Publish Wave app to Hugging Face

.dockerignore

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+.venv/
+.git/
+.gitignore
+.dockerignore
+Dockerfile
+README.md

Dockerfile

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+# Accept Python version during build
+ARG PYTHON_VERSION="3.8"
+
+FROM python:${PYTHON_VERSION}-slim
+
+# Install OS dependencies
+RUN apt-get update && apt-get -y upgrade \
+    && export DEBIAN_FRONTEND=noninteractive \
+    && apt-get -y install --no-install-recommends curl build-essential
+
+# Create a non-root user
+RUN useradd --create-home appuser
+USER appuser
+WORKDIR /home/appuser/app
+
+# Install Wave
+ARG WAVE_VERSION="0.20.0"
+
+ENV WAVE_HOME="/home/appuser/wave"
+RUN \
+    mkdir -p "${WAVE_HOME}" && \
+    curl -fsSL https://github.com/h2oai/wave/releases/download/v${WAVE_VERSION}/wave-${WAVE_VERSION}-linux-amd64.tar.gz | tar -C ${WAVE_HOME} -xzv 2>&1
+ENV WAVE_PATH="${WAVE_HOME}/wave-${WAVE_VERSION}-linux-amd64"
+
+# Create a virtual environment
+ENV VIRTUAL_ENV=/home/appuser/venv
+RUN python3 -m venv $VIRTUAL_ENV
+ENV PATH="$VIRTUAL_ENV/bin:$PATH"
+
+# Install Python dependencies
+COPY requirements.txt .
+RUN pip install --upgrade pip && pip install --no-cache-dir -r requirements.txt
+
+# Copy app code
+COPY --chown=appuser:appuser . .
+
+# Set permissions for the Entrypoint script
+RUN chmod +x docker-entrypoint.sh
+
+ARG PYTHON_MODULE
+ENV PYTHON_MODULE="${PYTHON_MODULE}"
+
+ENTRYPOINT [ "./docker-entrypoint.sh" ]

