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@@ -5,7 +5,7 @@ from threading import Timer
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import pandas as pd
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-from utils import RedisHelper, data_check, get_feature_data, send_msg_to_feishu
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+from utils import RedisHelper, data_check, get_feature_data, send_msg_to_feishu, request_get
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from config import set_config
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from log import Log
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config_, _ = set_config()
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@@ -14,10 +14,8 @@ redis_helper = RedisHelper()
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features = [
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'apptype',
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- 'adcode',
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- 'visit_uv_today',
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- 'visit_uv_yesterday',
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- 'b'
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+ '分组',
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+ '广告uv'
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]
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@@ -62,6 +60,53 @@ def get_threshold_record_new(ad_abtest_abcode_config, feature_df, threshold_reco
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return threshold_record_new, robot_msg_record
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+def get_threshold_record_new_by_uv(ad_abtest_abcode_config, feature_df, threshold_record, ad_target_uv):
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+ """根据广告uv计算新的阈值参数"""
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+ robot_msg_record = []
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+ threshold_record_new = threshold_record.copy()
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+ for app_type, target_uv_mapping in ad_target_uv.items():
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+ update_threshold_params = ad_abtest_abcode_config.get(int(app_type))
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+ ab_test_id = update_threshold_params.get('ab_test_id')
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+ temp_df = feature_df[feature_df['apptype'] == int(app_type)]
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+ for ab_test_group, target_uv in target_uv_mapping.items():
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+ threshold_update = update_threshold_params.get('threshold_update')
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+
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+ for app_type, config_params in ad_abtest_abcode_config.items():
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+ # 获取对应端的数据, 更新阈值参数
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+ # log_.info(f"app_type = {app_type}")
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+ temp_df = feature_df[feature_df['apptype'] == app_type]
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+ ab_test_id = config_params.get('ab_test_id')
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+ threshold_update = config_params.get('threshold_update')
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+
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+ for config_name, ab_code_list in ab_test_config.items():
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+ ad_abtest_tag = f"{ab_test_id}-{config_name}"
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+ # log_.info(f"ad_abtest_tag = {ad_abtest_tag}")
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+ if len(ab_code_list) > 0:
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+ b_mean = temp_df[temp_df['adcode'].isin(ab_code_list)]['b'].mean()
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+ if b_mean < 0:
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+ # 阈值按梯度调高
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+ gradient = up_threshold_update[config_name].get('gradient')
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+ update_range = up_threshold_update[config_name].get('update_range')
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+ b_i = (b_mean * -1) // gradient + 1
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+ threshold_param_new = float(threshold_record.get(ad_abtest_tag)) + update_range * b_i
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+ elif b_mean > 0.1:
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+ # 阈值按梯度调低
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+ gradient = down_threshold_update[config_name].get('gradient')
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+ update_range = down_threshold_update[config_name].get('update_range')
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+ b_i = (b_mean - 0.1) // gradient + 1
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+ threshold_param_new = float(threshold_record.get(ad_abtest_tag)) - update_range * b_i
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+ else:
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+ continue
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+ if threshold_param_new > 0:
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+ threshold_record_new[ad_abtest_tag] = threshold_param_new
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+ robot_msg_record.append({'appType': app_type, 'abtestTag': ad_abtest_tag,
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+ 'gradient': round(gradient, 4), 'range': round(update_range, 4),
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+ 'i': int(b_i),
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+ 'paramOld': round(float(threshold_record.get(ad_abtest_tag)), 4),
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+ 'paramNew': round(threshold_param_new, 4)})
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+ return threshold_record_new, robot_msg_record
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+
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+
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def update_threshold(threshold_record_old, threshold_record_new):
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"""更新阈值"""
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ad_mid_group_list = [group for class_key, group_list in config_.AD_MID_GROUP.items()
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@@ -87,7 +132,7 @@ def update_threshold(threshold_record_old, threshold_record_new):
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redis_helper.set_data_to_redis(key_name=key_name, value=threshold_new)
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-def update_ad_abtest_threshold(project, table, dt, ad_abtest_abcode_config):
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+def update_ad_abtest_threshold(project, table, dt, ad_abtest_abcode_config, ad_target_uv):
