zcashd/qa/rpc-tests/test_framework/util.py

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# Copyright (c) 2014 The Bitcoin Core developers
# Distributed under the MIT software license, see the accompanying
# file COPYING or https://www.opensource.org/licenses/mit-license.php .
#
# Helpful routines for regression testing
#
# Add python-bitcoinrpc to module search path:
import os
import sys
from binascii import hexlify, unhexlify
from base64 import b64encode
from decimal import Decimal, ROUND_DOWN
import json
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
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import random
import shutil
import subprocess
import tempfile
import time
import re
import errno
from . import coverage
from .authproxy import AuthServiceProxy, JSONRPCException
COVERAGE_DIR = None
PRE_BLOSSOM_BLOCK_TARGET_SPACING = 150
POST_BLOSSOM_BLOCK_TARGET_SPACING = 75
def enable_coverage(dirname):
"""Maintain a log of which RPC calls are made during testing."""
global COVERAGE_DIR
COVERAGE_DIR = dirname
def get_rpc_proxy(url, node_number, timeout=None):
"""
Args:
url (str): URL of the RPC server to call
node_number (int): the node number (or id) that this calls to
Kwargs:
timeout (int): HTTP timeout in seconds
Returns:
AuthServiceProxy. convenience object for making RPC calls.
"""
proxy_kwargs = {}
if timeout is not None:
proxy_kwargs['timeout'] = timeout
proxy = AuthServiceProxy(url, **proxy_kwargs)
proxy.url = url # store URL on proxy for info
coverage_logfile = coverage.get_filename(
COVERAGE_DIR, node_number) if COVERAGE_DIR else None
return coverage.AuthServiceProxyWrapper(proxy, coverage_logfile)
def p2p_port(n):
return 11000 + n + os.getpid()%999
def rpc_port(n):
return 12000 + n + os.getpid()%999
def check_json_precision():
"""Make sure json library being used does not lose precision converting BTC values"""
n = Decimal("20000000.00000003")
satoshis = int(json.loads(json.dumps(float(n)))*1.0e8)
if satoshis != 2000000000000003:
raise RuntimeError("JSON encode/decode loses precision")
def bytes_to_hex_str(byte_str):
return hexlify(byte_str).decode('ascii')
def hex_str_to_bytes(hex_str):
return unhexlify(hex_str.encode('ascii'))
def str_to_b64str(string):
return b64encode(string.encode('utf-8')).decode('ascii')
def sync_blocks(rpc_connections, wait=1):
"""
Wait until everybody has the same block count, and has notified
all internal listeners of them
"""
while True:
counts = [ x.getblockcount() for x in rpc_connections ]
if counts == [ counts[0] ]*len(counts):
break
time.sleep(wait)
# Now that the block counts are in sync, wait for the internal
# notifications to finish
while True:
notified = [ x.getblockchaininfo()['fullyNotified'] for x in rpc_connections ]
if notified == [ True ] * len(notified):
break
time.sleep(wait)
def sync_mempools(rpc_connections, wait=1):
"""
Wait until everybody has the same transactions in their memory
pools, and has notified all internal listeners of them
"""
while True:
pool = set(rpc_connections[0].getrawmempool())
num_match = 1
for i in range(1, len(rpc_connections)):
if set(rpc_connections[i].getrawmempool()) == pool:
num_match = num_match+1
if num_match == len(rpc_connections):
break
time.sleep(wait)
# Now that the mempools are in sync, wait for the internal
# notifications to finish
while True:
notified = [ x.getmempoolinfo()['fullyNotified'] for x in rpc_connections ]
if notified == [ True ] * len(notified):
break
time.sleep(wait)
bitcoind_processes = {}
def initialize_datadir(dirname, n):
datadir = os.path.join(dirname, "node"+str(n))
if not os.path.isdir(datadir):
os.makedirs(datadir)
with open(os.path.join(datadir, "zcash.conf"), 'w') as f:
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f.write("regtest=1\n")
f.write("showmetrics=0\n")
f.write("rpcuser=rt\n")
f.write("rpcpassword=rt\n")
f.write("port="+str(p2p_port(n))+"\n")
f.write("rpcport="+str(rpc_port(n))+"\n")
f.write("listenonion=0\n")
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
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return datadir
def rpc_url(i, rpchost=None):
return "http://rt:rt@%s:%d" % (rpchost or '127.0.0.1', rpc_port(i))
def wait_for_bitcoind_start(process, url, i):
'''
Wait for bitcoind to start. This means that RPC is accessible and fully initialized.
Raise an exception if bitcoind exits during initialization.
