content stringlengths 7 1.05M | fixed_cases stringlengths 1 1.28M |
|---|---|
def outer ():
def inner():
print(x )
x = 12
inner()
outer() | def outer():
def inner():
print(x)
x = 12
inner()
outer() |
print ("--------------------------------------------------")
cad1 = "separar"
print (cad1)
nuevo_string1 = ",".join(cad1)
print (nuevo_string1)
print ("--------------------------------------------------")
cad2 = "mi archivo de texto.txt"
print (cad2)
nuevo_string2 = cad2.split()
nuevo_string2 = "_".join(nuevo_string2)
print (nuevo_string2)
print ("--------------------------------------------------")
cad3 = "su clave es: 1540"
print (cad3)
nuevo_string3 = cad3.replace(cad3[13:], "XXXX")
print (nuevo_string3)
print ("--------------------------------------------------")
cad4 = "2552552550"
print (cad4)
nuevo_string4 = cad4.replace("55", "55.")
print (nuevo_string4)
nuevo_string4 = nuevo_string4.split(".")
print (nuevo_string4)
nuevo_string4 = ".".join(nuevo_string4)
print (nuevo_string4)
print ("--------------------------------------------------")
| print('--------------------------------------------------')
cad1 = 'separar'
print(cad1)
nuevo_string1 = ','.join(cad1)
print(nuevo_string1)
print('--------------------------------------------------')
cad2 = 'mi archivo de texto.txt'
print(cad2)
nuevo_string2 = cad2.split()
nuevo_string2 = '_'.join(nuevo_string2)
print(nuevo_string2)
print('--------------------------------------------------')
cad3 = 'su clave es: 1540'
print(cad3)
nuevo_string3 = cad3.replace(cad3[13:], 'XXXX')
print(nuevo_string3)
print('--------------------------------------------------')
cad4 = '2552552550'
print(cad4)
nuevo_string4 = cad4.replace('55', '55.')
print(nuevo_string4)
nuevo_string4 = nuevo_string4.split('.')
print(nuevo_string4)
nuevo_string4 = '.'.join(nuevo_string4)
print(nuevo_string4)
print('--------------------------------------------------') |
def is_even(n):
if n % 2 == 0:
return True
def is_positive(n):
if n >= 0:
return True
def get_result(collection):
result = [str(x) for x in collection]
return ", ".join(result)
numbers = [int(x) for x in input().split(", ")]
positive_nums = []
negative_nums = []
even_nums = []
odd_nums = []
for n in numbers:
if is_positive(n):
positive_nums.append(n)
else:
negative_nums.append(n)
if is_even(n):
even_nums.append(n)
else:
odd_nums.append(n)
print(f"Positive: {get_result(positive_nums)}")
print(f"Negative: {get_result(negative_nums)}")
print(f"Even: {get_result(even_nums)}")
print(f"Odd: {get_result(odd_nums)}") | def is_even(n):
if n % 2 == 0:
return True
def is_positive(n):
if n >= 0:
return True
def get_result(collection):
result = [str(x) for x in collection]
return ', '.join(result)
numbers = [int(x) for x in input().split(', ')]
positive_nums = []
negative_nums = []
even_nums = []
odd_nums = []
for n in numbers:
if is_positive(n):
positive_nums.append(n)
else:
negative_nums.append(n)
if is_even(n):
even_nums.append(n)
else:
odd_nums.append(n)
print(f'Positive: {get_result(positive_nums)}')
print(f'Negative: {get_result(negative_nums)}')
print(f'Even: {get_result(even_nums)}')
print(f'Odd: {get_result(odd_nums)}') |
def multi_print(number = 3, word = "Hallo"):
for i in range(0, number):
print(str(i) + " " + word)
multi_print(1, "Hallo")
print("--")
multi_print()
print("--")
multi_print(2)
print("--")
multi_print(word = "Welt")
print("--")
multi_print(word = "Welt", number = 5)
print("--")
| def multi_print(number=3, word='Hallo'):
for i in range(0, number):
print(str(i) + ' ' + word)
multi_print(1, 'Hallo')
print('--')
multi_print()
print('--')
multi_print(2)
print('--')
multi_print(word='Welt')
print('--')
multi_print(word='Welt', number=5)
print('--') |
"""
The structure of a blockchain, Which is accessed like JSON or a dict.
"""
block = {
"index": 1,
"timestamp": 1506057125.900785,
"transactions": [
{
"sender": "8527147fe1f5426f9dd545de4b27ee00",
"recipient": "a77f5cdfa2934df3954a5c7c7da5df1f",
"amount": 5,
}
],
"proof": 324984774000,
"previous_hash": "2cf24dba5fb0a30e26e83b2ac5b9e29e1b161e5c1fa7425e73043362938b9824",
}
| """
The structure of a blockchain, Which is accessed like JSON or a dict.
"""
block = {'index': 1, 'timestamp': 1506057125.900785, 'transactions': [{'sender': '8527147fe1f5426f9dd545de4b27ee00', 'recipient': 'a77f5cdfa2934df3954a5c7c7da5df1f', 'amount': 5}], 'proof': 324984774000, 'previous_hash': '2cf24dba5fb0a30e26e83b2ac5b9e29e1b161e5c1fa7425e73043362938b9824'} |
# Copyright (c) 2021 Graphcore Ltd. All rights reserved.
_blank_symbol_ctc = '_'
_pad_symbol = '#'
_characters = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ\' '
# Export all symbols:
symbols = [_blank_symbol_ctc] + list(_characters) + [_pad_symbol]
# Mappings from symbol to numeric ID and vice versa
# (remember - ID zero is reserved for blank symbol of CTC loss)
_symbol_to_id = {s: i for i, s in enumerate(symbols)}
_id_to_symbol = {i: s for i, s in enumerate(symbols)}
def text_to_sequence(text):
""" converts text to sequence of numeric IDs """
# putting space for punctuations
space_id = _symbol_to_id[' ']
return [_symbol_to_id.get(s, space_id) if s not in [_blank_symbol_ctc, _pad_symbol] else space_id
for s in text]
def sequence_to_text(sequence, seq_length):
""" converts numeric sequence to text """
pad_id = _symbol_to_id[_pad_symbol]
return "".join([_id_to_symbol[id] for id in sequence[0:seq_length] if id != pad_id])
def pad_text_sequence(text_sequence, max_text_sequence_length):
""" pad numeric text sequence if required """
pad = max_text_sequence_length - len(text_sequence)
if pad <= 0:
return text_sequence[0:max_text_sequence_length]
return text_sequence + [_symbol_to_id[_pad_symbol]] * pad
| _blank_symbol_ctc = '_'
_pad_symbol = '#'
_characters = "ABCDEFGHIJKLMNOPQRSTUVWXYZ' "
symbols = [_blank_symbol_ctc] + list(_characters) + [_pad_symbol]
_symbol_to_id = {s: i for (i, s) in enumerate(symbols)}
_id_to_symbol = {i: s for (i, s) in enumerate(symbols)}
def text_to_sequence(text):
""" converts text to sequence of numeric IDs """
space_id = _symbol_to_id[' ']
return [_symbol_to_id.get(s, space_id) if s not in [_blank_symbol_ctc, _pad_symbol] else space_id for s in text]
def sequence_to_text(sequence, seq_length):
""" converts numeric sequence to text """
pad_id = _symbol_to_id[_pad_symbol]
return ''.join([_id_to_symbol[id] for id in sequence[0:seq_length] if id != pad_id])
def pad_text_sequence(text_sequence, max_text_sequence_length):
""" pad numeric text sequence if required """
pad = max_text_sequence_length - len(text_sequence)
if pad <= 0:
return text_sequence[0:max_text_sequence_length]
return text_sequence + [_symbol_to_id[_pad_symbol]] * pad |
PEER_DID_NUMALGO_0 = "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V"
DID_DOC_NUMALGO_O_BASE58 = """
{
"id": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"authentication": [
{
"id": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"type": "Ed25519VerificationKey2018",
"controller": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"publicKeyBase58": "ByHnpUCFb1vAfh9CFZ8ZkmUZguURW8nSw889hy6rD8L7"
}
]
}
"""
DID_DOC_NUMALGO_O_MULTIBASE = """
{
"id": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"authentication": [
{
"id": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"type": "Ed25519VerificationKey2020",
"controller": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"publicKeyMultibase": "z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V"
}
]
}
"""
DID_DOC_NUMALGO_O_JWK = """
{
"id": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"authentication": [
{
"id": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"type": "JsonWebKey2020",
"controller": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"publicKeyJwk": {
"kty": "OKP",
"crv": "Ed25519",
"x": "owBhCbktDjkfS6PdQddT0D3yjSitaSysP3YimJ_YgmA"
}
}
]
}
"""
PEER_DID_NUMALGO_2 = (
"did:peer:2"
+ ".Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc"
+ ".Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V"
+ ".Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg"
+ ".SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0"
)
DID_DOC_NUMALGO_2_BASE58 = """
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",
"authentication": [
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"type": "Ed25519VerificationKey2018",
"controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",
"publicKeyBase58": "ByHnpUCFb1vAfh9CFZ8ZkmUZguURW8nSw889hy6rD8L7"
},
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg",
"type": "Ed25519VerificationKey2018",
"controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",
"publicKeyBase58": "3M5RCDjPTWPkKSN3sxUmmMqHbmRPegYP1tjcKyrDbt9J"
}
],
"keyAgreement": [
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc",
"type": "X25519KeyAgreementKey2019",
"controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",
"publicKeyBase58": "JhNWeSVLMYccCk7iopQW4guaSJTojqpMEELgSLhKwRr"
}
],
"service": [
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#didcommmessaging-0",
"type": "DIDCommMessaging",
"serviceEndpoint": "https://example.com/endpoint",
"routingKeys": [
"did:example:somemediator#somekey"
],
"accept": [
"didcomm/v2", "didcomm/aip2;env=rfc587"
]
}
]
}
"""
DID_DOC_NUMALGO_2_MULTIBASE = """
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",
"authentication": [
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"type": "Ed25519VerificationKey2020",
"controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",
"publicKeyMultibase": "z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V"
},
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg",
"type": "Ed25519VerificationKey2020",
"controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",
"publicKeyMultibase": "z6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg"
}
],
"keyAgreement": [
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc",
"type": "X25519KeyAgreementKey2020",
"controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",
"publicKeyMultibase": "z6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc"
}
],
"service": [
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#didcommmessaging-0",
"type": "DIDCommMessaging",
"serviceEndpoint": "https://example.com/endpoint",
"routingKeys": [
"did:example:somemediator#somekey"
],
"accept": [
"didcomm/v2", "didcomm/aip2;env=rfc587"
]
}
]
}
"""
DID_DOC_NUMALGO_2_JWK = """
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",
"authentication": [
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"type": "JsonWebKey2020",
"controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",
"publicKeyJwk": {
"kty": "OKP",
"crv": "Ed25519",
"x": "owBhCbktDjkfS6PdQddT0D3yjSitaSysP3YimJ_YgmA"
}
},
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg",
"type": "JsonWebKey2020",
"controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",
"publicKeyJwk": {
"kty": "OKP",
"crv": "Ed25519",
"x": "Itv8B__b1-Jos3LCpUe8EdTFGTCa_Dza6_3848P3R70"
}
}
],
"keyAgreement": [
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc",
"type": "JsonWebKey2020",
"controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",
"publicKeyJwk": {
"kty": "OKP",
"crv": "X25519",
"x": "BIiFcQEn3dfvB2pjlhOQQour6jXy9d5s2FKEJNTOJik"
}
}
],
"service": [
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#didcommmessaging-0",
"type": "DIDCommMessaging",
"serviceEndpoint": "https://example.com/endpoint",
"routingKeys": [
"did:example:somemediator#somekey"
],
"accept": [
"didcomm/v2", "didcomm/aip2;env=rfc587"
]
}
]
}
"""
PEER_DID_NUMALGO_2_2_SERVICES = (
"did:peer:2"
+ ".Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud"
+ ".Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V"
+ ".SW3sidCI6ImRtIiwicyI6Imh0dHBzOi8vZXhhbXBsZS5jb20vZW5kcG9pbnQiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5Il19LHsidCI6ImV4YW1wbGUiLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludDIiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5MiJdLCJhIjpbImRpZGNvbW0vdjIiLCJkaWRjb21tL2FpcDI7ZW52PXJmYzU4NyJdfV0"
)
DID_DOC_NUMALGO_2_MULTIBASE_2_SERVICES = """
{
"id": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.SW3sidCI6ImRtIiwicyI6Imh0dHBzOi8vZXhhbXBsZS5jb20vZW5kcG9pbnQiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5Il19LHsidCI6ImV4YW1wbGUiLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludDIiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5MiJdLCJhIjpbImRpZGNvbW0vdjIiLCJkaWRjb21tL2FpcDI7ZW52PXJmYzU4NyJdfV0",
"authentication": [
{
"id": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.SW3sidCI6ImRtIiwicyI6Imh0dHBzOi8vZXhhbXBsZS5jb20vZW5kcG9pbnQiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5Il19LHsidCI6ImV4YW1wbGUiLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludDIiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5MiJdLCJhIjpbImRpZGNvbW0vdjIiLCJkaWRjb21tL2FpcDI7ZW52PXJmYzU4NyJdfV0#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"type": "Ed25519VerificationKey2020",
"controller": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.SW3sidCI6ImRtIiwicyI6Imh0dHBzOi8vZXhhbXBsZS5jb20vZW5kcG9pbnQiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5Il19LHsidCI6ImV4YW1wbGUiLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludDIiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5MiJdLCJhIjpbImRpZGNvbW0vdjIiLCJkaWRjb21tL2FpcDI7ZW52PXJmYzU4NyJdfV0",
"publicKeyMultibase": "z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V"
}
],
"keyAgreement": [
{
"id": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.SW3sidCI6ImRtIiwicyI6Imh0dHBzOi8vZXhhbXBsZS5jb20vZW5kcG9pbnQiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5Il19LHsidCI6ImV4YW1wbGUiLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludDIiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5MiJdLCJhIjpbImRpZGNvbW0vdjIiLCJkaWRjb21tL2FpcDI7ZW52PXJmYzU4NyJdfV0#6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud",
"type": "X25519KeyAgreementKey2020",
"controller": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.SW3sidCI6ImRtIiwicyI6Imh0dHBzOi8vZXhhbXBsZS5jb20vZW5kcG9pbnQiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5Il19LHsidCI6ImV4YW1wbGUiLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludDIiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5MiJdLCJhIjpbImRpZGNvbW0vdjIiLCJkaWRjb21tL2FpcDI7ZW52PXJmYzU4NyJdfV0",
"publicKeyMultibase": "z6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud"
}
],
"service": [
{
"id": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.SW3sidCI6ImRtIiwicyI6Imh0dHBzOi8vZXhhbXBsZS5jb20vZW5kcG9pbnQiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5Il19LHsidCI6ImV4YW1wbGUiLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludDIiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5MiJdLCJhIjpbImRpZGNvbW0vdjIiLCJkaWRjb21tL2FpcDI7ZW52PXJmYzU4NyJdfV0#didcommmessaging-0",
"type": "DIDCommMessaging",
"serviceEndpoint": "https://example.com/endpoint",
"routingKeys": [
"did:example:somemediator#somekey"
]
},
{
"id": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.SW3sidCI6ImRtIiwicyI6Imh0dHBzOi8vZXhhbXBsZS5jb20vZW5kcG9pbnQiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5Il19LHsidCI6ImV4YW1wbGUiLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludDIiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5MiJdLCJhIjpbImRpZGNvbW0vdjIiLCJkaWRjb21tL2FpcDI7ZW52PXJmYzU4NyJdfV0#example-1",
"type": "example",
"serviceEndpoint": "https://example.com/endpoint2",
"routingKeys": [
"did:example:somemediator#somekey2"
],
"accept": ["didcomm/v2", "didcomm/aip2;env=rfc587"]
}
]
}
"""
PEER_DID_NUMALGO_2_NO_SERVICES = (
"did:peer:2"
+ ".Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud"
+ ".Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V"
)
DID_DOC_NUMALGO_2_MULTIBASE_NO_SERVICES = """
{
"id": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"authentication": [
{
"id": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"type": "Ed25519VerificationKey2020",
"controller": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"publicKeyMultibase": "z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V"
}
],
"keyAgreement": [
{
"id": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V#6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud",
"type": "X25519KeyAgreementKey2020",
"controller": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"publicKeyMultibase": "z6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud"
}
]
}
"""
PEER_DID_NUMALGO_2_MINIMAL_SERVICES = "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9"
DID_DOC_NUMALGO_2_MULTIBASE_MINIMAL_SERVICES = """
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9",
"authentication": [
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",
"type": "Ed25519VerificationKey2020",
"controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9",
"publicKeyMultibase": "z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V"
},
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9#6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg",
"type": "Ed25519VerificationKey2020",
"controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9",
"publicKeyMultibase": "z6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg"
}
],
"keyAgreement": [
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9#6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc",
"type": "X25519KeyAgreementKey2020",
"controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9",
"publicKeyMultibase": "z6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc"
}
],
"service": [
{
"id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9#didcommmessaging-0",
"serviceEndpoint": "https://example.com/endpoint",
"type": "DIDCommMessaging"
}
]
}
"""
| peer_did_numalgo_0 = 'did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V'
did_doc_numalgo_o_base58 = '\n {\n "id": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "authentication": [\n {\n "id": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "type": "Ed25519VerificationKey2018",\n "controller": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "publicKeyBase58": "ByHnpUCFb1vAfh9CFZ8ZkmUZguURW8nSw889hy6rD8L7"\n }\n ]\n }\n '
did_doc_numalgo_o_multibase = '\n {\n "id": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "authentication": [\n {\n "id": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "type": "Ed25519VerificationKey2020",\n "controller": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "publicKeyMultibase": "z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V"\n }\n ]\n }\n '
did_doc_numalgo_o_jwk = '\n {\n "id": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "authentication": [\n {\n "id": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "type": "JsonWebKey2020",\n "controller": "did:peer:0z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "publicKeyJwk": {\n "kty": "OKP",\n "crv": "Ed25519",\n "x": "owBhCbktDjkfS6PdQddT0D3yjSitaSysP3YimJ_YgmA"\n }\n }\n ]\n }\n '
peer_did_numalgo_2 = 'did:peer:2' + '.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc' + '.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V' + '.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg' + '.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0'
did_doc_numalgo_2_base58 = '\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",\n "authentication": [\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "type": "Ed25519VerificationKey2018",\n "controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",\n "publicKeyBase58": "ByHnpUCFb1vAfh9CFZ8ZkmUZguURW8nSw889hy6rD8L7"\n },\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg",\n "type": "Ed25519VerificationKey2018",\n "controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",\n "publicKeyBase58": "3M5RCDjPTWPkKSN3sxUmmMqHbmRPegYP1tjcKyrDbt9J"\n }\n ],\n "keyAgreement": [\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc",\n "type": "X25519KeyAgreementKey2019",\n "controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",\n "publicKeyBase58": "JhNWeSVLMYccCk7iopQW4guaSJTojqpMEELgSLhKwRr"\n }\n ],\n "service": [\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#didcommmessaging-0",\n "type": "DIDCommMessaging",\n "serviceEndpoint": "https://example.com/endpoint",\n "routingKeys": [\n "did:example:somemediator#somekey"\n ],\n "accept": [\n "didcomm/v2", "didcomm/aip2;env=rfc587"\n ]\n }\n ]\n }\n '
did_doc_numalgo_2_multibase = '\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",\n "authentication": [\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "type": "Ed25519VerificationKey2020",\n "controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",\n "publicKeyMultibase": "z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V"\n },\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg",\n "type": "Ed25519VerificationKey2020",\n "controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",\n "publicKeyMultibase": "z6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg"\n }\n ],\n "keyAgreement": [\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc",\n "type": "X25519KeyAgreementKey2020",\n "controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",\n "publicKeyMultibase": "z6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc"\n }\n ],\n "service": [\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#didcommmessaging-0",\n "type": "DIDCommMessaging",\n "serviceEndpoint": "https://example.com/endpoint",\n "routingKeys": [\n "did:example:somemediator#somekey"\n ],\n "accept": [\n "didcomm/v2", "didcomm/aip2;env=rfc587"\n ]\n }\n ]\n }\n '
did_doc_numalgo_2_jwk = '\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",\n "authentication": [\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "type": "JsonWebKey2020",\n "controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",\n "publicKeyJwk": {\n "kty": "OKP",\n "crv": "Ed25519",\n "x": "owBhCbktDjkfS6PdQddT0D3yjSitaSysP3YimJ_YgmA"\n }\n },\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg",\n "type": "JsonWebKey2020",\n "controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",\n "publicKeyJwk": {\n "kty": "OKP",\n "crv": "Ed25519",\n "x": "Itv8B__b1-Jos3LCpUe8EdTFGTCa_Dza6_3848P3R70"\n }\n }\n ],\n "keyAgreement": [\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc",\n "type": "JsonWebKey2020",\n "controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0",\n "publicKeyJwk": {\n "kty": "OKP",\n "crv": "X25519",\n "x": "BIiFcQEn3dfvB2pjlhOQQour6jXy9d5s2FKEJNTOJik"\n }\n }\n ],\n "service": [\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCIsInIiOlsiZGlkOmV4YW1wbGU6c29tZW1lZGlhdG9yI3NvbWVrZXkiXSwiYSI6WyJkaWRjb21tL3YyIiwiZGlkY29tbS9haXAyO2Vudj1yZmM1ODciXX0#didcommmessaging-0",\n "type": "DIDCommMessaging",\n "serviceEndpoint": "https://example.com/endpoint",\n "routingKeys": [\n "did:example:somemediator#somekey"\n ],\n "accept": [\n "didcomm/v2", "didcomm/aip2;env=rfc587"\n ]\n }\n ]\n }\n '
peer_did_numalgo_2_2_services = 'did:peer:2' + '.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud' + '.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V' + '.SW3sidCI6ImRtIiwicyI6Imh0dHBzOi8vZXhhbXBsZS5jb20vZW5kcG9pbnQiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5Il19LHsidCI6ImV4YW1wbGUiLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludDIiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5MiJdLCJhIjpbImRpZGNvbW0vdjIiLCJkaWRjb21tL2FpcDI7ZW52PXJmYzU4NyJdfV0'
did_doc_numalgo_2_multibase_2_services = '\n {\n "id": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.SW3sidCI6ImRtIiwicyI6Imh0dHBzOi8vZXhhbXBsZS5jb20vZW5kcG9pbnQiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5Il19LHsidCI6ImV4YW1wbGUiLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludDIiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5MiJdLCJhIjpbImRpZGNvbW0vdjIiLCJkaWRjb21tL2FpcDI7ZW52PXJmYzU4NyJdfV0",\n "authentication": [\n {\n "id": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.SW3sidCI6ImRtIiwicyI6Imh0dHBzOi8vZXhhbXBsZS5jb20vZW5kcG9pbnQiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5Il19LHsidCI6ImV4YW1wbGUiLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludDIiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5MiJdLCJhIjpbImRpZGNvbW0vdjIiLCJkaWRjb21tL2FpcDI7ZW52PXJmYzU4NyJdfV0#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "type": "Ed25519VerificationKey2020",\n "controller": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.SW3sidCI6ImRtIiwicyI6Imh0dHBzOi8vZXhhbXBsZS5jb20vZW5kcG9pbnQiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5Il19LHsidCI6ImV4YW1wbGUiLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludDIiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5MiJdLCJhIjpbImRpZGNvbW0vdjIiLCJkaWRjb21tL2FpcDI7ZW52PXJmYzU4NyJdfV0",\n "publicKeyMultibase": "z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V"\n }\n ],\n "keyAgreement": [\n {\n "id": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.SW3sidCI6ImRtIiwicyI6Imh0dHBzOi8vZXhhbXBsZS5jb20vZW5kcG9pbnQiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5Il19LHsidCI6ImV4YW1wbGUiLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludDIiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5MiJdLCJhIjpbImRpZGNvbW0vdjIiLCJkaWRjb21tL2FpcDI7ZW52PXJmYzU4NyJdfV0#6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud",\n "type": "X25519KeyAgreementKey2020",\n "controller": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.SW3sidCI6ImRtIiwicyI6Imh0dHBzOi8vZXhhbXBsZS5jb20vZW5kcG9pbnQiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5Il19LHsidCI6ImV4YW1wbGUiLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludDIiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5MiJdLCJhIjpbImRpZGNvbW0vdjIiLCJkaWRjb21tL2FpcDI7ZW52PXJmYzU4NyJdfV0",\n "publicKeyMultibase": "z6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud"\n }\n ],\n "service": [\n {\n "id": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.SW3sidCI6ImRtIiwicyI6Imh0dHBzOi8vZXhhbXBsZS5jb20vZW5kcG9pbnQiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5Il19LHsidCI6ImV4YW1wbGUiLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludDIiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5MiJdLCJhIjpbImRpZGNvbW0vdjIiLCJkaWRjb21tL2FpcDI7ZW52PXJmYzU4NyJdfV0#didcommmessaging-0",\n "type": "DIDCommMessaging",\n "serviceEndpoint": "https://example.com/endpoint",\n "routingKeys": [\n "did:example:somemediator#somekey"\n ]\n },\n {\n "id": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.SW3sidCI6ImRtIiwicyI6Imh0dHBzOi8vZXhhbXBsZS5jb20vZW5kcG9pbnQiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5Il19LHsidCI6ImV4YW1wbGUiLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludDIiLCJyIjpbImRpZDpleGFtcGxlOnNvbWVtZWRpYXRvciNzb21la2V5MiJdLCJhIjpbImRpZGNvbW0vdjIiLCJkaWRjb21tL2FpcDI7ZW52PXJmYzU4NyJdfV0#example-1",\n "type": "example",\n "serviceEndpoint": "https://example.com/endpoint2",\n "routingKeys": [\n "did:example:somemediator#somekey2"\n ],\n "accept": ["didcomm/v2", "didcomm/aip2;env=rfc587"]\n }\n ]\n }\n '
peer_did_numalgo_2_no_services = 'did:peer:2' + '.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud' + '.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V'
did_doc_numalgo_2_multibase_no_services = '\n {\n "id": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "authentication": [\n {\n "id": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "type": "Ed25519VerificationKey2020",\n "controller": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "publicKeyMultibase": "z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V"\n }\n ],\n "keyAgreement": [\n {\n "id": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V#6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud",\n "type": "X25519KeyAgreementKey2020",\n "controller": "did:peer:2.Ez6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "publicKeyMultibase": "z6LSpSrLxbAhg2SHwKk7kwpsH7DM7QjFS5iK6qP87eViohud"\n }\n ]\n }\n '
peer_did_numalgo_2_minimal_services = 'did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9'
did_doc_numalgo_2_multibase_minimal_services = '\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9",\n "authentication": [\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9#6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V",\n "type": "Ed25519VerificationKey2020",\n "controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9",\n "publicKeyMultibase": "z6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V"\n },\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9#6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg",\n "type": "Ed25519VerificationKey2020",\n "controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9",\n "publicKeyMultibase": "z6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg"\n }\n ],\n "keyAgreement": [\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9#6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc",\n "type": "X25519KeyAgreementKey2020",\n "controller": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9",\n "publicKeyMultibase": "z6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc"\n }\n ],\n "service": [\n {\n "id": "did:peer:2.Ez6LSbysY2xFMRpGMhb7tFTLMpeuPRaqaWM1yECx2AtzE3KCc.Vz6MkqRYqQiSgvZQdnBytw86Qbs2ZWUkGv22od935YF4s8M7V.Vz6MkgoLTnTypo3tDRwCkZXSccTPHRLhF4ZnjhueYAFpEX6vg.SeyJ0IjoiZG0iLCJzIjoiaHR0cHM6Ly9leGFtcGxlLmNvbS9lbmRwb2ludCJ9#didcommmessaging-0",\n "serviceEndpoint": "https://example.com/endpoint",\n "type": "DIDCommMessaging"\n }\n ]\n }\n ' |
class Solution:
def longestSubsequence(self, arr: List[int], diff: int) -> int:
dp = {}
for num in arr:
if num - diff in dp:
cnt = dp.pop(num - diff)
dp[num] = max(dp.get(num, 0), cnt + 1)
else:
dp[num] = max(dp.get(num, 0), 1)
return max(dp.values())
| class Solution:
def longest_subsequence(self, arr: List[int], diff: int) -> int:
dp = {}
for num in arr:
if num - diff in dp:
cnt = dp.pop(num - diff)
dp[num] = max(dp.get(num, 0), cnt + 1)
else:
dp[num] = max(dp.get(num, 0), 1)
return max(dp.values()) |
numbers = [1, 45, 31, 12, 60]
for number in numbers:
if number % 8 == 0:
print ("THe numbers are unacccepetble")
break
else:
print ("The Numbers are good") | numbers = [1, 45, 31, 12, 60]
for number in numbers:
if number % 8 == 0:
print('THe numbers are unacccepetble')
break
else:
print('The Numbers are good') |
'''
Given a string, determine if it is a palindrome, considering only alphanumeric characters and ignoring cases.
