def compile_asset_pair_market_info():
"""Compiles the pair-level statistics that show on the View Prices page of counterwallet, for instance"""
#loop through all open orders, and compile a listing of pairs, with a count of open orders for each pair
mongo_db = config.mongo_db
end_dt = datetime.datetime.utcnow()
start_dt = end_dt - datetime.timedelta(days=1)
start_block_index, end_block_index = util.get_block_indexes_for_dates(start_dt=start_dt, end_dt=end_dt)
open_orders = util.call_jsonrpc_api("get_orders",
{ 'filters': [
{'field': 'give_remaining', 'op': '>', 'value': 0},
{'field': 'get_remaining', 'op': '>', 'value': 0},
{'field': 'fee_required_remaining', 'op': '>=', 'value': 0},
{'field': 'fee_provided_remaining', 'op': '>=', 'value': 0},
],
'status': 'open',
'show_expired': False,
}, abort_on_error=True)['result']
pair_data = {}
asset_info = {}
def get_price(base_quantity_normalized, quote_quantity_normalized):
return float(D(quote_quantity_normalized / base_quantity_normalized ))
#COMPOSE order depth, lowest ask, and highest bid column data
for o in open_orders:
(base_asset, quote_asset) = util.assets_to_asset_pair(o['give_asset'], o['get_asset'])
pair = '%s/%s' % (base_asset, quote_asset)
base_asset_info = asset_info.get(base_asset, mongo_db.tracked_assets.find_one({ 'asset': base_asset }))
if base_asset not in asset_info: asset_info[base_asset] = base_asset_info
quote_asset_info = asset_info.get(quote_asset, mongo_db.tracked_assets.find_one({ 'asset': quote_asset }))
if quote_asset not in asset_info: asset_info[quote_asset] = quote_asset_info
pair_data.setdefault(pair, {'open_orders_count': 0, 'lowest_ask': None, 'highest_bid': None,
'completed_trades_count': 0, 'vol_base': 0, 'vol_quote': 0})
#^ highest ask = open order selling base, highest bid = open order buying base
#^ we also initialize completed_trades_count, vol_base, vol_quote because every pair inited here may
# not have cooresponding data out of the trades_data_by_pair aggregation below
pair_data[pair]['open_orders_count'] += 1
base_quantity_normalized = util_bitcoin.normalize_quantity(o['give_quantity'] if base_asset == o['give_asset'] else o['get_quantity'], base_asset_info['divisible'])
quote_quantity_normalized = util_bitcoin.normalize_quantity(o['give_quantity'] if quote_asset == o['give_asset'] else o['get_quantity'], quote_asset_info['divisible'])
order_price = get_price(base_quantity_normalized, quote_quantity_normalized)
if base_asset == o['give_asset']: #selling base
if pair_data[pair]['lowest_ask'] is None or order_price < pair_data[pair]['lowest_ask']:
pair_data[pair]['lowest_ask'] = order_price
elif base_asset == o['get_asset']: #buying base
if pair_data[pair]['highest_bid'] is None or order_price > pair_data[pair]['highest_bid']:
pair_data[pair]['highest_bid'] = order_price
#COMPOSE volume data (in XCP and BTC), and % change data
#loop through all trade volume over the past 24h, and match that to the open orders
trades_data_by_pair = mongo_db.trades.aggregate([
{"$match": {
"block_time": {"$gte": start_dt, "$lte": end_dt } }
},
{"$project": {
"base_asset": 1,
"quote_asset": 1,
"base_quantity_normalized": 1, #to derive base volume
"quote_quantity_normalized": 1 #to derive quote volume
}},
{"$group": {
"_id": {"base_asset": "$base_asset", "quote_asset": "$quote_asset"},
"vol_base": {"$sum": "$base_quantity_normalized"},
"vol_quote": {"$sum": "$quote_quantity_normalized"},
"count": {"$sum": 1},
}}
])
trades_data_by_pair = [] if not trades_data_by_pair['ok'] else trades_data_by_pair['result']
for e in trades_data_by_pair:
pair = '%s/%s' % (e['_id']['base_asset'], e['_id']['quote_asset'])