app.py

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+# Note: Main must be imported even though it is not used.
+from h2o_wave import Q, ui, app, main, data, on
+import numpy as np
+import pandas as pd
+import random
+import time
+import asyncio
+
+NUMBER_SENSORS = 4
+LIMIT_LEN_SHOWING = 20
+REALTIME_UPDATE = 5  # seconds
+list_data = []
+line_charts_data = []  # [(sensor_id, [data]), ...]
+for i in range(NUMBER_SENSORS):
+    line_charts_data.append((i, []))
+start_year = 1991
+while True:
+    for i in range(NUMBER_SENSORS):
+        random_value = random.uniform(1, 50)  # Generate a random value between 1 and 50
+        value = (str(start_year), random_value)
+        line_charts_data[i][1].append(value)
+    start_year += 1
+    if start_year == 2021:
+        break
+
+
+async def update_value(q: Q):
+    while True:
+        time.sleep(REALTIME_UPDATE)
+        #  TODO: Update realtime values for current stats cards
+        # value_counts = random.randint(0, 100)
+        # percentages = random.random()
+        percentages = np.random.random(NUMBER_SENSORS)
+        value_counts = np.random.randint(0, 100, NUMBER_SENSORS)
+
+        show_multiple_stats_cards(q, value_counts, percentages)
+        await q.page.save()
+
+
+async def api_get_data():
+    global list_data, line_charts_data, start_year
+    while True:
+        for i in range(NUMBER_SENSORS):
+            random_value = random.uniform(1, 50)  # Generate a random value between 1 and 50
+            value = (str(start_year), random_value)
+            line_charts_data[i][1].append(value)
+        start_year += 1
+        await asyncio.sleep(REALTIME_UPDATE)
+
+
+async def update_charts(q: Q):
+    global line_charts_data
+    while True:
+        time.sleep(REALTIME_UPDATE)
+        for sensor_data in line_charts_data:
+            sensor_id = str(sensor_data[0])
+            data = sensor_data[1]
+            limites_showing_data = LIMIT_LEN_SHOWING if len(data) > LIMIT_LEN_SHOWING else len(data)
+            show_line_graph(q, sensor_id, data[-limites_showing_data:])
+
+        percentages = np.random.random(NUMBER_SENSORS)
+        value_counts = np.random.randint(0, 100, NUMBER_SENSORS)
+        show_multiple_stats_cards(q, value_counts, percentages)
+        await q.page.save()
+
+
+def on_startup():
+    print('App started!')
+
+
+def on_shutdown():
+    print('App stopped!')
+
+
+task_data = asyncio.create_task(api_get_data())
+
+
+@app('/sensor', on_startup=on_startup, on_shutdown=on_shutdown, mode='broadcast')
+async def sever(q: Q):
+    apply_layout(q)
+    show_homepage(q)
+    # show_histograms(q, df, index=[1, 7, 8])
+
+    # await update_value(q)
+    await update_charts(q)
+    # await q.page.save()
+
+
+def show_homepage(q: Q):
+    q.page['header'] = ui.header_card(
+        box=ui.box('header', width='100%', height='86px'),
+        icon='Video360Generic',
+        icon_color='White',
+        title='AgroTrack Application',
+        subtitle='담양농업기술센터')
+
+    q.page['footer'] = ui.footer_card(
+        box='footer',
+        caption='Copyright (C) [AISeed](https://sprout-fibre-be6.notion.site/AISEED-40e62bb70c024a2c974c0a7051aca86f?pvs=4) Designed by [Blackhole](https://github.com/andrewlee1807/)')
+
+
+def apply_layout(q: Q):
+    q.page['meta'] = ui.meta_card(box='', theme='oceanic', title="SmartFarm's Sensor Dashboard",
+                                  layouts=[
+                                      ui.layout(
+                                          breakpoint='xl',
+                                          width='1600px',
+                                          zones=[
+                                              ui.zone('header'),
+                                              ui.zone('body', direction=ui.ZoneDirection.ROW, zones=[
+                                                  ui.zone('content', direction=ui.ZoneDirection.COLUMN, zones=[
+                                                      ui.zone('section1'),
+                                                      ui.zone('top', size='300px', direction=ui.ZoneDirection.ROW),
+                                                      ui.zone('section2'),
+                                                      ui.zone('bottom', direction=ui.ZoneDirection.ROW),
+                                                      ui.zone('chart1', direction=ui.ZoneDirection.ROW),
+                                                  ]),
+                                              ]),
+                                              ui.zone('footer')
+                                          ]),
+                                  ])
+
+
+## Making stats cards
+def make_stats_card_data(q: Q, column):
+    value_counts = column.value_counts()
+    total = value_counts.sum()
+    return value_counts[1], total
+
+
+# Randomly generate data for stats cards: percentage and value (randomly generated)
+
+
+def show_stats_card(q: Q, name, value_count, percentage):
+    q.page['stat_' + name] = ui.tall_gauge_stat_card(
+        box=ui.box('top', width='12.5%'),
+        title='Number of houses with ' + name,
+        value='={{intl one}}',
+        aux_value='={{intl perc style="percent" minimum_fraction_digits=2 maximum_fraction_digits=2 }}',
+        progress=percentage,
+        data=dict(one=int(value_count), perc=float(percentage)),
+        plot_color='$red'
+    )
+
+
+def show_multiple_stats_cards(q: Q, value_counts, percentages):
+    for i, j in enumerate(zip(value_counts, percentages)):
+        name = "feature_" + str(i)
+        value_count, percentage = j
+        show_stats_card(q, name, value_count, percentage)
+
+
+# Making histograms
+def make_histogram_data(values):
+    count, division = np.histogram(values)
+    return [(x, y) for x, y in zip(division.tolist(), count.tolist())]
+
+
+def show_histogram(q: Q, values, variable_name, index):
+    q.page['feat' + str(index)] = ui.tall_series_stat_card(
+        box=ui.box('bottom', width='25%'),
+        title='Linear tall series' + variable_name,
+        value='=${{intl qux minimum_fraction_digits=2 maximum_fraction_digits=2}}',
+        aux_value='={{intl quux style="percent" minimum_fraction_digits=1 maximum_fraction_digits=1}}',
+        data=dict(qux=800, quux=80 / 100),
+        plot_type='area',
+        plot_category='foo',
+        plot_value='qux',
+        plot_color='$yellow',
+        plot_data=data('foo qux', 3, rows=[[90, 0.9], [50, 0.5], [80, 0.8]]),
+        plot_zero_value=0,
+        plot_curve='smooth',
+    )
+
+
+def show_line_graph(q: Q, name, data_rows):
+    q.page['section2'] = ui.section_card(box='section2',
+                                         title='Plot of the data',
+                                         subtitle='')
+    position = 'bottom' if int(name) < 2 else 'chart1'
+    q.page[name] = ui.plot_card(
+        box=ui.box(position, width='50%'),
+        title='Sensor ' + name,
+        animate=True,
+        data=data('time value', LIMIT_LEN_SHOWING, rows=data_rows),
+        events=['select_marks'],
+        plot=ui.plot([
+            ui.mark(type='line',
+                    x_scale='time',
+                    x='=time',
+                    y='=value',
+                    y_min=0, interactive=True),
+            ui.mark(type='point',
+                    x='=time',
+                    # x='={{intl year type="time" month="numeric" day="numeric" hour="numeric" minute="numeric" hourCycle="h24" }}',
+                    y='=value',
+                    size=4,
+                    fill_color='#FFFF28',
+                    x_title='Time', y_title='Value',
+                    interactive=True),
+        ]),
+    )
+
+
+@on('select_marks')
+async def on_marks_selected(q: Q):
+    print("Click")

docker-entrypoint.sh

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+#!/usr/bin/env bash
+
+set -e
+
+export H2O_WAVE_ADDRESS="http://127.0.0.1:${PORT}"
+
+printf '\n$ ( cd %s && ./waved -listen ":%s" & )\n\n' "${WAVE_PATH}" "${PORT}"
+(cd "${WAVE_PATH}" && ./waved -listen ":${PORT}" &)
+
+sleep 3
+
+printf '\n$ wave run --no-reload --no-autostart %s\n\n' "$PYTHON_MODULE"
+
+exec wave run --no-reload --no-autostart "$PYTHON_MODULE"

requirements.txt

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+h2o-wave
+numpy
+pandas