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# 获取当前阈值参数值
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threshold_record = redis_helper.get_data_from_redis(key_name=config_.KEY_NAME_PREFIX_AD_THRESHOLD_RECORD)
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threshold_record = eval(threshold_record)
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@@ -95,10 +140,11 @@ def update_ad_abtest_threshold(project, table, dt, ad_abtest_abcode_config):
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# 获取uv数据
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feature_df = get_feature_data(project=project, table=table, features=features, dt=dt)
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feature_df['apptype'] = feature_df['apptype'].astype(int)
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- feature_df['b'] = feature_df['b'].astype(float)
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- # 根据活跃人数变化计算新的阈值参数
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- threshold_record_new, robot_msg_record = get_threshold_record_new(
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- ad_abtest_abcode_config=ad_abtest_abcode_config, feature_df=feature_df, threshold_record=threshold_record)
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+ feature_df['广告uv'] = feature_df['广告uv'].astype(float)
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+ # 根据广告uv变化计算新的阈值参数
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+ threshold_record_new, robot_msg_record = get_threshold_record_new_by_uv(
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+ ad_abtest_abcode_config=ad_abtest_abcode_config, feature_df=feature_df,
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+ threshold_record=threshold_record, ad_target_uv=ad_target_uv)
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log_.info(f"threshold_record_new = {threshold_record_new}")
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# 更新阈值
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update_threshold(threshold_record_old=threshold_record, threshold_record_new=threshold_record_new)
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@@ -108,23 +154,54 @@ def update_ad_abtest_threshold(project, table, dt, ad_abtest_abcode_config):
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return robot_msg_record
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+def get_ad_target_uv():
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+ """获取管理后台开启自动调整阈值开关的目标uv值"""
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+ ad_target_uv = {}
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+ result = request_get(request_url=config_.GET_AD_TARGET_UV_URL)
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+ if result is None:
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+ log_.info('获取管理后台广告目标uv值失败！')
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+ return ad_target_uv
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+ if result['code'] != 0:
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+ log_.info('获取管理后台广告目标uv值失败！')
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+ return ad_target_uv
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+ if not result['content']:
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+ return ad_target_uv
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+ for item in result['content']:
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+ app_type = item['productId']
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+ target_uv_mapping = {}
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+ for uv_item in item['uvTargetDetails']:
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+ ab_group = uv_item['abParam']
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+ target_uv = uv_item['uvTarget']
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+ target_uv_mapping[ab_group] = target_uv
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+ ad_target_uv[app_type] = target_uv_mapping
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+ return ad_target_uv
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+
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+
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def timer_check():
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try:
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+ # 获取自动调整阈值参数
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ad_abtest_abcode_config = config_.AD_ABTEST_ABCODE_CONFIG
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project = config_.AD_THRESHOLD_AUTO_UPDATE_DATA.get('project')
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table = config_.AD_THRESHOLD_AUTO_UPDATE_DATA.get('table')
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now_date = datetime.datetime.today()
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now_min = datetime.datetime.now().minute
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log_.info(f"now_date: {datetime.datetime.strftime(now_date, '%Y%m%d%H')}")
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- dt = datetime.datetime.strftime(now_date - datetime.timedelta(hours=1), '%Y%m%d%H')
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+
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+ # 管理后台获取开启自动调整阈值开关的目标uv值
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+ ad_target_uv = get_ad_target_uv()
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+ log_.info(f"ad_target_uv: {ad_target_uv}")
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+ if len(ad_target_uv) == 0:
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+ return
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# 查看当前更新的数据是否已准备好
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+ dt = datetime.datetime.strftime(now_date - datetime.timedelta(hours=1), '%Y%m%d%H')
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data_count = data_check(project=project, table=table, dt=dt)
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if data_count > 0:
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log_.info(f"data count = {data_count}")
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# 数据准备好，进行更新
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robot_msg_record = update_ad_abtest_threshold(
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- project=project, table=table, dt=dt, ad_abtest_abcode_config=ad_abtest_abcode_config)
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+ project=project, table=table, dt=dt,
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+ ad_abtest_abcode_config=ad_abtest_abcode_config, ad_target_uv=ad_target_uv)
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if len(robot_msg_record) > 0:
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robot_msg_record_text = "\n".join([str(item) for item in robot_msg_record])
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msg = f"threshold_param_update: \n{robot_msg_record_text.replace(', ', ', ')}\n"
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