Note: For the purpose of this problem, we define empty string as valid palindrome.
Example 1:
Input: "A man, a plan, a canal: Panama"
Output: true
Example 2:
Input: "race a car"
Output: false
'''
class Solution(object):
def isPalindrome(self, s):
"""
:type s: str
:rtype: bool
"""
alpha = []
for c in s:
if c.isalnum():
alpha.append(c.lower())
for i in xrange(len(alpha) // 2):
if alpha[i] != alpha[len(alpha) - i - 1]:
return False
return True
| """
Given a string, determine if it is a palindrome, considering only alphanumeric characters and ignoring cases.
Note: For the purpose of this problem, we define empty string as valid palindrome.
Example 1:
Input: "A man, a plan, a canal: Panama"
Output: true
Example 2:
Input: "race a car"
Output: false
"""
class Solution(object):
def is_palindrome(self, s):
"""
:type s: str
:rtype: bool
"""
alpha = []
for c in s:
if c.isalnum():
alpha.append(c.lower())
for i in xrange(len(alpha) // 2):
if alpha[i] != alpha[len(alpha) - i - 1]:
return False
return True |
class rational:
def __init__(self, x, y):
gcd = self.__gcd(x, y)
self.d = x // gcd # denominator
self.n = y // gcd # numerator
def __gcd(self, x, y):
while y > 0:
x, y = y, x % y
return x
def __add__(self, other):
return rational(
self.n * other.d + self.d * other.n,
self.n * other.n
)
def __mul__(self, other):
return rational(
self.d * other.d,
self.n * other.n
)
@staticmethod
def add(r1, r2):
return r1 + r2
@staticmethod
def mul(r1, r2):
return r1 * r2
def __str__(self):
return "{}/{}".format(self.d, self.n)
if __name__ == "__main__":
r1 = rational(8, 6)
r2 = rational(5, 2)
print("r1 =", r1)
print("r2 =", r2)
print("r1 + r2 =", r1 + r2)
print("r1 * r2 =", r1 * r2)
print("add(r1, r2) =", rational.add(r1, r2))
print("mul(r1, r2) =", rational.mul(r1, r2)) | class Rational:
def __init__(self, x, y):
gcd = self.__gcd(x, y)
self.d = x // gcd
self.n = y // gcd
def __gcd(self, x, y):
while y > 0:
(x, y) = (y, x % y)
return x
def __add__(self, other):
return rational(self.n * other.d + self.d * other.n, self.n * other.n)
def __mul__(self, other):
return rational(self.d * other.d, self.n * other.n)
@staticmethod
def add(r1, r2):
return r1 + r2
@staticmethod
def mul(r1, r2):
return r1 * r2
def __str__(self):
return '{}/{}'.format(self.d, self.n)
if __name__ == '__main__':
r1 = rational(8, 6)
r2 = rational(5, 2)
print('r1 =', r1)
print('r2 =', r2)
print('r1 + r2 =', r1 + r2)
print('r1 * r2 =', r1 * r2)
print('add(r1, r2) =', rational.add(r1, r2))
print('mul(r1, r2) =', rational.mul(r1, r2)) |
#module for data updating
def update_data_set(text_file_name:str, data:{'Time':int, "Mood":int, "Age":int}, class_res:int):
'''Given a text file name and data, it will open the text file
and update the file with new data in format "int,int,int" '''
file = open(text_file_name, "a")
elements_for_data_input=["\n",
data['Time'],
',',
data['Mood'],
',',
data['Age'],
',',
class_res]
for item in range(len(elements_for_data_input)):
file.write(str(elements_for_data_input[item]))
file.close()
| def update_data_set(text_file_name: str, data: {'Time': int, 'Mood': int, 'Age': int}, class_res: int):
"""Given a text file name and data, it will open the text file
and update the file with new data in format "int,int,int" """
file = open(text_file_name, 'a')
elements_for_data_input = ['\n', data['Time'], ',', data['Mood'], ',', data['Age'], ',', class_res]
for item in range(len(elements_for_data_input)):
file.write(str(elements_for_data_input[item]))
file.close() |
# https://www.codementor.io/moyosore/a-dive-into-python-closures-and-decorators-part-1-9mpr98pgr
def add_all_arguments(*args):
result = 0
for i in args:
result += i
return result
print(add_all_arguments(1, 5, 7, 9, 10)) # 32
print(add_all_arguments(1, 9)) # 10
print(add_all_arguments(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)) # 55
print(add_all_arguments(1)) # 1
print(add_all_arguments()) # 0
def print_arguments(**kwargs):
print(kwargs)
print_arguments(name="Moyosore")
# {'name': 'moyosore'}
print_arguments(name="Moyosore", country="Nigeria")
# {'name': 'moyosore', 'country': 'Nigeria'}
print_arguments()
# {}
def print_argument_values(**kwargs):
for key, value in kwargs.items():
print(f"{key}: {value}")
print_argument_values(name="Moyosore", country="Nigeria")
# name: Moyosore
# country: Nigeria
"""
Args and kwargs can be used together in a function, with args always coming before kwargs. If there are any other required arguments, they come before args and kwargs
"""
def add_and_mul1(*args, **kwargs):
pass
def add_and_mul2(my_arg, *args, **kwargs):
pass
def add_and_mul3(my_arg, my_arg_1, *args, **kwargs):
pass
| def add_all_arguments(*args):
result = 0
for i in args:
result += i
return result
print(add_all_arguments(1, 5, 7, 9, 10))
print(add_all_arguments(1, 9))
print(add_all_arguments(1, 2, 3, 4, 5, 6, 7, 8, 9, 10))
print(add_all_arguments(1))
print(add_all_arguments())
def print_arguments(**kwargs):
print(kwargs)
print_arguments(name='Moyosore')
print_arguments(name='Moyosore', country='Nigeria')
print_arguments()
def print_argument_values(**kwargs):
for (key, value) in kwargs.items():
print(f'{key}: {value}')
print_argument_values(name='Moyosore', country='Nigeria')
'\nArgs and kwargs can be used together in a function, with args always coming before kwargs. If there are any other required arguments, they come before args and kwargs\n\n'
def add_and_mul1(*args, **kwargs):
pass
def add_and_mul2(my_arg, *args, **kwargs):
pass
def add_and_mul3(my_arg, my_arg_1, *args, **kwargs):
pass |
# Do DFS on input. Maintin a set of keys_collected. Do not push a room if it's there in the keys_collected set.
class Solution(object):
def canVisitAllRooms(self, rooms):
"""
:type rooms: List[List[int]]
:rtype: bool
"""
S = [rooms[0]]
keys_collected = set([0])
while S:
node = S.pop()
for k in node:
if k not in keys_collected:
S.append(rooms[k])
keys_collected.add(k)
if len(keys_collected) == len(rooms):
return True
return False
| class Solution(object):
def can_visit_all_rooms(self, rooms):
"""
:type rooms: List[List[int]]
:rtype: bool
"""
s = [rooms[0]]
keys_collected = set([0])
while S:
node = S.pop()
for k in node:
if k not in keys_collected:
S.append(rooms[k])
keys_collected.add(k)
if len(keys_collected) == len(rooms):
return True
return False |
"""Constants"""
DOMAIN = "grocy"
DOMAIN_DATA = "{}_data".format(DOMAIN)
DOMAIN_EVENT = "grocy_updated"
DOMAIN_SERVICE = "{}"
# Integration local data
DATA_GROCY = "grocy"
DATA_DATA = "data"
DATA_ENTITIES = "entities"
DATA_STORE_CONF = "store_conf"
# Domain events
EVENT_ADDED_TO_LIST='added_to_list'
EVENT_SUBTRACT_FROM_LIST='subtract_from_list'
EVENT_PRODUCT_REMOVED='product_removed'
EVENT_PRODUCT_ADDED='product_added'
EVENT_PRODUCT_UPDATED='product_updated'
EVENT_SYNC_DONE='sync_done'
EVENT_GROCY_ERROR='error'
# Configuration
CONF_APIKEY = "apikey"
CONF_AMOUNT = "amount"
CONF_NAME = "name"
CONF_VALUE = "value"
CONF_SHOPPING_LIST_ID = 'shopping_list'
CONF_PRODUCT_DESCRIPTION = 'product_description'
CONF_PRODUCT_GROUP_ID = 'product_group_id'
CONF_PRODUCT_LOCATION_ID = 'product_location_id'
CONF_STORE = 'store'
CONF_BARCODE = 'barcode'
CONF_UNIT_OF_MEASUREMENT = 'unit_of_measurement'
# Defaults
DEFAULT_AMOUNT = 1
DEFAULT_STORE = ''
DEFAULT_SHOPPING_LIST_ID = 1
DEFAULT_PRODUCT_DESCRIPTION = ""
# Services
ADD_TO_LIST_SERVICE = DOMAIN_SERVICE.format('add_to_list')
SUBTRACT_FROM_LIST_SERVICE = DOMAIN_SERVICE.format('subtract_from_list')
ADD_PRODUCT_SERVICE = DOMAIN_SERVICE.format('add_product')
REMOVE_PRODUCT_SERVICE = DOMAIN_SERVICE.format('remove_product')
ADD_FAVORITE_SERVICE = DOMAIN_SERVICE.format('add_favorite')
REMOVE_FAVORITE_SERVICE = DOMAIN_SERVICE.format('remove_favorite')
FILL_CART_SERVICE = DOMAIN_SERVICE.format('fill_cart')
EMPTY_CART_SERVICE = DOMAIN_SERVICE.format('empty_cart')
SYNC_SERVICE = DOMAIN_SERVICE.format('sync')
DEBUG_SERVICE = DOMAIN_SERVICE.format('debug')
# Device classes
STOCK_NAME = "stock"
CHORES_NAME = "chores"
PRODUCTS_NAME = "products"
SHOPPING_LIST_NAME = "shopping_list"
SHOPPING_LISTS_NAME = "shopping_lists"
LOCATIONS_NAME = "locations"
QUANTITY_UNITS_NAME = "quantity_units"
PRODUCT_GROUPS_NAME = "product_groups"
| """Constants"""
domain = 'grocy'
domain_data = '{}_data'.format(DOMAIN)
domain_event = 'grocy_updated'
domain_service = '{}'
data_grocy = 'grocy'
data_data = 'data'
data_entities = 'entities'
data_store_conf = 'store_conf'
event_added_to_list = 'added_to_list'
event_subtract_from_list = 'subtract_from_list'
event_product_removed = 'product_removed'
event_product_added = 'product_added'
event_product_updated = 'product_updated'
event_sync_done = 'sync_done'
event_grocy_error = 'error'
conf_apikey = 'apikey'
conf_amount = 'amount'
conf_name = 'name'
conf_value = 'value'
conf_shopping_list_id = 'shopping_list'
conf_product_description = 'product_description'
conf_product_group_id = 'product_group_id'
conf_product_location_id = 'product_location_id'
conf_store = 'store'
conf_barcode = 'barcode'
conf_unit_of_measurement = 'unit_of_measurement'
default_amount = 1
default_store = ''
default_shopping_list_id = 1
default_product_description = ''
add_to_list_service = DOMAIN_SERVICE.format('add_to_list')
subtract_from_list_service = DOMAIN_SERVICE.format('subtract_from_list')
add_product_service = DOMAIN_SERVICE.format('add_product')
remove_product_service = DOMAIN_SERVICE.format('remove_product')
add_favorite_service = DOMAIN_SERVICE.format('add_favorite')
remove_favorite_service = DOMAIN_SERVICE.format('remove_favorite')
fill_cart_service = DOMAIN_SERVICE.format('fill_cart')
empty_cart_service = DOMAIN_SERVICE.format('empty_cart')
sync_service = DOMAIN_SERVICE.format('sync')
debug_service = DOMAIN_SERVICE.format('debug')
stock_name = 'stock'
chores_name = 'chores'
products_name = 'products'
shopping_list_name = 'shopping_list'
shopping_lists_name = 'shopping_lists'
locations_name = 'locations'
quantity_units_name = 'quantity_units'
product_groups_name = 'product_groups' |
number_for_fibonacci = int(input("Enter Fibonacci number: "))
first_num = 0
second_num = 1
while second_num <= number_for_fibonacci:
print(second_num)
first_num, second_num = second_num, first_num + second_num
print("Fibonacci number") | number_for_fibonacci = int(input('Enter Fibonacci number: '))
first_num = 0
second_num = 1
while second_num <= number_for_fibonacci:
print(second_num)
(first_num, second_num) = (second_num, first_num + second_num)
print('Fibonacci number') |
def collected_materials(key_materials_dict:dict, junk_materials_dict:dict, material:str, quantity:int):
if material=="shards" or material=="fragments" or material=="motes":
key_materials_dict[material]+=quantity
else:
if material not in junk_materials.keys():
junk_materials[material]=quantity
else:
junk_materials[material]+=quantity
key_materials = {"shards": 0, "fragments": 0, "motes": 0}
junk_materials={}
items_obtained=""
while items_obtained == "":
current_line=input().split()
for i in range (0,len(current_line),2):
material_quantity=int(current_line[i])
material_name=current_line[i+1].lower()
collected_materials(key_materials,junk_materials,material_name,material_quantity)
if key_materials['shards']>=250:
items_obtained="Shadowmourne"
key_materials["shards"]-=250
break
elif key_materials['fragments']>=250:
items_obtained="Valanyr"
key_materials['fragments']-=250
break
elif key_materials['motes']>=250:
items_obtained="Dragonwrath"
key_materials['motes']-=250
break
print(f"{items_obtained} obtained!")
for (material_name,material_quantity) in sorted(key_materials.items(),key=lambda kvp:(-kvp[1],kvp[0])):
print(f"{material_name}: {material_quantity}")
for (junk_materials_name,junk_materials_quantity) in sorted(junk_materials.items(), key=lambda kvp: kvp[0]):
print(f"{junk_materials_name}: {junk_materials_quantity}")
| def collected_materials(key_materials_dict: dict, junk_materials_dict: dict, material: str, quantity: int):
if material == 'shards' or material == 'fragments' or material == 'motes':
key_materials_dict[material] += quantity
elif material not in junk_materials.keys():
junk_materials[material] = quantity
else:
junk_materials[material] += quantity
key_materials = {'shards': 0, 'fragments': 0, 'motes': 0}
junk_materials = {}
items_obtained = ''
while items_obtained == '':
current_line = input().split()
for i in range(0, len(current_line), 2):
material_quantity = int(current_line[i])
material_name = current_line[i + 1].lower()
collected_materials(key_materials, junk_materials, material_name, material_quantity)
if key_materials['shards'] >= 250:
items_obtained = 'Shadowmourne'
key_materials['shards'] -= 250
break
elif key_materials['fragments'] >= 250:
items_obtained = 'Valanyr'
key_materials['fragments'] -= 250
break
elif key_materials['motes'] >= 250:
items_obtained = 'Dragonwrath'
key_materials['motes'] -= 250
break
print(f'{items_obtained} obtained!')
for (material_name, material_quantity) in sorted(key_materials.items(), key=lambda kvp: (-kvp[1], kvp[0])):
print(f'{material_name}: {material_quantity}')
for (junk_materials_name, junk_materials_quantity) in sorted(junk_materials.items(), key=lambda kvp: kvp[0]):
print(f'{junk_materials_name}: {junk_materials_quantity}') |
t_host = "localhost"
t_port = "5432"
t_dbname = "insert_db_name"
t_user = "insert_user"
t_pw = "insert_pw"
photo_request_data = {
"CAD6E": {
"id": 218,
"coords_x": -5.9357153,
"coords_y": 54.5974748,
"land_hash": "1530850C9A6F5FF56B66AC16301584EC"
},
"TEST1": {
"id": 1,
"coords_x": 11.111111,
"coords_y": 22.222222,
"land_hash": "11111111111111111111111"
}
} | t_host = 'localhost'
t_port = '5432'
t_dbname = 'insert_db_name'
t_user = 'insert_user'
t_pw = 'insert_pw'
photo_request_data = {'CAD6E': {'id': 218, 'coords_x': -5.9357153, 'coords_y': 54.5974748, 'land_hash': '1530850C9A6F5FF56B66AC16301584EC'}, 'TEST1': {'id': 1, 'coords_x': 11.111111, 'coords_y': 22.222222, 'land_hash': '11111111111111111111111'}} |
def pad_in(string: str, space: int) -> str:
"""
>>> pad_in('abc', 0)
'abc'
>>> pad_in('abc', 2)
' abc'
"""
return "".join([" "] * space) + string
def without_ends(string: str) -> str:
"""
>>> without_ends('abc')
'b'
"""
return string[1:-1]
def without_first(string: str) -> str:
"""
>>> without_first('abc')
'bc'
"""
return string[1:]
def without_last(string: str) -> str:
"""
>>> without_last('abc')
'ab'
"""
return string[:-1]
def quote(string: str) -> str:
"""
>>> quote('abc')
'\"abc\"'
>>> quote('"abc"')
'\"abc\"'
"""
return string if string.startswith('"') and string.endswith('"') else f'"{string}"'
def handle(string: str) -> str:
"""
>>> handle('https://github.com/user/repo')
'user/repo'
>>> handle('user/repo')
'user/repo'
>>> handle('')
''
"""
splt = string.split("/")
return "/".join(splt[-2:] if len(splt) >= 2 else splt)
def pluralize(count: int, unit: str) -> str:
"""
Pluralize a count and given its units.
>>> pluralize(1, 'file')
'1 file'
>>> pluralize(2, 'file')
'2 files'
>>> pluralize(0, 'file')
'0 files'
"""
return f"{count} {unit}{'s' if count != 1 else ''}"
def remove_prefix(string: str, prefix: str) -> str:
"""
>>> remove_prefix('abc', 'ab')
'c'
>>> remove_prefix('abc', 'd')
'abc'
>>> remove_prefix('abc', 'abcd')
'abc'
"""
return string[len(prefix) :] if string.startswith(prefix) else string
| def pad_in(string: str, space: int) -> str:
"""
>>> pad_in('abc', 0)
'abc'
>>> pad_in('abc', 2)
' abc'
"""
return ''.join([' '] * space) + string
def without_ends(string: str) -> str:
"""
>>> without_ends('abc')
'b'
"""
return string[1:-1]
def without_first(string: str) -> str:
"""
>>> without_first('abc')
'bc'
"""
return string[1:]
def without_last(string: str) -> str:
"""
>>> without_last('abc')
'ab'
"""
return string[:-1]
def quote(string: str) -> str:
"""
>>> quote('abc')
'"abc"'
>>> quote('"abc"')
'"abc"'
"""
return string if string.startswith('"') and string.endswith('"') else f'"{string}"'
def handle(string: str) -> str:
"""
>>> handle('https://github.com/user/repo')
'user/repo'
>>> handle('user/repo')
'user/repo'
>>> handle('')
''
"""
splt = string.split('/')
return '/'.join(splt[-2:] if len(splt) >= 2 else splt)
def pluralize(count: int, unit: str) -> str:
"""
Pluralize a count and given its units.
