def __init__(self):
"""
Initialization method. Here is where we poll the database and the BitStamp API to collect relevant data.
"""
# The first step is to fetch and store transactions from the backend to ensure that our knowledge of transactional data is up to Date
push_transactions.push(log=False)
# The next step is to fetch current price data from the sqlite3 database
conn = sqlite3.connect( bitcoin.get_db() )
cursor = conn.cursor()
values = cursor.execute('''SELECT "time", "buy", "sell", "wa_buy", "wa_sell" FROM "prices" ORDER BY "time" DESC LIMIT 1''').fetchone()
self.time = values[0]
self.buy = values[1]
self.sell = values[2]
self.avg_buy = values[3]
self.avg_sell = values[4]
# Use BitStamp API client to fetch the USD and BTC balance
bal = client.balance()
self.usd_balance = float(bal['usd_balance'])
self.btc_balance = float(bal['btc_balance'])
# Query "transactions" table to database to get the latest buy and sell prices and the times they occurred (needed for orienting/analysis)
values = cursor.execute('''SELECT "time", "rate" FROM "transactions" WHERE "usd" > 0 ORDER BY "time" DESC LIMIT 1''').fetchone()
self.last_sell_time = values[0]
self.last_sell_price = values[1]
values = cursor.execute('''SELECT "time", "rate" FROM "transactions" WHERE "usd" < 0 ORDER BY "time" DESC LIMIT 1''').fetchone()
self.last_buy_time = values[0]
self.last_buy_price = values[1]
# Fetch all buy prices since the last time BTC was sold
self.buy_prices = []
for values in cursor.execute('''SELECT "buy" FROM "prices" WHERE "time" > ?''', (self.last_sell_time,)):
self.buy_prices.append(values[0])
# Fetch all sell prices since the last time BTC was bought
self.sell_prices = []
self.weighted_sell_prices = []
for values in cursor.execute('''SELECT "sell", "wa_sell" FROM "prices" WHERE "time" > ?''', (self.last_buy_time, )):
self.sell_prices.append(values[0])
self.weighted_sell_prices.append(values[1])
# Convert array of prices in to R vectors
self.buy_prices = robjects.FloatVector(self.buy_prices)
self.sell_prices = robjects.FloatVector(self.sell_prices)
self.weighted_sell_prices = robjects.FloatVector(self.weighted_sell_prices)
cursor.close()
def push(log=True):
"""
Fetches transactions from BitStamp and pushes them in to the sqlite3 database where they are used to determine the
latest buy and sell prices.
"""
conn = sqlite3.connect( bitcoin.get_db() )
cursor = conn.cursor()
if log: print("Fetching transactions from BitStamp server ...")
data = bitcoin.client.transactions()
if log: print("Inserting data in to 'transactions' table ...")
for trx in data:
ts = unix_timestamp(trx['datetime'])
cursor.execute('''REPLACE INTO "transactions" ("time", "usd", "btc", "rate") VALUES (?,?,?,?)''', (ts, trx['usd'], trx['btc'], trx['btc_usd']))
conn.commit()
conn.close()
if log: print("Done\n")
#
#
# Author: Abid H. Mujtaba
# Date: 2014-04-05
#
# This script reads buy and price data from the database, calculates the first and second finite differences and stores
# it in the database.
import rpy2.robjects as robjects
import sqlite3
from bitcoin import get_db, round2
if __name__ == '__main__':
conn = sqlite3.connect(get_db())
cursor = conn.cursor()
s_time = []
s_buy = []
s_sell = []
print("Reading in time and prices from database.")
for values in cursor.execute(
'''SELECT "time", "buy", "sell" FROM "prices"'''):
s_time.append(values[0])
s_buy.append(values[1])
s_sell.append(values[2])
def __init__(self):
"""
Initialization method. Here is where we poll the database and the BitStamp API to collect relevant data.
