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from datetime import datetime, timedelta
base = datetime.today()
numdays = 5
date_list = [base - timedelta(days=x) for x in range(0,numdays)]

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DATES = np.array([])
for i in dates:
     DATES = np.append(DATES,datetime.strptime(i,'%m/%d/%Y %H%M'))

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import numpy as np
import datetime
def datestr_to_datetime(x):
    return datetime.datetime.strptime(x,'%Y-%m-%dT%H:%M:%SZ')

# where dates is some list of dates as a string... 
# vectorize the function
converttime = np.vectorize(datestr_to_datetime)
DATES = converttime(dates)

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# where dates is a list or numpy array of epoch dates...
DATE = [datetime.utcfromtimestamp(x) for x in dates]

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# To untar just about everything
tar -xzvf models.tar.gz 20160101/models/hrrr/

# To untar just the HRRR pressure fields for analysis hours
tar -zxvf models.tar.gz --wildcards --no-anchored 'hrrr.t*z.wrfprsf00.grib2'

$ to untar just the HRRR surface fields for analysis hours
tar -zxvf models.tar.gz --wildcards --no-anchored 'hrrr.t*z.wrfsfcf00.grib2'

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# Brian Blaylock
# ATMOS 6910 Homework
# 10 November 2016

# Look at the figures here: 
# http://kbkb-wx-python.blogspot.com/2016/11/verifying-gfs-dewpoint-data-with.html

"""
[X] Reads a GRiB forecast file from the GFS (15%)
[X] Extracts Temperature and Relative Humidity from ingest (5%)

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import os
OUTDIR = '/this/path/will/be/created/'
if not os.path.exists(OUTDIR):
    os.makedirs(OUTDIR)

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import sys,getopt
#from netCDF4 import Dataset  # use scipy instead
from scipy.io import netcdf #### <--- This is the library to import.
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import os
from datetime import datetime, timedelta
import coltbls as coltbls
from mpl_toolkits.basemap import Basemap

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# Brian Blaylock
# March 24, 2017                           Yesterday Salt Lake had lots of rain

"""
Fast download of HRRR grib2 files with threading
"""

from queue import Queue 
from threading import Thread
from datetime import datetime, timedelta

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# Brian Blaylock
# March 10, 2017
# updated: July 26, 2017

"""
Download a single variable from the HRRR archive using cURL

Steps:
    1) Read the lines from the Metadata .idx file
    2) Identify the byte range for the variable of interest