update

pages/2_📚_PDF预览.py

@@ -2,7 +2,7 @@ from meutils.pipe import *
 from appzoo.streamlit_app import Page
 
 import streamlit as st
-
+import streamlit.components.v1 as components
 
 class MyPage(Page):
     """
@@ -10,6 +10,8 @@ class MyPage(Page):
     """
 
     def main(self):
+
+
         with st.form("PDF"):
             file = st.file_uploader("选择待上传的PDF文件", type=['pdf', 'docx', 'xlsx'])
 

pages/889_机器监控.py

@@ -0,0 +1,118 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Project      : Python.
+# @File         : 991_streamlit_apex_charts
+# @Time         : 2022/10/17 上午10:48
+# @Author       : yuanjie
+# @WeChat       : meutils
+# @Software     : PyCharm
+# @Description  : 
+
+
+import psutil
+import streamlit as st
+import time
+import datetime
+from streamlit_autorefresh import st_autorefresh
+from streamlit_apex_charts import bar_chart, pie_chart
+import pandas as pd
+import platform
+import os
+
+
+st.set_page_config(page_title="系统信息查看器", page_icon="💻", layout="wide")
+
+#st_autorefresh(interval=5000, limit=100000, key="Mr.R")
+
+st.header("系统信息查看器")
+base_infor = [[datetime.datetime.now().strftime("%Y-%m-%d %H: %M: %S"),str(psutil.users()[0][0]),platform.platform()]]
+df_base_infor = pd.DataFrame(base_infor, columns=["当前时间","登陆者","操作系统"])
+st.table(df_base_infor)
+
+#获取网卡名称
+def get_key():
+    key_info = psutil.net_io_counters(pernic=True).keys()  # 获取网卡名称
+    recv = {}
+    sent = {}
+    for key in key_info:
+        recv.setdefault(key, psutil.net_io_counters(pernic=True).get(key).bytes_recv)  # 各网卡接收的字节数
+        sent.setdefault(key, psutil.net_io_counters(pernic=True).get(key).bytes_sent)  # 各网卡发送的字节数
+    return key_info, recv, sent
+
+#获取网卡速率
+def get_rate(func):
+    key_info, old_recv, old_sent = func()  # 上一秒收集的数据
+    time.sleep(1)
+    key_info, now_recv, now_sent = func()  # 当前所收集的数据
+    net_in = {}
+    net_out = {}
+    for key in key_info:
+        net_in.setdefault(key, (now_recv.get(key) - old_recv.get(key)) / 1024)  # 每秒接收速率
+        net_out.setdefault(key, (now_sent.get(key) - old_sent.get(key)) / 1024) # 每秒发送速率
+    return key_info, net_in, net_out
+
+
+c1, c2, c3 = st.columns(3)
+
+with c1:
+    #内存
+    mem = psutil.virtual_memory()
+    zj = float(mem.total) / 1024 / 1024 / 1024
+    ysy = float(mem.used) / 1024 / 1024 / 1024
+    kx = float(mem.free) / 1024 / 1024 / 1024
+
+    data_neicun = [[round(ysy,2),round(kx, 2)]]
+    df_neicun = pd.DataFrame(data_neicun, columns=["已用内存","空闲内存"])
+    pie_chart("内存使用情况(GB)", df_neicun)
+
+
+    #CPU
+    cpu_liyonglv = (str(psutil.cpu_percent(1))) + '%'
+    cpu_data = [[cpu_liyonglv]]
+    df_cpu = pd.DataFrame(cpu_data, columns=["CPU利用率"])
+    bar_chart("CPU利用率(%)", df_cpu)
+
+with c2:
+    #磁盘
+    dk = psutil.disk_usage('/')
+    total = dk.total / 1024 / 1024 / 1024
+    used = dk.used / 1024 / 1024 / 1024
+    free = dk.free / 1024 / 1024 / 1024
+
+    cipan_shiyong = [[used, free]]
+    df_cipan = pd.DataFrame(cipan_shiyong, columns=["已使用磁盘大小","空闲磁盘大小"])
+    pie_chart("磁盘使用率(%)", df_cipan)
+
+    #网络速率
+    key_info, net_in, net_out = get_rate(get_key)
+    wangka_liuliang = []
+    for key in key_info:
+             wangka_liuliang.append([net_in.get(key),net_out.get(key)])
+    speed_internet = wangka_liuliang
+    df_speed = pd.DataFrame(speed_internet, columns=["下行速率","上行速率"])
+    bar_chart("网络速率(kb/s)", df_speed)
+
+
+
+with c3:
+    #进程信息
+    pids = psutil.pids()
+    process = []
+    for pid in pids:
+        p = psutil.Process(pid)
+        process_name = p.name()
+        process.append([pid, process_name, p.is_running()])
+
+    df_process = pd.DataFrame(process, columns=["PID","进程名","是否还在运行"])
+    st.dataframe(df_process)
+
+    # #已安装软件
+    # import wmi
+    # c = wmi.WMI()
+    # software_list = []
+    # for s in c.Win32_Product():
+    #     software_list.append([s.Caption, s.Vendor, s.Version])
+    # if len(software_list)>1:
+    #     st.dataframe(pd.DataFrame(software_list, columns=["名称","发布人","版本"]))
+    # else:
+    #     st.info("正在导出已安装的软件程序列表")