>>> pluralize(1, 'file')
'1 file'
>>> pluralize(2, 'file')
'2 files'
>>> pluralize(0, 'file')
'0 files'
"""
return f"{count} {unit}{('s' if count != 1 else '')}"
def remove_prefix(string: str, prefix: str) -> str:
"""
>>> remove_prefix('abc', 'ab')
'c'
>>> remove_prefix('abc', 'd')
'abc'
>>> remove_prefix('abc', 'abcd')
'abc'
"""
return string[len(prefix):] if string.startswith(prefix) else string |
def algorithm(K1,K2, B, weight_vec, datapoints, true_labels, lambda_lasso, penalty_func_name='norm1', calculate_score=False):
'''
Outer loop is gradient ascent algorithm, the variable 'new_weight_vec' here is the dual variable we are interested in
Inner loop is still our Nlasso algorithm
:param K1,K2 : the number of iterations
:param D: the block incidence matrix
:param weight_vec: a list containing the edges's weights of the graph
:param datapoints: a dictionary containing the data of each node in the graph needed for the algorithm 1
:param true_labels: a list containing the true labels of the nodes
:param samplingset: the sampling set
:param lambda_lasso: the parameter lambda
:param penalty_func_name: the name of the penalty function used in the algorithm
:return new_w: the predicted weigh vectors for each node
'''
'''
Sigma: the block diagonal matrix Sigma
'''
Sigma = np.diag(np.full(weight_vec.shape, 0.9 / 2))
T_matrix = np.diag(np.array((1.0 / (np.sum(abs(B), 0)))).ravel())
'''
T_matrix: the block diagonal matrix T
'''
E, N = B.shape
'''
shape of the graph
'''
m, n = datapoints[1]['features'].shape
'''
shape of the feature vectors of each node in the graph
'''
# # define the penalty function
# if penalty_func_name == 'norm1':
# penalty_func = Norm1Pelanty(lambda_lasso, weight_vec, Sigma, n)
# elif penalty_func_name == 'norm2':
# penalty_func = Norm2Pelanty(lambda_lasso, weight_vec, Sigma, n)
# elif penalty_func_name == 'mocha':
# penalty_func = MOCHAPelanty(lambda_lasso, weight_vec, Sigma, n)
# else:
# raise Exception('Invalid penalty name')
new_w = np.array([np.zeros(n) for i in range(N)])
new_u = np.array([np.zeros(n) for i in range(E)])
new_weight_vec = weight_vec
# starting algorithm 1
Loss = {}
iteration_scores = []
for j in range(K1):
new_B = np.dot(np.diag(new_weight_vec),B)
T_matrix = np.diag(np.array((1.0 / (np.sum(abs(new_B), 0)))).ravel())
T = np.array((1.0 / (np.sum(abs(new_B), 0)))).ravel()
for iterk in range(K2):
# if iterk % 100 == 0:
# print ('iter:', iterk)
prev_w = np.copy(new_w)
# line 2 algorithm 1
hat_w = new_w - np.dot(T_matrix, np.dot(new_B.T, new_u))
for i in range(N):
optimizer = datapoints[i]['optimizer']
new_w[i] = optimizer.optimize(datapoints[i]['features'],
datapoints[i]['label'],
hat_w[i],
T[i])
# line 9 algortihm 1
tilde_w = 2 * new_w - prev_w
new_u = new_u + np.dot(Sigma, np.dot(new_B, tilde_w))
penalty_func = Norm1Pelanty(lambda_lasso, new_weight_vec, Sigma, n)
new_u = penalty_func.update(new_u)
new_weight_vec = new_weight_vec +0.1*np.linalg.norm(np.dot(B, new_w),ord=1,axis=1)
# # calculate the MSE of the predicted weight vectors
# if calculate_score:
# Y_pred = []
# for i in range(N):
# Y_pred.append(np.dot(datapoints[i]['features'], new_w[i]))
# iteration_scores.append(mean_squared_error(true_labels.reshape(N, m), Y_pred))
Loss[j] = total_loss(datapoints,new_w,new_B,new_weight_vec)
return new_w, new_weight_vec,Loss,iteration_scores | def algorithm(K1, K2, B, weight_vec, datapoints, true_labels, lambda_lasso, penalty_func_name='norm1', calculate_score=False):
"""
Outer loop is gradient ascent algorithm, the variable 'new_weight_vec' here is the dual variable we are interested in
Inner loop is still our Nlasso algorithm
:param K1,K2 : the number of iterations
:param D: the block incidence matrix
:param weight_vec: a list containing the edges's weights of the graph
:param datapoints: a dictionary containing the data of each node in the graph needed for the algorithm 1
:param true_labels: a list containing the true labels of the nodes
:param samplingset: the sampling set
:param lambda_lasso: the parameter lambda
:param penalty_func_name: the name of the penalty function used in the algorithm
:return new_w: the predicted weigh vectors for each node
"""
'\n Sigma: the block diagonal matrix Sigma\n \n \n '
sigma = np.diag(np.full(weight_vec.shape, 0.9 / 2))
t_matrix = np.diag(np.array(1.0 / np.sum(abs(B), 0)).ravel())
'\n T_matrix: the block diagonal matrix T\n '
(e, n) = B.shape
'\n shape of the graph\n '
(m, n) = datapoints[1]['features'].shape
'\n shape of the feature vectors of each node in the graph\n '
new_w = np.array([np.zeros(n) for i in range(N)])
new_u = np.array([np.zeros(n) for i in range(E)])
new_weight_vec = weight_vec
loss = {}
iteration_scores = []
for j in range(K1):
new_b = np.dot(np.diag(new_weight_vec), B)
t_matrix = np.diag(np.array(1.0 / np.sum(abs(new_B), 0)).ravel())
t = np.array(1.0 / np.sum(abs(new_B), 0)).ravel()
for iterk in range(K2):
prev_w = np.copy(new_w)
hat_w = new_w - np.dot(T_matrix, np.dot(new_B.T, new_u))
for i in range(N):
optimizer = datapoints[i]['optimizer']
new_w[i] = optimizer.optimize(datapoints[i]['features'], datapoints[i]['label'], hat_w[i], T[i])
tilde_w = 2 * new_w - prev_w
new_u = new_u + np.dot(Sigma, np.dot(new_B, tilde_w))
penalty_func = norm1_pelanty(lambda_lasso, new_weight_vec, Sigma, n)
new_u = penalty_func.update(new_u)
new_weight_vec = new_weight_vec + 0.1 * np.linalg.norm(np.dot(B, new_w), ord=1, axis=1)
Loss[j] = total_loss(datapoints, new_w, new_B, new_weight_vec)
return (new_w, new_weight_vec, Loss, iteration_scores) |
#!/usr/bin/env python2
class RDHSSet:
def __init__(self, path):
with open(path, 'r') as f:
self.regions = [ tuple(line.strip().split()[:4]) for line in f ]
self.indexmap = { x: i for i, x in enumerate(self.regions) }
self.accessionIndexMap = { x[-1]: i for i, x in enumerate(self.regions) }
def __len__(self):
return len(self.regions)
def indexesForChromosome(self, chromosome):
return { self.indexmap[x] for x in self.regions if x[0] == chromosome }
def indexesForChromosomes(self, chromosomes):
r = set()
for x in chromosomes:
r = r.union(self.indexesForChromosome(x))
return r
def accessionsForChromosome(self, chromosome):
return { x[-1] for x in self.regions if x[0] == chromosome }
| class Rdhsset:
def __init__(self, path):
with open(path, 'r') as f:
self.regions = [tuple(line.strip().split()[:4]) for line in f]
self.indexmap = {x: i for (i, x) in enumerate(self.regions)}
self.accessionIndexMap = {x[-1]: i for (i, x) in enumerate(self.regions)}
def __len__(self):
return len(self.regions)
def indexes_for_chromosome(self, chromosome):
return {self.indexmap[x] for x in self.regions if x[0] == chromosome}
def indexes_for_chromosomes(self, chromosomes):
r = set()
for x in chromosomes:
r = r.union(self.indexesForChromosome(x))
return r
def accessions_for_chromosome(self, chromosome):
return {x[-1] for x in self.regions if x[0] == chromosome} |
def getLeapYear(year):
while True:
if year%400==0:
return year
elif year%4==0 and year%100!=0:
return year
else:
year +=1
if __name__=='__main__':
leap_year_list = []
cur_year = int(input("Enter any year :"))
leap_year = getLeapYear(cur_year)
for i in range(15):
leap_year_list.append(leap_year)
leap_year +=4
print(leap_year_list) | def get_leap_year(year):
while True:
if year % 400 == 0:
return year
elif year % 4 == 0 and year % 100 != 0:
return year
else:
year += 1
if __name__ == '__main__':
leap_year_list = []
cur_year = int(input('Enter any year :'))
leap_year = get_leap_year(cur_year)
for i in range(15):
leap_year_list.append(leap_year)
leap_year += 4
print(leap_year_list) |
for number in range(1, 101):
if number % 3 == 0 and number % 5 == 0:
print(f"{number} FizzBuzz")
elif number % 3 == 0:
print(f"{number} Fizz")
elif number % 5 == 0:
print(f"{number} Buzz")
else:
print(number)
| for number in range(1, 101):
if number % 3 == 0 and number % 5 == 0:
print(f'{number} FizzBuzz')
elif number % 3 == 0:
print(f'{number} Fizz')
elif number % 5 == 0:
print(f'{number} Buzz')
else:
print(number) |
{{notice}}
workers = 4
errorlog = "{{proj_root}}/run/log/gunicorn.error"
accesslog = "{{proj_root}}/run/log/gunicorn.access"
loglevel = "debug"
bind = ["127.0.0.1:9001"]
| {{notice}}
workers = 4
errorlog = '{{proj_root}}/run/log/gunicorn.error'
accesslog = '{{proj_root}}/run/log/gunicorn.access'
loglevel = 'debug'
bind = ['127.0.0.1:9001'] |
class Relevance(object):
'''Incooperation with result file and qrels file
Attributes:
qid, int, query id
judgement_docid_list: list of list, judged docids in TREC qrels
supervised_docid_list: list, top docids from unsupervised models, e.g. BM25, QL.
'''
def __init__(self, qid, judged_docid_list, supervised_docid_list, supervised_score_list):
self._qid = qid
self._judged_docid_list = judged_docid_list
self._supervised_docid_list = supervised_docid_list
self._supervised_score_list = supervised_score_list
def get_qid(self):
return self._qid
def get_judged_docid_list(self):
return self._judged_docid_list
def get_supervised_docid_list(self):
return self._supervised_docid_list
def get_supervised_score_list(self):
return self._supervised_score_list | class Relevance(object):
"""Incooperation with result file and qrels file
Attributes:
qid, int, query id
judgement_docid_list: list of list, judged docids in TREC qrels
supervised_docid_list: list, top docids from unsupervised models, e.g. BM25, QL.
"""
def __init__(self, qid, judged_docid_list, supervised_docid_list, supervised_score_list):
self._qid = qid
self._judged_docid_list = judged_docid_list
self._supervised_docid_list = supervised_docid_list
self._supervised_score_list = supervised_score_list
def get_qid(self):
return self._qid
def get_judged_docid_list(self):
return self._judged_docid_list
def get_supervised_docid_list(self):
return self._supervised_docid_list
def get_supervised_score_list(self):
return self._supervised_score_list |
#!/usr/bin/env python
# encoding: utf-8
"""
@author: Bocheng.Zhang
@license: Apache Licence
@contact: bocheng0000@gmail.com
@file: config.py
@time: 2019/11/6 10:35
"""
# [environment]
ela_url = "coreservices-mainchain-privnet.elastos.org"
did_url = "coreservices-didsidechain-privnet.elastos.org"
# faucet account
faucet = {"address": "EVpUKLScc3BmTyJ9xnd6aGSv3o8eAtFKNw",
"publickey": "0359762e6e27e6119cf041ea0cb5046869c78f3a72549f4061d63dc48d91117957",
"privatekey": "f384428447fd58fc0525494bd0f6f3df23fcb49098f4b5a50a9e97a71c6d2880"}
tx_fee = 100 # sela
| """
@author: Bocheng.Zhang
@license: Apache Licence
@contact: bocheng0000@gmail.com
@file: config.py
@time: 2019/11/6 10:35
"""
ela_url = 'coreservices-mainchain-privnet.elastos.org'
did_url = 'coreservices-didsidechain-privnet.elastos.org'
faucet = {'address': 'EVpUKLScc3BmTyJ9xnd6aGSv3o8eAtFKNw', 'publickey': '0359762e6e27e6119cf041ea0cb5046869c78f3a72549f4061d63dc48d91117957', 'privatekey': 'f384428447fd58fc0525494bd0f6f3df23fcb49098f4b5a50a9e97a71c6d2880'}
tx_fee = 100 |
def our_range(*args):
start = 0
end = 10
step = 1
if len(args) == 1:
end = args[0]
elif 2 <= len(args) <= 3:
start = args[0]
end = args[1]
if len(args) == 3:
step = args[2]
elif len(args) > 3:
raise SyntaxError
i = start
while i < end:
yield i
i += step
for j in our_range(5):
print(j)
print()
for j in our_range(2, 6):
print(j)
print()
for j in our_range(3, 30, 9):
print(j)
| def our_range(*args):
start = 0
end = 10
step = 1
if len(args) == 1:
end = args[0]
elif 2 <= len(args) <= 3:
start = args[0]
end = args[1]
if len(args) == 3:
step = args[2]
elif len(args) > 3:
raise SyntaxError
i = start
while i < end:
yield i
i += step
for j in our_range(5):
print(j)
print()
for j in our_range(2, 6):
print(j)
print()
for j in our_range(3, 30, 9):
print(j) |
def part1(input_data):
numbers, boards = parse_input(input_data)
for number in numbers:
# Put number on all boards
for board in boards:
for row in board:
for i in range(len(row)):
if number == row[i]:
row[i] = "x"
# Check for bingo
for board in boards:
for row in board:
if "".join(row) == "xxxxx":
return int(number) * unmarked_sum(board)
for column in zip(*board):
if "".join(column) == "xxxxx":
return int(number) * unmarked_sum(board)
def part2(input_data):
numbers, boards = parse_input(input_data)
board_scores = [0 for x in boards]
last_index = None
for number in numbers:
# Put number on all boards
for board in boards:
for row in board:
for i in range(len(row)):
if number == row[i]:
row[i] = "x"
# Check for bingo
for i, board in enumerate(boards):
for row in board:
if "".join(row) == "xxxxx" and board_scores[i] == 0:
board_scores[i] = int(number) * unmarked_sum(board)
last_index = i
for column in zip(*board):
if "".join(column) == "xxxxx" and board_scores[i] == 0:
board_scores[i] = int(number) * unmarked_sum(board)
last_index = i
return board_scores[last_index]
def unmarked_sum(board):
return sum(
map(
lambda x: sum(map(lambda y: int(y) if y != "x" else 0, x)),
board,
)
)
def parse_input(input_data):
numbers = input_data[0].split(",")
boards = []
for i in range(1, len(input_data), 6):
rows = input_data[i + 1 : i + 6]
rows = list(
map(lambda x: list(filter(lambda y: len(y) > 0, x.split(" "))), rows)
)
boards.append(rows)
return numbers, boards
if __name__ == "__main__":
with open("input", "r") as input_file:
input_data = list(map(lambda x: x.strip(), input_file.readlines()))
print(part1(input_data))
print(part2(input_data))
| def part1(input_data):
(numbers, boards) = parse_input(input_data)
for number in numbers:
for board in boards:
for row in board:
for i in range(len(row)):
if number == row[i]:
row[i] = 'x'
for board in boards:
for row in board:
if ''.join(row) == 'xxxxx':
return int(number) * unmarked_sum(board)
for column in zip(*board):
if ''.join(column) == 'xxxxx':
return int(number) * unmarked_sum(board)
def part2(input_data):
(numbers, boards) = parse_input(input_data)
board_scores = [0 for x in boards]
last_index = None
for number in numbers:
for board in boards:
for row in board:
for i in range(len(row)):
if number == row[i]:
row[i] = 'x'
for (i, board) in enumerate(boards):
for row in board:
if ''.join(row) == 'xxxxx' and board_scores[i] == 0:
board_scores[i] = int(number) * unmarked_sum(board)
last_index = i
for column in zip(*board):
if ''.join(column) == 'xxxxx' and board_scores[i] == 0:
board_scores[i] = int(number) * unmarked_sum(board)
last_index = i
return board_scores[last_index]
def unmarked_sum(board):
return sum(map(lambda x: sum(map(lambda y: int(y) if y != 'x' else 0, x)), board))
def parse_input(input_data):
numbers = input_data[0].split(',')
boards = []
for i in range(1, len(input_data), 6):
rows = input_data[i + 1:i + 6]
rows = list(map(lambda x: list(filter(lambda y: len(y) > 0, x.split(' '))), rows))
boards.append(rows)
return (numbers, boards)
if __name__ == '__main__':
with open('input', 'r') as input_file:
input_data = list(map(lambda x: x.strip(), input_file.readlines()))
print(part1(input_data))
print(part2(input_data)) |
load("@bazel_skylib//lib:paths.bzl", "paths")
load(
"//caffe2/test:defs.bzl",
"define_tests",
)
def define_pipeline_tests():
test_files = native.glob(["**/test_*.py"])
TESTS = {}
for test_file in test_files:
test_file_name = paths.basename(test_file)
test_name = test_file_name.replace("test_", "").replace(".py", "")
TESTS[test_name] = [test_file]
define_tests(
pytest = True,
tests = TESTS,
external_deps = [("pytest", None)],
resources = ["conftest.py"],
)
| load('@bazel_skylib//lib:paths.bzl', 'paths')
load('//caffe2/test:defs.bzl', 'define_tests')
def define_pipeline_tests():
test_files = native.glob(['**/test_*.py'])
tests = {}
for test_file in test_files:
test_file_name = paths.basename(test_file)
test_name = test_file_name.replace('test_', '').replace('.py', '')
TESTS[test_name] = [test_file]
define_tests(pytest=True, tests=TESTS, external_deps=[('pytest', None)], resources=['conftest.py']) |
# definitions.py
IbConfig = {
'telepotChatId': '572145851',
'googleServiceKeyFile' : 'GoogleCloudServiceKey.json',
'telepotToken' : '679545486:AAEbCBdedlJ1lxFXpN1a-J-6LfgFQ4cAp04',
'startMessage' : 'Hallo, ich bin unsere dolmetschende Eule. Stelle mich bitte auf deine Handflaeche und ich sage dir, was dein tauber Gegenueber schreibt. Wenn du etwas sagst, teile ich das deinem Gegenueber mit',
'listenLanguage' : 'de_DE', # de_DE, en_US, en_UK, en_AU, etc. See https://cloud.google.com/speech-to-text/docs/languages
'speakLanguage' : 'de', # de, en_US, en_UK, en_AU. See gtts-cli --all
'micDeviceIndex' : 0,
}
| ib_config = {'telepotChatId': '572145851', 'googleServiceKeyFile': 'GoogleCloudServiceKey.json', 'telepotToken': '679545486:AAEbCBdedlJ1lxFXpN1a-J-6LfgFQ4cAp04', 'startMessage': 'Hallo, ich bin unsere dolmetschende Eule. Stelle mich bitte auf deine Handflaeche und ich sage dir, was dein tauber Gegenueber schreibt. Wenn du etwas sagst, teile ich das deinem Gegenueber mit', 'listenLanguage': 'de_DE', 'speakLanguage': 'de', 'micDeviceIndex': 0} |
class Graph:
def __init__(self,nodes,edges):
self.graph=[]
for i in range(nodes+1):
self.graph.append([])
self.visited=[False]*(len(self.graph))
def addEdge(self,v1,v2):
self.graph[v1].append(v2)
def dfs(self,source):
self.visited[source]=True
print(source)
for i in self.graph[source]:
if not self.visited[i]:
self.dfs(i)
def dfs_stack(self,source):
stack=[]
stack.append(source)
self.visited[source] = True
while stack:
top=stack.pop()
print(top)
for i in self.graph[top]:
if not self.visited[i]:
stack.append(i)
self.visited[i]=True
g=Graph(4,5)
g.addEdge(1,2)
g.addEdge(1,3)
g.addEdge(1,4)
g.addEdge(3,4)
g.addEdge(4,2)
g.dfs_stack(1) | class Graph:
def __init__(self, nodes, edges):
self.graph = []
for i in range(nodes + 1):
self.graph.append([])
self.visited = [False] * len(self.graph)
def add_edge(self, v1, v2):
self.graph[v1].append(v2)
def dfs(self, source):
self.visited[source] = True
print(source)
for i in self.graph[source]:
if not self.visited[i]:
self.dfs(i)
def dfs_stack(self, source):
stack = []
stack.append(source)
self.visited[source] = True
while stack:
top = stack.pop()
print(top)
for i in self.graph[top]:
if not self.visited[i]:
stack.append(i)
self.visited[i] = True
g = graph(4, 5)
g.addEdge(1, 2)
g.addEdge(1, 3)
g.addEdge(1, 4)
g.addEdge(3, 4)
g.addEdge(4, 2)
g.dfs_stack(1) |
inp = list(map(float, input().split()))
inp.sort(reverse=True)
a, b, c = inp
if a >= b + c:
print('NAO FORMA TRIANGULO')
else:
if a ** 2 == b ** 2 + c ** 2:
print('TRIANGULO RETANGULO')
elif a ** 2 > b ** 2 + c ** 2:
print('TRIANGULO OBTUSANGULO')
else:
print('TRIANGULO ACUTANGULO')
if a == b and b == c:
print('TRIANGULO EQUILATERO')
elif a == b or a == c or b == c:
print('TRIANGULO ISOSCELES')
| inp = list(map(float, input().split()))
inp.sort(reverse=True)
(a, b, c) = inp
if a >= b + c:
print('NAO FORMA TRIANGULO')
else:
if a ** 2 == b ** 2 + c ** 2:
print('TRIANGULO RETANGULO')
elif a ** 2 > b ** 2 + c ** 2:
print('TRIANGULO OBTUSANGULO')
else:
print('TRIANGULO ACUTANGULO')
if a == b and b == c:
print('TRIANGULO EQUILATERO')
elif a == b or a == c or b == c:
print('TRIANGULO ISOSCELES') |
__all__ = ['CONFIG', 'get']
CONFIG = {
'model_save_dir': "./output/MicroExpression",
'num_classes': 7,
'total_images': 17245,
'epochs': 20,
'batch_size': 32,
'image_shape': [3, 224, 224],
'LEARNING_RATE': {
'params': {
'lr': 0.00375
}
},
'OPTIMIZER': {
'params': {
'momentum': 0.9
},
'regularizer': {
'function': 'L2',
'factor': 0.000001
}
},
'LABEL_MAP': [
"disgust",
"others",
"sadness",
"happiness",
"surprise",
"repression",
"fear"
]
}
def get(full_path):
for id, name in enumerate(full_path.split('.')):
if id == 0:
config = CONFIG
config = config[name]
return config
| __all__ = ['CONFIG', 'get']
config = {'model_save_dir': './output/MicroExpression', 'num_classes': 7, 'total_images': 17245, 'epochs': 20, 'batch_size': 32, 'image_shape': [3, 224, 224], 'LEARNING_RATE': {'params': {'lr': 0.00375}}, 'OPTIMIZER': {'params': {'momentum': 0.9}, 'regularizer': {'function': 'L2', 'factor': 1e-06}}, 'LABEL_MAP': ['disgust', 'others', 'sadness', 'happiness', 'surprise', 'repression', 'fear']}
def get(full_path):
for (id, name) in enumerate(full_path.split('.')):
if id == 0:
config = CONFIG
config = config[name]
return config |
n=str(input("Enter the string"))
le=len(n)
dig=0
alp=0
for i in range(le):
if n[i].isdigit():
dig=dig+1
elif n[i].isalpha():
alp=alp+1
else:
continue
print("Letters count is : %d"%alp)
print("Digits count is : %d"%dig)
| n = str(input('Enter the string'))
le = len(n)
dig = 0
alp = 0
for i in range(le):
if n[i].isdigit():
dig = dig + 1
elif n[i].isalpha():
alp = alp + 1
else:
continue
print('Letters count is : %d' % alp)
print('Digits count is : %d' % dig) |
# Author: Will Killian
# https://www.github.com/willkill07
#
# Copyright 2021
# All Rights Reserved
class Lab:
_all = dict()
lab_id = 200
def min_id():
"""
Returns the maximum number for the lab IDs (always 200)
"""
return 200
def max_id():
"""
Returns the maximum number for the lab IDs
"""
return Lab.lab_id - 1
def get(id):
"""
Given an ID of a lab, return the instance
"""
return Lab._all[id]
def __init__(self, name: str):
# update id to be a unique identifier
self.id = Lab.lab_id
Lab.lab_id += 1
self.name = name
Lab._all[self.id] = self
def __repr__(self):
"""
Pretty Print representation of a course is its subject, number, and section
"""
return f'{self.name}' | class Lab:
_all = dict()
lab_id = 200
def min_id():
"""
Returns the maximum number for the lab IDs (always 200)
"""
return 200
def max_id():
"""
Returns the maximum number for the lab IDs
"""
return Lab.lab_id - 1
def get(id):
"""
Given an ID of a lab, return the instance
"""
return Lab._all[id]
def __init__(self, name: str):
self.id = Lab.lab_id
Lab.lab_id += 1
self.name = name
Lab._all[self.id] = self
def __repr__(self):
"""
Pretty Print representation of a course is its subject, number, and section
"""
return f'{self.name}' |
# -*- coding: utf-8 -*-
class GeocoderException(Exception):
"""Base class for all the reverse geocoder module exceptions."""
class InitializationError(GeocoderException):
"""Catching this error will catch all initialization-related errors."""
class CsvReadError(InitializationError):
"""Could not open the locations csv file."""
class CsvParseError(InitializationError):
"""Could not parse the locations csv file."""
| class Geocoderexception(Exception):
"""Base class for all the reverse geocoder module exceptions."""
class Initializationerror(GeocoderException):
"""Catching this error will catch all initialization-related errors."""
class Csvreaderror(InitializationError):
"""Could not open the locations csv file."""
class Csvparseerror(InitializationError):
"""Could not parse the locations csv file.""" |
#Given a decimal number n, your task is to convert it
#to its binary equivalent using a recursive function.
