from django.http import JsonResponse
from django.shortcuts import render
from .utils import *
import logging
from django.conf import settings
import json
from pyecharts import options
from pyecharts.charts import Line, Page, Pie
logger = logging.getLogger(__name__)
def get_xaxis_days(days=60):
"""
获取 X 坐标，按天。取两个月数据
"""
xaxis_days = []
for i in range(0, days):
xaxis_days.append(time.strftime("%Y%m%d", time.localtime(time.time() - i * 86400)))
xaxis_days.sort()
return xaxis_days
def api_profile_line_chart() -> Line:
"""
接口平均耗时
:return:
"""
xaxis = get_xaxis_days(days=10)
apis = list(filter(lambda x: x, R.smembers(settings.REDIS_API_KEY)))
line = (
Line()
.add_xaxis(xaxis)
.set_global_opts(title_opts=options.TitleOpts(title="API 耗时走势"),
yaxis_opts=options.AxisOpts(
is_scale=True,
splitline_opts=options.SplitLineOpts(is_show=True)
),
tooltip_opts=options.TooltipOpts(trigger='axis'),
)
)
for api in apis:
if api in get_profile_apis():
api_redis_keys = [settings.REDIS_API_AVG_KEY % (api, day) for day in xaxis]
api_profile = R.mget(*api_redis_keys)
line.add_yaxis(api, api_profile, is_connect_nones=True, is_smooth=True,
label_opts=options.LabelOpts(is_show=False))
return line.dump_options()
def uv_line_chart() -> Line:
"""
UV折线图，包括总 UV、新用户 UV、注册 UV
"""
xaxis = get_xaxis_days()
uv_all_redis_keys = [settings.REDIS_UV_ALL_KEY % day for day in xaxis]
uv_new_redis_keys = [settings.REDIS_UV_NEW_KEY % day for day in xaxis]
uv_reg_redis_keys = [settings.REDIS_REG_KEY % day for day in xaxis]
uv_all = R.mget(*uv_all_redis_keys)
uv_new = R.mget(*uv_new_redis_keys)
uv_reg = R.mget(*uv_reg_redis_keys)
line = (
Line()
.add_xaxis(xaxis)
.add_yaxis("总用户数（访问设备）", uv_all, is_connect_nones=True, is_smooth=True)
.add_yaxis("新用户数（一周未访问）", uv_new, is_connect_nones=True, is_smooth=True)
.add_yaxis("注册用户数", uv_reg, is_connect_nones=True, is_smooth=True)
.set_global_opts(title_opts=options.TitleOpts(title="用户数走势"),
yaxis_opts=options.AxisOpts(
is_scale=True,
splitline_opts=options.SplitLineOpts(is_show=True)
),
tooltip_opts=options.TooltipOpts(trigger='axis'),
)
.dump_options()
)
return line
def refer_pv_line_chart() -> Line:
"""
UV折线图，外域的每天流量趋势
"""
xaxis = get_xaxis_days()
uv_zhihu_redis_keys = [settings.REDIS_REFER_PV_DAY_KEY % ('link.zhihu.com', day) for day in xaxis]
uv_ryf_redis_keys = [settings.REDIS_REFER_PV_DAY_KEY % ('www.ruanyifeng.com', day) for day in xaxis]
uv_github_redis_keys = [settings.REDIS_REFER_PV_DAY_KEY % ('github.com', day) for day in xaxis]
uv_baidu_redis_keys = [settings.REDIS_REFER_PV_DAY_KEY % ('www.baidu.com', day) for day in xaxis]
uv_google_redis_keys = [settings.REDIS_REFER_PV_DAY_KEY % ('www.google.com', day) for day in xaxis]
uv_wanqu_redis_keys = [settings.REDIS_REFER_PV_DAY_KEY % ('wanqu.co', day) for day in xaxis]
uv_zhihu = R.mget(*uv_zhihu_redis_keys)
uv_ryf = R.mget(*uv_ryf_redis_keys)
uv_github = R.mget(*uv_github_redis_keys)
uv_baidu = R.mget(*uv_baidu_redis_keys)
uv_google = R.mget(*uv_google_redis_keys)
uv_wanqu = R.mget(*uv_wanqu_redis_keys)
line = (
Line()
.add_xaxis(xaxis)
.add_yaxis("zhihu", uv_zhihu, is_connect_nones=True, is_smooth=True)
.add_yaxis("ruanyifeng", uv_ryf, is_connect_nones=True, is_smooth=True)
.add_yaxis("github", uv_github, is_connect_nones=True, is_smooth=True)
.add_yaxis("baidu", uv_baidu, is_connect_nones=True, is_smooth=True)
.add_yaxis("google", uv_google, is_connect_nones=True, is_smooth=True)
.add_yaxis("wanqu", uv_wanqu, is_connect_nones=True, is_smooth=True)
.set_global_opts(title_opts=options.TitleOpts(title="Referer各域名PV走势"),
yaxis_opts=options.AxisOpts(
is_scale=True,
splitline_opts=options.SplitLineOpts(is_show=True)
),
tooltip_opts=options.TooltipOpts(trigger='axis'),
)
.dump_options()
)
return line
def refer_pie_chart() -> Pie:
refer_hosts = list(filter(lambda x: x, R.smembers(settings.REDIS_REFER_ALL_KEY)))
refer_host_pv_keys = [settings.REDIS_REFER_PV_KEY % host for host in refer_hosts]
c = (
Pie()
.add(
"",
[list(z) for z in zip(refer_hosts, R.mget(*refer_host_pv_keys)) if int(z[1]) > 100],
# radius=["30%", "75%"],
# rosetype="radius",
)
.set_global_opts(
title_opts=options.TitleOpts(title="Referer来源占比"),
legend_opts=options.LegendOpts(
type_="scroll", pos_left="80%", orient="vertical"
),
)
.set_series_opts(label_opts=options.LabelOpts(formatter="{b}: {c}"))
.dump_options()
)
return c
def get_uv_chart_data(request):
return JsonResponse(json.loads(uv_line_chart()))
def get_refer_pie_data(request):
return JsonResponse(json.loads(refer_pie_chart()))
def get_refer_pv_chart_data(request):
return JsonResponse(json.loads(refer_pv_line_chart()))
def get_api_profile_chart_data(request):
return JsonResponse(json.loads(api_profile_line_chart()))
def dashboard(request):
return render(request, 'dashboard/index.html')
def get_warn_log(request):
warn_log_file = settings.LOGGING['handlers']['my_warn']['filename']
logs = list(reversed(open(warn_log_file).read().split('\n')))[:500]
logs = [l for l in logs if l]
context = dict()
context['logs'] = logs
return render(request, 'dashboard/logs.html', context=context)
