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"COUNTRY","Country","INDICATOR","Indicator","SEX","Gender","EDUCATION_LEV","Education level","MOBILITY","Mobility status","EDUCATION_FIELD","Field","YEAR","Year","Value","Flag Codes","Flags" | |
"AUS","Australia","ENRL_SHARE_MOBILE-FIELDS","Share of mobile students by field","_T","Total","ISCED11_5","Short-cycle tertiary education","MOB","Mobile including homecoming nationals","_T","Total","9999","Latest available year",32.568,, | |
"AUS","Australia","ENRL_SHARE_MOBILE-FIELDS","Share of mobile students by field","_T","Total","ISCED11_6","Bachelor’s or equivalent level","MOB","Mobile including homecoming nationals","_T","Total","9999","Latest available year",17.26,, | |
"AUS","Australia","ENRL_SHARE_MOBILE-FIELDS","Share of mobile students by field","_T","Total","ISCED11_7","Master’s or equivalent level","MOB","Mobile including homecoming nationals","_T","Total","9999","Latest available year",56.32,, | |
"AUS","Australia","ENRL_SHARE_MOBILE-FIELDS","Share of mobile students by field","_T","Total","ISCED11_8","Doctoral or equ |
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from platypush.context import get_plugin | |
from platypush.event.hook import hook | |
from platypush.message.event.application import ApplicationStartedEvent | |
@hook(ApplicationStartedEvent) | |
def on_application_started(event, **_): | |
cam = get_plugin('camera.pi') | |
cam.start_streaming() |
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from platypush.context import get_plugin | |
from platypush.event.hook import hook | |
from platypush.message.event.custom import CustomEvent | |
@hook(CustomEvent, subtype='baby-cry', state='positive') | |
def on_baby_cry_start(event, **_): | |
pb = get_plugin('pushbullet') | |
pb.send_note(title='Baby cry status', body='The baby is crying!') |
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#!/usr/bin/python3 | |
import argparse | |
import logging | |
import os | |
import sys | |
from platypush import RedisBus | |
from platypush.message.event.custom import CustomEvent |
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import os | |
from micmon.audio import AudioDevice | |
from micmon.model import Model | |
model_dir = os.path.expanduser('~/models/sound-detect') | |
model = Model.load(model_dir) | |
audio_system = 'alsa' # Supported: alsa and pulse | |
audio_device = 'plughw:2,0' # Get list of recognized input devices with arecord -l |
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import os | |
from tensorflow.keras import layers | |
from micmon.dataset import Dataset | |
from micmon.model import Model | |
# This is a directory that contains the saved .npz dataset files | |
datasets_dir = os.path.expanduser('~/datasets/sound-detect/data') | |
# This is the output directory where the model will be saved |
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import os | |
from micmon.audio import AudioDirectory, AudioPlayer, AudioFile | |
from micmon.dataset import DatasetWriter | |
basedir = os.path.expanduser('~/datasets/sound-detect') | |
audio_dir = os.path.join(basedir, 'audio') | |
datasets_dir = os.path.join(basedir, 'data') | |
cutoff_frequencies = [250, 2500] |
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// Platypush sample user script to simplify/distill the content of a web page | |
async (app, args) => { | |
const url = await app.getURL(); | |
// Get and parse the page body through the Mercury API | |
const dom = await app.getDOM(); | |
const html = dom.body.innerHTML; | |
const response = await app.mercury.parse(url, html); | |
// Define a new DOM that contains the simplified body as well as |