pages/991_streamlit_apex_charts.py

@@ -1,118 +1,19 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-# @Project      : Python.
-# @File         : 991_streamlit_apex_charts
-# @Time         : 2022/10/17 上午10:48
-# @Author       : yuanjie
-# @WeChat       : meutils
-# @Software     : PyCharm
-# @Description  : 
-
-
-import psutil
-import streamlit as st
-import time
-import datetime
-from streamlit_autorefresh import st_autorefresh
-from streamlit_apex_charts import bar_chart, pie_chart
+import numpy as np
 import pandas as pd
-import platform
-import os
-
-
-st.set_page_config(page_title="系统信息查看器", page_icon="💻", layout="wide")
-
-#st_autorefresh(interval=5000, limit=100000, key="Mr.R")
-
-st.header("系统信息查看器")
-base_infor = [[datetime.datetime.now().strftime("%Y-%m-%d %H: %M: %S"),str(psutil.users()[0][0]),platform.platform()]]
-df_base_infor = pd.DataFrame(base_infor, columns=["当前时间","登陆者","操作系统"])
-st.table(df_base_infor)
-
-#获取网卡名称
-def get_key():
-    key_info = psutil.net_io_counters(pernic=True).keys()  # 获取网卡名称
-    recv = {}
-    sent = {}
-    for key in key_info:
-        recv.setdefault(key, psutil.net_io_counters(pernic=True).get(key).bytes_recv)  # 各网卡接收的字节数
-        sent.setdefault(key, psutil.net_io_counters(pernic=True).get(key).bytes_sent)  # 各网卡发送的字节数
-    return key_info, recv, sent
-
-#获取网卡速率
-def get_rate(func):
-    key_info, old_recv, old_sent = func()  # 上一秒收集的数据
-    time.sleep(1)
-    key_info, now_recv, now_sent = func()  # 当前所收集的数据
-    net_in = {}
-    net_out = {}
-    for key in key_info:
-        net_in.setdefault(key, (now_recv.get(key) - old_recv.get(key)) / 1024)  # 每秒接收速率
-        net_out.setdefault(key, (now_sent.get(key) - old_sent.get(key)) / 1024) # 每秒发送速率
-    return key_info, net_in, net_out
+import streamlit as st
+from streamlit_apex_charts import line_chart, bar_chart, pie_chart, area_chart, radar_chart
 
+st.set_page_config(layout="wide")
 
-c1, c2, c3 = st.columns(3)
+df = pd.DataFrame(np.random.randint(1, 10, size=(10, 3)), columns=['Apple', 'Microsoft', 'Google'])
 