#The binary number output must be of length 8 bits.
def binary(n):
if n == 0:
return 0
else:
return (n % 2 + 10*binary(int(n // 2)))
def convert_8_bit(n):
s = str(n)
while len(s)<8:
s = '0' + s
return s
def dec_to_binary(n):
return convert_8_bit(binary(n))
def main():
T = int(input())
n = []
for _ in range(0,T):
temp = int(input())
n.append(dec_to_binary(temp))
print(*n,sep="\n")
if __name__=='__main__':
try: main()
except: pass | def binary(n):
if n == 0:
return 0
else:
return n % 2 + 10 * binary(int(n // 2))
def convert_8_bit(n):
s = str(n)
while len(s) < 8:
s = '0' + s
return s
def dec_to_binary(n):
return convert_8_bit(binary(n))
def main():
t = int(input())
n = []
for _ in range(0, T):
temp = int(input())
n.append(dec_to_binary(temp))
print(*n, sep='\n')
if __name__ == '__main__':
try:
main()
except:
pass |
'''
Author: Shuailin Chen
Created Date: 2021-09-14
Last Modified: 2021-12-29
content:
'''
# optimizer
optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
optimizer_config = dict()
# learning policy
lr_config = dict(policy='poly', power=0.9, min_lr=1e-4, by_epoch=False)
# runtime settings
runner = dict(type='MyIterBasedRunner', max_iters=10000)
# runner = dict(type='IterBasedRunner', max_iters=20000)
checkpoint_config = dict(by_epoch=False, interval=100000)
# evaluation = dict(interval=50, metric='mIoU', pre_eval=True)
evaluation = dict(interval=1000, metric='mIoU', pre_eval=True)
| """
Author: Shuailin Chen
Created Date: 2021-09-14
Last Modified: 2021-12-29
content:
"""
optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
optimizer_config = dict()
lr_config = dict(policy='poly', power=0.9, min_lr=0.0001, by_epoch=False)
runner = dict(type='MyIterBasedRunner', max_iters=10000)
checkpoint_config = dict(by_epoch=False, interval=100000)
evaluation = dict(interval=1000, metric='mIoU', pre_eval=True) |
keys = {
"accept": 30,
"add": 107,
"apps": 93,
"attn": 246,
"back": 8,
"browser_back": 166,
"browser_forward": 167,
"cancel": 3,
"capital": 20,
"clear": 12,
"control": 17,
"convert": 28,
"crsel": 247,
"decimal": 110,
"delete": 46,
"divide": 111,
"down": 40,
"end": 35,
"ereof": 249,
"escape": 27,
"execute": 43,
"exsel": 248,
"f1": 112,
"f10": 121,
"f11": 122,
"f12": 123,
"f13": 124,
"f14": 125,
"f15": 126,
"f16": 127,
"f17": 128,
"f18": 129,
"f19": 130,
"f2": 113,
"f20": 131,
"f21": 132,
"f22": 133,
"f23": 134,
"f24": 135,
"f3": 114,
"f4": 115,
"f5": 116,
"f6": 117,
"f7": 118,
"f8": 119,
"f9": 120,
"final": 24,
"hangeul": 21,
"hangul": 21,
"hanja": 25,
"help": 47,
"home": 36,
"insert": 45,
"junja": 23,
"kana": 21,
"kanji": 25,
"lbutton": 1,
"lcontrol": 162,
"left": 37,
"lmenu": 164,
"lshift": 160,
"lwin": 91,
"mbutton": 4,
"media_next_track": 176,
"media_play_pause": 179,
"media_prev_track": 177,
"menu": 18,
"modechange": 31,
"multiply": 106,
"next": 34,
"noname": 252,
"nonconvert": 29,
"numlock": 144,
"numpad0": 96,
"numpad1": 97,
"numpad2": 98,
"numpad3": 99,
"numpad4": 100,
"numpad5": 101,
"numpad6": 102,
"numpad7": 103,
"numpad8": 104,
"numpad9": 105,
"oem_clear": 254,
"pa1": 253,
"pagedown": 34,
"pageup": 33,
"pause": 19,
"play": 250,
"print": 42,
"prior": 33,
"processkey": 229,
"rbutton": 2,
"rcontrol": 163,
"return": 13,
"right": 39,
"rmenu": 165,
"rshift": 161,
"rwin": 92,
"scroll": 145,
"select": 41,
"separator": 108,
"shift": 16,
"snapshot": 44,
"space": 32,
"subtract": 109,
"tab": 9,
"up": 38,
"volume_down": 174,
"volume_mute": 173,
"volume_up": 175,
"xbutton1": 5,
"xbutton2": 6,
"zoom": 251,
"/": 191,
";": 218,
"[": 219,
"\\": 220,
"]": 221,
"'": 222,
"=": 187,
"-": 189,
";": 186,
}
modifiers = {"alt": 1, "control": 2, "shift": 4, "win": 8}
| keys = {'accept': 30, 'add': 107, 'apps': 93, 'attn': 246, 'back': 8, 'browser_back': 166, 'browser_forward': 167, 'cancel': 3, 'capital': 20, 'clear': 12, 'control': 17, 'convert': 28, 'crsel': 247, 'decimal': 110, 'delete': 46, 'divide': 111, 'down': 40, 'end': 35, 'ereof': 249, 'escape': 27, 'execute': 43, 'exsel': 248, 'f1': 112, 'f10': 121, 'f11': 122, 'f12': 123, 'f13': 124, 'f14': 125, 'f15': 126, 'f16': 127, 'f17': 128, 'f18': 129, 'f19': 130, 'f2': 113, 'f20': 131, 'f21': 132, 'f22': 133, 'f23': 134, 'f24': 135, 'f3': 114, 'f4': 115, 'f5': 116, 'f6': 117, 'f7': 118, 'f8': 119, 'f9': 120, 'final': 24, 'hangeul': 21, 'hangul': 21, 'hanja': 25, 'help': 47, 'home': 36, 'insert': 45, 'junja': 23, 'kana': 21, 'kanji': 25, 'lbutton': 1, 'lcontrol': 162, 'left': 37, 'lmenu': 164, 'lshift': 160, 'lwin': 91, 'mbutton': 4, 'media_next_track': 176, 'media_play_pause': 179, 'media_prev_track': 177, 'menu': 18, 'modechange': 31, 'multiply': 106, 'next': 34, 'noname': 252, 'nonconvert': 29, 'numlock': 144, 'numpad0': 96, 'numpad1': 97, 'numpad2': 98, 'numpad3': 99, 'numpad4': 100, 'numpad5': 101, 'numpad6': 102, 'numpad7': 103, 'numpad8': 104, 'numpad9': 105, 'oem_clear': 254, 'pa1': 253, 'pagedown': 34, 'pageup': 33, 'pause': 19, 'play': 250, 'print': 42, 'prior': 33, 'processkey': 229, 'rbutton': 2, 'rcontrol': 163, 'return': 13, 'right': 39, 'rmenu': 165, 'rshift': 161, 'rwin': 92, 'scroll': 145, 'select': 41, 'separator': 108, 'shift': 16, 'snapshot': 44, 'space': 32, 'subtract': 109, 'tab': 9, 'up': 38, 'volume_down': 174, 'volume_mute': 173, 'volume_up': 175, 'xbutton1': 5, 'xbutton2': 6, 'zoom': 251, '/': 191, ';': 218, '[': 219, '\\': 220, ']': 221, "'": 222, '=': 187, '-': 189, ';': 186}
modifiers = {'alt': 1, 'control': 2, 'shift': 4, 'win': 8} |
N = int(input())
A = list(map(int, input().split()))
A.sort()
left, right = 0, 2*N-1
moist = A.count(0) // 2
while left < right and A[left] < 0 and A[right] > 0:
if abs(A[left]) == A[right]:
moist += 1
left += 1
right -= 1
elif abs(A[left]) > A[right]:
left += 1
else:
right -= 1
left, right = 0, 2*N-1
wet = 0
while left < right:
if A[left] + A[right] <= 0:
left += 1
else:
wet += 1
left += 1
right -= 1
left, right = 0, 2*N-1
dry = 0
while left < right:
if A[left] + A[right] >= 0:
right -= 1
else:
dry += 1
left += 1
right -= 1
print(dry, wet, moist)
| n = int(input())
a = list(map(int, input().split()))
A.sort()
(left, right) = (0, 2 * N - 1)
moist = A.count(0) // 2
while left < right and A[left] < 0 and (A[right] > 0):
if abs(A[left]) == A[right]:
moist += 1
left += 1
right -= 1
elif abs(A[left]) > A[right]:
left += 1
else:
right -= 1
(left, right) = (0, 2 * N - 1)
wet = 0
while left < right:
if A[left] + A[right] <= 0:
left += 1
else:
wet += 1
left += 1
right -= 1
(left, right) = (0, 2 * N - 1)
dry = 0
while left < right:
if A[left] + A[right] >= 0:
right -= 1
else:
dry += 1
left += 1
right -= 1
print(dry, wet, moist) |
def printSlope(equation):
xIndex = equation.find('x')
if xIndex == -1:
print(0)
elif xIndex == 2:
print(1)
else:
slopeString = equation[2:xIndex]
if slopeString == "-":
print(-1)
else:
print(slopeString)
printSlope("y=2x+5") #prints 2
printSlope("y=-1299x+5") #prints -1299
printSlope("y=x+5") #prints 1
printSlope("y=-x+5") #prints -1
printSlope("y=5") #prints 0
| def print_slope(equation):
x_index = equation.find('x')
if xIndex == -1:
print(0)
elif xIndex == 2:
print(1)
else:
slope_string = equation[2:xIndex]
if slopeString == '-':
print(-1)
else:
print(slopeString)
print_slope('y=2x+5')
print_slope('y=-1299x+5')
print_slope('y=x+5')
print_slope('y=-x+5')
print_slope('y=5') |
#!/usr/bin/env python
#-*- coding: utf-8 -*-
"""
__title__ = 'replace'
__author__ = 'JieYuan'
__mtime__ = '2019-05-06'
"""
def replace(s, dic):
return s.translate(str.maketrans(dic))
if __name__ == '__main__':
print(replace('abcd', {'a': '8', 'd': '88'}))
| """
__title__ = 'replace'
__author__ = 'JieYuan'
__mtime__ = '2019-05-06'
"""
def replace(s, dic):
return s.translate(str.maketrans(dic))
if __name__ == '__main__':
print(replace('abcd', {'a': '8', 'd': '88'})) |
def profile_most_probable_kmer(text, k, profile):
highest_prob = -1
most_probable_kmer = ""
for i in range(len(text) - k + 1):
kmer = text[i : i+k]
prob = 1
for index, nucleotide in enumerate(kmer):
prob *= profile[nucleotide][index]
if prob > highest_prob:
highest_prob = prob
most_probable_kmer = kmer
return most_probable_kmer
if __name__ == '__main__':
with open("dataset_159_3.txt") as f:
text = f.readline().strip()
k = int(f.readline().strip())
profile = {}
for letter in ['A', 'C', 'G', 'T']:
profile[letter] = [float(item) for item in f.readline().strip().split()]
print(profile_most_probable_kmer(text, k, profile))
| def profile_most_probable_kmer(text, k, profile):
highest_prob = -1
most_probable_kmer = ''
for i in range(len(text) - k + 1):
kmer = text[i:i + k]
prob = 1
for (index, nucleotide) in enumerate(kmer):
prob *= profile[nucleotide][index]
if prob > highest_prob:
highest_prob = prob
most_probable_kmer = kmer
return most_probable_kmer
if __name__ == '__main__':
with open('dataset_159_3.txt') as f:
text = f.readline().strip()
k = int(f.readline().strip())
profile = {}
for letter in ['A', 'C', 'G', 'T']:
profile[letter] = [float(item) for item in f.readline().strip().split()]
print(profile_most_probable_kmer(text, k, profile)) |
ROW_COUNT = 128
COLUMN_COUNT = 8
def solve(input):
return max(map(lambda i: BoardingPass(i).seat_id, input))
class BoardingPass:
def __init__(self, data, row_count=ROW_COUNT, column_count=COLUMN_COUNT):
self.row = self._search(
data = data[:7],
low_char='F',
high_char='B',
i=0,
min_value=0,
max_value=row_count
)
self.column = self._search(
data = data[7:],
low_char='L',
high_char='R',
i=0,
min_value=0,
max_value=column_count
)
self.seat_id = Seat(self.row, self.column).id
def _search(self, data, low_char, high_char, i, min_value, max_value):
if i == len(data) - 1:
assert max_value - min_value == 2
if data[i] == low_char:
return min_value
elif data[i] == high_char:
return max_value - 1
else:
raise Exception(f'Expected {low_char} or {high_char} got {data[i]}')
mid_value = int((max_value - min_value) / 2) + min_value
if data[i] == low_char:
return self._search(data, low_char, high_char, i + 1, min_value, mid_value)
elif data[i] == high_char:
return self._search(data, low_char, high_char, i + 1, mid_value, max_value)
else:
raise Exception(f'Expected {low_char} or {high_char} got {data[i]}')
class Seat:
def __init__(self, row, column):
self.id = (row * 8) + column
| row_count = 128
column_count = 8
def solve(input):
return max(map(lambda i: boarding_pass(i).seat_id, input))
class Boardingpass:
def __init__(self, data, row_count=ROW_COUNT, column_count=COLUMN_COUNT):
self.row = self._search(data=data[:7], low_char='F', high_char='B', i=0, min_value=0, max_value=row_count)
self.column = self._search(data=data[7:], low_char='L', high_char='R', i=0, min_value=0, max_value=column_count)
self.seat_id = seat(self.row, self.column).id
def _search(self, data, low_char, high_char, i, min_value, max_value):
if i == len(data) - 1:
assert max_value - min_value == 2
if data[i] == low_char:
return min_value
elif data[i] == high_char:
return max_value - 1
else:
raise exception(f'Expected {low_char} or {high_char} got {data[i]}')
mid_value = int((max_value - min_value) / 2) + min_value
if data[i] == low_char:
return self._search(data, low_char, high_char, i + 1, min_value, mid_value)
elif data[i] == high_char:
return self._search(data, low_char, high_char, i + 1, mid_value, max_value)
else:
raise exception(f'Expected {low_char} or {high_char} got {data[i]}')
class Seat:
def __init__(self, row, column):
self.id = row * 8 + column |
f = open('day3.txt', 'r')
data = f.readlines()
oneCount = 0
threeCount = 0
fiveCount = 0
sevenCount = 0
evenCount = 0
pos1 = 0
pos3 = 0
pos5 = 0
pos7 = 0
posEven = 0
even = True
for line in data:
line = line.replace("\n", '')
if line[pos1 % len(line)] == '#':
oneCount += 1
if line[pos3 % len(line)] == '#':
threeCount += 1
if line[pos5 % len(line)] == '#':
fiveCount += 1
if line[pos7 % len(line)] == '#':
sevenCount += 1
if line[posEven % len(line)] == '#' and even:
evenCount += 1
pos1 += 1
pos3 += 3
pos5 += 5
pos7 += 7
if not even:
posEven += 1
even = not even
print(str(evenCount * oneCount * threeCount * fiveCount * sevenCount))
| f = open('day3.txt', 'r')
data = f.readlines()
one_count = 0
three_count = 0
five_count = 0
seven_count = 0
even_count = 0
pos1 = 0
pos3 = 0
pos5 = 0
pos7 = 0
pos_even = 0
even = True
for line in data:
line = line.replace('\n', '')
if line[pos1 % len(line)] == '#':
one_count += 1
if line[pos3 % len(line)] == '#':
three_count += 1
if line[pos5 % len(line)] == '#':
five_count += 1
if line[pos7 % len(line)] == '#':
seven_count += 1
if line[posEven % len(line)] == '#' and even:
even_count += 1
pos1 += 1
pos3 += 3
pos5 += 5
pos7 += 7
if not even:
pos_even += 1
even = not even
print(str(evenCount * oneCount * threeCount * fiveCount * sevenCount)) |
def porrada(seq, passo):
atual = 0
while len(seq) > 1:
atual += passo - 1
while atual > len(seq) - 1:
atual -= len(seq)
seq.pop(atual)
return seq[0] + 1
quantidade_de_casos = int(input())
for c in range(quantidade_de_casos):
entrada = input().split()
n = list(range(int(entrada[0])))
m = int(entrada[1])
print(f'Case {c + 1}: {porrada(n, m)}')
| def porrada(seq, passo):
atual = 0
while len(seq) > 1:
atual += passo - 1
while atual > len(seq) - 1:
atual -= len(seq)
seq.pop(atual)
return seq[0] + 1
quantidade_de_casos = int(input())
for c in range(quantidade_de_casos):
entrada = input().split()
n = list(range(int(entrada[0])))
m = int(entrada[1])
print(f'Case {c + 1}: {porrada(n, m)}') |
n = int(input())
arr = list(map(int, input().split(' ')))
arr.sort(reverse=True)
res = 0
for i in range(n):
res += arr[i]*2**i
print(res)
| n = int(input())
arr = list(map(int, input().split(' ')))
arr.sort(reverse=True)
res = 0
for i in range(n):
res += arr[i] * 2 ** i
print(res) |
class Solution:
def minInsertions(self, s: str) -> int:
right = count = 0
for c in s:
if c == '(':
if right & 1:
right -= 1
count += 1
right += 2
else:
right -= 1
if right < 0:
right = 1
count += 1
return right + count
| class Solution:
def min_insertions(self, s: str) -> int:
right = count = 0
for c in s:
if c == '(':
if right & 1:
right -= 1
count += 1
right += 2
else:
right -= 1
if right < 0:
right = 1
count += 1
return right + count |
# Given an array of integers, return indices of the two numbers such that they add up to a specific target.
# You may assume that each input would have exactly one solution, and you may not use the same element twice.
# Example:
# Given nums = [2, 7, 11, 15], target = 9,
# Because nums[0] + nums[1] = 2 + 7 = 9,
# return [0, 1].
class Solution(object):
def twoSum(self, nums, target):
"""
O(m)
O(m)
:type nums: List[int]
:type target: int
:rtype: List[int]
"""
dic = {}
for i in range(len(nums)):
if nums[i] in dic:
return [dic[nums[i]], i]
else:
dic[target- nums[i]] = i
return []
| class Solution(object):
def two_sum(self, nums, target):
"""
O(m)
O(m)
:type nums: List[int]
:type target: int
:rtype: List[int]
"""
dic = {}
for i in range(len(nums)):
if nums[i] in dic:
return [dic[nums[i]], i]
else:
dic[target - nums[i]] = i
return [] |
S = input()
N = len(S)
A = [0]*(N+1)
B = [0]*(N+1)
for i in range(N):
if S[i] == '<':
A[i+1] = A[i]+1
else:
A[i+1] = 0
for i in range(N):
if S[N-i-1] == '>':
B[N-i-1] = B[N-i]+1
else:
B[N-i-1] = 0
ans = 0
for i in range(N+1):
ans += max(A[i], B[i])
print(ans)
| s = input()
n = len(S)
a = [0] * (N + 1)
b = [0] * (N + 1)
for i in range(N):
if S[i] == '<':
A[i + 1] = A[i] + 1
else:
A[i + 1] = 0
for i in range(N):
if S[N - i - 1] == '>':
B[N - i - 1] = B[N - i] + 1
else:
B[N - i - 1] = 0
ans = 0
for i in range(N + 1):
ans += max(A[i], B[i])
print(ans) |
'''
Write a program that takes an integer argument and
retums all the primes between 1 and that integer.
For example, if the input is 18, you should return
[2, 3, 5, 7, 11, 13, 17].
'''
def generate_primes(n): # Time: O(n log log n) | Space: O(n)
primes = []
# is_prime[p] represents if p is prime or not.
# Initially, set each to true, except for 0 and 1.
# Then use sieving to eliminate non-primes.
is_prime = [False, False] + [True] * (n - 1)
for p in range(2, n + 1):
if is_prime[p]:
primes.append(p)
# Turn false all multiples of p.
for i in range(p, n+1, p):
is_prime[i] = False
return primes
assert(generate_primes(18) == [2, 3, 5, 7, 11, 13, 17])
# Ignore even numbers and eliminate multiples of p2
# This will give better performance, but does not
# reflect on complexity
def generate_primes_square(n): # Time: O(n log log n) | Space: O(n)
if n < 2:
return []
primes = [2] # Store the first prime number
# is_prime[p] represents if (2i + 3) is prime or not.
# Initially, set each to true.
# Then use sieving to eliminate non-primes.
size = (n - 3) // 2 + 1
is_prime = [True] * size
for i in range(size):
if is_prime[i]:
p = i * 2 + 3
primes.append(p)
# Sieving fron p^2, where p^2 = (4i^2 + 12i + 9).
# The index in is_prime is (2i^2 + 6i + 3) because
# is_prime[i] represents 2i + 3.
# Note that we need to use long for j because p^2 might overflow.
for j in range(2 * i**2 + 6 * i + 3, size, p):
is_prime[j] = False
return primes
assert(generate_primes_square(18) == [2, 3, 5, 7, 11, 13, 17])
| """
Write a program that takes an integer argument and
retums all the primes between 1 and that integer.
For example, if the input is 18, you should return
[2, 3, 5, 7, 11, 13, 17].
"""
def generate_primes(n):
primes = []
is_prime = [False, False] + [True] * (n - 1)
for p in range(2, n + 1):
if is_prime[p]:
primes.append(p)
for i in range(p, n + 1, p):
is_prime[i] = False
return primes
assert generate_primes(18) == [2, 3, 5, 7, 11, 13, 17]
def generate_primes_square(n):
if n < 2:
return []
primes = [2]
size = (n - 3) // 2 + 1
is_prime = [True] * size
for i in range(size):
if is_prime[i]:
p = i * 2 + 3
primes.append(p)
for j in range(2 * i ** 2 + 6 * i + 3, size, p):
is_prime[j] = False
return primes
assert generate_primes_square(18) == [2, 3, 5, 7, 11, 13, 17] |
"""
gdcdatamodel.migrations.update_case_cache
--------------------
Functionality to fix stale case caches in _related_cases edge tables.
"""
def update_related_cases(driver, node_id):
"""Removes and re-adds the edge between the given node and it's parent
to cascade the new relationship to _related_cases through the
graph
"""
with driver.session_scope() as session:
node = driver.nodes().ids(node_id).one()
edges_out = node.edges_out
for edge in edges_out:
edge_cls = edge.__class__
copied_edge = edge_cls(
src_id=edge.src_id,
dst_id=edge.dst_id,
properties=dict(edge.props),
system_annotations=dict(edge.sysan),
)
# Delete the edge
driver.edges(edge_cls).filter(
edge_cls.src_id == copied_edge.src_id,
edge_cls.dst_id == copied_edge.dst_id,
).delete()
session.expunge(edge)
# Re-add the edge to force a refresh of the stale cache
session.add(copied_edge)
# Assert the edge was re-added or abort the session
driver.edges(edge_cls).filter(
edge_cls.src_id == copied_edge.src_id,
edge_cls.dst_id == copied_edge.dst_id,
).one()
def update_cache_cache_tree(driver, case):
"""Updates the _related_cases case cache for all children in the
:param:`case` tree
"""
visited = set()
with driver.session_scope():
for neighbor in case.edges_in:
if neighbor.src_id in visited:
continue
update_related_cases(driver, neighbor.src_id)
visited.add(neighbor.src_id)
| """
gdcdatamodel.migrations.update_case_cache
--------------------
Functionality to fix stale case caches in _related_cases edge tables.
