index
int64 0
731k
| package
stringlengths 2
98
⌀ | name
stringlengths 1
76
| docstring
stringlengths 0
281k
⌀ | code
stringlengths 4
8.19k
| signature
stringlengths 2
42.8k
⌀ | embed_func_code
listlengths 768
768
|
|---|---|---|---|---|---|---|
24,384 | py3rijndael.rijndael | __init__ | null | def __init__(self, key, block_size: int = 16):
if block_size not in (16, 24, 32):
raise ValueError('Invalid block size: %s' % str(block_size))
if len(key) not in (16, 24, 32):
raise ValueError('Invalid key size: %s' % str(len(key)))
self.block_size = block_size
self.key = key
rounds = num_rounds[len(key)][block_size]
b_c = block_size // 4
# encryption round keys
k_e = [[0] * b_c for _ in range(rounds + 1)]
# decryption round keys
k_d = [[0] * b_c for _ in range(rounds + 1)]
round_key_count = (rounds + 1) * b_c
k_c = len(key) // 4
# copy user material bytes into temporary ints
tk = []
for i in range(0, k_c):
tk.append((ord(key[i * 4:i * 4 + 1]) << 24) | (ord(key[i * 4 + 1:i * 4 + 1 + 1]) << 16) |
(ord(key[i * 4 + 2: i * 4 + 2 + 1]) << 8) | ord(key[i * 4 + 3:i * 4 + 3 + 1]))
# copy values into round key arrays
t = 0
j = 0
while j < k_c and t < round_key_count:
k_e[t // b_c][t % b_c] = tk[j]
k_d[rounds - (t // b_c)][t % b_c] = tk[j]
j += 1
t += 1
r_con_pointer = 0
while t < round_key_count:
# extrapolate using phi (the round key evolution function)
tt = tk[k_c - 1]
tk[0] ^= (S[(tt >> 16) & 0xFF] & 0xFF) << 24 ^ \
(S[(tt >> 8) & 0xFF] & 0xFF) << 16 ^ \
(S[tt & 0xFF] & 0xFF) << 8 ^ \
(S[(tt >> 24) & 0xFF] & 0xFF) ^ \
(r_con[r_con_pointer] & 0xFF) << 24
r_con_pointer += 1
if k_c != 8:
for i in range(1, k_c):
tk[i] ^= tk[i - 1]
else:
for i in range(1, k_c // 2):
tk[i] ^= tk[i - 1]
tt = tk[k_c // 2 - 1]
tk[k_c // 2] ^= (S[tt & 0xFF] & 0xFF) ^ \
(S[(tt >> 8) & 0xFF] & 0xFF) << 8 ^ \
(S[(tt >> 16) & 0xFF] & 0xFF) << 16 ^ \
(S[(tt >> 24) & 0xFF] & 0xFF) << 24
for i in range(k_c // 2 + 1, k_c):
tk[i] ^= tk[i - 1]
# copy values into round key arrays
j = 0
while j < k_c and t < round_key_count:
k_e[t // b_c][t % b_c] = tk[j]
k_d[rounds - (t // b_c)][t % b_c] = tk[j]
j += 1
t += 1
# inverse MixColumn where needed
for r in range(1, rounds):
for j in range(b_c):
tt = k_d[r][j]
k_d[r][j] = (
U1[(tt >> 24) & 0xFF] ^
U2[(tt >> 16) & 0xFF] ^
U3[(tt >> 8) & 0xFF] ^
U4[tt & 0xFF]
)
self.Ke = k_e
self.Kd = k_d
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24,385 | py3rijndael.rijndael | decrypt | null | def decrypt(self, cipher):
if len(cipher) != self.block_size:
raise ValueError(
'wrong block length, expected %s got %s' % (
str(self.block_size),
str(len(cipher))
)
)
k_d = self.Kd
b_c = self.block_size // 4
rounds = len(k_d) - 1
if b_c == 4:
s_c = 0
elif b_c == 6:
s_c = 1
else:
s_c = 2
s1 = shifts[s_c][1][1]
s2 = shifts[s_c][2][1]
s3 = shifts[s_c][3][1]
a = [0] * b_c
# temporary work array
t = [0] * b_c
# cipher to ints + key
for i in range(b_c):
t[i] = (ord(cipher[i * 4: i * 4 + 1]) << 24 |
ord(cipher[i * 4 + 1: i * 4 + 1 + 1]) << 16 |
ord(cipher[i * 4 + 2: i * 4 + 2 + 1]) << 8 |
ord(cipher[i * 4 + 3: i * 4 + 3 + 1])) ^ k_d[0][i]
# apply round transforms
for r in range(1, rounds):
for i in range(b_c):
a[i] = (T5[(t[i] >> 24) & 0xFF] ^
T6[(t[(i + s1) % b_c] >> 16) & 0xFF] ^
T7[(t[(i + s2) % b_c] >> 8) & 0xFF] ^
T8[t[(i + s3) % b_c] & 0xFF]) ^ k_d[r][i]
t = copy.copy(a)
# last round is special
result = []
for i in range(b_c):
tt = k_d[rounds][i]
result.append((Si[(t[i] >> 24) & 0xFF] ^ (tt >> 24)) & 0xFF)
