为streamlit提供登录界面

准备工作

pip install streamlit-authenticator

创建 YAML 文件：config.yaml

credentials:
  usernames:
    liba001:
      email: jsmith@gmail.com
      name: John Smith
      password: abc # To be replaced with hashed password
    liba002:
      email: rbriggs@gmail.com
      name: Rebecca Briggs
      password: def # To be replaced with hashed password
cookie:
  expiry_days: 365
  key: random_signature_key # Must be string
  name: random_cookie_name
preauthorized:
  emails:
  - melsby@gmail.com

使用 Hasher 模块将纯文本密码转换为哈希密码：

import streamlit_authenticator as stauth
hashed_passwords = stauth.Hasher(['abc', 'def']).generate()
print(hashed_passwords)

将 YAML 文件中的纯文本密码替换为生成的哈希密码

开始主程序

import yaml
from yaml.loader import SafeLoader
with open('config.yaml') as file:
    config = yaml.load(file, Loader=SafeLoader)

authenticator = Authenticate(
    config['credentials'],
    config['cookie']['name'],
    config['cookie']['key'],
    config['cookie']['expiry_days'],
    config['preauthorized']
)
name, authentication_status, username = authenticator.login('Login', 'main')

if authentication_status:
    authenticator.logout('Logout', 'main')
    st.write(f'Welcome *{name}*')
    st.title('Some content')
elif authentication_status == False:
    st.error('Username/password is incorrect')
elif authentication_status == None:
    st.warning('Please enter your username and password')

streamlit实时网页

import time  # to simulate a real time data, time loop

import numpy as np  # np mean, np random
import pandas as pd  # read csv, df manipulation
import plotly.express as px  # interactive charts
import streamlit as st  # 🎈 data web app development

st.set_page_config(
    page_title="Real-Time Data Science Dashboard",
    page_icon="✅",
    layout="wide",
)

# read csv from a github repo
dataset_url = "https://raw.githubusercontent.com/Lexie88rus/bank-marketing-analysis/master/bank.csv"

# read csv from a URL
@st.experimental_memo
def get_data() -> pd.DataFrame:
    return pd.read_csv(dataset_url)

df = get_data()

# dashboard title
st.title("Real-Time / Live Data Science Dashboard")

# top-level filters
job_filter = st.selectbox("Select the Job", pd.unique(df["job"]))

# creating a single-element container
placeholder = st.empty()

# dataframe filter
df = df[df["job"] == job_filter]

# near real-time / live feed simulation
for seconds in range(200):

    df["age_new"] = df["age"] * np.random.choice(range(1, 5))
    df["balance_new"] = df["balance"] * np.random.choice(range(1, 5))

    # creating KPIs
    avg_age = np.mean(df["age_new"])

    count_married = int(
        df[(df["marital"] == "married")]["marital"].count()
        + np.random.choice(range(1, 30))
    )

    balance = np.mean(df["balance_new"])

    with placeholder.container():

        # create three columns
        kpi1, kpi2, kpi3 = st.columns(3)

        # fill in those three columns with respective metrics or KPIs
        kpi1.metric(
            label="Age ⏳",
            value=round(avg_age),
            delta=round(avg_age) - 10,
        )
        
        kpi2.metric(
            label="Married Count 💍",
            value=int(count_married),
            delta=-10 + count_married,
        )
        
        kpi3.metric(
            label="A/C Balance ＄",
            value=f"$ {round(balance,2)} ",
            delta=-round(balance / count_married) * 100,
        )

        # create two columns for charts
        fig_col1, fig_col2 = st.columns(2)
        with fig_col1:
            st.markdown("### First Chart")
            fig = px.density_heatmap(
                data_frame=df, y="age_new", x="marital"
            )
            st.write(fig)
            
        with fig_col2:
            st.markdown("### Second Chart")
            fig2 = px.histogram(data_frame=df, x="age_new")
            st.write(fig2)

        st.markdown("### Detailed Data View")
        st.dataframe(df)
        time.sleep(1)

树莓派安装配置数据库mariadb-server并建库建表插入数据

sudo apt update
sudo atp upgrade -y
sudo apt-get install mariadb-server

配置

sudo mysql_secure_installation

创建数据库

建库建表

pi@raspberrypi:~ $ mysql -u root -p
Enter password: 
Welcome to the MariaDB monitor.  Commands end with ; or \g.
Your MariaDB connection id is 38
Server version: 10.5.19-MariaDB-0+deb11u2 Debian 11

Copyright (c) 2000, 2018, Oracle, MariaDB Corporation Ab and others.

Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.

MariaDB [(none)]> create database mydb;
Query OK, 1 row affected (0.001 sec)

MariaDB [(none)]> use mydb;
Database changed
MariaDB [mydb]> CREATE TABLE salesdata(
    -> user_id INT NOT NULL AUTO_INCREMENT,
    -> username VARCHAR(40) NOT NULL,
    -> password VARCHAR(40) NOT NULL,
    -> PRIMARY KEY(user_id)
    -> );


MariaDB [mydb]> show databases;
+--------------------+
| Database           |
+--------------------+
| information_schema |
| mydb               |
| mysql              |
| performance_schema |
+--------------------+
4 rows in set (0.001 sec)

MariaDB [mydb]>

向表格中插入数据

MariaDB [mydb]> INSERT INTO salesdata(username,password) VALUES("liba001","20252025");
Query OK, 1 row affected (0.004 sec)

MariaDB [mydb]>

查询数据

MariaDB [mydb]> select * from salesdata;
+---------+----------+----------+
| user_id | username | password |
+---------+----------+----------+
|       1 | liba001  | 20252025 |
+---------+----------+----------+
1 row in set (0.001 sec)

MariaDB [mydb]>