streamlit - Warp10 和流线型集成？

Question

两个简单的问题：

1. Warp10 是否集成到 streamlit 以提供可视化？
2. 如果是这样，请您具体说明如何实现？

提前谢谢你。

最好的祝愿，

Answer 1

流光中没有直接集成 Warp 10。

尽管 streamlit 可以处理任何类型的数据，但它主要集中在 pandas DataFrame 上。DataFrames 是表格，而 Warp 10 Geo Time Series 是时间序列。因此，即使 Warp 10 被集成到 streamlit 中，它也需要一些代码来正确格式化 streamlit 的数据以充分发挥其潜力。

话虽如此，下面是一个关于如何使用流光显示存储在 Warp 10 中的数据的小示例：

import json
from datetime import datetime, timedelta

import requests
import streamlit as st
from bokeh.palettes import Category10_10 as palette
from bokeh.plotting import figure

# Should be put in a configuration file.
fetch_endpoint = 'http://localhost:8080/api/v0/fetch'
token = 'READ'  # Change that to your actual token


def load_data_as_json(selector, start, end):
    headers = {'X-Warp10-Token': token}
    params = {'selector': selector, 'start': start, 'end': end, 'format': 'json'}
    r = requests.get(fetch_endpoint, params=params, headers=headers)
    return r.text


st.title('Warp 10 Test')

# Input parameters
selector = st.text_input('Selector', value="~streamlit.*{}")
start_date = st.date_input('Start date', value=datetime.now() - timedelta(days=10))
start_time = st.time_input('Start time')
end_date = st.date_input('End date')
end_time = st.time_input('End time')

# Convert datetime.dates and datetime.times to microseconds (default time unit in Warp 10)
start = int(datetime.combine(start_date, start_time).timestamp()) * 1000000
end = int(datetime.combine(end_date, end_time).timestamp()) * 1000000

# Make the query to Warp 10 and get back a json.
json_data = load_data_as_json(selector, start, end)
gtss = json.loads(json_data)

# Iterate through the json and populate a Bokeh graph.
p = figure(title='GTSs', x_axis_label='time', y_axis_label='value')
for gts_index, gts in enumerate(gtss):
    tss = []
    vals = []
    for point in gts['v']:
        tss.append(point[0])
        vals.append(point[-1])
    p.line(x=tss, y=vals, legend_label=gts['c'] + json.dumps(gts['l']), color=palette[gts_index % len(palette)])
st.bokeh_chart(p, use_container_width=True)

# Also display the json.
st.json(json_data)