result.append((Si[(t[(i + s1) % b_c] >> 16) & 0xFF] ^ (tt >> 16)) & 0xFF)
result.append((Si[(t[(i + s2) % b_c] >> 8) & 0xFF] ^ (tt >> 8)) & 0xFF)
result.append((Si[t[(i + s3) % b_c] & 0xFF] ^ tt) & 0xFF)
out = bytes()
for xx in result:
out += bytes([xx])
return out
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24,386 | py3rijndael.rijndael | encrypt | null | def encrypt(self, source):
if len(source) != self.block_size:
raise ValueError(
'Wrong block length, expected %s got %s' % (
str(self.block_size),
str(len(source))
)
)
k_e = self.Ke
b_c = self.block_size // 4
rounds = len(k_e) - 1
if b_c == 4:
s_c = 0
elif b_c == 6:
s_c = 1
else:
s_c = 2
s1 = shifts[s_c][1][0]
s2 = shifts[s_c][2][0]
s3 = shifts[s_c][3][0]
a = [0] * b_c
# temporary work array
t = []
# source to ints + key
for i in range(b_c):
t.append((ord(source[i * 4: i * 4 + 1]) << 24 |
ord(source[i * 4 + 1: i * 4 + 1 + 1]) << 16 |
ord(source[i * 4 + 2: i * 4 + 2 + 1]) << 8 |
ord(source[i * 4 + 3: i * 4 + 3 + 1])) ^ k_e[0][i])
# apply round transforms
for r in range(1, rounds):
for i in range(b_c):
a[i] = (T1[(t[i] >> 24) & 0xFF] ^
T2[(t[(i + s1) % b_c] >> 16) & 0xFF] ^
T3[(t[(i + s2) % b_c] >> 8) & 0xFF] ^
T4[t[(i + s3) % b_c] & 0xFF]) ^ k_e[r][i]
t = copy.copy(a)
# last round is special
result = []
for i in range(b_c):
tt = k_e[rounds][i]
result.append((S[(t[i] >> 24) & 0xFF] ^ (tt >> 24)) & 0xFF)
result.append((S[(t[(i + s1) % b_c] >> 16) & 0xFF] ^ (tt >> 16)) & 0xFF)
result.append((S[(t[(i + s2) % b_c] >> 8) & 0xFF] ^ (tt >> 8)) & 0xFF)
result.append((S[t[(i + s3) % b_c] & 0xFF] ^ tt) & 0xFF)
out = bytes()
for xx in result:
out += bytes([xx])
return out
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24,387 | py3rijndael.rijndael | RijndaelCbc | null | class RijndaelCbc(Rijndael):
def __init__(self, key: bytes, iv: bytes, padding: PaddingBase, block_size: int=16):
super().__init__(key=key, block_size=block_size)
self.iv = iv
self.padding = padding
def encrypt(self, source: bytes):
ppt = self.padding.encode(source)
offset = 0
ct = bytes()
v = self.iv
while offset < len(ppt):
block = ppt[offset:offset + self.block_size]
block = self.x_or_block(block, v)
block = super().encrypt(block)
ct += block
offset += self.block_size
v = block
return ct
def decrypt(self, cipher):
assert len(cipher) % self.block_size == 0
ppt = bytes()
offset = 0
v = self.iv
while offset < len(cipher):
block = cipher[offset:offset + self.block_size]
decrypted = super().decrypt(block)
ppt += self.x_or_block(decrypted, v)
offset += self.block_size
v = block
pt = self.padding.decode(ppt)
return pt
def x_or_block(self, b1, b2):
i = 0
r = bytes()
while i < self.block_size:
r += bytes([ord(b1[i:i+1]) ^ ord(b2[i:i+1])])
i += 1
return r
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24,388 | py3rijndael.rijndael | __init__ | null | def __init__(self, key: bytes, iv: bytes, padding: PaddingBase, block_size: int=16):
super().__init__(key=key, block_size=block_size)
self.iv = iv
self.padding = padding
| (self, key: bytes, iv: bytes, padding: py3rijndael.paddings.PaddingBase, block_size: int = 16) | [
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24,389 | py3rijndael.rijndael | decrypt | null | def decrypt(self, cipher):
assert len(cipher) % self.block_size == 0
ppt = bytes()
offset = 0
v = self.iv
while offset < len(cipher):
block = cipher[offset:offset + self.block_size]
decrypted = super().decrypt(block)
ppt += self.x_or_block(decrypted, v)