'''
while True:
if process.poll() is not None:
raise Exception('bitcoind exited with status %i during initialization' % process.returncode)
try:
rpc = get_rpc_proxy(url, i)
rpc.getblockcount()
break # break out of loop on success
except IOError as e:
if e.errno != errno.ECONNREFUSED: # Port not yet open?
raise # unknown IO error
except JSONRPCException as e: # Initialization phase
if e.error['code'] != -28: # RPC in warmup?
raise # unkown JSON RPC exception
time.sleep(0.25)
def initialize_chain(test_dir):
"""
Create (or copy from cache) a 200-block-long chain and
4 wallets.
"""
# Due to the consensus change fix for the timejacking attack, we need to
# ensure that the cache is pretty fresh. Specifically, we need the median
# time past of the chain tip of the cache to be no more than 90 minutes
# behind the current local time, or else mined blocks will be rejected by
# all nodes, halting the test. With Sapling active by default, this requires
# the chain tip itself to be no more than 75 minutes behind the current
# local time.
#
# We address this here, by regenerating the cache if it is more than 60
# minutes old. This gives 15 minutes of slack initially that an RPC test has
# to complete in, if it is started right at the oldest cache time. Within an
# individual test, the first five calls to `generate` will each advance the
# median time past of the chain tip by 2.5 minutes (with Sapling active by
# default). Therefore, if the logic between the completion of any two
# adjacent calls to `generate` within a test takes longer than 2.5 minutes,
# the excess will subtract from the slack.
if os.path.isdir(os.path.join("cache", "node0")):
if os.stat("cache").st_mtime + (60 * 60) < time.time():
print("initialize_chain(): Removing stale cache")
shutil.rmtree("cache")
if (not os.path.isdir(os.path.join("cache","node0"))
or not os.path.isdir(os.path.join("cache","node1"))
or not os.path.isdir(os.path.join("cache","node2"))
or not os.path.isdir(os.path.join("cache","node3"))):
#find and delete old cache directories if any exist
for i in range(4):
if os.path.isdir(os.path.join("cache","node"+str(i))):
shutil.rmtree(os.path.join("cache","node"+str(i)))
# Create cache directories, run bitcoinds:
for i in range(4):
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
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datadir=initialize_datadir("cache", i)
args = [ os.getenv("BITCOIND", "bitcoind"), "-keypool=1", "-datadir="+datadir, "-discover=0" ]
args.extend([
'-nuparams=5ba81b19:1', # Overwinter
'-nuparams=76b809bb:1', # Sapling
])
if i > 0:
args.append("-connect=127.0.0.1:"+str(p2p_port(0)))
bitcoind_processes[i] = subprocess.Popen(args)
if os.getenv("PYTHON_DEBUG", ""):
print("initialize_chain: bitcoind started, waiting for RPC to come up")
wait_for_bitcoind_start(bitcoind_processes[i], rpc_url(i), i)
if os.getenv("PYTHON_DEBUG", ""):
print("initialize_chain: RPC succesfully started")
rpcs = []
for i in range(4):
try:
rpcs.append(get_rpc_proxy(rpc_url(i), i))
except:
sys.stderr.write("Error connecting to "+rpc_url(i)+"\n")
sys.exit(1)
# Create a 200-block-long chain; each of the 4 nodes
# gets 25 mature blocks and 25 immature.
# Blocks are created with timestamps 2.5 minutes apart (matching the
# chain defaulting above to Sapling active), starting 200 * 2.5 minutes
# before the current time.
block_time = int(time.time()) - (200 * PRE_BLOSSOM_BLOCK_TARGET_SPACING)
for i in range(2):
for peer in range(4):
for j in range(25):
set_node_times(rpcs, block_time)
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rpcs[peer].generate(1)
block_time += PRE_BLOSSOM_BLOCK_TARGET_SPACING
# Must sync before next peer starts generating blocks
sync_blocks(rpcs)
# Check that local time isn't going backwards
assert_greater_than(time.time() + 1, block_time)
# Shut them down, and clean up cache directories:
stop_nodes(rpcs)
wait_bitcoinds()
for i in range(4):
os.remove(log_filename("cache", i, "debug.log"))
os.remove(log_filename("cache", i, "db.log"))
os.remove(log_filename("cache", i, "peers.dat"))
os.remove(log_filename("cache", i, "fee_estimates.dat"))
for i in range(4):
from_dir = os.path.join("cache", "node"+str(i))
to_dir = os.path.join(test_dir, "node"+str(i))
shutil.copytree(from_dir, to_dir)
initialize_datadir(test_dir, i) # Overwrite port/rpcport in zcash.conf
def initialize_chain_clean(test_dir, num_nodes):
"""
Create an empty blockchain and num_nodes wallets.