+line_chart('Line chart', df)
+c1, c2 = st.columns(2)
 with c1:
-    #内存
-    mem = psutil.virtual_memory()
-    zj = float(mem.total) / 1024 / 1024 / 1024
-    ysy = float(mem.used) / 1024 / 1024 / 1024
-    kx = float(mem.free) / 1024 / 1024 / 1024
-
-    data_neicun = [[round(ysy,2),round(kx, 2)]]
-    df_neicun = pd.DataFrame(data_neicun, columns=["已用内存","空闲内存"])
-    pie_chart("内存使用情况(GB)", df_neicun)
-
-
-    #CPU
-    cpu_liyonglv = (str(psutil.cpu_percent(1))) + '%'
-    cpu_data = [[cpu_liyonglv]]
-    df_cpu = pd.DataFrame(cpu_data, columns=["CPU利用率"])
-    bar_chart("CPU利用率(%)", df_cpu)
-
+    bar_chart('Bar chart', df)
+    pie_chart('Pie chart', df)
 with c2:
-    #磁盘
-    dk = psutil.disk_usage('/')
-    total = dk.total / 1024 / 1024 / 1024
-    used = dk.used / 1024 / 1024 / 1024
-    free = dk.free / 1024 / 1024 / 1024
-
-    cipan_shiyong = [[used, free]]
-    df_cipan = pd.DataFrame(cipan_shiyong, columns=["已使用磁盘大小","空闲磁盘大小"])
-    pie_chart("磁盘使用率(%)", df_cipan)
-
-    #网络速率
-    key_info, net_in, net_out = get_rate(get_key)
-    wangka_liuliang = []
-    for key in key_info:
-             wangka_liuliang.append([net_in.get(key),net_out.get(key)])
-    speed_internet = wangka_liuliang
-    df_speed = pd.DataFrame(speed_internet, columns=["下行速率","上行速率"])
-    bar_chart("网络速率(kb/s)", df_speed)
-
-
-
-with c3:
-    #进程信息
-    pids = psutil.pids()
-    process = []
-    for pid in pids:
-        p = psutil.Process(pid)
-        process_name = p.name()
-        process.append([pid, process_name, p.is_running()])
-
-    df_process = pd.DataFrame(process, columns=["PID","进程名","是否还在运行"])
-    st.dataframe(df_process)
+    area_chart('Area chart', df)
+    radar_chart('Radar chart', df)
 
-    # #已安装软件
-    # import wmi
-    # c = wmi.WMI()
-    # software_list = []
-    # for s in c.Win32_Product():
-    #     software_list.append([s.Caption, s.Vendor, s.Version])
-    # if len(software_list)>1:
-    #     st.dataframe(pd.DataFrame(software_list, columns=["名称","发布人","版本"]))
-    # else:
-    #     st.info("正在导出已安装的软件程序列表")
+# https://discuss.streamlit.io/t/new-component-streamlit-apex-charts/18769/3

pages/997_streamlit_aggrid.py

@@ -0,0 +1,16 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Project      : Python.
+# @File         : 997_streamlit_aggrid
+# @Time         : 2022/10/17 下午1:14
+# @Author       : yuanjie
+# @WeChat       : meutils
+# @Software     : PyCharm
+# @Description  : 
+
+
+from st_aggrid import AgGrid
+import pandas as pd
+
+df = pd.read_csv('./data/airline-safety.csv')
+AgGrid(df)

pages/998_streamlit_agraph.py

@@ -0,0 +1,49 @@
+import streamlit as st
+from streamlit_agraph import agraph, Node, Edge, Config
+
+
+c1, c2 = st.columns(2)
+
+
+with c1:
+
+    nodes = []
+    edges = []
+    nodes.append(Node(id="Spiderman",
+                      label="Peter Parker",
+                      size=25,
+                      shape="circularImage",
+                      image="http://marvel-force-chart.surge.sh/marvel_force_chart_img/top_spiderman.png")
+                 )  # includes **kwargs
+    nodes.append(Node(id="Captain_Marvel",
+                      size=25,
+                      shape="circularImage",
+                      image="http://marvel-force-chart.surge.sh/marvel_force_chart_img/top_captainmarvel.png")
+                 )
+    edges.append(Edge(source="Captain_Marvel",
+                      label="friend_of",
+                      target="Spiderman",
+                      # **kwargs
+                      )
+                 )
+
+    config = Config(width=500,
+                    height=500,
+                    # **kwargs
+                    )
+
+    return_value = agraph(nodes=nodes, edges=edges, config=config)
+
+with c2:
+    # Currently not workin since update to agraph 2.0 - work in progress
+    from rdflib import Graph
+    from streamlit_agraph import TripleStore, agraph
+
+    graph = Graph()
+    graph.parse("http://www.w3.org/People/Berners-Lee/card")
+    store = TripleStore()
+
+    for subj, pred, obj in graph:
+        store.add_triple(subj, pred, obj, "")
+
+    agraph(list(store.getNodes()), list(store.getEdges()), config)

requirements.txt

@@ -10,3 +10,6 @@ https://mirror.baidu.com/pypi/packages/78/38/76a3357c4adb31d0074bb7adb8c4c813830
 streamlit_chat
 streamlit_text_rating
 streamlit_echarts
+streamlit-aggrid
+streamlit-agraph
+rdflib