offset += self.block_size
v = block
pt = self.padding.decode(ppt)
return pt
| (self, cipher) | [
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24,390 | py3rijndael.rijndael | encrypt | null | def encrypt(self, source: bytes):
ppt = self.padding.encode(source)
offset = 0
ct = bytes()
v = self.iv
while offset < len(ppt):
block = ppt[offset:offset + self.block_size]
block = self.x_or_block(block, v)
block = super().encrypt(block)
ct += block
offset += self.block_size
v = block
return ct
| (self, source: bytes) | [
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24,391 | py3rijndael.rijndael | x_or_block | null | def x_or_block(self, b1, b2):
i = 0
r = bytes()
while i < self.block_size:
r += bytes([ord(b1[i:i+1]) ^ ord(b2[i:i+1])])
i += 1
return r
| (self, b1, b2) | [
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24,392 | py3rijndael.paddings | ZeroPadding |
Specified for hashes and MACs as Padding Method 1 in ISO/IEC 10118-1 and ISO/IEC 9797-1.
| class ZeroPadding(PaddingBase):
"""
Specified for hashes and MACs as Padding Method 1 in ISO/IEC 10118-1 and ISO/IEC 9797-1.
"""
def encode(self, source):
pad_size = self.block_size - ((len(source) + self.block_size - 1) % self.block_size + 1)
return source + b'\0' * pad_size
def decode(self, source):
assert len(source) % self.block_size == 0
offset = len(source)
if offset == 0:
return b''
end = offset - self.block_size + 1
while offset > end:
offset -= 1
if source[offset]:
return source[:offset + 1]
return source[:end]
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24,394 | py3rijndael.paddings | decode | null | def decode(self, source):
assert len(source) % self.block_size == 0
offset = len(source)
if offset == 0:
return b''
end = offset - self.block_size + 1
while offset > end:
offset -= 1
if source[offset]:
return source[:offset + 1]
return source[:end]
| (self, source) | [
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24,395 | py3rijndael.paddings | encode | null | def encode(self, source):
pad_size = self.block_size - ((len(source) + self.block_size - 1) % self.block_size + 1)
return source + b'\0' * pad_size
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24,399 | okta_jwt_verifier.jwt_verifier | AccessTokenVerifier | null | class AccessTokenVerifier():
def __init__(self,
issuer=None,
audience='api://default',
request_executor=RequestExecutor,
max_retries=MAX_RETRIES,
request_timeout=REQUEST_TIMEOUT,
max_requests=MAX_REQUESTS,
leeway=LEEWAY,
cache_jwks=True,
proxy=None):
"""
Args:
issuer: string, full URI of the token issuer, required
audience: string, expected audience, optional
request_executor: RequestExecutor class or its subclass, optional
max_retries: int, number of times to retry a failed network request, optional
request_timeout: int, max request timeout, optional
max_requests: int, max number of concurrent requests
leeway: int, amount of time to expand the window for token expiration (to work around clock skew)
cache_jwks: bool, optional
"""
self._jwt_verifier = BaseJWTVerifier(issuer=issuer,
client_id='client_id_stub',
audience=audience,
request_executor=request_executor,
max_retries=max_retries,
request_timeout=request_timeout,
max_requests=max_requests,
leeway=leeway,
cache_jwks=cache_jwks,
proxy=proxy)
async def verify(self, token, claims_to_verify=('iss', 'aud', 'exp')):
await self._jwt_verifier.verify_access_token(token, claims_to_verify)
