def _parse_query(query):
coin, interval_string = _split_query(query)
coin = coin.upper()
coin2 = None
if '/' in coin:
coin, coin2 = coin.split('/', 1)
if coins_names.coin_name(coin) == '' and currencies_names.currency_name(coin) == '':
raise SyntaxError("Invalid coin/currency name: %s" % coin)
if coin2 and coins_names.coin_name(coin2) == '' and currencies_names.currency_name(coin2) == '':
raise SyntaxError("Invalid coin/currency name: %s" % coin2)
try:
time_begin, time_end = interval.parse_interval(interval_string)
except OverflowError:
# to be fixed: ranges like yesterday, today, now and so on
raise RuntimeError("Wrong range specification: %s" % interval_string)
if time_begin is None or time_end is None:
raise SyntaxError("Invalid time interval specification: %s" % interval_string)
return coin, coin2, time_begin, time_end
def _parse_query(query):
coin, interval_string = _split_query(query)
coin = coin.upper()
coin2 = None
if '/' in coin:
coin, coin2 = coin.split('/', 1)
if coins_names.coin_name(coin) == '' and currencies_names.currency_name(
coin) == '':
raise SyntaxError("Invalid coin/currency name: %s" % coin)
if coin2 and coins_names.coin_name(
coin2) == '' and currencies_names.currency_name(coin2) == '':
raise SyntaxError("Invalid coin/currency name: %s" % coin2)
try:
time_begin, time_end = interval.parse_interval(interval_string)
except OverflowError:
# to be fixed: ranges like yesterday, today, now and so on
raise RuntimeError("Wrong range specification: %s" % interval_string)
if time_begin is None or time_end is None:
raise SyntaxError("Invalid time interval specification: %s" %
interval_string)
return coin, coin2, time_begin, time_end
def _make_header(self):
coin_symbol = self.data['meta']['symbol']
coin_name = coins_names.coin_name(coin_symbol)
meta = self.data['meta']
interval_name = interval.from_secs(self.interval)
time_interval = "%s +%s" % (self._format_time(
meta['time_begin']), interval_name)
#self._format_time(meta['time_end'], show_date=True, show_time=True),
output = "\n"
if self.currency == 'USD':
output += u"{-1▶ %s (%s) }{1▶}" % (coin_name, coin_symbol)
else:
currency_symbol = self.currency
currency_name = currencies_names.currency_name(self.currency)
if not currency_name:
currency_name = coins_names.coin_name(self.currency)
output += u"{-1▶ %s (%s) to %s (%s) }{1▶}" % \
(coin_name, coin_symbol, currency_name, currency_symbol)
#output += u"{1%s (%s)}," % (coin_name, coin_symbol)
output += " %s" % (time_interval)
output += " %s\n" % self._show_change_percentage()[1]
output += "\n\n"
return output
def _make_header(self):
coin_symbol = self.data['meta']['symbol']
coin_name = coins_names.coin_name(coin_symbol)
meta = self.data['meta']
interval_name = interval.from_secs(self.interval)
time_interval = "%s +%s" % (
self._format_time(meta['time_begin']),
interval_name)
#self._format_time(meta['time_end'], show_date=True, show_time=True),
output = "\n"
if self.currency == 'USD':
output += u"{-1▶ %s (%s) }{1▶}" % (coin_name, coin_symbol)
else:
currency_symbol = self.currency
currency_name = currencies_names.currency_name(self.currency)
if not currency_name:
currency_name = coins_names.coin_name(self.currency)
output += u"{-1▶ %s (%s) to %s (%s) }{1▶}" % \
(coin_name, coin_symbol, currency_name, currency_symbol)
#output += u"{1%s (%s)}," % (coin_name, coin_symbol)
output += " %s" % (time_interval)
output += " %s\n" % self._show_change_percentage()[1]
output += "\n\n"
return output
def view(query, use_currency=None):
"""
Main rendering function, entry point for this module.
Returns rendered view for the ``query``.
If currency is specified in ``query``, it overrides ``currency``.
If ``currency`` is not specified, USD is used.
"""
try:
coin, coin2, time_begin, time_end = _parse_query(query)
except SyntaxError as e_msg:
raise RuntimeError("%s" % e_msg)
# if currency is specified in the domain name (use_currency)
# but not in the query, then we use it as the output currency
if use_currency \
and not coin2 \
and (coins_names.coin_name(use_currency) != '' \
or currencies_names.currency_name(use_currency) != ''):
coin2 = use_currency
print(coin2)
ticks = 80
if coin2:
data = aggregate.get_aggregated_pair(coin, coin2, time_begin, time_end,
ticks)
else:
data = aggregate.get_aggregated_coin(coin, time_begin, time_end, ticks)
if data['ticks'] == []:
raise RuntimeError("No data found for your query. Wrong range?")
#import json
#print json.dumps(data['meta'], indent=True)
warnings = []
if data['meta']['time_begin'] - time_begin > 3600 * 24:
warnings.append(
"for the moment, rate.sx has historical data only starting from 2018-Jan-07"
)
options = dict(
width=80,
height=25,
msg_interval='@' not in query,
currency=coin2 or 'USD',
warnings=warnings,
)
dia = Diagram(data, (time_begin, time_end), options=options)
return dia.make_view()
def view(query, use_currency=None):
"""
Main rendering function, entry point for this module.