pair_data.setdefault(pair, {'open_orders_count': 0, 'lowest_ask': None, 'highest_bid': None})
#^ initialize an empty pair in the event there are no open orders for that pair, but there ARE completed trades for it
pair_data[pair]['completed_trades_count'] = e['count']
pair_data[pair]['vol_base'] = e['vol_base']
pair_data[pair]['vol_quote'] = e['vol_quote']
#compose price data, relative to BTC and XCP
mps_xcp_btc, xcp_btc_price, btc_xcp_price = get_price_primatives()
for pair, e in pair_data.iteritems():
base_asset, quote_asset = pair.split('/')
_24h_vol_in_btc = None
_24h_vol_in_xcp = None
#derive asset price data, expressed in BTC and XCP, for the given volumes
if base_asset == config.XCP:
_24h_vol_in_xcp = e['vol_base']
_24h_vol_in_btc = util_bitcoin.round_out(e['vol_base'] * xcp_btc_price) if xcp_btc_price else 0
elif base_asset == config.BTC:
_24h_vol_in_xcp = util_bitcoin.round_out(e['vol_base'] * btc_xcp_price) if btc_xcp_price else 0
_24h_vol_in_btc = e['vol_base']
else: #base is not XCP or BTC
price_summary_in_xcp, price_summary_in_btc, price_in_xcp, price_in_btc, aggregated_price_in_xcp, aggregated_price_in_btc = \
get_xcp_btc_price_info(base_asset, mps_xcp_btc, xcp_btc_price, btc_xcp_price, with_last_trades=0, start_dt=start_dt, end_dt=end_dt)
if price_in_xcp:
_24h_vol_in_xcp = util_bitcoin.round_out(e['vol_base'] * price_in_xcp)
if price_in_btc:
_24h_vol_in_btc = util_bitcoin.round_out(e['vol_base'] * price_in_btc)
if _24h_vol_in_xcp is None or _24h_vol_in_btc is None:
#the base asset didn't have price data against BTC or XCP, or both...try against the quote asset instead
price_summary_in_xcp, price_summary_in_btc, price_in_xcp, price_in_btc, aggregated_price_in_xcp, aggregated_price_in_btc = \
get_xcp_btc_price_info(quote_asset, mps_xcp_btc, xcp_btc_price, btc_xcp_price, with_last_trades=0, start_dt=start_dt, end_dt=end_dt)
if _24h_vol_in_xcp is None and price_in_xcp:
_24h_vol_in_xcp = util_bitcoin.round_out(e['vol_quote'] * price_in_xcp)
if _24h_vol_in_btc is None and price_in_btc:
_24h_vol_in_btc = util_bitcoin.round_out(e['vol_quote'] * price_in_btc)
pair_data[pair]['24h_vol_in_{}'.format(config.XCP.lower())] = _24h_vol_in_xcp #might still be None
pair_data[pair]['24h_vol_in_{}'.format(config.BTC.lower())] = _24h_vol_in_btc #might still be None
#get % change stats -- start by getting the first trade directly before the 24h period starts
prev_trade = mongo_db.trades.find({
"base_asset": base_asset,
"quote_asset": quote_asset,
"block_time": {'$lt': start_dt}}).sort('block_time', pymongo.DESCENDING).limit(1)
latest_trade = mongo_db.trades.find({
"base_asset": base_asset,
"quote_asset": quote_asset}).sort('block_time', pymongo.DESCENDING).limit(1)
if not prev_trade.count(): #no previous trade before this 24hr period
pair_data[pair]['24h_pct_change'] = None
else:
prev_trade = prev_trade[0]
latest_trade = latest_trade[0]
prev_trade_price = get_price(prev_trade['base_quantity_normalized'], prev_trade['quote_quantity_normalized'])
latest_trade_price = get_price(latest_trade['base_quantity_normalized'], latest_trade['quote_quantity_normalized'])
pair_data[pair]['24h_pct_change'] = ((latest_trade_price - prev_trade_price) / prev_trade_price) * 100
pair_data[pair]['last_updated'] = end_dt
#print "PRODUCED", pair, pair_data[pair]
mongo_db.asset_pair_market_info.update( {'base_asset': base_asset, 'quote_asset': quote_asset}, {"$set": pair_data[pair]}, upsert=True)
#remove any old pairs that were not just updated
mongo_db.asset_pair_market_info.remove({'last_updated': {'$lt': end_dt}})
logging.info("Recomposed 24h trade statistics for %i asset pairs: %s" % (len(pair_data), ', '.join(pair_data.keys())))
def compile_asset_pair_market_info():