"""
def update_related_cases(driver, node_id):
"""Removes and re-adds the edge between the given node and it's parent
to cascade the new relationship to _related_cases through the
graph
"""
with driver.session_scope() as session:
node = driver.nodes().ids(node_id).one()
edges_out = node.edges_out
for edge in edges_out:
edge_cls = edge.__class__
copied_edge = edge_cls(src_id=edge.src_id, dst_id=edge.dst_id, properties=dict(edge.props), system_annotations=dict(edge.sysan))
driver.edges(edge_cls).filter(edge_cls.src_id == copied_edge.src_id, edge_cls.dst_id == copied_edge.dst_id).delete()
session.expunge(edge)
session.add(copied_edge)
driver.edges(edge_cls).filter(edge_cls.src_id == copied_edge.src_id, edge_cls.dst_id == copied_edge.dst_id).one()
def update_cache_cache_tree(driver, case):
"""Updates the _related_cases case cache for all children in the
:param:`case` tree
"""
visited = set()
with driver.session_scope():
for neighbor in case.edges_in:
if neighbor.src_id in visited:
continue
update_related_cases(driver, neighbor.src_id)
visited.add(neighbor.src_id) |
n = int(input())
l = []
for i in range(0, n):
l.append(int(input()))
for orig_num in l:
count = 0
num = orig_num
while num != 0:
digit = num % 10
if digit == 0:
pass
elif orig_num % digit == 0:
count += 1
num = int(num / 10)
print (count) | n = int(input())
l = []
for i in range(0, n):
l.append(int(input()))
for orig_num in l:
count = 0
num = orig_num
while num != 0:
digit = num % 10
if digit == 0:
pass
elif orig_num % digit == 0:
count += 1
num = int(num / 10)
print(count) |
class Qseq(str):
def __init__(self, seq):
self.qkey = None
self.parent = None
self.parental_id = None
self.parental_class = None
self.name = None
self.item = None
def __getitem__(self, item):
value = super().__getitem__(item)
if self.parental_class == "QUEEN" and self.parent is not None and self.parent.topology == "circular":
if type(item) == slice:
if item.start is None:
start = 0
elif item.start < 0:
start = len(self) + item.start
else:
start = item.start
if item.stop is None:
stop = len(self)
elif item.stop < 0:
stop = len(self) + item.stop
else:
stop = item.stop
if item.step is None:
step = 1
if start > stop:
value = str(self)[start:] + str(self)[:stop]
value = value[::step]
else:
value = super().__getitem__(item)
else:
pass
value = Qseq(value)
else:
value = Qseq(value)
value.qkey = self.qkey
value.parent = self.parent
value.parental_id = self.parental_id
value.parental_class = self.parental_class
value.name = self.name
if value.item is None:
value.item = item
else:
value.item = slice(value.item.start + item.start, value.item.start + item.stop)
return value
| class Qseq(str):
def __init__(self, seq):
self.qkey = None
self.parent = None
self.parental_id = None
self.parental_class = None
self.name = None
self.item = None
def __getitem__(self, item):
value = super().__getitem__(item)
if self.parental_class == 'QUEEN' and self.parent is not None and (self.parent.topology == 'circular'):
if type(item) == slice:
if item.start is None:
start = 0
elif item.start < 0:
start = len(self) + item.start
else:
start = item.start
if item.stop is None:
stop = len(self)
elif item.stop < 0:
stop = len(self) + item.stop
else:
stop = item.stop
if item.step is None:
step = 1
if start > stop:
value = str(self)[start:] + str(self)[:stop]
value = value[::step]
else:
value = super().__getitem__(item)
else:
pass
value = qseq(value)
else:
value = qseq(value)
value.qkey = self.qkey
value.parent = self.parent
value.parental_id = self.parental_id
value.parental_class = self.parental_class
value.name = self.name
if value.item is None:
value.item = item
else:
value.item = slice(value.item.start + item.start, value.item.start + item.stop)
return value |
rios = {
'nilo' : 'egito',
'rio grande' : 'brasil',
'rio parana' : 'brasil'
}
for key,value in rios.items():
print(' O rio ' + key.title() + ' corre pelo ' + value.title())
for key in rios.keys():
print(key.title())
for value in rios.values():
print(value.title())
| rios = {'nilo': 'egito', 'rio grande': 'brasil', 'rio parana': 'brasil'}
for (key, value) in rios.items():
print(' O rio ' + key.title() + ' corre pelo ' + value.title())
for key in rios.keys():
print(key.title())
for value in rios.values():
print(value.title()) |
def hello(name):
"""Generate a friendly greeting.
Greeting is an important part of culture. This function takes a name and
generates a friendly greeting for it.
Parameters
----------
name : str
A name.
Returns
-------
str
A greeting.
"""
return 'Hello {name}'.format(name=name)
| def hello(name):
"""Generate a friendly greeting.
Greeting is an important part of culture. This function takes a name and
generates a friendly greeting for it.
Parameters
----------
name : str
A name.
Returns
-------
str
A greeting.
"""
return 'Hello {name}'.format(name=name) |
vowels2 = set('aeiiiouuu')
word = input('Provide a word to search for vowels:').lower()
found = vowels2.intersection(set(word))
for v in found:
print(v) | vowels2 = set('aeiiiouuu')
word = input('Provide a word to search for vowels:').lower()
found = vowels2.intersection(set(word))
for v in found:
print(v) |
#!/usr/bin/env python2.7
"""
Read the file agents.raw and output agents.txt, a readable file
"""
if __name__=="__main__":
with open("agents.raw","r") as f:
with open("agents.txt","w") as out:
for line in f:
if(line[0] in '+|'):
out.write(line)
| """
Read the file agents.raw and output agents.txt, a readable file
"""
if __name__ == '__main__':
with open('agents.raw', 'r') as f:
with open('agents.txt', 'w') as out:
for line in f:
if line[0] in '+|':
out.write(line) |
# -*- coding: utf-8 -*-
"""mul.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1fvc_bX8oobfbr_O2r1pCpgOd2CTckXe9
"""
def mul(num1, num2):
print('Result is: ', num1 * num2) | """mul.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1fvc_bX8oobfbr_O2r1pCpgOd2CTckXe9
"""
def mul(num1, num2):
print('Result is: ', num1 * num2) |
class Solution:
def wordPattern(self, pattern: str, str: str) -> bool:
table = {}
mapped = set()
words = str.split()
if len(words) != len(pattern):
return False
for i, word in enumerate(words):
if word in table:
if table[word] != pattern[i]:
return False
else:
if pattern[i] in mapped:
return False
table[word] = pattern[i]
mapped.add(pattern[i])
return True
| class Solution:
def word_pattern(self, pattern: str, str: str) -> bool:
table = {}
mapped = set()
words = str.split()
if len(words) != len(pattern):
return False
for (i, word) in enumerate(words):
if word in table:
if table[word] != pattern[i]:
return False
else:
if pattern[i] in mapped:
return False
table[word] = pattern[i]
mapped.add(pattern[i])
return True |
HOST = 'localhost'
PORT = 61613
VERSION = '1.2'
BROKER = 'activemq'
LOGIN, PASSCODE, VIRTUALHOST = {
'activemq': ('', '', ''),
'apollo': ('admin', 'password', 'mybroker'),
'rabbitmq': ('guest', 'guest', '/')
}[BROKER]
| host = 'localhost'
port = 61613
version = '1.2'
broker = 'activemq'
(login, passcode, virtualhost) = {'activemq': ('', '', ''), 'apollo': ('admin', 'password', 'mybroker'), 'rabbitmq': ('guest', 'guest', '/')}[BROKER] |
# python3.7
"""Configuration for testing StyleGAN on FF-HQ (1024) dataset.
All settings are particularly used for one replica (GPU), such as `batch_size`
and `num_workers`.
"""
runner_type = 'StyleGANRunner'
gan_type = 'stylegan'
resolution = 1024
batch_size = 16
data = dict(
num_workers=4,
# val=dict(root_dir='data/ffhq', resolution=resolution),
val=dict(root_dir='data/ffhq.zip', data_format='zip',
resolution=resolution),
)
modules = dict(
discriminator=dict(
model=dict(gan_type=gan_type, resolution=resolution),
kwargs_val=dict(),
),
generator=dict(
model=dict(gan_type=gan_type, resolution=resolution),
kwargs_val=dict(trunc_psi=0.7, trunc_layers=8, randomize_noise=False),
)
)
| """Configuration for testing StyleGAN on FF-HQ (1024) dataset.
All settings are particularly used for one replica (GPU), such as `batch_size`
and `num_workers`.
"""
runner_type = 'StyleGANRunner'
gan_type = 'stylegan'
resolution = 1024
batch_size = 16
data = dict(num_workers=4, val=dict(root_dir='data/ffhq.zip', data_format='zip', resolution=resolution))
modules = dict(discriminator=dict(model=dict(gan_type=gan_type, resolution=resolution), kwargs_val=dict()), generator=dict(model=dict(gan_type=gan_type, resolution=resolution), kwargs_val=dict(trunc_psi=0.7, trunc_layers=8, randomize_noise=False))) |
def Num2581():
M = int(input())
N = int(input())
minPrimeNum = 0
sumPrimeNum = 0
primeNums = []
for dividend in range(M, N+1):
if dividend == 1:
continue
primeNums.append(dividend)
sumPrimeNum += dividend
for divisor in range(2, dividend):
if dividend % divisor == 0:
primeNums.pop()
sumPrimeNum -= dividend
break
if len(primeNums) == 0:
print("-1")
else:
minPrimeNum = primeNums[0]
sumPrimeNum = sum(primeNums)
print(str(sumPrimeNum))
print(str(minPrimeNum))
Num2581()
| def num2581():
m = int(input())
n = int(input())
min_prime_num = 0
sum_prime_num = 0
prime_nums = []
for dividend in range(M, N + 1):
if dividend == 1:
continue
primeNums.append(dividend)
sum_prime_num += dividend
for divisor in range(2, dividend):
if dividend % divisor == 0:
primeNums.pop()
sum_prime_num -= dividend
break
if len(primeNums) == 0:
print('-1')
else:
min_prime_num = primeNums[0]
sum_prime_num = sum(primeNums)
print(str(sumPrimeNum))
print(str(minPrimeNum))
num2581() |
#takes a list of options as input which will be printed as a numerical list
#Also optionally takes messages as input to be printed after the options but before input request
#Ultimately the users choice is returned
def selector(options,*messages):
rego = 'y'
while rego.lower() == "y":
n=1
for x in options:
print(str(n) + ". " + str(x))
n = n + 1
n=1
print("")
for arg in messages:
print(arg)
choice = input( " :> ")
if choice == "":
return False
try:
i_choice = int(choice)
except ValueError:
print("\nError: Sorry, that's not a valid entry, please enter a number from the list.")
rego = input("\nWould you like to try again? Type Y for yes or N for no :> ")
if rego.lower() == "y":
pass
else:
break
print("")
p=1
for x in options:
if int(choice) == p:
value = x
p = p + 1
p=1
if value in options:
return value
else:
if not value:
print("\nError: Sorry, that's not a valid entry, please enter a number from the list")
rego = input("Would you like to try again? Type Y for yes or N for no :> ")
return False
| def selector(options, *messages):
rego = 'y'
while rego.lower() == 'y':
n = 1
for x in options:
print(str(n) + '. ' + str(x))
n = n + 1
n = 1
print('')
for arg in messages:
print(arg)
choice = input(' :> ')
if choice == '':
return False
try:
i_choice = int(choice)
except ValueError:
print("\nError: Sorry, that's not a valid entry, please enter a number from the list.")
rego = input('\nWould you like to try again? Type Y for yes or N for no :> ')
if rego.lower() == 'y':
pass
else:
break
print('')
p = 1
for x in options:
if int(choice) == p:
value = x
p = p + 1
p = 1
if value in options:
return value
elif not value:
print("\nError: Sorry, that's not a valid entry, please enter a number from the list")
rego = input('Would you like to try again? Type Y for yes or N for no :> ')
return False |
"""A module to keep track of a relinearization key."""
class BFVRelinKey:
"""An instance of a relinearization key.
The relinearization key consists of a list of values, as specified
in Version 1 of the BFV paper, generated in key_generator.py.
Attributes:
base (int): Base used in relinearization in Version 1.
keys (list of tuples of Polynomials): List of elements in the
relinearization key. Each element of the list is a pair of
polynomials.
"""
def __init__(self, base, keys):
"""Sets relinearization key to given inputs.
Args:
base (int): Base used for relinearization.
keys (list of tuples of Polynomials): List of elements in the
relinearization key.
"""
self.base = base
self.keys = keys
def __str__(self):
"""Represents RelinKey as a string.
Returns:
A string which represents the RelinKey.
"""
return 'Base: ' + str(self.base) + '\n' + str(self.keys)
| """A module to keep track of a relinearization key."""
class Bfvrelinkey:
"""An instance of a relinearization key.
The relinearization key consists of a list of values, as specified
in Version 1 of the BFV paper, generated in key_generator.py.
Attributes:
base (int): Base used in relinearization in Version 1.
keys (list of tuples of Polynomials): List of elements in the
relinearization key. Each element of the list is a pair of
polynomials.
"""
def __init__(self, base, keys):
"""Sets relinearization key to given inputs.
Args:
base (int): Base used for relinearization.
keys (list of tuples of Polynomials): List of elements in the
relinearization key.
"""
self.base = base
self.keys = keys
def __str__(self):
"""Represents RelinKey as a string.
Returns:
A string which represents the RelinKey.
"""
return 'Base: ' + str(self.base) + '\n' + str(self.keys) |
class Wrapping(object):
def __init__(self, klass, wrapped_klass, dependency_functions):
self._klass = klass
self._wrapped_klass = wrapped_klass
self._dependency_functions = dependency_functions
def wrap(self):
for dependency_method in self._dependency_functions:
self._access_class_dependency(dependency_method)
setattr(self._klass, '__getattr__', self._getattr())
setattr(self._klass, '__init__', self._init())
return self._klass
def _access_class_dependency(self, method_name):
def _call_dependency_method(wrapper_instance, *args, **kwargs):
method = getattr(wrapper_instance._wrapped, method_name)
return method(wrapper_instance._dependency, *args, **kwargs)
setattr(self._klass, method_name, _call_dependency_method)
def _getattr(self):
def _inner(wrapper_instance, name):
if hasattr(wrapper_instance._wrapped, name):
return getattr(wrapper_instance._wrapped, name)
raise AttributeError(self._missing_attribute_message(name))
return _inner
def _missing_attribute_message(self, name):
return "'{}' object has no attribute '{}'".format(self._klass.__name__, name)
def _init(self):
def _inner(wrapper_instance, dependency):
wrapper_instance._dependency = dependency
wrapper_instance._wrapped = self._wrapped_klass()
return _inner
def wrap_class_with_dependency(wrapped_klass, *dependency_functions):
def _wrap(klass):
return Wrapping(klass, wrapped_klass, dependency_functions).wrap()
return _wrap
| class Wrapping(object):
def __init__(self, klass, wrapped_klass, dependency_functions):
self._klass = klass
self._wrapped_klass = wrapped_klass
self._dependency_functions = dependency_functions
def wrap(self):
for dependency_method in self._dependency_functions:
self._access_class_dependency(dependency_method)
setattr(self._klass, '__getattr__', self._getattr())
setattr(self._klass, '__init__', self._init())
return self._klass
def _access_class_dependency(self, method_name):
def _call_dependency_method(wrapper_instance, *args, **kwargs):
method = getattr(wrapper_instance._wrapped, method_name)
return method(wrapper_instance._dependency, *args, **kwargs)
setattr(self._klass, method_name, _call_dependency_method)
def _getattr(self):
def _inner(wrapper_instance, name):
if hasattr(wrapper_instance._wrapped, name):
return getattr(wrapper_instance._wrapped, name)
raise attribute_error(self._missing_attribute_message(name))
return _inner
def _missing_attribute_message(self, name):
return "'{}' object has no attribute '{}'".format(self._klass.__name__, name)
def _init(self):
def _inner(wrapper_instance, dependency):
wrapper_instance._dependency = dependency
wrapper_instance._wrapped = self._wrapped_klass()
return _inner
def wrap_class_with_dependency(wrapped_klass, *dependency_functions):
def _wrap(klass):
return wrapping(klass, wrapped_klass, dependency_functions).wrap()
return _wrap |
"""
templates for urls
"""
URL = """router.register(r'%(path)s', %(model)sViewSet)
"""
VIEWSET_IMPORT = """from %(app)s.views import %(model)sViewSet
"""
URL_PATTERNS = """urlpatterns = [
path("", include(router.urls)),
]"""
SETUP = """from rest_framework import routers
from django.urls import include, path
router = routers.DefaultRouter()
"""
| """
templates for urls
"""
url = "router.register(r'%(path)s', %(model)sViewSet)\n\n"
viewset_import = 'from %(app)s.views import %(model)sViewSet\n'
url_patterns = 'urlpatterns = [\n path("", include(router.urls)),\n]'
setup = 'from rest_framework import routers\nfrom django.urls import include, path\n\nrouter = routers.DefaultRouter()\n\n' |
def roman_number(num):
if num > 3999:
print("enter number less than 3999")
return
#take 2 list symbol and value symbol having roman of each integer in list value
value = [1000,900,500,400,100,90,50,40,10,9,5,4,1]
symbol = ["M","CM","D","CD","C","XC","L","XL","X","IX","V","IV","I"]
roman = ""
i=0
while num>0:
#then we have to check the the range of value
#divide the number with all values starting from zero
div = num//value[i]
#mod to get part of number
num = num%value[i]
while div:
roman = roman+symbol[i]
#loop goes till div become zero
div = div-1
i=i+1
return roman
num = int(input("enter an integer number: "))
print(f" Roman Numeral of {num} is {roman_number(num)}") | def roman_number(num):
if num > 3999:
print('enter number less than 3999')
return
value = [1000, 900, 500, 400, 100, 90, 50, 40, 10, 9, 5, 4, 1]
symbol = ['M', 'CM', 'D', 'CD', 'C', 'XC', 'L', 'XL', 'X', 'IX', 'V', 'IV', 'I']
roman = ''
i = 0
while num > 0:
div = num // value[i]
num = num % value[i]
while div:
roman = roman + symbol[i]
div = div - 1
i = i + 1
return roman
num = int(input('enter an integer number: '))
print(f' Roman Numeral of {num} is {roman_number(num)}') |
AN_ESCAPED_NEWLINE = "\n"
AN_ESCAPED_TAB = "\t"
A_COMMA = ","
A_QUOTE = "'"
A_TAB = "\t"
DOUBLE_QUOTES = "\""
NEWLINE = "\n"
| an_escaped_newline = '\n'
an_escaped_tab = '\t'
a_comma = ','
a_quote = "'"
a_tab = '\t'
double_quotes = '"'
newline = '\n' |
#!/usr/bin/env python3
#
# Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License..
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
class ScholarshipBuilder:
@staticmethod
def setName(scholarship, name):
scholarship["scholarshipName"] = name
@staticmethod
def setId(scholarship, id):
scholarship["id"] = str(int(id))
@staticmethod
def setSchoolsList(scholarship, schoolsList):
scholarship["schoolsList"] = schoolsList.split(",")
@staticmethod
def setURL(scholarship, url):
scholarship["URL"] = url
@staticmethod
def setYear(scholarship, year):
scholarship["year"] = year
@staticmethod
def setIntroduction(scholarship, intro):
scholarship["introduction"] = intro
@staticmethod
def setIsRenewable(scholarship, isRenewable):
scholarship["isRenewable"] = isRenewable == "yes" or isRenewable == "Yes"
@staticmethod
def setNumberOfYears(scholarship, years):
scholarship["numberOfYears"] = years
@staticmethod
def setAmountPerYear(scholarship, amount):
scholarship["amountPerYear"] = amount
@staticmethod
def setLocationRequirements(scholarship, locationRequirements):
scholarship["locationRequirements"] = locationRequirements.split(';')
@staticmethod
def setAcademicRequirements(scholarship, academicRequirements):
scholarship["academicRequirements"] = academicRequirements.split(';')
@staticmethod
def setEthnicityRaceRequirements(scholarship, ethnicityRaceRequirements):
scholarship["ethnicityRaceRequirements"] = ethnicityRaceRequirements.split(';')
@staticmethod
def setGenderRequirements(scholarship, genders):
scholarship["genderRequriements"] = genders.split(';')
@staticmethod
def setNationalOriginRequirements(scholarship, nations):
scholarship["nationalOriginRequirements"] = nations.split(';')
@staticmethod
def setOtherRequirements(scholarship, otherRequirements):
scholarship["otherRequirements"] = otherRequirements.split(';')
@staticmethod
def setFinancialRequirements(scholarship, financialRequirements):
scholarship["financialRequirements"] = financialRequirements.split(';')
@staticmethod
def setApplicationProcess(scholarship, applicationProcess):
scholarship["applicationProcess"] = applicationProcess
@staticmethod
def setSchoolsNameToIDMap(scholarship):
nameToIDMap = {}
for school in scholarship["schoolsList"]:
nameToIDMap[school] = ""
scholarship["schoolIdList"] = nameToIDMap
| class Scholarshipbuilder:
@staticmethod
def set_name(scholarship, name):
scholarship['scholarshipName'] = name
@staticmethod
def set_id(scholarship, id):
scholarship['id'] = str(int(id))
@staticmethod
def set_schools_list(scholarship, schoolsList):
scholarship['schoolsList'] = schoolsList.split(',')
@staticmethod
def set_url(scholarship, url):
scholarship['URL'] = url
@staticmethod
def set_year(scholarship, year):
scholarship['year'] = year
@staticmethod
def set_introduction(scholarship, intro):
scholarship['introduction'] = intro
@staticmethod
def set_is_renewable(scholarship, isRenewable):
scholarship['isRenewable'] = isRenewable == 'yes' or isRenewable == 'Yes'
@staticmethod
def set_number_of_years(scholarship, years):
scholarship['numberOfYears'] = years
@staticmethod
def set_amount_per_year(scholarship, amount):
scholarship['amountPerYear'] = amount
@staticmethod
def set_location_requirements(scholarship, locationRequirements):
scholarship['locationRequirements'] = locationRequirements.split(';')
@staticmethod
def set_academic_requirements(scholarship, academicRequirements):
scholarship['academicRequirements'] = academicRequirements.split(';')
@staticmethod
def set_ethnicity_race_requirements(scholarship, ethnicityRaceRequirements):
scholarship['ethnicityRaceRequirements'] = ethnicityRaceRequirements.split(';')
@staticmethod
def set_gender_requirements(scholarship, genders):
scholarship['genderRequriements'] = genders.split(';')
@staticmethod
def set_national_origin_requirements(scholarship, nations):
scholarship['nationalOriginRequirements'] = nations.split(';')
@staticmethod
def set_other_requirements(scholarship, otherRequirements):
scholarship['otherRequirements'] = otherRequirements.split(';')
@staticmethod
def set_financial_requirements(scholarship, financialRequirements):
scholarship['financialRequirements'] = financialRequirements.split(';')
@staticmethod
def set_application_process(scholarship, applicationProcess):
scholarship['applicationProcess'] = applicationProcess
@staticmethod
def set_schools_name_to_id_map(scholarship):
name_to_id_map = {}
for school in scholarship['schoolsList']:
nameToIDMap[school] = ''
scholarship['schoolIdList'] = nameToIDMap |
class MyClass:
def __init__(self, name):
self.__name = name
def Show(self):
print(self.__name)
c1 = MyClass('c1')
c2 = MyClass('c2')
c3 = MyClass('c3')
c4 = MyClass('c4')
a = {x.Show() for x in {c1, c2, c3, c4} if x not in {c1, c2}}
| class Myclass:
def __init__(self, name):
self.__name = name
def show(self):
print(self.__name)
c1 = my_class('c1')
c2 = my_class('c2')
c3 = my_class('c3')
c4 = my_class('c4')
a = {x.Show() for x in {c1, c2, c3, c4} if x not in {c1, c2}} |
@metadata_reactor
def install_git(metadata):
return {
'apt': {
'packages': {
'git': {
'installed': True,
},
}
},
}
| @metadata_reactor
def install_git(metadata):
return {'apt': {'packages': {'git': {'installed': True}}}} |
if __name__ == '__main__':
n,m = map(int,input().split())
l = map(int,input().split())
a = set(map(int,input().split()))
b = set(map(int,input().split()))
happy = 0
for i in l:
if i in a:
happy += 1
elif i in b:
happy -= 1
print(happy)
# print(sum([(i in a) - (i in b) for i in l])) | if __name__ == '__main__':
(n, m) = map(int, input().split())
l = map(int, input().split())
a = set(map(int, input().split()))
b = set(map(int, input().split()))
happy = 0
for i in l:
if i in a:
happy += 1
elif i in b:
happy -= 1
print(happy) |
#!/usr/bin/env python
"""Python-LCS Algorithm, Author: Matt Nichols
Copied from https://github.com/man1/Python-LCS/blob/master/lcs.py
Modified for running LCS inside P4SC merging algorithm
"""
### solve the longest common subsequence problem
# get the matrix of LCS lengths at each sub-step of the recursive process
# (m+1 by n+1, where m=len(list1) & n=len(list2) ... it's one larger in each direction
# so we don't have to special-case the x-1 cases at the first elements of the iteration
def lcs_mat(list1, list2):
m = len(list1)
n = len(list2)
# construct the matrix, of all zeroes
mat = [[0] * (n+1) for row in range(m+1)]
# populate the matrix, iteratively
for row in range(1, m+1):
for col in range(1, n+1):
if list1[row - 1] == list2[col - 1]:
# if it's the same element, it's one longer than the LCS of the truncated lists
mat[row][col] = mat[row - 1][col - 1] + 1
else:
# they're not the same, so it's the the maximum of the lengths of the LCSs of the two options (different list truncated in each case)
mat[row][col] = max(mat[row][col - 1], mat[row - 1][col])
# the matrix is complete
return mat
# backtracks all the LCSs through a provided matrix
def all_lcs(lcs_dict, mat, list1, list2, index1, index2):
# if we've calculated it already, just return that
if (lcs_dict.has_key((index1, index2))): return lcs_dict[(index1, index2)]
# otherwise, calculate it recursively
if (index1 == 0) or (index2 == 0): # base case
return [[]]
elif list1[index1 - 1] == list2[index2 - 1]:
# elements are equal! Add it to all LCSs that pass through these indices
lcs_dict[(index1, index2)] = [prevs + [list1[index1 - 1]] for prevs in all_lcs(lcs_dict, mat, list1, list2, index1 - 1, index2 - 1)]
return lcs_dict[(index1, index2)]
else:
lcs_list = [] # set of sets of LCSs from here
# not the same, so follow longer path recursively
if mat[index1][index2 - 1] >= mat[index1 - 1][index2]:
before = all_lcs(lcs_dict, mat, list1, list2, index1, index2 - 1)
for series in before: # iterate through all those before
if not series in lcs_list: lcs_list.append(series) # and if it's not already been found, append to lcs_list
if mat[index1 - 1][index2] >= mat[index1][index2 - 1]:
before = all_lcs(lcs_dict, mat, list1, list2, index1 - 1, index2)
for series in before:
if not series in lcs_list: lcs_list.append(series)
lcs_dict[(index1, index2)] = lcs_list
return lcs_list
# return a set of the sets of longest common subsequences in list1 and list2
def lcs(list1, list2):
# mapping of indices to list of LCSs, so we can cut down recursive calls enormously
mapping = dict()
