def _collect_price_time_series(self):
"""Parse the requested JSON for daily close time series data
and daily average time series data.
Returns:
tuple: Ordered pair of dictionaries containing time series data
for both the daily close time series and daily average time series.
Keys are strings representing ms since epoch.
Values are integers representing the signal (amount of gp)
"""
r = requests.get(self.GRAPH_URL)
#dictionary of 2 dictionaries, "daily" and "average"
response = r.json()
daily_series = TimeSeries.from_dictionary(response["daily"])
average_series = TimeSeries.from_dictionary(response["average"])
return (daily_series, average_series)
def _collect_volume_time_series(self):
"""Parse the OSRS GX tradeable item webpage for trade volume data.
Returns:
dict: Single dictionary containing trade volume time series data.
Keys are strings in `%Y-%m-%d` format.
Values are integers representing the number of unites moved by close.
"""
#fetch the item page as text
page_as_text = requests.get(self.VOLUME_URL).text
#search the item page for tags that contain volume information
volume_tags = re.findall("trade180.push.*", page_as_text)
volume_series = {}
#iterate over all the tags just found
for match in volume_tags:
tv_pairs = re.findall("Date\(.*\), \d+", match)
#separate the timestamps from volume data
for pair in tv_pairs:
t, v = tuple(pair.split(','))
#remove text surrounding Y/M/D piece of timestamp
t = t.strip("Date('").strip("')'")
volume_series[t] = int(v)
volume_series = TimeSeries.from_dictionary(volume_series)
return volume_series