"""Compiles the pair-level statistics that show on the View Prices page of counterwallet, for instance"""
#loop through all open orders, and compile a listing of pairs, with a count of open orders for each pair
mongo_db = config.mongo_db
end_dt = datetime.datetime.utcnow()
start_dt = end_dt - datetime.timedelta(days=1)
start_block_index, end_block_index = util.get_block_indexes_for_dates(
start_dt=start_dt, end_dt=end_dt)
open_orders = util.call_jsonrpc_api("get_orders", {
'filters': [
{
'field': 'give_remaining',
'op': '>',
'value': 0
},
{
'field': 'get_remaining',
'op': '>',
'value': 0
},
{
'field': 'fee_required_remaining',
'op': '>=',
'value': 0
},
{
'field': 'fee_provided_remaining',
'op': '>=',
'value': 0
},
],
'status':
'open',
'show_expired':
False,
},
abort_on_error=True)['result']
pair_data = {}
asset_info = {}
def get_price(base_quantity_normalized, quote_quantity_normalized):
return float(D(quote_quantity_normalized / base_quantity_normalized))
#COMPOSE order depth, lowest ask, and highest bid column data
for o in open_orders:
(base_asset,
quote_asset) = util.assets_to_asset_pair(o['give_asset'],
o['get_asset'])
pair = '%s/%s' % (base_asset, quote_asset)
base_asset_info = asset_info.get(
base_asset, mongo_db.tracked_assets.find_one({'asset':
base_asset}))
if base_asset not in asset_info:
asset_info[base_asset] = base_asset_info
quote_asset_info = asset_info.get(
quote_asset,
mongo_db.tracked_assets.find_one({'asset': quote_asset}))
if quote_asset not in asset_info:
asset_info[quote_asset] = quote_asset_info
pair_data.setdefault(
pair, {
'open_orders_count': 0,
'lowest_ask': None,
'highest_bid': None,
'completed_trades_count': 0,
'vol_base': 0,
'vol_quote': 0
})
#^ highest ask = open order selling base, highest bid = open order buying base
#^ we also initialize completed_trades_count, vol_base, vol_quote because every pair inited here may
# not have cooresponding data out of the trades_data_by_pair aggregation below
pair_data[pair]['open_orders_count'] += 1
base_quantity_normalized = util_bitcoin.normalize_quantity(
o['give_quantity'] if base_asset == o['give_asset'] else
o['get_quantity'], base_asset_info['divisible'])
quote_quantity_normalized = util_bitcoin.normalize_quantity(
o['give_quantity'] if quote_asset == o['give_asset'] else
o['get_quantity'], quote_asset_info['divisible'])
order_price = get_price(base_quantity_normalized,
quote_quantity_normalized)
if base_asset == o['give_asset']: #selling base
if pair_data[pair]['lowest_ask'] is None or order_price < pair_data[
pair]['lowest_ask']:
pair_data[pair]['lowest_ask'] = order_price
elif base_asset == o['get_asset']: #buying base
if pair_data[pair][
'highest_bid'] is None or order_price > pair_data[pair][
'highest_bid']:
pair_data[pair]['highest_bid'] = order_price
#COMPOSE volume data (in XDP and DOGE), and % change data
#loop through all trade volume over the past 24h, and match that to the open orders
trades_data_by_pair = mongo_db.trades.aggregate([
{
"$match": {
"block_time": {
"$gte": start_dt,
"$lte": end_dt
}
}
},
{
"$project": {
"base_asset": 1,
"quote_asset": 1,
"base_quantity_normalized": 1, #to derive base volume
"quote_quantity_normalized": 1 #to derive quote volume
}
},
{
"$group": {
"_id": {
"base_asset": "$base_asset",
"quote_asset": "$quote_asset"
},
"vol_base": {
"$sum": "$base_quantity_normalized"
},
"vol_quote": {
"$sum": "$quote_quantity_normalized"
},
"count": {
"$sum": 1
},
}
}
])
trades_data_by_pair = [] if not trades_data_by_pair[
'ok'] else trades_data_by_pair['result']
for e in trades_data_by_pair:
pair = '%s/%s' % (e['_id']['base_asset'], e['_id']['quote_asset'])
pair_data.setdefault(pair, {