"""
# The first step is to fetch and store transactions from the backend to ensure that our knowledge of transactional data is up to Date
push_transactions.push(log=False)
# The next step is to fetch current price data from the sqlite3 database
conn = sqlite3.connect(bitcoin.get_db())
cursor = conn.cursor()
values = cursor.execute(
'''SELECT "time", "buy", "sell", "wa_buy", "wa_sell" FROM "prices" ORDER BY "time" DESC LIMIT 1'''
).fetchone()
self.time = values[0]
self.buy = values[1]
self.sell = values[2]
self.avg_buy = values[3]
self.avg_sell = values[4]
# Use BitStamp API client to fetch the USD and BTC balance
bal = client.balance()
self.usd_balance = float(bal['usd_balance'])
self.btc_balance = float(bal['btc_balance'])
# Query "transactions" table to database to get the latest buy and sell prices and the times they occurred (needed for orienting/analysis)
values = cursor.execute(
'''SELECT "time", "rate" FROM "transactions" WHERE "usd" > 0 ORDER BY "time" DESC LIMIT 1'''
).fetchone()
self.last_sell_time = values[0]
self.last_sell_price = values[1]
values = cursor.execute(
'''SELECT "time", "rate" FROM "transactions" WHERE "usd" < 0 ORDER BY "time" DESC LIMIT 1'''
).fetchone()
self.last_buy_time = values[0]
self.last_buy_price = values[1]
# Fetch all buy prices since the last time BTC was sold
self.buy_prices = []
for values in cursor.execute(
'''SELECT "buy" FROM "prices" WHERE "time" > ?''',
(self.last_sell_time, )):
self.buy_prices.append(values[0])
# Fetch all sell prices since the last time BTC was bought
self.sell_prices = []
self.weighted_sell_prices = []
for values in cursor.execute(
'''SELECT "sell", "wa_sell" FROM "prices" WHERE "time" > ?''',
(self.last_buy_time, )):
self.sell_prices.append(values[0])
self.weighted_sell_prices.append(values[1])
# Convert array of prices in to R vectors
self.buy_prices = robjects.FloatVector(self.buy_prices)
self.sell_prices = robjects.FloatVector(self.sell_prices)
self.weighted_sell_prices = robjects.FloatVector(
self.weighted_sell_prices)
cursor.close()
# See the License for the specific language governing permissions and
# limitations under the License.
#
#
# Author: Abid H. Mujtaba
# Date: 2014-03-27
#
# A script for extracting the last 6 hours of buy prices (180 samples) from the database and storing it in a file.
import sqlite3
import bitcoin
SAMPLES = 6 * 60
if __name__ == '__main__':
fout = open('buy.txt', 'w')
conn = sqlite3.connect(bitcoin.get_db())
cursor = conn.cursor()
for values in cursor.execute('''SELECT "buy" FROM (SELECT "time", "buy" FROM "prices" ORDER BY "time" DESC LIMIT ?) ORDER BY "time" ASC''', (SAMPLES,)): # Get list of times in descending order
fout.write("%.2f\n" % values[0])
conn.close();
fout.close();
# See the License for the specific language governing permissions and
# limitations under the License.
#
#
# Author: Abid H. Mujtaba
# Date: 2014-03-27
#
# A script for extracting the last 6 hours of buy prices (180 samples) from the database and storing it in a file.
import sqlite3
import bitcoin
SAMPLES = 6 * 60
if __name__ == '__main__':
fout = open('buy.txt', 'w')
conn = sqlite3.connect(bitcoin.get_db())
cursor = conn.cursor()
for values in cursor.execute(
'''SELECT "buy" FROM (SELECT "time", "buy" FROM "prices" ORDER BY "time" DESC LIMIT ?) ORDER BY "time" ASC''',
(SAMPLES, )): # Get list of times in descending order
fout.write("%.2f\n" % values[0])
conn.close()
fout.close()
# Author: Abid H. Mujtaba
# Date: 2014-04-05
#
# This script reads buy and price data from the database, calculates the first and second finite differences and stores
# it in the database.
import rpy2.robjects as robjects
import sqlite3
from bitcoin import get_db, round2
if __name__ == '__main__':
conn = sqlite3.connect( get_db() )
cursor = conn.cursor()
s_time = []
s_buy = []
s_sell = []
print("Reading in time and prices from database.")
for values in cursor.execute('''SELECT "time", "buy", "sell" FROM "prices"'''):
s_time.append( values[0] )
s_buy.append( values[1] )
s_sell.append( values[2] )