Useful if a test case wants complete control over initialization.
"""
for i in range(num_nodes):
initialize_datadir(test_dir, i)
def _rpchost_to_args(rpchost):
'''Convert optional IP:port spec to rpcconnect/rpcport args'''
if rpchost is None:
return []
match = re.match('(\[[0-9a-fA-f:]+\]|[^:]+)(?::([0-9]+))?$', rpchost)
if not match:
raise ValueError('Invalid RPC host spec ' + rpchost)
rpcconnect = match.group(1)
rpcport = match.group(2)
if rpcconnect.startswith('['): # remove IPv6 [...] wrapping
rpcconnect = rpcconnect[1:-1]
rv = ['-rpcconnect=' + rpcconnect]
if rpcport:
rv += ['-rpcport=' + rpcport]
return rv
def start_node(i, dirname, extra_args=None, rpchost=None, timewait=None, binary=None, stderr=None):
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
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"""
Start a bitcoind and return RPC connection to it
"""
datadir = os.path.join(dirname, "node"+str(i))
if binary is None:
binary = os.getenv("BITCOIND", "bitcoind")
args = [ binary, "-datadir="+datadir, "-keypool=1", "-discover=0", "-rest" ]
args.extend([
'-nuparams=5ba81b19:1', # Overwinter
'-nuparams=76b809bb:1', # Sapling
])
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
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if extra_args is not None: args.extend(extra_args)
bitcoind_processes[i] = subprocess.Popen(args, stderr=stderr)
if os.getenv("PYTHON_DEBUG", ""):
print("start_node: bitcoind started, waiting for RPC to come up")
url = rpc_url(i, rpchost)
wait_for_bitcoind_start(bitcoind_processes[i], url, i)
if os.getenv("PYTHON_DEBUG", ""):
print("start_node: RPC succesfully started")
proxy = get_rpc_proxy(url, i, timeout=timewait)
if COVERAGE_DIR:
coverage.write_all_rpc_commands(COVERAGE_DIR, proxy)
return proxy
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
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def assert_start_raises_init_error(i, dirname, extra_args=None, expected_msg=None):
with tempfile.SpooledTemporaryFile(max_size=2**16) as log_stderr:
try:
node = start_node(i, dirname, extra_args, stderr=log_stderr)
stop_node(node, i)
except Exception as e:
assert 'bitcoind exited' in str(e) #node must have shutdown
if expected_msg is not None:
log_stderr.seek(0)
stderr = log_stderr.read().decode('utf-8')
if expected_msg not in stderr:
raise AssertionError("Expected error \"" + expected_msg + "\" not found in:\n" + stderr)
else:
if expected_msg is None:
assert_msg = "bitcoind should have exited with an error"
else:
assert_msg = "bitcoind should have exited with expected error " + expected_msg
raise AssertionError(assert_msg)
def start_nodes(num_nodes, dirname, extra_args=None, rpchost=None, binary=None):
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
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"""
Start multiple bitcoinds, return RPC connections to them
"""
if extra_args is None: extra_args = [ None for i in range(num_nodes) ]
if binary is None: binary = [ None for i in range(num_nodes) ]
rpcs = []
try:
for i in range(num_nodes):
rpcs.append(start_node(i, dirname, extra_args[i], rpchost, binary=binary[i]))
except: # If one node failed to start, stop the others
stop_nodes(rpcs)
raise
return rpcs
def log_filename(dirname, n_node, logname):
return os.path.join(dirname, "node"+str(n_node), "regtest", logname)
def check_node(i):
bitcoind_processes[i].poll()
return bitcoind_processes[i].returncode
def stop_node(node, i):
node.stop()
bitcoind_processes[i].wait()
del bitcoind_processes[i]
def stop_nodes(nodes):
for node in nodes:
node.stop()
del nodes[:] # Emptying array closes connections as a side effect
def set_node_times(nodes, t):
for node in nodes:
node.setmocktime(t)
def wait_bitcoinds():
# Wait for all bitcoinds to cleanly exit
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for bitcoind in list(bitcoind_processes.values()):
bitcoind.wait()
bitcoind_processes.clear()
def connect_nodes(from_connection, node_num):
ip_port = "127.0.0.1:"+str(p2p_port(node_num))
from_connection.addnode(ip_port, "onetry")
# poll until version handshake complete to avoid race conditions
# with transaction relaying
while any(peer['version'] == 0 for peer in from_connection.getpeerinfo()):
time.sleep(0.1)
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def connect_nodes_bi(nodes, a, b):
connect_nodes(nodes[a], b)
connect_nodes(nodes[b], a)
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
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def find_output(node, txid, amount):
"""
Return index to output of txid with value amount
Raises exception if there is none.
