def ip_code_count(datacore, *args, **kwargs):
"""
根据ip和状态码返回对应的访问次数
"""
aim_data = datacore.groupby('ip')['StatusCode'].value_counts().rename(
'count').sort_values(ascending=False)
return data_after_argument(aim_data, *args, **kwargs)
def ip_count(datacore, *args, **kwargs):
"""
根据ip返回对应的访问次数
"""
aim_data = datacore['ip'].value_counts().rename('count').sort_values(
ascending=False)
return data_after_argument(aim_data, *args, **kwargs)
def ip_traffic(datacore, *args, **kwargs):
"""
根据ip返回对应的流量
"""
aim_data = datacore.groupby('ip').sum()['TrafficSize'].sort_values(
ascending=False)
return data_after_argument(aim_data, *args, **kwargs)
def data_by_factor(datacore, *args, **kwargs):
"""
根据限制条件返回清洗后的日志数据
"""
aim_data = datacore
# 过滤指定的状态码，支持nxx的形式
if kwargs.get('status_code'):
if str(kwargs['status_code'])[1:] == 'xx':
aim_data = aim_data[
(int(kwargs.get('status_code')[0]) *
100 <= aim_data.StatusCode)
& (aim_data.StatusCode <
(int(kwargs.get('status_code')[0]) + 1) * 100)]
else:
aim_data = aim_data[aim_data.StatusCode == int(
kwargs['status_code'])]
if kwargs.get('url'):
aim_data = aim_data[aim_data.url == kwargs.get('url')]
if kwargs.get('ip'):
aim_data = aim_data[aim_data.ip == kwargs.get('ip')]
if kwargs.get('referer'):
aim_data = aim_data[aim_data.referer == kwargs.get('referer')]
if kwargs.get('start_time'):
aim_data = aim_data[
kwargs.get('start_time') < aim_data.request_time.values]
if kwargs.get('end_time'):
aim_data = aim_data[
aim_data.request_time.values < kwargs.get('end_time')]
return data_after_argument(aim_data, *args, **kwargs)
def time_traffic(datacore, *args, **kwargs):
"""
返回指定时间段产生的流量
"""
aim_data = datacore.groupby('request_time')['TrafficSize'].sum()
aim_data = series_to_dataframe(aim_data, (['time'], 'traffic'))
if kwargs.get('start_time'):
aim_data = aim_data[kwargs.get('start_time') < aim_data['time']]
if kwargs.get('end_time'):
aim_data = aim_data[aim_data['time'] < kwargs.get('end_time')]
return data_after_argument(aim_data, *args, **kwargs)
def time_count(datacore, *args, **kwargs):
"""
返回指定时间段对应的访问次数
"""
aim_data = datacore['request_time'].value_counts(
sort=False).rename('count').sort_index()
aim_data = series_to_dataframe(aim_data, (['time'], 'count'))
if kwargs.get('start_time'):
aim_data = aim_data[kwargs.get('start_time') < aim_data['time']]
if kwargs.get('end_time'):
aim_data = aim_data[aim_data['time'] < kwargs.get('end_time')]
return data_after_argument(aim_data, *args, **kwargs)