Returns rendered view for the ``query``.
If currency is specified in ``query``, it overrides ``currency``.
If ``currency`` is not specified, USD is used.
"""
try:
coin, coin2, time_begin, time_end = _parse_query(query)
except SyntaxError as e_msg:
raise RuntimeError("%s" % e_msg)
# if currency is specified in the domain name (use_currency)
# but not in the query, then we use it as the output currency
if use_currency \
and not coin2 \
and (coins_names.coin_name(use_currency) != '' \
or currencies_names.currency_name(use_currency) != ''):
coin2 = use_currency
print coin2
ticks = 80
if coin2:
data = aggregate.get_aggregated_pair(coin, coin2, time_begin, time_end, ticks)
else:
data = aggregate.get_aggregated_coin(coin, time_begin, time_end, ticks)
if data['ticks'] == []:
raise RuntimeError("No data found for your query. Wrong range?")
#import json
#print json.dumps(data['meta'], indent=True)
warnings = []
if data['meta']['time_begin'] - time_begin > 3600*24:
warnings.append(
"for the moment, rate.sx has historical data only starting from 2018-Jan-07")
options = dict(
width=80,
height=25,
msg_interval='@' not in query,
currency=coin2 or 'USD',
warnings=warnings,
)
dia = Diagram(data, (time_begin, time_end), options=options)
return dia.make_view()
def get_data(query, use_currency=None):
try:
coin, coin2, time_begin, time_end = _parse_query(query)
except SyntaxError as e_msg:
raise RuntimeError("%s" % e_msg)
# if currency is specified in the domain name (use_currency)
# but not in the query, then we use it as the output currency
if use_currency \
and not coin2 \
and (coins_names.coin_name(use_currency) != '' \
or currencies_names.currency_name(use_currency) != ''):
coin2 = use_currency
ticks = 80
if coin2:
data = aggregate.get_aggregated_pair(coin, coin2, time_begin, time_end,
ticks)
else:
data = aggregate.get_aggregated_coin(coin, time_begin, time_end, ticks)
return data
def get_aggregated_pair(coin1,
coin2,
time_start,
time_end,
number_of_ticks,
key=None): # pylint: disable=too-many-locals,too-many-arguments,too-many-branches,too-many-statements
"""
Aggregate coin pairs (or coin and currency pairs).
It works this way: find data for ``coin1`` and find data for ``coin2``,
after that divide ``coin1`` data by ``coin2`` pairwise.
This method is approximate for aggregated values.
``coin2`` can be a currency.
"""
coin2_is_currency = bool(currency_name(coin2))
desired_interval = (time_end - time_start) / number_of_ticks
chosen_interval = None
for interval_name, interval_size in sorted(INTERVAL.items(),
key=lambda x: -x[1]):
if interval_size < desired_interval:
chosen_interval = interval_name
# if interval is so small, we need to use the raw and not the aggregated data
collection_name = None
if chosen_interval:
collection_name = 'coins_%s' % chosen_interval
if key is None:
key = "price_usd"
entries1 = MONGO_READER.get_raw_data(coin1,
time_start,
time_end,
collection_name=collection_name)
if entries1 == []:
return {'meta': {}, 'ticks': []}
# depeding on (1) that we have a currency in coin2 or not
# and (2) if data is aggregated, we have to read entries2 from different collections
# and in one case postprocess them
if coin2_is_currency:
if collection_name is None:
currencies_collection = 'currencies'
else:
currencies_collection = collection_name.replace(
'coins_', 'currencies_')
fields = {'timestamp': 1, coin2: 1}
entries2 = MONGO_READER.get_raw_data(
None,
time_start,
time_end,
collection_name=currencies_collection,
fields=fields)
new_entries2 = []
for entry in entries2:
entry.update({key: entry[coin2]})
new_entries2.append(entry)
entries2 = new_entries2
else:
entries2 = MONGO_READER.get_raw_data(coin2,
time_start,
time_end,
collection_name=collection_name)
meta = {}
ticks = []
sum_ = 0
if collection_name is None:
# not aggregated data
meta = {
'symbol': entries1[0]['symbol'],
'begin': entries1[0][key] / entries2[0][key],
'end': entries1[-1][key] / entries2[-1][key],
'time_begin': entries1[0]['timestamp'],
'time_end': entries1[-1]['timestamp'],
'min': entries1[0][key] / entries2[0][key],
'max': entries1[0][key] / entries2[0][key],
'time_min': entries1[0]['timestamp'],
'time_max': entries1[0]['timestamp'],
}
for entry1, entry2 in zip(entries1, entries2):
this_value = entry1[key] / entry2[key]
ticks.append(this_value)
sum_ += this_value
if this_value > meta['max']:
meta['max'] = this_value
meta['time_max'] = entry1['timestamp']
if this_value < meta['min']:
meta['min'] = this_value
meta['time_min'] = entry1['timestamp']
else:
# aggregated data
# this parameter should be taken to the ticks
take_this = 'avg'
meta = {
'symbol': entries1[0]['symbol'],
'begin': entries1[0][key]['begin'] / entries2[0][key]['begin'],
'end': entries1[-1][key]['end'] / entries2[-1][key]['end'],
'time_begin': entries1[0]['timestamp'],
'time_end': entries1[-1]['time_end'],
'min': entries1[0][key]['min'] / entries2[0][key]['max'],
'max': entries1[0][key]['max'] / entries2[0][key]['min'],
'time_min': entries1[0][key]['time_min'],
'time_max': entries1[0][key]['time_max'],
}
for entry1, entry2 in zip(entries1, entries2):
this_value = entry1[key][take_this] / entry2[key][take_this]
ticks.append(this_value)
sum_ += this_value
if this_value > meta['max']:
meta['max'] = this_value
meta['time_max'] = entry1[key]['time_max']
if this_value < meta['min']:
meta['min'] = this_value
meta['time_min'] = entry1[key]['time_min']
meta['avg'] = sum_ / len(ticks)
return {
'ticks': ticks,
'meta': meta,
}
def get_aggregated_pair(coin1, coin2, time_start, time_end, number_of_ticks, key=None): # pylint: disable=too-many-locals,too-many-arguments,too-many-branches,too-many-statements
"""
Aggregate coin pairs (or coin and currency pairs).
