feat: Simplify firmware; Add Dashboards

08-power-quality-monitor/dashboard/.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+secrets.toml

08-power-quality-monitor/dashboard/Pipfile

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+[[source]]
+url = "https://pypi.org/simple"
+verify_ssl = true
+name = "pypi"
+
+[packages]
+altair = "*"
+pandas = "*"
+streamlit = "*"
+snowflake-connector-python = "==2.7.6"
+matplotlib = "*"
+streamlit-option-menu = "*"
+
+[dev-packages]
+
+[requires]
+python_version = "3.9"

08-power-quality-monitor/dashboard/Power_Monitor.py

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+import streamlit as st
+import pandas as pd
+import numpy as np
+import snowflake.connector
+
+hours_in_year = 8760
+elec_emission_factor = 0.85
+
+# Initialize connection.
+@st.cache_resource
+def init_connection():
+    return snowflake.connector.connect(**st.secrets["snowflake"])
+
+conn = init_connection()
+
+power_cols = ['Serial Number', 'Device ID', 'Created', 'Apparent Power', 'Frequency', 'Last Current', 'Last Power', 'Power Factor', 'Reactive Power']
+device_cols = ['Device ID', 'Serial Number', 'Maximum Current', 'Maximum Power', 'Maximum Voltage', 'Maximum Power Factor', 'Maximum Reactive Power']
+
+# Perform query of Snowflake database.
+@st.cache_data(ttl=600)
+def run_query(query):
+    print(f'Running query: {query}')
+
+    with conn.cursor() as cur:
+        cur.execute(query)
+        return cur.fetchall()
+
+# queries to run every time we load the page
+devices_query = run_query("select * from devices_vw;")
+
+# Get data from POWER_VW based on options.
+def get_data():
+    if len(sort) > 0:
+        # escape single quotes
+        sort_clean = sort.replace("'", "''")
+        query = f'select Serial_Number AS "Serial Number", Device as "Device ID", Created, APPARENT_POWER as "Apparent Power", Frequency, LAST_CURRENT as "Last Current", LAST_POWER as "Last Power", POWER_FACTOR as "Power Factor", REACTIVE_POWER as "Reactive Power" from POWER_VW where SERIAL_NUMBER = \'{sort_clean}\' AND CREATED IS NOT NULL order by CREATED desc limit {num_records};'
+    else:
+        query = f'select Serial_Number AS "Serial Number", Device as "Device ID", Created, APPARENT_POWER as "Apparent Power", Frequency, LAST_CURRENT as "Last Current", LAST_POWER as "Last Power", POWER_FACTOR as "Power Factor", REACTIVE_POWER as "Reactive Power" from POWER_VW WHERE CREATED IS NOT NULL order by CREATED desc limit {num_records};'
+    return run_query(query)
+
+with st.sidebar:
+    # Get list of devices and serial numbers for the Sort by Device option.
+    device_rows = devices_query
+    device_rows = sorted(device_rows, key=lambda x: x[0])
+
+    # Get keys from device_rows.
+    device_names = [row[1] for row in device_rows]
+    device_keys = [row[0] for row in device_rows]
+
+    """
+    ### Options
+    """
+    num_records = st.slider('Records to fetch?', 10, 1000, 100)
+    sort = st.selectbox('Device',options=device_names, key=device_keys[0])
+    show_map = st.checkbox('Show map?', False)
+    show_charts = st.checkbox('Show charts?', True)
+    show_table_data = st.checkbox('Show table data?', False)
+
+
+"""
+# Blues Power Monitoring Demo
+"""
+devices_df = pd.DataFrame(device_rows, columns=device_cols)
+
+st.dataframe(devices_df, hide_index=True, use_container_width=True)
+
+if show_map:
+    """
+    ### Power Monitor Device Locations
+    """
+    device_locations_query = run_query("select * from device_locations_vw;")
+    locations_cols = ['Device ID', 'Serial Number', 'latitude', 'longitude']
+
+    power_locations = pd.DataFrame(device_locations_query, columns=locations_cols)[["latitude", "longitude"]]
+
+    st.map(power_locations)
+
+if show_table_data or show_charts:
+    # find the index of the selected device
+    device_index = device_names.index(sort)
+    st.write(f'### Data for {sort} ({device_keys[device_index]})')
+
+    data = get_data()
+    power_df = pd.DataFrame(data, columns=power_cols)
+
+    kwh_per_year = round((power_df['Last Power'][0] / 1000) * hours_in_year, 2)
+    last_kwh_per_year = round((power_df['Last Power'][1] / 1000) * hours_in_year, 2)
+
+    co2_per_year = round(kwh_per_year * elec_emission_factor, 2)
+    last_co2_per_year = round(last_kwh_per_year * elec_emission_factor, 2)
+
+    col1, col2 = st.columns(2)
+
+    col1.metric(label="Projected Annual Emissions 🌲", value=f"{co2_per_year} Kg of CO2", delta=f"{round(co2_per_year-last_co2_per_year, 2)} Kg of CO2", delta_color="inverse")
+    col2.metric(label="Projected Annual Power Use 🔌", value=f"{kwh_per_year} KwH", delta=f"{(kwh_per_year-last_kwh_per_year)} KwH", delta_color="inverse")
+
+    st.divider()
+
+    col1, col2, col3 = st.columns(3)
+
+    col1.metric(label="Apparent Power", value=power_df['Apparent Power'][0], delta=(power_df['Apparent Power'][0]-power_df['Apparent Power'][1]), delta_color="inverse")
+    col2.metric(label="Last Power", value=f"{power_df['Last Power'][0]} Watts", delta=f"{(power_df['Last Power'][0]-power_df['Last Power'][1])} Watts", delta_color="inverse")
+    col3.metric(label="Reactive Power", value=f"{power_df['Reactive Power'][0]} VAR", delta=f"{round(power_df['Reactive Power'][0]-power_df['Reactive Power'][1] ,2)} VAR", delta_color="inverse")
+
+    if show_table_data:
+       st.dataframe(power_df, hide_index=True)
+
+    if show_charts:
+        st.area_chart(data=power_df[['Apparent Power', 'Last Power','Created']], x='Created', y=['Apparent Power', 'Last Power'])
+        st.area_chart(data=power_df[['Reactive Power','Created']], x='Created', y=['Reactive Power'])

08-power-quality-monitor/dashboard/pages/About.py

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+import streamlit as st
+
+st.markdown(
+"""
+# Blues Power Monitoring Demo!
+
+This demo pulls data from Snowflake that was routed from [this Notehub project](https://notehub.io/project/app:eb43a9ae-0b78-4508-93c2-d39dc511fb70).
+
+The application in question is a Notecard and Notecarrier-F-based device. The Swan-powered host
+application takes readings from a connected Dr. Wattson device that monitors
+power through a connected supply and sends those readings to the Notecard.
+
+Raw JSON is routed to Snowflake using the Snowflake SQL API and transformed into
+a structured data tables using views, with a view for `power.qo`, `_session.qo`
+events.
+
+"""
+)

08-power-quality-monitor/dashboard/requirements.txt

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+altair
+pandas
+streamlit==1.23.0
+snowflake-connector-python==2.7.6
+matplotlib