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#!/usr/bin/python
"""
How many planes are in the air?
Will they get grounded when everyone panics from COVID-19?
Let's find out.
Author: SJ Pratt
Date: 29 February 2020
"""
from opensky_api import OpenSkyApi as sky
import statistics as stat
import pandas as pd
import datetime as dt
# epoch = dt.datetime.utcfromtimestamp(0)
#def unixSecs(myTime):
# return (myTime - epoch).total_seconds()
def isNum(item):
"""
Not used - exporting data to R
"""
try:
float(item)
return True
except:
return False
def stats(vals):
"""
Assumes vals is a list of numerics
(I ended up not using this function - export data to csv and let R handle it)
"""
rawLen = len(vals)
vals = [x for x in vals if isNum(x)]
minimum = min(vals)
maximum = max(vals)
n = len(vals)
nans = rawLen - n
mean = stat.mean(vals)
median = stat.median(vals)
return {'n':n, 'min':minimum, 'max':maximum, 'mean':mean, 'median':median, 'NaN': nans}
def makeListofDicts(StateVector):
"""
Just get the data back from the complicated object FFS
"""
data = [] # empty list. Each element will be a dict
for plane in StateVector:
data.append(plane.__dict__)
return data
planes = sky().get_states().states
planeDict = makeListofDicts(planes)
planeFrame = pd.DataFrame.from_dict(planeDict)
planeFrame['timeStamp'] = "{:%Y%m%dT%H%M}".format(dt.datetime.now())
with open('covidPlanes.csv', 'a') as out:
planeFrame.to_csv(out, mode = 'a', index = False, header = out.tell()==0)
# Brief info for Journald
flying = [x for x in planes if not x.on_ground]
print('Planes: {} Flying: {}'.format(len(planes), len(flying)))
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