| (issuer=None, audience='api://default', request_executor=<class 'okta_jwt_verifier.request_executor.RequestExecutor'>, max_retries=1, request_timeout=30, max_requests=10, leeway=120, cache_jwks=True, proxy=None) | [
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24,400 | okta_jwt_verifier.jwt_verifier | __init__ |
Args:
issuer: string, full URI of the token issuer, required
audience: string, expected audience, optional
request_executor: RequestExecutor class or its subclass, optional
max_retries: int, number of times to retry a failed network request, optional
request_timeout: int, max request timeout, optional
max_requests: int, max number of concurrent requests
leeway: int, amount of time to expand the window for token expiration (to work around clock skew)
cache_jwks: bool, optional
| def __init__(self,
issuer=None,
audience='api://default',
request_executor=RequestExecutor,
max_retries=MAX_RETRIES,
request_timeout=REQUEST_TIMEOUT,
max_requests=MAX_REQUESTS,
leeway=LEEWAY,
cache_jwks=True,
proxy=None):
"""
Args:
issuer: string, full URI of the token issuer, required
audience: string, expected audience, optional
request_executor: RequestExecutor class or its subclass, optional
max_retries: int, number of times to retry a failed network request, optional
request_timeout: int, max request timeout, optional
max_requests: int, max number of concurrent requests
leeway: int, amount of time to expand the window for token expiration (to work around clock skew)
cache_jwks: bool, optional
"""
self._jwt_verifier = BaseJWTVerifier(issuer=issuer,
client_id='client_id_stub',
audience=audience,
request_executor=request_executor,
max_retries=max_retries,
request_timeout=request_timeout,
max_requests=max_requests,
leeway=leeway,
cache_jwks=cache_jwks,
proxy=proxy)
| (self, issuer=None, audience='api://default', request_executor=<class 'okta_jwt_verifier.request_executor.RequestExecutor'>, max_retries=1, request_timeout=30, max_requests=10, leeway=120, cache_jwks=True, proxy=None) | [
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24,401 | okta_jwt_verifier.jwt_verifier | verify | null | def __init__(self,
issuer=None,
audience='api://default',
request_executor=RequestExecutor,
max_retries=MAX_RETRIES,
request_timeout=REQUEST_TIMEOUT,
max_requests=MAX_REQUESTS,
leeway=LEEWAY,
cache_jwks=True,
proxy=None):
"""
Args:
issuer: string, full URI of the token issuer, required
audience: string, expected audience, optional
request_executor: RequestExecutor class or its subclass, optional
max_retries: int, number of times to retry a failed network request, optional
request_timeout: int, max request timeout, optional
max_requests: int, max number of concurrent requests
leeway: int, amount of time to expand the window for token expiration (to work around clock skew)
cache_jwks: bool, optional
"""
self._jwt_verifier = BaseJWTVerifier(issuer=issuer,
client_id='client_id_stub',
audience=audience,
request_executor=request_executor,
max_retries=max_retries,
request_timeout=request_timeout,
max_requests=max_requests,
leeway=leeway,
cache_jwks=cache_jwks,
proxy=proxy)
| (self, token, claims_to_verify=('iss', 'aud', 'exp')) | [
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24,402 | okta_jwt_verifier.jwt_verifier | BaseJWTVerifier | null | class BaseJWTVerifier():
def __init__(self,
issuer=None,
client_id='client_id_stub',
audience='api://default',
request_executor=RequestExecutor,
max_retries=MAX_RETRIES,
request_timeout=REQUEST_TIMEOUT,