# start the process...
return all_lcs(mapping, lcs_mat(list1, list2), list1, list2, len(list1), len(list2));
| """Python-LCS Algorithm, Author: Matt Nichols
Copied from https://github.com/man1/Python-LCS/blob/master/lcs.py
Modified for running LCS inside P4SC merging algorithm
"""
def lcs_mat(list1, list2):
m = len(list1)
n = len(list2)
mat = [[0] * (n + 1) for row in range(m + 1)]
for row in range(1, m + 1):
for col in range(1, n + 1):
if list1[row - 1] == list2[col - 1]:
mat[row][col] = mat[row - 1][col - 1] + 1
else:
mat[row][col] = max(mat[row][col - 1], mat[row - 1][col])
return mat
def all_lcs(lcs_dict, mat, list1, list2, index1, index2):
if lcs_dict.has_key((index1, index2)):
return lcs_dict[index1, index2]
if index1 == 0 or index2 == 0:
return [[]]
elif list1[index1 - 1] == list2[index2 - 1]:
lcs_dict[index1, index2] = [prevs + [list1[index1 - 1]] for prevs in all_lcs(lcs_dict, mat, list1, list2, index1 - 1, index2 - 1)]
return lcs_dict[index1, index2]
else:
lcs_list = []
if mat[index1][index2 - 1] >= mat[index1 - 1][index2]:
before = all_lcs(lcs_dict, mat, list1, list2, index1, index2 - 1)
for series in before:
if not series in lcs_list:
lcs_list.append(series)
if mat[index1 - 1][index2] >= mat[index1][index2 - 1]:
before = all_lcs(lcs_dict, mat, list1, list2, index1 - 1, index2)
for series in before:
if not series in lcs_list:
lcs_list.append(series)
lcs_dict[index1, index2] = lcs_list
return lcs_list
def lcs(list1, list2):
mapping = dict()
return all_lcs(mapping, lcs_mat(list1, list2), list1, list2, len(list1), len(list2)) |
# // This is a generated file, modify: generate/templates/binding.gyp.
{
"targets": [{
"target_name": "nodegit",
"dependencies": [
"<(module_root_dir)/vendor/libgit2.gyp:libgit2"
],
"sources": [
"src/nodegit.cc",
"src/wrapper.cc",
"src/functions/copy.cc",
"src/attr.cc",
"src/blame.cc",
"src/blame_hunk.cc",
"src/blame_options.cc",
"src/blob.cc",
"src/branch.cc",
"src/branch_iterator.cc",
"src/buf.cc",
"src/checkout.cc",
"src/checkout_options.cc",
"src/cherry.cc",
"src/cherry_pick_options.cc",
"src/clone.cc",
"src/clone_options.cc",
"src/commit.cc",
"src/config.cc",
"src/cred.cc",
"src/cred_default.cc",
"src/cred_userpass_payload.cc",
"src/diff.cc",
"src/diff_delta.cc",
"src/diff_file.cc",
"src/diff_hunk.cc",
"src/diff_line.cc",
"src/diff_options.cc",
"src/diff_perfdata.cc",
"src/diff_stats.cc",
"src/error.cc",
"src/filter.cc",
"src/filter_list.cc",
"src/giterr.cc",
"src/graph.cc",
"src/ignore.cc",
"src/index.cc",
"src/index_conflict_iterator.cc",
"src/index_entry.cc",
"src/index_time.cc",
"src/indexer.cc",
"src/libgit2.cc",
"src/mempack.cc",
"src/merge.cc",
"src/merge_file_input.cc",
"src/merge_head.cc",
"src/merge_options.cc",
"src/merge_result.cc",
"src/message.cc",
"src/note.cc",
"src/note_iterator.cc",
"src/object.cc",
"src/odb.cc",
"src/odb_object.cc",
"src/oid.cc",
"src/oid_shorten.cc",
"src/packbuilder.cc",
"src/patch.cc",
"src/pathspec.cc",
"src/pathspec_match_list.cc",
"src/push.cc",
"src/push_options.cc",
"src/refdb.cc",
"src/reference.cc",
"src/reflog.cc",
"src/reflog_entry.cc",
"src/refspec.cc",
"src/remote.cc",
"src/remote_callbacks.cc",
"src/repository.cc",
"src/repository_init_options.cc",
"src/revert.cc",
"src/revert_options.cc",
"src/revparse.cc",
"src/revwalk.cc",
"src/signature.cc",
"src/smart.cc",
"src/stash.cc",
"src/status.cc",
"src/status_list.cc",
"src/strarray.cc",
"src/submodule.cc",
"src/tag.cc",
"src/threads.cc",
"src/time.cc",
"src/trace.cc",
"src/transfer_progress.cc",
"src/transport.cc",
"src/tree.cc",
"src/tree_entry.cc",
"src/treebuilder.cc",
],
"include_dirs": [
"vendor/libv8-convert",
"<!(node -e \"require('nan')\")"
],
"cflags": [
"-Wall",
"-std=c++11"
],
"conditions": [
[
"OS=='mac'", {
"xcode_settings": {
"GCC_ENABLE_CPP_EXCEPTIONS": "YES",
"MACOSX_DEPLOYMENT_TARGET": "10.7",
"WARNING_CFLAGS": [
"-Wno-unused-variable",
"-Wint-conversions",
"-Wmissing-field-initializers"
],
"OTHER_CPLUSPLUSFLAGS": [
"-std=gnu++11",
"-stdlib=libc++"
],
"OTHER_LDFLAGS": [
"-stdlib=libc++"
]
}
}
]
]
}]
} | {'targets': [{'target_name': 'nodegit', 'dependencies': ['<(module_root_dir)/vendor/libgit2.gyp:libgit2'], 'sources': ['src/nodegit.cc', 'src/wrapper.cc', 'src/functions/copy.cc', 'src/attr.cc', 'src/blame.cc', 'src/blame_hunk.cc', 'src/blame_options.cc', 'src/blob.cc', 'src/branch.cc', 'src/branch_iterator.cc', 'src/buf.cc', 'src/checkout.cc', 'src/checkout_options.cc', 'src/cherry.cc', 'src/cherry_pick_options.cc', 'src/clone.cc', 'src/clone_options.cc', 'src/commit.cc', 'src/config.cc', 'src/cred.cc', 'src/cred_default.cc', 'src/cred_userpass_payload.cc', 'src/diff.cc', 'src/diff_delta.cc', 'src/diff_file.cc', 'src/diff_hunk.cc', 'src/diff_line.cc', 'src/diff_options.cc', 'src/diff_perfdata.cc', 'src/diff_stats.cc', 'src/error.cc', 'src/filter.cc', 'src/filter_list.cc', 'src/giterr.cc', 'src/graph.cc', 'src/ignore.cc', 'src/index.cc', 'src/index_conflict_iterator.cc', 'src/index_entry.cc', 'src/index_time.cc', 'src/indexer.cc', 'src/libgit2.cc', 'src/mempack.cc', 'src/merge.cc', 'src/merge_file_input.cc', 'src/merge_head.cc', 'src/merge_options.cc', 'src/merge_result.cc', 'src/message.cc', 'src/note.cc', 'src/note_iterator.cc', 'src/object.cc', 'src/odb.cc', 'src/odb_object.cc', 'src/oid.cc', 'src/oid_shorten.cc', 'src/packbuilder.cc', 'src/patch.cc', 'src/pathspec.cc', 'src/pathspec_match_list.cc', 'src/push.cc', 'src/push_options.cc', 'src/refdb.cc', 'src/reference.cc', 'src/reflog.cc', 'src/reflog_entry.cc', 'src/refspec.cc', 'src/remote.cc', 'src/remote_callbacks.cc', 'src/repository.cc', 'src/repository_init_options.cc', 'src/revert.cc', 'src/revert_options.cc', 'src/revparse.cc', 'src/revwalk.cc', 'src/signature.cc', 'src/smart.cc', 'src/stash.cc', 'src/status.cc', 'src/status_list.cc', 'src/strarray.cc', 'src/submodule.cc', 'src/tag.cc', 'src/threads.cc', 'src/time.cc', 'src/trace.cc', 'src/transfer_progress.cc', 'src/transport.cc', 'src/tree.cc', 'src/tree_entry.cc', 'src/treebuilder.cc'], 'include_dirs': ['vendor/libv8-convert', '<!(node -e "require(\'nan\')")'], 'cflags': ['-Wall', '-std=c++11'], 'conditions': [["OS=='mac'", {'xcode_settings': {'GCC_ENABLE_CPP_EXCEPTIONS': 'YES', 'MACOSX_DEPLOYMENT_TARGET': '10.7', 'WARNING_CFLAGS': ['-Wno-unused-variable', '-Wint-conversions', '-Wmissing-field-initializers'], 'OTHER_CPLUSPLUSFLAGS': ['-std=gnu++11', '-stdlib=libc++'], 'OTHER_LDFLAGS': ['-stdlib=libc++']}}]]}]} |
# Text for QML styles
chl_style = """
<!DOCTYPE qgis PUBLIC 'http://mrcc.com/qgis.dtd' 'SYSTEM'>
<qgis version="2.4.0-Chugiak" minimumScale="0" maximumScale="1e+08" hasScaleBasedVisibilityFlag="0">
<pipe>
<rasterrenderer opacity="1" alphaBand="0" classificationMax="1.44451" classificationMinMaxOrigin="CumulativeCutFullExtentEstimated" band="1" classificationMin="0.01504" type="singlebandpseudocolor">
<rasterTransparency/>
<rastershader>
<colorrampshader colorRampType="INTERPOLATED" clip="0">
<item alpha="255" value="0.01504" label="0.015040" color="#0000ff"/>
<item alpha="255" value="0.486765" label="0.486765" color="#02ff00"/>
<item alpha="255" value="0.95849" label="0.958490" color="#fffa00"/>
<item alpha="255" value="1.44451" label="1.444510" color="#ff0000"/>
</colorrampshader>
</rastershader>
</rasterrenderer>
<brightnesscontrast brightness="0" contrast="-6"/>
<huesaturation colorizeGreen="128" colorizeOn="0" colorizeRed="255" colorizeBlue="128" grayscaleMode="0" saturation="0" colorizeStrength="100"/>
<rasterresampler maxOversampling="2"/>
</pipe>
<blendMode>0</blendMode>
</qgis>
"""
sst_style = """
<!DOCTYPE qgis PUBLIC 'http://mrcc.com/qgis.dtd' 'SYSTEM'>
<qgis version="2.4.0-Chugiak" minimumScale="0" maximumScale="1e+08" hasScaleBasedVisibilityFlag="0">
<pipe>
<rasterrenderer opacity="1" alphaBand="-1" classificationMax="29.129" classificationMinMaxOrigin="CumulativeCutFullExtentEstimated" band="1" classificationMin="-1.66383" type="singlebandpseudocolor">
<rasterTransparency/>
<rastershader>
<colorrampshader colorRampType="INTERPOLATED" clip="0">
<item alpha="255" value="-1.66383" label="-1.663830" color="#2c7bb6"/>
<item alpha="255" value="6.03438" label="6.034378" color="#abd9e9"/>
<item alpha="255" value="13.7326" label="13.732585" color="#ffffbf"/>
<item alpha="255" value="21.4308" label="21.430792" color="#fdae61"/>
<item alpha="255" value="29.129" label="29.129000" color="#d7191c"/>
</colorrampshader>
</rastershader>
</rasterrenderer>
<brightnesscontrast brightness="0" contrast="0"/>
<huesaturation colorizeGreen="128" colorizeOn="0" colorizeRed="255" colorizeBlue="128" grayscaleMode="0" saturation="0" colorizeStrength="100"/>
<rasterresampler maxOversampling="2"/>
</pipe>
<blendMode>0</blendMode>
</qgis>
"""
def makeqml(pth, style):
f = open('{}/style.qml'.format(pth), 'w')
f.write(style)
f.close()
return '{}/style.qml'.format(pth)
| chl_style = '\n<!DOCTYPE qgis PUBLIC \'http://mrcc.com/qgis.dtd\' \'SYSTEM\'>\n<qgis version="2.4.0-Chugiak" minimumScale="0" maximumScale="1e+08" hasScaleBasedVisibilityFlag="0">\n <pipe>\n <rasterrenderer opacity="1" alphaBand="0" classificationMax="1.44451" classificationMinMaxOrigin="CumulativeCutFullExtentEstimated" band="1" classificationMin="0.01504" type="singlebandpseudocolor">\n <rasterTransparency/>\n <rastershader>\n <colorrampshader colorRampType="INTERPOLATED" clip="0">\n <item alpha="255" value="0.01504" label="0.015040" color="#0000ff"/>\n <item alpha="255" value="0.486765" label="0.486765" color="#02ff00"/>\n <item alpha="255" value="0.95849" label="0.958490" color="#fffa00"/>\n <item alpha="255" value="1.44451" label="1.444510" color="#ff0000"/>\n </colorrampshader>\n </rastershader>\n </rasterrenderer>\n <brightnesscontrast brightness="0" contrast="-6"/>\n <huesaturation colorizeGreen="128" colorizeOn="0" colorizeRed="255" colorizeBlue="128" grayscaleMode="0" saturation="0" colorizeStrength="100"/>\n <rasterresampler maxOversampling="2"/>\n </pipe>\n <blendMode>0</blendMode>\n</qgis>\n'
sst_style = '\n<!DOCTYPE qgis PUBLIC \'http://mrcc.com/qgis.dtd\' \'SYSTEM\'>\n<qgis version="2.4.0-Chugiak" minimumScale="0" maximumScale="1e+08" hasScaleBasedVisibilityFlag="0">\n <pipe>\n <rasterrenderer opacity="1" alphaBand="-1" classificationMax="29.129" classificationMinMaxOrigin="CumulativeCutFullExtentEstimated" band="1" classificationMin="-1.66383" type="singlebandpseudocolor">\n <rasterTransparency/>\n <rastershader>\n <colorrampshader colorRampType="INTERPOLATED" clip="0">\n <item alpha="255" value="-1.66383" label="-1.663830" color="#2c7bb6"/>\n <item alpha="255" value="6.03438" label="6.034378" color="#abd9e9"/>\n <item alpha="255" value="13.7326" label="13.732585" color="#ffffbf"/>\n <item alpha="255" value="21.4308" label="21.430792" color="#fdae61"/>\n <item alpha="255" value="29.129" label="29.129000" color="#d7191c"/>\n </colorrampshader>\n </rastershader>\n </rasterrenderer>\n <brightnesscontrast brightness="0" contrast="0"/>\n <huesaturation colorizeGreen="128" colorizeOn="0" colorizeRed="255" colorizeBlue="128" grayscaleMode="0" saturation="0" colorizeStrength="100"/>\n <rasterresampler maxOversampling="2"/>\n </pipe>\n <blendMode>0</blendMode>\n</qgis>\n'
def makeqml(pth, style):
f = open('{}/style.qml'.format(pth), 'w')
f.write(style)
f.close()
return '{}/style.qml'.format(pth) |
a = 10
b = 20
c = 300000
| a = 10
b = 20
c = 300000 |
# Definition for a binary tree node.
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
class Solution:
def averageOfLevels(self, root):
"""
:type root: TreeNode
:rtype: List[float]
"""
if not root:
return []
result = []
level = [root]
while level:
new_level = []
total = 0
for node in level:
total += node.val
if node.left:
new_level.append(node.left)
if node.right:
new_level.append(node.right)
result.append(total/len(level))
level = new_level
return result
| class Solution:
def average_of_levels(self, root):
"""
:type root: TreeNode
:rtype: List[float]
"""
if not root:
return []
result = []
level = [root]
while level:
new_level = []
total = 0
for node in level:
total += node.val
if node.left:
new_level.append(node.left)
if node.right:
new_level.append(node.right)
result.append(total / len(level))
level = new_level
return result |
class Solution:
def addBinary(self, a: str, b: str) -> str:
x=int(a,2)
y=int(b,2)
return bin(x+y)[2:]
| class Solution:
def add_binary(self, a: str, b: str) -> str:
x = int(a, 2)
y = int(b, 2)
return bin(x + y)[2:] |
for i in range(int(input())):
n = int(input())
s = input()
a,b = [-1 for j in range(26)],[1e5 for j in range(26)]
for j in range(n):
if(a[ord(s[j])-97]==-1):
a[ord(s[j])-97] = j
else:
if(j-a[ord(s[j])-97]<b[ord(s[j])-97]):
b[ord(s[j])-97] = j-a[ord(s[j])-97]
a[ord(s[j])-97] = j
print(max(n-min(b),0))
| for i in range(int(input())):
n = int(input())
s = input()
(a, b) = ([-1 for j in range(26)], [100000.0 for j in range(26)])
for j in range(n):
if a[ord(s[j]) - 97] == -1:
a[ord(s[j]) - 97] = j
else:
if j - a[ord(s[j]) - 97] < b[ord(s[j]) - 97]:
b[ord(s[j]) - 97] = j - a[ord(s[j]) - 97]
a[ord(s[j]) - 97] = j
print(max(n - min(b), 0)) |
class Solution:
def minDistance(self, word1: str, word2: str) -> int:
edits = [[x for x in range(len(word1) + 1)] for y in range(len(word2) + 1)]
for i in range(1, len(word2) + 1):
edits[i][0] = edits[i - 1][0] + 1
for i in range(1, len(word2) + 1):
for j in range(1, len(word1) + 1):
if word2[i - 1] == word1[j - 1]:
edits[i][j] = edits[i - 1][j - 1]
else:
edits[i][j] = 1 + min(edits[i][j - 1], edits[i - 1][j - 1], edits[i - 1][j])
return edits[-1][-1]
| class Solution:
def min_distance(self, word1: str, word2: str) -> int:
edits = [[x for x in range(len(word1) + 1)] for y in range(len(word2) + 1)]
for i in range(1, len(word2) + 1):
edits[i][0] = edits[i - 1][0] + 1
for i in range(1, len(word2) + 1):
for j in range(1, len(word1) + 1):
if word2[i - 1] == word1[j - 1]:
edits[i][j] = edits[i - 1][j - 1]
else:
edits[i][j] = 1 + min(edits[i][j - 1], edits[i - 1][j - 1], edits[i - 1][j])
return edits[-1][-1] |
ENHANCED_PEER_MOBILIZATION = 'enhanced_peer_mobilization'
CHAMP_CAMEROON = 'champ_client_forms'
TARGET_XMLNS = 'http://openrosa.org/formdesigner/A79467FD-4CDE-47B6-8218-4394699A5C95'
PREVENTION_XMLNS = 'http://openrosa.org/formdesigner/DF2FBEEA-31DE-4537-9913-07D57591502C'
POST_TEST_XMLNS = 'http://openrosa.org/formdesigner/E2B4FD32-9A62-4AE8-AAB0-0CE4B8C28AA1'
ACCOMPAGNEMENT_XMLNS = 'http://openrosa.org/formdesigner/027DEB76-422B-434C-9F53-ECBBE21F890F'
SUIVI_MEDICAL_XMLNS = 'http://openrosa.org/formdesigner/7C8BC256-0E79-4A96-9ECB-D6D8C50CD69E'
| enhanced_peer_mobilization = 'enhanced_peer_mobilization'
champ_cameroon = 'champ_client_forms'
target_xmlns = 'http://openrosa.org/formdesigner/A79467FD-4CDE-47B6-8218-4394699A5C95'
prevention_xmlns = 'http://openrosa.org/formdesigner/DF2FBEEA-31DE-4537-9913-07D57591502C'
post_test_xmlns = 'http://openrosa.org/formdesigner/E2B4FD32-9A62-4AE8-AAB0-0CE4B8C28AA1'
accompagnement_xmlns = 'http://openrosa.org/formdesigner/027DEB76-422B-434C-9F53-ECBBE21F890F'
suivi_medical_xmlns = 'http://openrosa.org/formdesigner/7C8BC256-0E79-4A96-9ECB-D6D8C50CD69E' |
def attack(state, attacking_moves_sequence):
new_state = state.__deepcopy__()
ATTACKING_TERRITORY_INDEX = 0
ENEMY_TERRITORY_INDEX = 1
for attacking_move in attacking_moves_sequence:
print("in attack attacking move",attacking_move)
print("new state map in attack", len(new_state.map))
print("enemy",attacking_move[ENEMY_TERRITORY_INDEX].territory_name)
attacking_territory = new_state.get_territory(attacking_move[ATTACKING_TERRITORY_INDEX])
enemy_territory = new_state.get_territory(attacking_move[ENEMY_TERRITORY_INDEX])
# print("in attack attacking and enemy",attacking_territory, enemy_territory )
# print("in attack ", len(new_state.get_owned_territories(attacking_territory.owner)), attacking_territory.number_of_armies, enemy_territory.number_of_armies)
# print("attacking army before ",attacking_territory.number_of_armies)
# print("enemy army before ",enemy_territory.number_of_armies)
attacking_territory.number_of_armies -= 1
enemy_territory.number_of_armies = 1
if attacking_territory.number_of_armies <= 0 or enemy_territory.number_of_armies <= 0 :
raise(ValueError("Not valid attack move sequence"))
enemy_territory.owner = attacking_territory.owner
print("owner",enemy_territory.owner, attacking_territory.owner)
print("owned territories after attacking",len(new_state.get_owned_territories(attacking_territory.owner)))
return new_state
def reinforce_territory(state, territory, additional_armies):
"""
Used to add reinforcement armies to a territory.
Args:
territory: The territory that will have the reinforcement.
additional_armies: the armies which will be added to the territory.
"""
keys = state.adjacency_list.keys()
for key in keys:
if key.territory_name == territory.territory_name:
key.number_of_armies += additional_armies
return
| def attack(state, attacking_moves_sequence):
new_state = state.__deepcopy__()
attacking_territory_index = 0
enemy_territory_index = 1
for attacking_move in attacking_moves_sequence:
print('in attack attacking move', attacking_move)
print('new state map in attack', len(new_state.map))
print('enemy', attacking_move[ENEMY_TERRITORY_INDEX].territory_name)
attacking_territory = new_state.get_territory(attacking_move[ATTACKING_TERRITORY_INDEX])
enemy_territory = new_state.get_territory(attacking_move[ENEMY_TERRITORY_INDEX])
attacking_territory.number_of_armies -= 1
enemy_territory.number_of_armies = 1
if attacking_territory.number_of_armies <= 0 or enemy_territory.number_of_armies <= 0:
raise value_error('Not valid attack move sequence')
enemy_territory.owner = attacking_territory.owner
print('owner', enemy_territory.owner, attacking_territory.owner)
print('owned territories after attacking', len(new_state.get_owned_territories(attacking_territory.owner)))
return new_state
def reinforce_territory(state, territory, additional_armies):
"""
Used to add reinforcement armies to a territory.
