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from pythonosc import udp_client | |
from time import sleep | |
client = udp_client.SimpleUDPClient('192.168.1.126', 10023) | |
for x in range(5): | |
for i in range(9): | |
client.send_message('/ch/0'+str(i)+'/mix/on', 0) | |
client.send_message('/ch/0'+str(i)+'/mix/fader', 0.1) | |
sleep(0.5) | |
for c in range(16): | |
client.send_message('/ch/0'+str(i)+'/config/color', c) |
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%%html | |
<script> | |
requirejs.config({ | |
paths: { | |
'phidget22': ['https://unpkg.com/phidget22@^3.10/browser/phidget22'], | |
}, // strip .js ^, require adds it back | |
}); | |
var usbconn; | |
require(['phidget22'], function(phidget22) { |
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class_code = '5L' | |
value = 12 | |
from datetime import datetime | |
import requests | |
import pandas as pd | |
ethercalc_id = 'callysto' # can be the same as class_code, or randomly generated | |
base_url = 'https://ethercalc.net/' | |
post_url = base_url+'_/'+ethercalc_id |
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import pandas as pd | |
import plotly.express as px | |
url = 'http://ets.aeso.ca/ets_web/ip/Market/Reports/CSDReportServlet' | |
df = pd.read_html(url, header=0) | |
updated = df[1].columns[-1].split(': ')[1] | |
legend = df[1]['Legend'].values.tolist() | |
notes = df[1]['Legend.1'].dropna().values.tolist() |
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# download csv files from https://climateknowledgeportal.worldbank.org/download-data | |
import pandas as pd | |
import os | |
df = pd.DataFrame() | |
for root, dirs, files in os.walk('.'): | |
for name in files: | |
if name.endswith('.csv'): | |
df2 = pd.read_csv(os.path.join(root, name), skiprows=1) |
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countries = sorted(['Canada','United States','Mexico','Costa Rica','China']) | |
year = '2013' | |
import pandas as pd | |
co2 = pd.read_csv('https://docs.google.com/spreadsheets/d/1VxxG9XJNG5oFXBo_0TTCP_sQ9wEv3Oy5SEOlR_0du5c/export?gid=1415343215&format=csv') | |
electricity = pd.read_csv('https://docs.google.com/spreadsheets/d/1L9CAwtcOoG3WfGkrFOYjAByaznce-DGE1dPK-1-23PU/export?gid=1944428591&format=csv') | |
y1 = co2[co2['country'].isin(countries)][year] | |
y2 = electricity[electricity['country'].isin(countries)][year]/1000 | |
y1_name = 'Carbon Dioxide Emissions per Person' |
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import pandas as pd | |
import plotly.express as px | |
df = pd.read_html('https://en.wikipedia.org/wiki/List_of_generating_stations_in_Alberta') | |
categories = ['coal','natural gas','dual fuel','biomass','geothermal','hydroelectric','wind','solar'] | |
values = [] | |
for i, c in enumerate(categories): | |
total = int(pd.to_numeric(df[i+1]['Capacity (MW)'], errors='coerce').sum()) | |
values.append(total) | |
px.pie(names=categories, values=values) |
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// Return Halo Infinite stats for a gamertag as a json string | |
// instructions for creating your own endpoint at https://docs.autocode.com/getting-started/creating-your-first-project/creating-an-endpoint/ | |
const lib = require('lib')({token: process.env.STDLIB_SECRET_TOKEN}); | |
module.exports = async (context) => { | |
const gamertag = context.params.gamertag; | |
// if no gamertag is passed return an error | |
if (!gamertag) { | |
return { |