max_requests=MAX_REQUESTS,
leeway=LEEWAY,
cache_jwks=True,
proxy=None):
"""
Args:
issuer: string, full URI of the token issuer, required
client_id: string, expected client_id, required
audience: string, expected audience, optional
request_executor: RequestExecutor class or its subclass, optional
max_retries: int, number of times to retry a failed network request, optional
request_timeout: int, max request timeout, optional
max_requests: int, max number of concurrent requests
leeway: int, amount of time to expand the window for token expiration (to work around clock skew)
cache_jwks: bool, optional
"""
# validate input data before any processing
config = {'issuer': issuer,
'client_id': client_id,
'audience': audience,
'max_retries': max_retries,
'request_timeout': request_timeout,
'max_requests': max_requests,
'leeway': leeway,
'cache_jwks': cache_jwks}
ConfigValidator(config).validate_config()
self.issuer = issuer
self.client_id = client_id
self.audience = audience
self.request_executor = request_executor(max_retries=max_retries,
max_requests=max_requests,
request_timeout=request_timeout,
proxy=proxy)
self.max_retries = max_retries
self.request_timeout = request_timeout
self.max_requests = max_requests
self.leeway = leeway
self.cache_jwks = cache_jwks
def parse_token(self, token):
"""Parse JWT token, get headers, claims and signature.
Return:
tuple (headers, claims, signing_input, signature)
"""
return JWTUtils.parse_token(token)
async def verify_access_token(self, token, claims_to_verify=('iss', 'aud', 'exp')):
"""Verify acess token.
Algorithm:
1. Retrieve and parse your Okta JSON Web Keys (JWK),
which should be checked periodically and cached by your application.
2. Decode the access token, which is in JSON Web Token format
3. Verify the signature used to sign the access token
4. Verify the claims found inside the access token
Default claims to verify for access token:
'exp' Expiration - The time after which the token is invalid.
'iss' Issuer - The principal that issued the JWT.
'aud' Audience - The recipient that the JWT is intended for.
Raise an Exception if any validation is failed, return None otherwise.
"""
try:
headers, claims, signing_input, signature = self.parse_token(token)
if headers.get('alg') != 'RS256':
raise JWTValidationException('Header claim "alg" is invalid.')
self.verify_claims(claims,
claims_to_verify=claims_to_verify,
leeway=self.leeway)
okta_jwk = await self.get_jwk(headers['kid'])
self.verify_signature(token, okta_jwk)
except JWTValidationException:
raise
except Exception as err:
raise JWTValidationException(str(err))
async def verify_id_token(self, token, claims_to_verify=('iss', 'exp'), nonce=None):
"""Verify id token.
Algorithm:
1. Retrieve and parse your Okta JSON Web Keys (JWK),
which should be checked periodically and cached by your application.
2. Decode the access token, which is in JSON Web Token format.
3. Verify the signature used to sign the access token.
4. Verify the claims found inside the access token.
5. Verify claim "cid" matches provided client_id.
6. If claim "nonce" was provided for token generation, it should be validated too.
Default claims to verify for id token:
'exp' Expiration - The time after which the token is invalid.
'iss' Issuer - The principal that issued the JWT.
'aud' Audience - The recipient that the JWT is intended for.
For ID token 'aud' should match Client ID
Raise an Exception if any validation is failed, return None otherwise.