Args:
territory: The territory that will have the reinforcement.
additional_armies: the armies which will be added to the territory.
"""
keys = state.adjacency_list.keys()
for key in keys:
if key.territory_name == territory.territory_name:
key.number_of_armies += additional_armies
return |
# You may need this if you really want to use a recursive solution!
# It raises the cap on how many recursions can happen. Use this at your own risk!
# sys.setrecursionlimit(100000)
def read_lines(filename):
try:
f = open(filename,"r")
lines = f.readlines()
f.close()
filtered_contents = []
for line in lines:
line = line.rstrip("\n")
filtered_contents.append(list(line)) #read lines converted to cells objects in list of lists
return filtered_contents
except FileNotFoundError:
print("{} does not exist!".format(filename))
exit()
def some(grid):
i = 0
while i < len(grid):
k = 0
while k < len(grid[i]):
if (grid[i][k] == "X" ): #Find X
row = int(i)
col = int(k)
return row,col
k += 1
i += 1
def solve(filename):
grid = read_lines(filename)
start_pos = some(grid)
x = start_pos[0]
y = start_pos[1]
ls = ["u","d","r","l"]
pass
# Base Cases
# # if (x,y outside maze) return false
# # if (x,y is goal) return true
# # if (x,y is wall) return false
# # if (x,y is air) return true
def solve(mode):
pass
if __name__ == "__main__":
solution_found = False
if solution_found:
pass
# Print your solution...
else:
print("There is no possible path.")
| def read_lines(filename):
try:
f = open(filename, 'r')
lines = f.readlines()
f.close()
filtered_contents = []
for line in lines:
line = line.rstrip('\n')
filtered_contents.append(list(line))
return filtered_contents
except FileNotFoundError:
print('{} does not exist!'.format(filename))
exit()
def some(grid):
i = 0
while i < len(grid):
k = 0
while k < len(grid[i]):
if grid[i][k] == 'X':
row = int(i)
col = int(k)
return (row, col)
k += 1
i += 1
def solve(filename):
grid = read_lines(filename)
start_pos = some(grid)
x = start_pos[0]
y = start_pos[1]
ls = ['u', 'd', 'r', 'l']
pass
def solve(mode):
pass
if __name__ == '__main__':
solution_found = False
if solution_found:
pass
else:
print('There is no possible path.') |
class MultiFilterCNNModel(object):
def __init__(self, max_sequences, word_index, embed_dim, embedding_matrix, filter_sizes,
num_filters, dropout, learning_rate, beta_1, beta_2, epsilon, n_classes):
sequence_input = Input(shape=(max_sequences,), dtype='int32')
embedding_layer = Embedding(len(word_index)+1, embed_dim, input_length=max_sequences,
weights=[embedding_matrix], trainable=True, mask_zero=False)(sequence_input)
filter_sizes = filter_sizes.split(',')
#embedding_layer_ex = K.expand_dims(embedding_layer, )
#embedding_layer_ex = Reshape()(embedding_layer)
conv_0 = Conv1D(num_filters, int(filter_sizes[0]), padding='valid', kernel_initializer='normal', activation='relu')(embedding_layer)
conv_1 = Conv1D(num_filters, int(filter_sizes[1]), padding='valid', kernel_initializer='normal', activation='relu')(embedding_layer)
conv_2 = Conv1D(num_filters, int(filter_sizes[2]), padding='valid', kernel_initializer='normal', activation='relu')(embedding_layer)
maxpool_0 = MaxPooling1D(pool_size=max_sequences - int(filter_sizes[0]) + 1, strides=1, padding='valid')(conv_0)
maxpool_1 = MaxPooling1D(pool_size=max_sequences - int(filter_sizes[1]) + 1, strides=1, padding='valid')(conv_1)
maxpool_2 = MaxPooling1D(pool_size=max_sequences - int(filter_sizes[2]) + 1, strides=1, padding='valid')(conv_2)
merged_tensor = merge([maxpool_0, maxpool_1, maxpool_2], mode='concat', concat_axis=1)
flatten = Flatten()(merged_tensor)
# average_pooling = AveragePooling2D(pool_size=(sequence_length,1),strides=(1,1),
# border_mode='valid', dim_ordering='tf')(inputs)
#
# reshape = Reshape()(average_pooling)
#reshape = Reshape((3*num_filters,))(merged_tensor)
dropout_layer = Dropout(dropout)(flatten)
softmax_layer = Dense(output_dim=n_classes, activation='softmax')(dropout_layer)
# this creates a model that includes
model = Model(inputs=sequence_input, outputs=softmax_layer)
adam = Adam(lr=learning_rate, beta_1=beta_1, beta_2=beta_2, epsilon=epsilon)
#sgd = optimizers.SGD(lr=0.001, decay=1e-5, momentum=0.9, nesterov=True)
model.compile(optimizer="adam", loss='categorical_crossentropy', metrics=["accuracy"])
self.model = model
| class Multifiltercnnmodel(object):
def __init__(self, max_sequences, word_index, embed_dim, embedding_matrix, filter_sizes, num_filters, dropout, learning_rate, beta_1, beta_2, epsilon, n_classes):
sequence_input = input(shape=(max_sequences,), dtype='int32')
embedding_layer = embedding(len(word_index) + 1, embed_dim, input_length=max_sequences, weights=[embedding_matrix], trainable=True, mask_zero=False)(sequence_input)
filter_sizes = filter_sizes.split(',')
conv_0 = conv1_d(num_filters, int(filter_sizes[0]), padding='valid', kernel_initializer='normal', activation='relu')(embedding_layer)
conv_1 = conv1_d(num_filters, int(filter_sizes[1]), padding='valid', kernel_initializer='normal', activation='relu')(embedding_layer)
conv_2 = conv1_d(num_filters, int(filter_sizes[2]), padding='valid', kernel_initializer='normal', activation='relu')(embedding_layer)
maxpool_0 = max_pooling1_d(pool_size=max_sequences - int(filter_sizes[0]) + 1, strides=1, padding='valid')(conv_0)
maxpool_1 = max_pooling1_d(pool_size=max_sequences - int(filter_sizes[1]) + 1, strides=1, padding='valid')(conv_1)
maxpool_2 = max_pooling1_d(pool_size=max_sequences - int(filter_sizes[2]) + 1, strides=1, padding='valid')(conv_2)
merged_tensor = merge([maxpool_0, maxpool_1, maxpool_2], mode='concat', concat_axis=1)
flatten = flatten()(merged_tensor)
dropout_layer = dropout(dropout)(flatten)
softmax_layer = dense(output_dim=n_classes, activation='softmax')(dropout_layer)
model = model(inputs=sequence_input, outputs=softmax_layer)
adam = adam(lr=learning_rate, beta_1=beta_1, beta_2=beta_2, epsilon=epsilon)
model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
self.model = model |
#!usr/bin/python
# -*- coding: utf-8 -*-
class Database(object):
"""Database class holding information about node/label relationships, mappings from nodes to images and from images to status."""
def __init__(self, root_name="core"):
"""Constuctor for the Database class.
Args:
root_name (str, optional): Name given to the reference abstract category. Defaults to "core".
"""
# Create the graph as a dict naming descendants of each node
self.graph = {root_name: set()}
# Mapping between each node/label and the images referencing it
self.nodes_images = {root_name: set()}
# Dict holding the current status of each image
self.images_status = dict()
def add_nodes(self, nodes):
"""Method to add nodes to the Database graph, given a parent-child relationship.
Args:
nodes (list): List of tuples describing nodes and their parent, to be added to the graph.
"""
for (name, parent) in nodes:
"""Possible improvements here:
- Introduce a hard check that each parent must exist
- Pre-sort the node list for dependencies / find the source(s) node(s) + ordering in a DAG.
e.g. [("core", None), ("A1", "A"), ("A", "core")] wouldn't be an issue.
"""
# Notify the parent node that the granularity has changed
self.notify_granularity(parent)
# Notify sibling nodes (parent's other children) that the coverage has changed
for sibling in self.graph[parent]:
self.notify_coverage(sibling)
# Formally add node to the graph (as itself + child of its parent) and create entry in mapping
self.graph[parent].add(name)
self.graph[name] = set()
self.nodes_images[name] = set()
def add_extract(self, images):
"""Method to add image labeling information in the Database.
Args:
images (dict): Mappings of each image to one or multiple labels/nodes.
"""
for image, nodes in images.items():
# Flag keeping track of whether the current image has referenced only known nodes so far.
valid_nodes = True
"""Nested loop for this reason: we need to update the status of an image if it references an invalid node.
Therefore we need to iterate both on images and nodes.
"""
for node in nodes:
""" From the description, it is not explicit whether invalid references to non-existent nodes should be kept. e.g. if `img003` references node `E` that is not in the graph, should this reference be kept in case node `E` is added later on.
Here we choose not to keep it, however in the opposite case, we can easily move the content of the if-statement outside.
"""
if node in self.graph:
self.nodes_images[node].add(image)
else:
# Report that an invalid reference was found for this image
valid_nodes = False
# Update the image status accordingly
self.images_status[image] = "valid" if valid_nodes else "invalid"
def get_extract_status(self):
"""Retrieve the status associated to each image, which was maintained on the fly as we updated the Database.
Returns:
[dict]: A dictionary of image names and their associated status.
"""
return self.images_status
def notify_granularity(self, node):
"""Helper method allowing to change the status of an image if there was an extension in granularity (only on valid images, no precendence over coverage changes).
Args:
node (string): Name of the node whose status needs an update
"""
for image in self.nodes_images[node]:
if self.images_status[image] == "valid":
self.images_status[image] = "granularity_staged"
def notify_coverage(self, node):
"""Helper method allowing to change the status of an image if there was an extension in coverage (only on valid images or images that have had their granularity changed).
Args:
node (string): Name of the node whose status needs an update
"""
for image in self.nodes_images[node]:
if self.images_status[image] in ["valid", "granularity_staged"]:
self.images_status[image] = "coverage_staged"
| class Database(object):
"""Database class holding information about node/label relationships, mappings from nodes to images and from images to status."""
def __init__(self, root_name='core'):
"""Constuctor for the Database class.
Args:
root_name (str, optional): Name given to the reference abstract category. Defaults to "core".
"""
self.graph = {root_name: set()}
self.nodes_images = {root_name: set()}
self.images_status = dict()
def add_nodes(self, nodes):
"""Method to add nodes to the Database graph, given a parent-child relationship.
Args:
nodes (list): List of tuples describing nodes and their parent, to be added to the graph.
"""
for (name, parent) in nodes:
'Possible improvements here:\n - Introduce a hard check that each parent must exist\n - Pre-sort the node list for dependencies / find the source(s) node(s) + ordering in a DAG.\n e.g. [("core", None), ("A1", "A"), ("A", "core")] wouldn\'t be an issue.\n '
self.notify_granularity(parent)
for sibling in self.graph[parent]:
self.notify_coverage(sibling)
self.graph[parent].add(name)
self.graph[name] = set()
self.nodes_images[name] = set()
def add_extract(self, images):
"""Method to add image labeling information in the Database.
Args:
images (dict): Mappings of each image to one or multiple labels/nodes.
"""
for (image, nodes) in images.items():
valid_nodes = True
'Nested loop for this reason: we need to update the status of an image if it references an invalid node.\n Therefore we need to iterate both on images and nodes.\n '
for node in nodes:
' From the description, it is not explicit whether invalid references to non-existent nodes should be kept. e.g. if `img003` references node `E` that is not in the graph, should this reference be kept in case node `E` is added later on.\n Here we choose not to keep it, however in the opposite case, we can easily move the content of the if-statement outside.\n '
if node in self.graph:
self.nodes_images[node].add(image)
else:
valid_nodes = False
self.images_status[image] = 'valid' if valid_nodes else 'invalid'
def get_extract_status(self):
"""Retrieve the status associated to each image, which was maintained on the fly as we updated the Database.
Returns:
[dict]: A dictionary of image names and their associated status.
"""
return self.images_status
def notify_granularity(self, node):
"""Helper method allowing to change the status of an image if there was an extension in granularity (only on valid images, no precendence over coverage changes).
Args:
node (string): Name of the node whose status needs an update
"""
for image in self.nodes_images[node]:
if self.images_status[image] == 'valid':
self.images_status[image] = 'granularity_staged'
def notify_coverage(self, node):
"""Helper method allowing to change the status of an image if there was an extension in coverage (only on valid images or images that have had their granularity changed).
Args:
node (string): Name of the node whose status needs an update
"""
for image in self.nodes_images[node]:
if self.images_status[image] in ['valid', 'granularity_staged']:
self.images_status[image] = 'coverage_staged' |
norm_cfg = dict(type='BN', requires_grad=True)
model = dict(
type='EncoderDecoder',
pretrained='open-mmlab://resnet50_v1c',
backbone=dict(
type='ResNetV1c',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
dilations=(1, 1, 2, 4),
strides=(1, 2, 1, 1),
norm_cfg=dict(type='BN', requires_grad=True),
norm_eval=False,
style='pytorch',
contract_dilation=True),
decode_head=dict(
type='PSPHead',
in_channels=2048,
in_index=3,
channels=512,
pool_scales=(1, 2, 3, 6),
dropout_ratio=0.1,
num_classes=6,
norm_cfg=dict(type='BN', requires_grad=True),
align_corners=False,
loss_decode=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
auxiliary_head=dict(
type='FCNHead',
in_channels=1024,
in_index=2,
channels=256,
num_convs=1,
concat_input=False,
dropout_ratio=0.1,
num_classes=6,
norm_cfg=dict(type='BN', requires_grad=True),
align_corners=False,
loss_decode=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
train_cfg=dict(),
test_cfg=dict(mode='whole'))
dataset_type = 'CardDataset'
data_root = '../card_dataset'
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
crop_size = (256, 256)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='Resize', img_scale=(500, 500), ratio_range=(0.5, 2.0)),
dict(type='RandomCrop', crop_size=(256, 256), cat_max_ratio=0.75),
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='PhotoMetricDistortion'),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size=(256, 256), pad_val=0, seg_pad_val=255),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img', 'gt_semantic_seg'])
]
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(500, 500),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
]
data = dict(
samples_per_gpu=8,
workers_per_gpu=8,
train=dict(
type='CardDataset',
data_root='../card_dataset',
img_dir='images',
ann_dir='labels',
pipeline=[
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations'),
dict(type='Resize', img_scale=(500, 500), ratio_range=(0.5, 2.0)),
dict(type='RandomCrop', crop_size=(256, 256), cat_max_ratio=0.75),
dict(type='RandomFlip', flip_ratio=0.5),
dict(type='PhotoMetricDistortion'),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='Pad', size=(256, 256), pad_val=0, seg_pad_val=255),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img', 'gt_semantic_seg'])
],
split='splits/train.txt'),
val=dict(
type='CardDataset',
data_root='../card_dataset',
img_dir='images',
ann_dir='labels',
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(500, 500),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
],
split='splits/val.txt'),
test=dict(
type='CardDataset',
data_root='../card_dataset',
img_dir='images',
ann_dir='labels',
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(500, 500),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
to_rgb=True),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
],
split='splits/val.txt'))
log_config = dict(
interval=10, hooks=[dict(type='TextLoggerHook', by_epoch=False)])
dist_params = dict(backend='nccl')
log_level = 'INFO'
load_from = 'checkpoints/pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338-2966598c.pth'
resume_from = None
workflow = [('train', 1)]
cudnn_benchmark = True
optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
# optimizer=dict(
# paramwise_cfg = dict(
# custom_keys={
# 'head': dict(lr_mult=10.)}))
optimizer_config = dict(type='OptimizerHook')
lr_config = dict(policy='poly', power=0.9, min_lr=0.0001, by_epoch=False)
runner = dict(type='IterBasedRunner', max_iters=200)
checkpoint_config = dict(by_epoch=False, interval=200, type='CheckpointHook')
evaluation = dict(interval=200, metric='mIoU', by_epoch=False)
work_dir = './work_dirs/tutorial'
seed = 0
gpu_ids = range(0, 1)
| norm_cfg = dict(type='BN', requires_grad=True)
model = dict(type='EncoderDecoder', pretrained='open-mmlab://resnet50_v1c', backbone=dict(type='ResNetV1c', depth=50, num_stages=4, out_indices=(0, 1, 2, 3), dilations=(1, 1, 2, 4), strides=(1, 2, 1, 1), norm_cfg=dict(type='BN', requires_grad=True), norm_eval=False, style='pytorch', contract_dilation=True), decode_head=dict(type='PSPHead', in_channels=2048, in_index=3, channels=512, pool_scales=(1, 2, 3, 6), dropout_ratio=0.1, num_classes=6, norm_cfg=dict(type='BN', requires_grad=True), align_corners=False, loss_decode=dict(type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)), auxiliary_head=dict(type='FCNHead', in_channels=1024, in_index=2, channels=256, num_convs=1, concat_input=False, dropout_ratio=0.1, num_classes=6, norm_cfg=dict(type='BN', requires_grad=True), align_corners=False, loss_decode=dict(type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)), train_cfg=dict(), test_cfg=dict(mode='whole'))
dataset_type = 'CardDataset'
data_root = '../card_dataset'
img_norm_cfg = dict(mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
crop_size = (256, 256)
train_pipeline = [dict(type='LoadImageFromFile'), dict(type='LoadAnnotations'), dict(type='Resize', img_scale=(500, 500), ratio_range=(0.5, 2.0)), dict(type='RandomCrop', crop_size=(256, 256), cat_max_ratio=0.75), dict(type='RandomFlip', flip_ratio=0.5), dict(type='PhotoMetricDistortion'), dict(type='Normalize', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True), dict(type='Pad', size=(256, 256), pad_val=0, seg_pad_val=255), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gt_semantic_seg'])]
test_pipeline = [dict(type='LoadImageFromFile'), dict(type='MultiScaleFlipAug', img_scale=(500, 500), flip=False, transforms=[dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict(type='Normalize', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True), dict(type='ImageToTensor', keys=['img']), dict(type='Collect', keys=['img'])])]
data = dict(samples_per_gpu=8, workers_per_gpu=8, train=dict(type='CardDataset', data_root='../card_dataset', img_dir='images', ann_dir='labels', pipeline=[dict(type='LoadImageFromFile'), dict(type='LoadAnnotations'), dict(type='Resize', img_scale=(500, 500), ratio_range=(0.5, 2.0)), dict(type='RandomCrop', crop_size=(256, 256), cat_max_ratio=0.75), dict(type='RandomFlip', flip_ratio=0.5), dict(type='PhotoMetricDistortion'), dict(type='Normalize', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True), dict(type='Pad', size=(256, 256), pad_val=0, seg_pad_val=255), dict(type='DefaultFormatBundle'), dict(type='Collect', keys=['img', 'gt_semantic_seg'])], split='splits/train.txt'), val=dict(type='CardDataset', data_root='../card_dataset', img_dir='images', ann_dir='labels', pipeline=[dict(type='LoadImageFromFile'), dict(type='MultiScaleFlipAug', img_scale=(500, 500), flip=False, transforms=[dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict(type='Normalize', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True), dict(type='ImageToTensor', keys=['img']), dict(type='Collect', keys=['img'])])], split='splits/val.txt'), test=dict(type='CardDataset', data_root='../card_dataset', img_dir='images', ann_dir='labels', pipeline=[dict(type='LoadImageFromFile'), dict(type='MultiScaleFlipAug', img_scale=(500, 500), flip=False, transforms=[dict(type='Resize', keep_ratio=True), dict(type='RandomFlip'), dict(type='Normalize', mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True), dict(type='ImageToTensor', keys=['img']), dict(type='Collect', keys=['img'])])], split='splits/val.txt'))
log_config = dict(interval=10, hooks=[dict(type='TextLoggerHook', by_epoch=False)])
dist_params = dict(backend='nccl')
log_level = 'INFO'
load_from = 'checkpoints/pspnet_r50-d8_512x1024_40k_cityscapes_20200605_003338-2966598c.pth'
resume_from = None
workflow = [('train', 1)]
cudnn_benchmark = True
optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
optimizer_config = dict(type='OptimizerHook')
lr_config = dict(policy='poly', power=0.9, min_lr=0.0001, by_epoch=False)
runner = dict(type='IterBasedRunner', max_iters=200)
checkpoint_config = dict(by_epoch=False, interval=200, type='CheckpointHook')
evaluation = dict(interval=200, metric='mIoU', by_epoch=False)
work_dir = './work_dirs/tutorial'
seed = 0
gpu_ids = range(0, 1) |
class Solution:
def longestAwesome(self, s: str) -> int:
table = {0 : -1}
mask = maxLen = 0
for i, c in enumerate(s):
mask ^= (1 << int(c))
for j in range(10):
mask2 = mask ^ (1 << j)
if mask2 in table:
maxLen = max(maxLen, i - table[mask2])
if mask in table:
maxLen = max(maxLen, i - table[mask])
else:
table[mask] = i
return maxLen
| class Solution:
def longest_awesome(self, s: str) -> int:
table = {0: -1}
mask = max_len = 0
for (i, c) in enumerate(s):
mask ^= 1 << int(c)
for j in range(10):
mask2 = mask ^ 1 << j
if mask2 in table:
max_len = max(maxLen, i - table[mask2])
if mask in table:
max_len = max(maxLen, i - table[mask])
else:
table[mask] = i
return maxLen |
# This is what gets created by TextField.as_tensor with a SingleIdTokenIndexer
# and a TokenCharactersIndexer; see the code snippet above. This time we're using
# more intuitive names for the indexers and embedders.
token_tensor = {
'tokens': {'tokens': torch.LongTensor([[2, 4, 3, 5]])},
'token_characters': {'token_characters': torch.LongTensor(
[[[2, 5, 3], [4, 0, 0], [2, 1, 4], [5, 4, 0]]])}
}
# This is for embedding each token.
embedding = Embedding(num_embeddings=6, embedding_dim=3)
# This is for encoding the characters in each token.
character_embedding = Embedding(num_embeddings=6, embedding_dim=3)
cnn_encoder = CnnEncoder(embedding_dim=3, num_filters=4, ngram_filter_sizes=[3])
token_encoder = TokenCharactersEncoder(character_embedding, cnn_encoder)
embedder = BasicTextFieldEmbedder(
token_embedders={'tokens': embedding, 'token_characters': token_encoder})
embedded_tokens = embedder(token_tensor)
print(embedded_tokens)
# This is what gets created by TextField.as_tensor with a SingleIdTokenIndexer,
# a TokenCharactersIndexer, and another SingleIdTokenIndexer for PoS tags;
# see the code above.
token_tensor = {
'tokens': {'tokens': torch.LongTensor([[2, 4, 3, 5]])},
'token_characters': {'token_characters': torch.LongTensor(
[[[2, 5, 3], [4, 0, 0], [2, 1, 4], [5, 4, 0]]])},
'pos_tag_tokens': {'tokens': torch.tensor([[2, 5, 3, 4]])}
}
vocab = Vocabulary()
vocab.add_tokens_to_namespace(
['This', 'is', 'some', 'text', '.'],
namespace='token_vocab')
vocab.add_tokens_to_namespace(
['T', 'h', 'i', 's', ' ', 'o', 'm', 'e', 't', 'x', '.'],
namespace='character_vocab')
vocab.add_tokens_to_namespace(
['DT', 'VBZ', 'NN', '.'],
namespace='pos_tag_vocab')
# Notice below how the 'vocab_namespace' parameter matches the name used above.
# We're showing here how the code works when we're constructing the Embedding from
# a configuration file, where the vocabulary object gets passed in behind the
# scenes (but the vocab_namespace parameter must be set in the config). If you are
# using a `build_model` method (see the quick start chapter) or instantiating the
# Embedding yourself directly, you can just grab the vocab size yourself and pass
# in num_embeddings, as we do above.
# This is for embedding each token.
embedding = Embedding(embedding_dim=3, vocab_namespace='token_vocab', vocab=vocab)
# This is for encoding the characters in each token.
character_embedding = Embedding(embedding_dim=4,
vocab_namespace='character_vocab',
vocab=vocab)
cnn_encoder = CnnEncoder(embedding_dim=4, num_filters=5, ngram_filter_sizes=[3])
token_encoder = TokenCharactersEncoder(character_embedding, cnn_encoder)
# This is for embedding the part of speech tag of each token.
pos_tag_embedding = Embedding(embedding_dim=6,
vocab_namespace='pos_tag_vocab',
vocab=vocab)
# Notice how these keys match the keys in the token_tensor dictionary above;
# these are the keys that you give to your TokenIndexers when constructing
# your TextFields in the DatasetReader.
embedder = BasicTextFieldEmbedder(
token_embedders={'tokens': embedding,
'token_characters': token_encoder,
'pos_tag_tokens': pos_tag_embedding})
embedded_tokens = embedder(token_tensor)
print(embedded_tokens)
| token_tensor = {'tokens': {'tokens': torch.LongTensor([[2, 4, 3, 5]])}, 'token_characters': {'token_characters': torch.LongTensor([[[2, 5, 3], [4, 0, 0], [2, 1, 4], [5, 4, 0]]])}}
embedding = embedding(num_embeddings=6, embedding_dim=3)
character_embedding = embedding(num_embeddings=6, embedding_dim=3)
cnn_encoder = cnn_encoder(embedding_dim=3, num_filters=4, ngram_filter_sizes=[3])
token_encoder = token_characters_encoder(character_embedding, cnn_encoder)
embedder = basic_text_field_embedder(token_embedders={'tokens': embedding, 'token_characters': token_encoder})
embedded_tokens = embedder(token_tensor)
print(embedded_tokens)
token_tensor = {'tokens': {'tokens': torch.LongTensor([[2, 4, 3, 5]])}, 'token_characters': {'token_characters': torch.LongTensor([[[2, 5, 3], [4, 0, 0], [2, 1, 4], [5, 4, 0]]])}, 'pos_tag_tokens': {'tokens': torch.tensor([[2, 5, 3, 4]])}}
vocab = vocabulary()
vocab.add_tokens_to_namespace(['This', 'is', 'some', 'text', '.'], namespace='token_vocab')
vocab.add_tokens_to_namespace(['T', 'h', 'i', 's', ' ', 'o', 'm', 'e', 't', 'x', '.'], namespace='character_vocab')
vocab.add_tokens_to_namespace(['DT', 'VBZ', 'NN', '.'], namespace='pos_tag_vocab')
embedding = embedding(embedding_dim=3, vocab_namespace='token_vocab', vocab=vocab)
character_embedding = embedding(embedding_dim=4, vocab_namespace='character_vocab', vocab=vocab)
cnn_encoder = cnn_encoder(embedding_dim=4, num_filters=5, ngram_filter_sizes=[3])
token_encoder = token_characters_encoder(character_embedding, cnn_encoder)
pos_tag_embedding = embedding(embedding_dim=6, vocab_namespace='pos_tag_vocab', vocab=vocab)
embedder = basic_text_field_embedder(token_embedders={'tokens': embedding, 'token_characters': token_encoder, 'pos_tag_tokens': pos_tag_embedding})
embedded_tokens = embedder(token_tensor)
print(embedded_tokens) |
{
"targets": [
{
"target_name": "decompressor",
"sources": ["decompressor.cpp"]
},
{
"target_name": "pow_solver",
"sources": ["pow_solver.cpp"]
}
]
}
| {'targets': [{'target_name': 'decompressor', 'sources': ['decompressor.cpp']}, {'target_name': 'pow_solver', 'sources': ['pow_solver.cpp']}]} |
class C4FileIO():
red_wins = 0
blue_wins = 0
def __init__(self):
try:
f = open("c4wins.txt", "r")
lines = f.readlines()
f.close()
if type(lines) == list:
self.deserialize_file(lines)
except FileNotFoundError:
print("File not found, writing new file.")
