currency and other utilities
Project description
denarius
currency and other utilities
introduction
denarius is a project, not a finished product. It features various utilities for collating cryptocurrency, mining, financial and other data, for plotting data and for accessing bank accounts. It features analyses of data for systematic descriptions, for predictions, for arbitrage etc.
setup
sudo apt-get install sqlite
wget https://github.com/mozilla/geckodriver/releases/download/v0.19.1/geckodriver-v0.19.1-linux64.tar.gz
tar -xvzf geckodriver-v0.19.1-linux64.tar.gz
rm geckodriver-v0.19.1-linux64.tar.gz
chmod +x geckodriver
sudo cp geckodriver /usr/local/bin/
sudo pip install denarius
Bitcoin values
The function ticker_Bitcoin returns data of the following form:
{'volume': 2050.1665002833397, 'last': 992.2553834529656, 'timestamp': 1487551580.0, 'bid': 991.8303740083114, 'vwap': 993.3415187004156, 'high': 1002.9278428409522, 'low': 981.3656970154892, 'ask': 992.2553834529656, 'open': 993.3887419720438}
It accesses data from Bitstamp.
feature |
description |
---|---|
last |
last Bitcoin price |
high |
last 24 hours price high |
low |
last 24 hours price low |
vwap |
last 24 hours volume weighted average price |
volume |
last 24 hours volume |
bid |
highest buy order |
ask |
lowest sell order |
timestamp |
UNIX timestamp date and time |
open |
first price of the day |
The function data_historical_Bitcoin returns by default data of the following form:
{'bpi': {'2017-02-17': 992.1077, '2017-02-16': 969.2414, '2017-02-15': 952.6512, '2017-02-14': 954.1432, '2017-02-13': 940.7982, '2017-02-12': 940.1764, '2017-02-11': 949.3397, '2017-02-10': 933.4325, '2017-02-19': 991.254, '2017-02-18': 997.0854}, 'time': {'updated': 'Feb 20, 2017 00:20:08 UTC', 'updatedISO': '2017-02-20T00:20:08+00:00'}, 'disclaimer': 'This data was produced from the CoinDesk Bitcoin Price Index. BPI value data returned as EUR.'}
With the option return_list, it returns data of the following form:
[['2017-02-10', 933.4325], ['2017-02-11', 949.3397], ['2017-02-12', 940.1764], ['2017-02-13', 940.7982], ['2017-02-14', 954.1432], ['2017-02-15', 952.6512], ['2017-02-16', 969.2414], ['2017-02-17', 992.1077], ['2017-02-18', 997.0854], ['2017-02-19', 991.254]]
With the option return_UNIX_times, it returns data of the following form:
[[1486684800, 933.4325], [1486771200, 949.3397], [1486857600, 940.1764], [1486944000, 940.7982], [1487030400, 954.1432], [1487116800, 952.6512], [1487203200, 969.2414], [1487289600, 992.1077], [1487376000, 997.0854], [1487462400, 991.254]]
LocalBitcoins
LocalBitcoins data is available via its API. For example, the following URL gives data on current trades in GBP available by national bank transfer:
The data returned by the API is of a form like this.
The function values_Bitcoin_LocalBitcoin returns the price values returned by calling the API in this way.
import denarius
denarius.values_Bitcoin_LocalBitcoin()
The script loop_save_LocalBitcoins_values_to_database.py loop records LocalBitcoins data to database. To address closed gateways arising from repeat calls, the script could be used in a way like the following:
while true; do
loop_save_LocalBitcoins_values_to_database.py --timeperiod=3600
sleep 5400
done
databases
A database of Bitcoin values can be saved in the following ways:
import denarius
denarius.save_database_Bitcoin(filename = "database.db")
import denarius
denarius.save_database_Bitcoin(filename = "database_Bitcoin_EUR.db", currency = "EUR")
denarius.save_database_Bitcoin(filename = "database_Bitcoin_GBP.db", currency = "GBP")
graphs
The function save_graph_Bitcoin creates a graph of Bitcoin historical values over a specified time. The function save_graph_LocalBitcoins creates a graph of LocalBitcoins Bitcoin lowest prices in GBP as recorded in a database by the script loop_save_LocalBitcoins_values_to_database.py.
denarius_graph_Bitcoin
The script denarius_graph_Bitcoin.py displays a PyQt GUI with a graph of the last Bitcoin values.
denarius_graph_Bitcoin.py --help
denarius_graph_Bitcoin.py
denarius_graph_Bitcoin.py --currency=EUR --days=100
LocalBitcoins
A graph can be generated of Bitcoin GBP value versus LocalBitcoins GBP lowest value:
import denarius
denarius.save_graph_Bitcoin_LocalBitcoins()
A graph can be generated of Bitcoin GBP value versus LocalBitcoins GBP lowest 5 values:
import denarius
denarius.save_graphs_Bitcoin_LocalBitcoins()
A graph can be generated of LocalBitcoins normalized prices over days:
A graph can be generated of LocalBitcoins normalized prices over weeks:
A graph can be generated of LocalBitcoins non-normalized prices over weeks:
Bollinger bands
KanoPool
KanoPool records for addresses can be recorded to CSV in a way like the following:
denarius_loop_save_KanoPool.py --help
denarius_loop_save_KanoPool.py --addresses=1Miner7R28PKcTRbEDwQt4ykMinunhTehs --interval=10
The CSV data can be analysed using the Jupyter Notebook KanoPool.ipynb.
Slush Pool
Slush Pool records for an address can be recorded to CSV in a way like the following:
denarius_loop_save_SlushPool.py --help
denarius_loop_save_SlushPool.py --addresses=1Miner7R28PKcTRbEDwQt4ykMinunhTehs --interval=60 --alarm=11800000 --slushloginname=user --slushworkername=worker1
The CSV fields are, in order, as follows:
address
hash rate
shares
UNIX timestamp
unconfirmed reward in Bitcoin
confirmed reward in Bitcoin
total reward (confirmed + unconfirmed) in Bitcoin
total payout since script launch in Bitcoin
number of blocks found since script launch
The CSV data can be analysed using the Jupyter Notebook SlushPool.ipynb.
RBS
The RBS module provides utilities for getting the balance and recent transactions of an RBS account using the RBS banking web interface, Selenium and Firefox. For convenience, account details can be stored in a credentials file, which is assumed by default to be ~/.rbs. The account code is an alphanumeric code extracted from the web interface. The content of a credentials file is of the following form, which is Python code:
customer_number = "XXXXXXXXXX"
PIN = "XXXXXX"
passcode = "XXXXXXXXXXXXXXXXXXXX"
account_code = "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
A dictionary of the current balance and a pandas DataFrame of recent transactions is returned by the function RBS.account_status.
import RBS
status = RBS.account_status()
balance = status["balance"]
df = status["transactions"]
The DataFrame features the fields date, description and amount. A transaction containing a certain reference or description could be selected in the following way:
df[df["description"].str.contains("transaction reference 123")]
The existence of a transaction can be tested in a way like the following:
if df[df["description"].str.contains("transaction reference 123")].values.any():
print("transaction found")
else:
print("transaction not found")
The script get_account_balance_RBS.py is available to open an RBS account web interface and to display the current balance and recent transactions in the terminal, optionally in a loop.
get_account_balance_RBS.py --loop
The script detect_transaction_RBS.py is available to search for a transaction or transactions with a specified reference.
detect_transaction_RBS.py --reference=123
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