"""
txdata = node.getrawtransaction(txid, 1)
for i in range(len(txdata["vout"])):
if txdata["vout"][i]["value"] == amount:
return i
raise RuntimeError("find_output txid %s : %s not found"%(txid,str(amount)))
def gather_inputs(from_node, amount_needed, confirmations_required=1):
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
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"""
Return a random set of unspent txouts that are enough to pay amount_needed
"""
assert(confirmations_required >=0)
utxo = from_node.listunspent(confirmations_required)
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
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random.shuffle(utxo)
inputs = []
total_in = Decimal("0.00000000")
while total_in < amount_needed and len(utxo) > 0:
t = utxo.pop()
total_in += t["amount"]
inputs.append({ "txid" : t["txid"], "vout" : t["vout"], "address" : t["address"] } )
if total_in < amount_needed:
raise RuntimeError("Insufficient funds: need %d, have %d"%(amount_needed, total_in))
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
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return (total_in, inputs)
def make_change(from_node, amount_in, amount_out, fee):
"""
Create change output(s), return them
"""
outputs = {}
amount = amount_out+fee
change = amount_in - amount
if change > amount*2:
# Create an extra change output to break up big inputs
change_address = from_node.getnewaddress()
# Split change in two, being careful of rounding:
outputs[change_address] = Decimal(change/2).quantize(Decimal('0.00000001'), rounding=ROUND_DOWN)
change = amount_in - amount - outputs[change_address]
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
2014-03-17 05:19:54 -07:00
if change > 0:
outputs[from_node.getnewaddress()] = change
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
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return outputs
def send_zeropri_transaction(from_node, to_node, amount, fee):
"""
Create&broadcast a zero-priority transaction.
Returns (txid, hex-encoded-txdata)
Ensures transaction is zero-priority by first creating a send-to-self,
2015-04-28 07:48:28 -07:00
then using its output
estimatefee / estimatepriority RPC methods New RPC methods: return an estimate of the fee (or priority) a transaction needs to be likely to confirm in a given number of blocks. Mike Hearn created the first version of this method for estimating fees. It works as follows: For transactions that took 1 to N (I picked N=25) blocks to confirm, keep N buckets with at most 100 entries in each recording the fees-per-kilobyte paid by those transactions. (separate buckets are kept for transactions that confirmed because they are high-priority) The buckets are filled as blocks are found, and are saved/restored in a new fee_estiamtes.dat file in the data directory. A few variations on Mike's initial scheme: To estimate the fee needed for a transaction to confirm in X buckets, all of the samples in all of the buckets are used and a median of all of the data is used to make the estimate. For example, imagine 25 buckets each containing the full 100 entries. Those 2,500 samples are sorted, and the estimate of the fee needed to confirm in the very next block is the 50'th-highest-fee-entry in that sorted list; the estimate of the fee needed to confirm in the next two blocks is the 150'th-highest-fee-entry, etc. That algorithm has the nice property that estimates of how much fee you need to pay to get confirmed in block N will always be greater than or equal to the estimate for block N+1. It would clearly be wrong to say "pay 11 uBTC and you'll get confirmed in 3 blocks, but pay 12 uBTC and it will take LONGER". A single block will not contribute more than 10 entries to any one bucket, so a single miner and a large block cannot overwhelm the estimates.
2014-03-17 05:19:54 -07:00
"""
# Create a send-to-self with confirmed inputs:
self_address = from_node.getnewaddress()
(total_in, inputs) = gather_inputs(from_node, amount+fee*2)
outputs = make_change(from_node, total_in, amount+fee, fee)
outputs[self_address] = float(amount+fee)
self_rawtx = from_node.createrawtransaction(inputs, outputs)
self_signresult = from_node.signrawtransaction(self_rawtx)
self_txid = from_node.sendrawtransaction(self_signresult["hex"], True)
vout = find_output(from_node, self_txid, amount+fee)
# Now immediately spend the output to create a 1-input, 1-output
# zero-priority transaction:
inputs = [ { "txid" : self_txid, "vout" : vout } ]
outputs = { to_node.getnewaddress() : float(amount) }
rawtx = from_node.createrawtransaction(inputs, outputs)
signresult = from_node.signrawtransaction(rawtx)
txid = from_node.sendrawtransaction(signresult["hex"], True)
return (txid, signresult["hex"])
def random_zeropri_transaction(nodes, amount, min_fee, fee_increment, fee_variants):
"""
Create a random zero-priority transaction.