def deserialize_file(self, lines):
for line in lines:
line = line.strip("\n")
w = line.split(",")
if w[0] == "red_wins":
self.red_wins = int(w[1])
elif w[0] == "blue_wins":
self.blue_wins = int(w[1])
def serialize_file(self):
f = open("c4wins.txt", "w")
f_str = ""
f_str += "red_wins," + str(self.red_wins) + " \n"
f_str += "blue_wins," + str(self.blue_wins) + " \n"
print(f_str)
f.write(f_str)
f.close()
| class C4Fileio:
red_wins = 0
blue_wins = 0
def __init__(self):
try:
f = open('c4wins.txt', 'r')
lines = f.readlines()
f.close()
if type(lines) == list:
self.deserialize_file(lines)
except FileNotFoundError:
print('File not found, writing new file.')
def deserialize_file(self, lines):
for line in lines:
line = line.strip('\n')
w = line.split(',')
if w[0] == 'red_wins':
self.red_wins = int(w[1])
elif w[0] == 'blue_wins':
self.blue_wins = int(w[1])
def serialize_file(self):
f = open('c4wins.txt', 'w')
f_str = ''
f_str += 'red_wins,' + str(self.red_wins) + ' \n'
f_str += 'blue_wins,' + str(self.blue_wins) + ' \n'
print(f_str)
f.write(f_str)
f.close() |
# Copyright (c) 2020 Digital Asset (Switzerland) GmbH and/or its affiliates. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
load("//bazel_tools:haskell.bzl", "da_haskell_test")
load("//bazel_tools/sh:sh.bzl", "sh_inline_test")
def damlc_compile_test(
name,
srcs,
main,
damlc = "//compiler/damlc",
stack_limit = "",
heap_limit = "",
**kwargs):
stack_opt = "-K" + stack_limit if stack_limit else ""
heap_opt = "-M" + heap_limit if heap_limit else ""
sh_inline_test(
name = name,
data = [damlc, main] + srcs,
cmd = """\
DAMLC=$$(canonicalize_rlocation $(rootpath {damlc}))
MAIN=$$(canonicalize_rlocation $(rootpath {main}))
TMP=$$(mktemp -d)
function cleanup() {{
rm -rf "$$TMP"
}}
trap cleanup EXIT
$$DAMLC compile $$MAIN -o $$TMP/out +RTS -s {stack_opt} {heap_opt}
""".format(
damlc = damlc,
main = main,
stack_opt = stack_opt,
heap_opt = heap_opt,
),
**kwargs
)
| load('//bazel_tools:haskell.bzl', 'da_haskell_test')
load('//bazel_tools/sh:sh.bzl', 'sh_inline_test')
def damlc_compile_test(name, srcs, main, damlc='//compiler/damlc', stack_limit='', heap_limit='', **kwargs):
stack_opt = '-K' + stack_limit if stack_limit else ''
heap_opt = '-M' + heap_limit if heap_limit else ''
sh_inline_test(name=name, data=[damlc, main] + srcs, cmd='DAMLC=$$(canonicalize_rlocation $(rootpath {damlc}))\nMAIN=$$(canonicalize_rlocation $(rootpath {main}))\n\nTMP=$$(mktemp -d)\nfunction cleanup() {{\n rm -rf "$$TMP"\n}}\ntrap cleanup EXIT\n\n$$DAMLC compile $$MAIN -o $$TMP/out +RTS -s {stack_opt} {heap_opt}\n'.format(damlc=damlc, main=main, stack_opt=stack_opt, heap_opt=heap_opt), **kwargs) |
class InfiniteLineup:
def __init__(self, players):
self.players = players
def lineup(self):
lineup_max = len(self.players)
idx = 0
while True:
if idx < lineup_max:
yield self.players[idx]
else:
idx = 0
yield self.players[idx]
idx += 1
def __repr__(self):
return f'<InfiniteLineup({self.players})'
def __str__(self):
return f'InfiniteLineup with the players: {self.players}'
astros = [
'Springer',
'Bregman',
'Altuve',
'Correa',
'Reddick',
'Gonzalez',
'McCann',
'Davis',
'Tucker'
]
full_lineup = InfiniteLineup(astros)
astros_lineup = full_lineup.lineup()
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
| class Infinitelineup:
def __init__(self, players):
self.players = players
def lineup(self):
lineup_max = len(self.players)
idx = 0
while True:
if idx < lineup_max:
yield self.players[idx]
else:
idx = 0
yield self.players[idx]
idx += 1
def __repr__(self):
return f'<InfiniteLineup({self.players})'
def __str__(self):
return f'InfiniteLineup with the players: {self.players}'
astros = ['Springer', 'Bregman', 'Altuve', 'Correa', 'Reddick', 'Gonzalez', 'McCann', 'Davis', 'Tucker']
full_lineup = infinite_lineup(astros)
astros_lineup = full_lineup.lineup()
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup))
print(next(astros_lineup)) |
class StoreObject:
def _log_template(self, token):
return f"<{token.server.upper()} {token.method}: {' '.join([str(token.params[k]) for k in token.params])}>"
async def get(self, token, *args, **kwargs):
raise NotImplementedError
async def set(self, token, response, *args, **kwargs):
raise NotImplementedError
async def post(self, token, body, *args, **kwargs):
raise NotImplementedError
async def put(self, token, body, *args, **kwargs):
raise NotImplementedError
async def clear(self, *args, **kwargs):
raise NotImplementedError
async def expire(self, *args, **kwargs):
raise NotImplementedError
async def delete(self, token, *args, **kwargs):
raise NotImplementedError
async def contains(self, token, *args, **kwargs):
raise NotImplementedError
@property
def classname(self):
return self.__class__.__name__
| class Storeobject:
def _log_template(self, token):
return f"<{token.server.upper()} {token.method}: {' '.join([str(token.params[k]) for k in token.params])}>"
async def get(self, token, *args, **kwargs):
raise NotImplementedError
async def set(self, token, response, *args, **kwargs):
raise NotImplementedError
async def post(self, token, body, *args, **kwargs):
raise NotImplementedError
async def put(self, token, body, *args, **kwargs):
raise NotImplementedError
async def clear(self, *args, **kwargs):
raise NotImplementedError
async def expire(self, *args, **kwargs):
raise NotImplementedError
async def delete(self, token, *args, **kwargs):
raise NotImplementedError
async def contains(self, token, *args, **kwargs):
raise NotImplementedError
@property
def classname(self):
return self.__class__.__name__ |
# ------------------------------
# 674. Longest Continuous Increasing Subsequence
#
# Description:
# Given an unsorted array of integers, find the length of longest continuous increasing subsequence (subarray).
# Example 1:
# Input: [1,3,5,4,7]
# Output: 3
# Explanation: The longest continuous increasing subsequence is [1,3,5], its length is 3.
# Even though [1,3,5,7] is also an increasing subsequence, it's not a continuous one where 5 and 7 are separated by 4.
#
# Example 2:
# Input: [2,2,2,2,2]
# Output: 1
# Explanation: The longest continuous increasing subsequence is [2], its length is 1.
#
# Note: Length of the array will not exceed 10,000.
# Version: 1.0
# 08/03/18 by Jianfa
# ------------------------------
class Solution(object):
def findLengthOfLCIS(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
maxlen = 1
curlen = 1
if len(nums) == 0 or len(nums) == 1:
return len(nums)
for i in range(len(nums) - 1):
if nums[i] < nums[i+1]:
curlen += 1
else:
maxlen = max(maxlen, curlen)
curlen = 1
maxlen = max(maxlen, curlen)
return maxlen
# Used for testing
if __name__ == "__main__":
test = Solution()
# ------------------------------
# Summary:
# | class Solution(object):
def find_length_of_lcis(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
maxlen = 1
curlen = 1
if len(nums) == 0 or len(nums) == 1:
return len(nums)
for i in range(len(nums) - 1):
if nums[i] < nums[i + 1]:
curlen += 1
else:
maxlen = max(maxlen, curlen)
curlen = 1
maxlen = max(maxlen, curlen)
return maxlen
if __name__ == '__main__':
test = solution() |
"""
Design and implement a data structure for Least Recently Used (LRU) cache. It
should support the following operations: get and set.
get(key) - Get the value (will always be positive) of the key if the key
exists in the cache, otherwise return -1.
set(key, value) - Set or insert the value if the key is not already present.
When the cache reached its capacity, it should invalidate the least recently
used item before inserting a new item.
TLE
"""
class LRUCache:
# @param capacity, an integer
def __init__(self, capacity):
self.capacity = capacity
self.times = {}
self.cache = {}
self.timestamp = 0
# @return an integer
def get(self, key):
self.timestamp += 1
if key in self.cache:
self.times[key] = self.timestamp
return self.cache[key]
return -1
# @param key, an integer
# @param value, an integer
# @return nothing
def set(self, key, value):
self.timestamp += 1
if key in self.cache:
self.times[key] = self.timestamp
else:
if len(self.cache) >= self.capacity:
lru_key = self.get_lru_key()
del self.cache[lru_key]
del self.times[lru_key]
self.cache[key] = value
self.times[key] = self.timestamp
def get_lru_key(self):
min_time = self.timestamp
res = None
for key in self.times:
if self.times[key] <= min_time:
res = key
min_time = self.times[key]
return res
| """
Design and implement a data structure for Least Recently Used (LRU) cache. It
should support the following operations: get and set.
get(key) - Get the value (will always be positive) of the key if the key
exists in the cache, otherwise return -1.
set(key, value) - Set or insert the value if the key is not already present.
When the cache reached its capacity, it should invalidate the least recently
used item before inserting a new item.
TLE
"""
class Lrucache:
def __init__(self, capacity):
self.capacity = capacity
self.times = {}
self.cache = {}
self.timestamp = 0
def get(self, key):
self.timestamp += 1
if key in self.cache:
self.times[key] = self.timestamp
return self.cache[key]
return -1
def set(self, key, value):
self.timestamp += 1
if key in self.cache:
self.times[key] = self.timestamp
else:
if len(self.cache) >= self.capacity:
lru_key = self.get_lru_key()
del self.cache[lru_key]
del self.times[lru_key]
self.cache[key] = value
self.times[key] = self.timestamp
def get_lru_key(self):
min_time = self.timestamp
res = None
for key in self.times:
if self.times[key] <= min_time:
res = key
min_time = self.times[key]
return res |
"""grating_coupler_meep - grating coupler meep"""
__version__ = "0.0.1"
__author__ = "Simon Bilodeau <<46427609+simbilod@users.noreply.github.com>>"
__all__ = []
| """grating_coupler_meep - grating coupler meep"""
__version__ = '0.0.1'
__author__ = 'Simon Bilodeau <<46427609+simbilod@users.noreply.github.com>>'
__all__ = [] |
class SIR:
def __init__(self, susceptible, infected, removed, region_id=None):
self.region_id = region_id
self.susceptible = susceptible
self.infected = infected
self.removed = removed
self.total_pop = susceptible + infected + removed
def copy(self):
return SIR(self.susceptible, self.infected, self.removed)
def __str__(self):
return "SIR(S={susceptible}, I={infected}, R={removed})".format(
susceptible=self.susceptible,
infected=self.infected,
removed=self.removed
)
# defines self == other
def __eq__(self, other):
return isinstance(other, SIR) and (
self.susceptible == other.susceptible,
self.infected == other.infected,
self.removed == other.removed
)
# defines self += other
def __iadd__(self, other):
if isinstance(other, SIR):
self.susceptible += other.susceptible
self.infected += other.infected
self.removed += other.removed
self.total_pop += other.total_pop
return self
elif other == 0:
return self
else:
return NotImplemented
# defines new = self + other
def __add__(self, other):
if isinstance(other, SIR):
new = self.copy()
return SIR.__iadd__(new, other)
elif other == 0:
return self.copy()
else:
return NotImplemented
# defines new = other + self
def __radd__(self, other):
if isinstance(other, SIR):
return SIR.__add__(self, other)
elif other == 0:
return self.copy()
else:
return NotImplemented
def replace(self, sir):
self.susceptible = sir.susceptible
self.infected = sir.infected
self.removed = sir.removed
self.total_pop = self.susceptible + self.infected + self.removed
def inc_infected(self, infected):
self.susceptible -= infected
self.infected += infected
def inc_removed(self, removed):
self.infected -= removed
self.removed += removed
def as_tuple(self, total=False):
if total:
return (
self.susceptible, self.infected,
self.removed, self.total_pop
)
else:
return (self.susceptible, self.infected, self.removed)
def transfer_to(self, add_s, add_i, add_r):
""" transfers people to sir object
Parameters
----------
add_s (Int) : wanted increase of susceptible
add_i (Int) : wanted increase of infected
add_r (Int) : wanted increase of removed
Returns
-------
None : Mutates the SIR object
"""
self.susceptible += add_s
self.infected += add_i
self.removed += add_r
self.total_pop += add_s + add_i + add_r
if self.total_pop < 0:
raise Exception("total population < 0 after transferring to region")
def transfer_from(self, rem_s, rem_i, rem_r):
""" transfers people to sir object
Parameters
----------
rem_s (Int) : wanted removal of susceptible
rem_i (Int) : wanted removal of infected
rem_r (Int) : wanted removal of removed
Returns
-------
None : Mutates the SIR object
"""
self.susceptible -= rem_s
self.infected -= rem_i
self.removed -= rem_r
self.total_pop -= rem_s + rem_i + rem_r
if self.total_pop < 0:
raise Exception("total population < 0 after transferring from region")
| class Sir:
def __init__(self, susceptible, infected, removed, region_id=None):
self.region_id = region_id
self.susceptible = susceptible
self.infected = infected
self.removed = removed
self.total_pop = susceptible + infected + removed
def copy(self):
return sir(self.susceptible, self.infected, self.removed)
def __str__(self):
return 'SIR(S={susceptible}, I={infected}, R={removed})'.format(susceptible=self.susceptible, infected=self.infected, removed=self.removed)
def __eq__(self, other):
return isinstance(other, SIR) and (self.susceptible == other.susceptible, self.infected == other.infected, self.removed == other.removed)
def __iadd__(self, other):
if isinstance(other, SIR):
self.susceptible += other.susceptible
self.infected += other.infected
self.removed += other.removed
self.total_pop += other.total_pop
return self
elif other == 0:
return self
else:
return NotImplemented
def __add__(self, other):
if isinstance(other, SIR):
new = self.copy()
return SIR.__iadd__(new, other)
elif other == 0:
return self.copy()
else:
return NotImplemented
def __radd__(self, other):
if isinstance(other, SIR):
return SIR.__add__(self, other)
elif other == 0:
return self.copy()
else:
return NotImplemented
def replace(self, sir):
self.susceptible = sir.susceptible
self.infected = sir.infected
self.removed = sir.removed
self.total_pop = self.susceptible + self.infected + self.removed
def inc_infected(self, infected):
self.susceptible -= infected
self.infected += infected
def inc_removed(self, removed):
self.infected -= removed
self.removed += removed
def as_tuple(self, total=False):
if total:
return (self.susceptible, self.infected, self.removed, self.total_pop)
else:
return (self.susceptible, self.infected, self.removed)
def transfer_to(self, add_s, add_i, add_r):
""" transfers people to sir object
Parameters
----------
add_s (Int) : wanted increase of susceptible
add_i (Int) : wanted increase of infected
add_r (Int) : wanted increase of removed
Returns
-------
None : Mutates the SIR object
"""
self.susceptible += add_s
self.infected += add_i
self.removed += add_r
self.total_pop += add_s + add_i + add_r
if self.total_pop < 0:
raise exception('total population < 0 after transferring to region')
def transfer_from(self, rem_s, rem_i, rem_r):
""" transfers people to sir object
Parameters
----------
rem_s (Int) : wanted removal of susceptible
rem_i (Int) : wanted removal of infected
rem_r (Int) : wanted removal of removed
Returns
-------
None : Mutates the SIR object
"""
self.susceptible -= rem_s
self.infected -= rem_i
self.removed -= rem_r
self.total_pop -= rem_s + rem_i + rem_r
if self.total_pop < 0:
raise exception('total population < 0 after transferring from region') |
a = 10
b = 22
while b - a > 4:
c = b - (2 * a)
if c > 0:
d = c + 1
else:
d = c + 5
a = a + 3
b = b - 2
| a = 10
b = 22
while b - a > 4:
c = b - 2 * a
if c > 0:
d = c + 1
else:
d = c + 5
a = a + 3
b = b - 2 |
_html = """<HTML><HEAD><?HEAD><BODY>{}</BODY><?HTML>"""
def index_page():
content = """This is a simple api for exploring the <a href="http://www.geonames.org">geonames</a> <a href="http://download.geonames.org/export/dump">data</a>, specificially the cities1000 data, which is cities with population of greater than or equal to 1000 people.
<p>
The api is rooted at /cities endpoints include:
<ul>
<li>/cities/<geonameid></li>
<li>/cities/<geonameid>/nearest/<k></li>
<li>/cities?name=<name to search for></li>
<li>/cities?partial_name=<name fragment to search for></li>
</ul>
</p>
<p>Here are some examples to get you started:
<ul>
<li><a href="/cities/5391959">/cities/5391959</a> will take you to the local entry to San Francisco, CA, USA</li>
<li><a href="/cities/5391959/nearest/3">/cities/5391959/nearest/3</a> will return a list of the three cities closest to San Francisco. Note, this will include San Francisco as the closest location to itself.</li>
<li><a href="/cities?name=Oakland">/citie?name=Oakland</a> will produce a list of cities named Oakland</li>
</ul>
</p>
"""
return _html.format(content)
def _city_desc(city, link_to_city_page=True):
link_content = """
<ul>
<li><em>Name</em>: {name}</li>
<li><em>geonameid</em>: <a href="/cities/{geonameid}">{geonameid}</a></li>
<li><em>Latitude</em>: {latitude}</li>
<li><em>Longitude</em>: {longitude}</li>
</ul>"""
nolink_content = """
<ul>
<li><em>Name</em>: {name}</li>
<li><em>geonameid</em>: {geonameid}</li>
<li><em>Latitude</em>: {latitude}</li>
<li><em>Longitude</em>: {longitude}</li>
</ul>"""
if link_to_city_page:
return link_content.format(**city)
else:
return nolink_content.format(**city)
def city_desc_page(city):
return _html.format(_city_desc(city, False))
def city_list_page(cities):
content = """<ol><li>{}</li></ol>"""
tmp = "</li><li>".join([_city_desc(cc) for cc in cities])
return _html.format(content.format(tmp))
def distances_page(distances):
content = """<ol><li>{}</li></ol>"""
_deet = """<ul>
<li><em>Distance:</em> {dist}</li>
<li><em>geonameid:</em> <a href="/cities/{geonameid}">{geonameid}</a></li>
</ul>"""
tmp = "</li><li>".join([_deet.format(**dc) for dc in distances])
return _html.format(content.format(tmp))
| _html = '<HTML><HEAD><?HEAD><BODY>{}</BODY><?HTML>'
def index_page():
content = 'This is a simple api for exploring the <a href="http://www.geonames.org">geonames</a> <a href="http://download.geonames.org/export/dump">data</a>, specificially the cities1000 data, which is cities with population of greater than or equal to 1000 people.\n\n<p>\nThe api is rooted at /cities endpoints include:\n<ul>\n <li>/cities/<geonameid></li>\n <li>/cities/<geonameid>/nearest/<k></li>\n <li>/cities?name=<name to search for></li>\n <li>/cities?partial_name=<name fragment to search for></li>\n</ul>\n</p>\n<p>Here are some examples to get you started:\n<ul>\n <li><a href="/cities/5391959">/cities/5391959</a> will take you to the local entry to San Francisco, CA, USA</li>\n <li><a href="/cities/5391959/nearest/3">/cities/5391959/nearest/3</a> will return a list of the three cities closest to San Francisco. Note, this will include San Francisco as the closest location to itself.</li>\n <li><a href="/cities?name=Oakland">/citie?name=Oakland</a> will produce a list of cities named Oakland</li>\n</ul>\n</p>\n\n'
return _html.format(content)
def _city_desc(city, link_to_city_page=True):
link_content = '\n<ul>\n <li><em>Name</em>: {name}</li>\n <li><em>geonameid</em>: <a href="/cities/{geonameid}">{geonameid}</a></li>\n <li><em>Latitude</em>: {latitude}</li>\n <li><em>Longitude</em>: {longitude}</li>\n</ul>'
nolink_content = '\n<ul>\n <li><em>Name</em>: {name}</li>\n <li><em>geonameid</em>: {geonameid}</li>\n <li><em>Latitude</em>: {latitude}</li>\n <li><em>Longitude</em>: {longitude}</li>\n</ul>'
if link_to_city_page:
return link_content.format(**city)
else:
return nolink_content.format(**city)
def city_desc_page(city):
return _html.format(_city_desc(city, False))
def city_list_page(cities):
content = '<ol><li>{}</li></ol>'
tmp = '</li><li>'.join([_city_desc(cc) for cc in cities])
return _html.format(content.format(tmp))
def distances_page(distances):
content = '<ol><li>{}</li></ol>'
_deet = '<ul>\n<li><em>Distance:</em> {dist}</li>\n<li><em>geonameid:</em> <a href="/cities/{geonameid}">{geonameid}</a></li>\n</ul>'
tmp = '</li><li>'.join([_deet.format(**dc) for dc in distances])
return _html.format(content.format(tmp)) |
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