token,
                "type": "30332",
                "direction": "top",
                "click_num": 3,
                "image": image_b64,
            }
        else:
            data = {
                "token": self.token,
                "type": "22222",
                "image": image_b64,
            }

        response = requests.post(
            JFBYM_API_URL,
            headers={"Content-Type": "application/json"},
            json=data,
            timeout=30,
        ).json()
        print(response)
        return response["data"]["data"]

    def handle_slider(
            self,
            capt_ele=None,
            slider_ele=None,
            drag_offset=1.5,
            inject_track_js=True,
    ):
        """
        完整滑块流程：截图 -> 打码 -> 注入轨迹 -> 拖动。
        成功返回 True，失败返回 False。
        """
        capt_ele = capt_ele or self.page.ele(CAPTCHA_IMG_XPATH, timeout=2)
        if not capt_ele:
            print("未找到验证码背景图")
            return False

        capt_ele.get_screenshot(self.screenshot_path)

        distance = self.verify(2)
        try:
            distance = float(distance)
        except (TypeError, ValueError):
            print(f"滑块距离格式异常：{distance}")
            return False
        print(f"滑块距离（接口原始值）：{distance}")

        slider_ele = slider_ele or self.page.ele(SLIDER_IMG_XPATH, timeout=2)
        if not slider_ele:
            print("未找到滑块")
            return False

        drag_distance = self._normalize_slider_distance(
            distance,
            capt_ele=capt_ele,
            slider_ele=slider_ele,
            screenshot_path=self.screenshot_path,
        )

        drag_px = max(0.0, float(drag_distance) - drag_offset)

        if inject_track_js:
            result = simulate(math.ceil(int(drag_distance)))
            self.page.run_js("window.xxxll = {};".format(result))
            time.sleep(3)

        self.simulate_slider_drag(slider_ele, drag_px)
        return True

    def has_captcha_modal(self):
        return bool(self.page.ele(CAPTCHA_MODAL_XPATH, timeout=1))

    def has_moveslide_modal(self):
        capt_cha = "xpath://img[@class='move-img']"
        return bool(self.page.ele(capt_cha, timeout=1))

    def _wait_for_slider(self, rounds=5):
        if self.has_moveslide_modal():
            return True
        for _ in range(rounds):
            time.sleep(1)
            if self.has_moveslide_modal():
                return True
        return False

    def handle_slider_until_gone(self, max_attempts=3, wait_after=2, slider_wait_rounds=5, **handle_kwargs):
        """
        处理滑块并在每次处理后检查验证码是否仍在页面。
        验证码消失返回 True；达到 max_attempts 仍存在返回 False。
        """
        if not self.has_captcha_modal():
            return True

        for attempt in range(1, max_attempts + 1):
            print(f"验证码处理 第 {attempt}/{max_attempts} 次")
            if not self._wait_for_slider(slider_wait_rounds):
                print("验证码弹窗在，但滑块元素未出现（可能非滑块类型）")
                if attempt >= max_attempts:
                    return False
                time.sleep(wait_after)
                continue

            ok = self.handle_slider(**handle_kwargs)
            if not ok:
                print("本次滑块处理失败")
            else:
                time.sleep(wait_after)
                if not self.has_captcha_modal():
                    print("验证码已消失")
                    return True
                print("验证码仍在页面")

            if attempt >= max_attempts:
                break
            time.sleep(wait_after)

        if self.has_captcha_modal():
            print(f"验证码处理失败，已尝试 {max_attempts} 次，弹窗仍在")
            return False
        return True


def handle_jd_slider_captcha(
    page,
    token=None,
    screenshot_path=None,
    max_attempts=3,
    wait_after=2,
    slider_wait_rounds=5,
    pause_listen=True,
    pause_listen_clear=False,
    **kwargs,
):
    """
    便捷入口：处理当前页面的京东滑块验证码，最多重试 max_attempts 次。
    返回 True：无需验证码或已成功通过；False：处理失败或验证码仍在。
    pause_listen：auto_crawl 等已开启 listen 的场景建议 True。
    pause_listen_clear：暂停时是否清空监听队列；采集中应为 False，避免丢掉首屏 wareList。
    """
    handler = JdCaptchaHandler(page, token=token, screenshot_path=screenshot_path)
    if not handler.has_captcha_modal():
        return True

    if pause_listen:
        with pause_page_listen(page, clear=pause_listen_clear):
            return handler.handle_slider_until_gone(
                max_attempts=max_attempts,
                wait_after=wait_after,
                slider_wait_rounds=slider_wait_rounds,
                **kwargs,
            )

    return handler.handle_slider_until_gone(
        max_attempts=max_attempts,
        wait_after=wait_after,
        slider_wait_rounds=slider_wait_rounds,
        **kwargs,
    )