Returns (txid, hex-encoded-transaction-data, fee)
"""
from_node = random.choice(nodes)
to_node = random.choice(nodes)
fee = min_fee + fee_increment*random.randint(0,fee_variants)
(txid, txhex) = send_zeropri_transaction(from_node, to_node, amount, fee)
return (txid, txhex, fee)
def random_transaction(nodes, amount, min_fee, fee_increment, fee_variants):
"""
Create a random transaction.
Returns (txid, hex-encoded-transaction-data, fee)
"""
from_node = random.choice(nodes)
to_node = random.choice(nodes)
fee = min_fee + fee_increment*random.randint(0,fee_variants)
(total_in, inputs) = gather_inputs(from_node, amount+fee)
outputs = make_change(from_node, total_in, amount, fee)
outputs[to_node.getnewaddress()] = float(amount)
rawtx = from_node.createrawtransaction(inputs, outputs)
signresult = from_node.signrawtransaction(rawtx)
txid = from_node.sendrawtransaction(signresult["hex"], True)
return (txid, signresult["hex"], fee)
def assert_equal(expected, actual, message=""):
if expected != actual:
if message:
message = "; %s" % message
raise AssertionError("(left == right)%s\n left: <%s>\n right: <%s>" % (message, str(expected), str(actual)))
def assert_true(condition, message = ""):
if not condition:
raise AssertionError(message)
def assert_false(condition, message = ""):
assert_true(not condition, message)
def assert_greater_than(thing1, thing2):
if thing1 <= thing2:
raise AssertionError("%s <= %s"%(str(thing1),str(thing2)))
def assert_raises(exc, fun, *args, **kwds):
try:
fun(*args, **kwds)
except exc:
pass
except Exception as e:
raise AssertionError("Unexpected exception raised: "+type(e).__name__)
else:
raise AssertionError("No exception raised")
2018-10-18 11:59:29 -07:00
def fail(message=""):
raise AssertionError(message)
# Returns an async operation result
def wait_and_assert_operationid_status_result(node, myopid, in_status='success', in_errormsg=None, timeout=300):
print('waiting for async operation {}'.format(myopid))
result = None
2019-11-20 12:12:46 -08:00
for _ in range(1, timeout):
results = node.z_getoperationresult([myopid])
if len(results) > 0:
result = results[0]
break
time.sleep(1)
assert_true(result is not None, "timeout occured")
status = result['status']
debug = os.getenv("PYTHON_DEBUG", "")
if debug:
print('...returned status: {}'.format(status))
errormsg = None
if status == "failed":
errormsg = result['error']['message']
if debug:
print('...returned error: {}'.format(errormsg))
assert_equal(in_errormsg, errormsg)
assert_equal(in_status, status, "Operation returned mismatched status. Error Message: {}".format(errormsg))
return result
# Returns txid if operation was a success or None
def wait_and_assert_operationid_status(node, myopid, in_status='success', in_errormsg=None, timeout=300):
result = wait_and_assert_operationid_status_result(node, myopid, in_status, in_errormsg, timeout)
if result['status'] == "success":
return result['result']['txid']
else:
return None
# Find a coinbase address on the node, filtering by the number of UTXOs it has.
# If no filter is provided, returns the coinbase address on the node containing
# the greatest number of spendable UTXOs.
# The default cached chain has one address per coinbase output.
def get_coinbase_address(node, expected_utxos=None):
addrs = [utxo['address'] for utxo in node.listunspent() if utxo['generated']]
assert(len(set(addrs)) > 0)
if expected_utxos is None:
addrs = [(addrs.count(a), a) for a in set(addrs)]
return sorted(addrs, reverse=True)[0][1]
addrs = [a for a in set(addrs) if addrs.count(a) == expected_utxos]
assert(len(addrs) > 0)
return addrs[0]
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def check_node_log(self, node_number, line_to_check, stop_node = True):
2020-03-06 14:17:18 -08:00
print("Checking node " + str(node_number) + " logs")
if stop_node:
self.nodes[node_number].stop()
bitcoind_processes[node_number].wait()
2020-03-06 14:17:18 -08:00
logpath = self.options.tmpdir + "/node" + str(node_number) + "/regtest/debug.log"
with open(logpath, "r") as myfile:
logdata = myfile.readlines()
for (n, logline) in enumerate(logdata):
2020-03-06 14:17:18 -08:00
if line_to_check in logline:
return n
raise AssertionError(repr(line_to_check) + " not found")