'open_orders_count': 0,
'lowest_ask': None,
'highest_bid': None
})
#^ initialize an empty pair in the event there are no open orders for that pair, but there ARE completed trades for it
pair_data[pair]['completed_trades_count'] = e['count']
pair_data[pair]['vol_base'] = e['vol_base']
pair_data[pair]['vol_quote'] = e['vol_quote']
#compose price data, relative to DOGE and XDP
mps_xcp_btc, xcp_btc_price, btc_xcp_price = get_price_primatives()
for pair, e in pair_data.iteritems():
base_asset, quote_asset = pair.split('/')
_24h_vol_in_btc = None
_24h_vol_in_xcp = None
#derive asset price data, expressed in DOGE and XDP, for the given volumes
if base_asset == config.XCP:
_24h_vol_in_xcp = e['vol_base']
_24h_vol_in_btc = util_bitcoin.round_out(
e['vol_base'] * xcp_btc_price) if xcp_btc_price else 0
elif base_asset == config.BTC:
_24h_vol_in_xcp = util_bitcoin.round_out(
e['vol_base'] * btc_xcp_price) if btc_xcp_price else 0
_24h_vol_in_btc = e['vol_base']
else: #base is not XDP or DOGE
price_summary_in_xcp, price_summary_in_btc, price_in_xcp, price_in_btc, aggregated_price_in_xcp, aggregated_price_in_btc = \
get_xcp_btc_price_info(base_asset, mps_xcp_btc, xcp_btc_price, btc_xcp_price, with_last_trades=0, start_dt=start_dt, end_dt=end_dt)
if price_in_xcp:
_24h_vol_in_xcp = util_bitcoin.round_out(e['vol_base'] *
price_in_xcp)
if price_in_btc:
_24h_vol_in_btc = util_bitcoin.round_out(e['vol_base'] *
price_in_btc)
if _24h_vol_in_xcp is None or _24h_vol_in_btc is None:
#the base asset didn't have price data against DOGE or XDP, or both...try against the quote asset instead
price_summary_in_xcp, price_summary_in_btc, price_in_xcp, price_in_btc, aggregated_price_in_xcp, aggregated_price_in_btc = \
get_xcp_btc_price_info(quote_asset, mps_xcp_btc, xcp_btc_price, btc_xcp_price, with_last_trades=0, start_dt=start_dt, end_dt=end_dt)
if _24h_vol_in_xcp is None and price_in_xcp:
_24h_vol_in_xcp = util_bitcoin.round_out(e['vol_quote'] *
price_in_xcp)
if _24h_vol_in_btc is None and price_in_btc:
_24h_vol_in_btc = util_bitcoin.round_out(e['vol_quote'] *
price_in_btc)
pair_data[pair]['24h_vol_in_{}'.format(
config.XCP.lower())] = _24h_vol_in_xcp #might still be None
pair_data[pair]['24h_vol_in_{}'.format(
config.BTC.lower())] = _24h_vol_in_btc #might still be None
#get % change stats -- start by getting the first trade directly before the 24h period starts
prev_trade = mongo_db.trades.find({
"base_asset": base_asset,
"quote_asset": quote_asset,
"block_time": {
'$lt': start_dt
}
}).sort('block_time', pymongo.DESCENDING).limit(1)
latest_trade = mongo_db.trades.find({
"base_asset": base_asset,
"quote_asset": quote_asset
}).sort('block_time', pymongo.DESCENDING).limit(1)
if not prev_trade.count(): #no previous trade before this 24hr period
pair_data[pair]['24h_pct_change'] = None
else:
prev_trade = prev_trade[0]
latest_trade = latest_trade[0]
prev_trade_price = get_price(
prev_trade['base_quantity_normalized'],
prev_trade['quote_quantity_normalized'])
latest_trade_price = get_price(
latest_trade['base_quantity_normalized'],
latest_trade['quote_quantity_normalized'])
pair_data[pair]['24h_pct_change'] = (
(latest_trade_price - prev_trade_price) /
prev_trade_price) * 100
pair_data[pair]['last_updated'] = end_dt
#print "PRODUCED", pair, pair_data[pair]
mongo_db.asset_pair_market_info.update(
{
'base_asset': base_asset,
'quote_asset': quote_asset
}, {"$set": pair_data[pair]},
upsert=True)
#remove any old pairs that were not just updated
mongo_db.asset_pair_market_info.remove({'last_updated': {'$lt': end_dt}})
logging.info("Recomposed 24h trade statistics for %i asset pairs: %s" %
(len(pair_data), ', '.join(pair_data.keys())))