"""
try:
headers, claims, signing_input, signature = self.parse_token(token)
if headers.get('alg') != 'RS256':
raise JWTValidationException('Header claim "alg" is invalid.')
self.verify_claims(claims,
claims_to_verify=claims_to_verify,
leeway=self.leeway)
okta_jwk = await self.get_jwk(headers['kid'])
self.verify_signature(token, okta_jwk)
# verify client_id and nonce
self.verify_client_id(claims['aud'])
if 'nonce' in claims and claims['nonce'] != nonce:
raise JWTValidationException('Claim "nonce" is invalid.')
except JWTValidationException:
raise
except Exception as err:
raise JWTValidationException(str(err))
def verify_client_id(self, aud):
"""Verify client_id match aud or one of its elements."""
if isinstance(aud, str):
if aud != self.client_id:
raise JWTValidationException('Claim "aud" does not match Client ID.')
elif isinstance(aud, list):
for elem in aud:
if elem == self.client_id:
return
raise JWTValidationException('Claim "aud" does not contain Client ID.')
else:
raise JWTValidationException('Claim "aud" has unsupported format.')
def verify_signature(self, token, okta_jwk):
"""Verify token signature using received jwk."""
JWTUtils.verify_signature(token, okta_jwk)
def verify_claims(self, claims, claims_to_verify, leeway=LEEWAY):
"""Verify claims are present and valid."""
JWTUtils.verify_claims(claims,
claims_to_verify,
self.audience,
self.issuer,
leeway)
def verify_expiration(self, token, leeway=LEEWAY):
"""Verify if token is not expired."""
JWTUtils.verify_expiration(token, leeway)
def _get_jwk_by_kid(self, jwks, kid):
"""Loop through given jwks and find jwk which matches by kid.
Return:
str if jwk match found, None - otherwise
"""
okta_jwk = None
for key in jwks['keys']:
if key['kid'] == kid:
okta_jwk = key
return okta_jwk
async def get_jwk(self, kid):
"""Get JWK by kid.
If key not found, clear cache and retry again to support keys rollover.
Return:
str - represents JWK
Raise JWKException if key not found after retry.
"""
jwks = await self.get_jwks()
okta_jwk = self._get_jwk_by_kid(jwks, kid)
if not okta_jwk:
# retry logic
self._clear_requests_cache()
jwks = await self.get_jwks()
okta_jwk = self._get_jwk_by_kid(jwks, kid)
if not okta_jwk:
raise JWKException('No matching JWK.')
return okta_jwk
async def get_jwks(self):
"""Get jwks_uri from claims and download jwks.
version from okta_jwt_verifier.__init__.py
"""
jwks_uri = self._construct_jwks_uri()
headers = {'User-Agent': f'okta-jwt-verifier-python/{version}',
| (issuer=None, client_id='client_id_stub', audience='api://default', request_executor=<class 'okta_jwt_verifier.request_executor.RequestExecutor'>, max_retries=1, request_timeout=30, max_requests=10, leeway=120, cache_jwks=True, proxy=None) | [
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24,403 | okta_jwt_verifier.jwt_verifier | __init__ |
Args:
issuer: string, full URI of the token issuer, required
client_id: string, expected client_id, required
audience: string, expected audience, optional
request_executor: RequestExecutor class or its subclass, optional
max_retries: int, number of times to retry a failed network request, optional
request_timeout: int, max request timeout, optional
max_requests: int, max number of concurrent requests
leeway: int, amount of time to expand the window for token expiration (to work around clock skew)
cache_jwks: bool, optional
| def __init__(self,
issuer=None,
client_id='client_id_stub',
audience='api://default',
request_executor=RequestExecutor,
max_retries=MAX_RETRIES,
request_timeout=REQUEST_TIMEOUT,
max_requests=MAX_REQUESTS,
leeway=LEEWAY,
cache_jwks=True,
proxy=None):
"""
Args:
issuer: string, full URI of the token issuer, required
client_id: string, expected client_id, required
audience: string, expected audience, optional
request_executor: RequestExecutor class or its subclass, optional
max_retries: int, number of times to retry a failed network request, optional
request_timeout: int, max request timeout, optional
max_requests: int, max number of concurrent requests
leeway: int, amount of time to expand the window for token expiration (to work around clock skew)
cache_jwks: bool, optional
"""
# validate input data before any processing
config = {'issuer': issuer,
'client_id': client_id,
'audience': audience,
'max_retries': max_retries,
'request_timeout': request_timeout,
'max_requests': max_requests,
'leeway': leeway,
'cache_jwks': cache_jwks}
ConfigValidator(config).validate_config()
self.issuer = issuer
self.client_id = client_id
self.audience = audience
self.request_executor = request_executor(max_retries=max_retries,
max_requests=max_requests,
request_timeout=request_timeout,
proxy=proxy)
self.max_retries = max_retries
self.request_timeout = request_timeout
self.max_requests = max_requests
self.leeway = leeway
self.cache_jwks = cache_jwks
| (self, issuer=None, client_id='client_id_stub', audience='api://default', request_executor=<class 'okta_jwt_verifier.request_executor.RequestExecutor'>, max_retries=1, request_timeout=30, max_requests=10, leeway=120, cache_jwks=True, proxy=None) | [
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24,404 | okta_jwt_verifier.jwt_verifier | _clear_requests_cache | Clear whole cache. | def _clear_requests_cache(self):
"""Clear whole cache."""