It works this way: find data for ``coin1`` and find data for ``coin2``,
after that divide ``coin1`` data by ``coin2`` pairwise.
This method is approximate for aggregated values.
``coin2`` can be a currency.
"""
coin2_is_currency = bool(currency_name(coin2))
desired_interval = (time_end-time_start)/number_of_ticks
chosen_interval = None
for interval_name, interval_size in sorted(INTERVAL.items(), key=lambda x: -x[1]):
if interval_size < desired_interval:
chosen_interval = interval_name
# if interval is so small, we need to use the raw and not the aggregated data
collection_name = None
if chosen_interval:
collection_name = 'coins_%s' % chosen_interval
if key is None:
key = "price_usd"
entries1 = MONGO_READER.get_raw_data(
coin1, time_start, time_end, collection_name=collection_name)
if entries1 == []:
return {'meta':{}, 'ticks':[]}
# depeding on (1) that we have a currency in coin2 or not
# and (2) if data is aggregated, we have to read entries2 from different collections
# and in one case postprocess them
if coin2_is_currency:
if collection_name is None:
currencies_collection = 'currencies'
else:
currencies_collection = collection_name.replace('coins_', 'currencies_')
fields = {'timestamp': 1, coin2: 1}
entries2 = MONGO_READER.get_raw_data(
None, time_start, time_end,
collection_name=currencies_collection,
fields=fields)
new_entries2 = []
for entry in entries2:
entry.update({key: entry[coin2]})
new_entries2.append(entry)
entries2 = new_entries2
else:
entries2 = MONGO_READER.get_raw_data(
coin2, time_start, time_end, collection_name=collection_name)
meta = {}
ticks = []
sum_ = 0
if collection_name is None:
# not aggregated data
meta = {
'symbol': entries1[0]['symbol'],
'begin': entries1[0][key]/entries2[0][key],
'end': entries1[-1][key]/entries2[-1][key],
'time_begin': entries1[0]['timestamp'],
'time_end': entries1[-1]['timestamp'],
'min': entries1[0][key]/entries2[0][key],
'max': entries1[0][key]/entries2[0][key],
'time_min': entries1[0]['timestamp'],
'time_max': entries1[0]['timestamp'],
}
for entry1, entry2 in zip(entries1, entries2):
this_value = entry1[key]/entry2[key]
ticks.append(this_value)
sum_ += this_value
if this_value > meta['max']:
meta['max'] = this_value
meta['time_max'] = entry1['timestamp']
if this_value < meta['min']:
meta['min'] = this_value
meta['time_min'] = entry1['timestamp']
else:
# aggregated data
# this parameter should be taken to the ticks
take_this = 'avg'
meta = {
'symbol': entries1[0]['symbol'],
'begin': entries1[0][key]['begin']/entries2[0][key]['begin'],
'end': entries1[-1][key]['end']/entries2[-1][key]['end'],
'time_begin': entries1[0]['timestamp'],
'time_end': entries1[-1]['time_end'],
'min': entries1[0][key]['min']/entries2[0][key]['max'],
'max': entries1[0][key]['max']/entries2[0][key]['min'],
'time_min': entries1[0][key]['time_min'],
'time_max': entries1[0][key]['time_max'],
}
for entry1, entry2 in zip(entries1, entries2):
this_value = entry1[key][take_this]/entry2[key][take_this]
ticks.append(this_value)
sum_ += this_value
if this_value > meta['max']:
meta['max'] = this_value
meta['time_max'] = entry1[key]['time_max']
if this_value < meta['min']:
meta['min'] = this_value
meta['time_min'] = entry1[key]['time_min']
meta['avg'] = sum_/len(ticks)
return {
'ticks': ticks,
'meta': meta,
}