self.request_executor.clear_cache()
| (self) | [
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24,405 | okta_jwt_verifier.jwt_verifier | _construct_jwks_uri | Construct URI for JWKs download.
Issuer URL should end with '/', automatic add '/' otherwise.
If the issuer URL does not contain /oauth2/, then:
jwks_uri_base = {issuer}/oauth2.
Otherwise: jwks_uri_base = {issuer}.
Final JWKS URI: {jwks_uri_base}/v1/keys
| def _construct_jwks_uri(self):
"""Construct URI for JWKs download.
Issuer URL should end with '/', automatic add '/' otherwise.
If the issuer URL does not contain /oauth2/, then:
jwks_uri_base = {issuer}/oauth2.
Otherwise: jwks_uri_base = {issuer}.
Final JWKS URI: {jwks_uri_base}/v1/keys
"""
jwks_uri_base = self.issuer
if not jwks_uri_base.endswith('/'):
jwks_uri_base = jwks_uri_base + '/'
if '/oauth2/' not in jwks_uri_base:
jwks_uri_base = urljoin(jwks_uri_base, 'oauth2/')
return urljoin(jwks_uri_base, 'v1/keys')
| (self) | [
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24,406 | okta_jwt_verifier.jwt_verifier | _get_jwk_by_kid | Loop through given jwks and find jwk which matches by kid.
Return:
str if jwk match found, None - otherwise
| def _get_jwk_by_kid(self, jwks, kid):
"""Loop through given jwks and find jwk which matches by kid.
Return:
str if jwk match found, None - otherwise
"""
okta_jwk = None
for key in jwks['keys']:
if key['kid'] == kid:
okta_jwk = key
return okta_jwk
| (self, jwks, kid) | [
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24,407 | okta_jwt_verifier.jwt_verifier | get_jwk | Get JWK by kid.
If key not found, clear cache and retry again to support keys rollover.
Return:
str - represents JWK
Raise JWKException if key not found after retry.
| def _get_jwk_by_kid(self, jwks, kid):
"""Loop through given jwks and find jwk which matches by kid.
Return:
str if jwk match found, None - otherwise
"""
okta_jwk = None
for key in jwks['keys']:
if key['kid'] == kid:
okta_jwk = key
return okta_jwk
| (self, kid) | [
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24,408 | okta_jwt_verifier.jwt_verifier | get_jwks | Get jwks_uri from claims and download jwks.
version from okta_jwt_verifier.__init__.py
| def _get_jwk_by_kid(self, jwks, kid):
"""Loop through given jwks and find jwk which matches by kid.
Return:
str if jwk match found, None - otherwise
"""
okta_jwk = None
for key in jwks['keys']:
if key['kid'] == kid:
okta_jwk = key
return okta_jwk
| (self) | [
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24,409 | okta_jwt_verifier.jwt_verifier | parse_token | Parse JWT token, get headers, claims and signature.
Return:
tuple (headers, claims, signing_input, signature)
| def parse_token(self, token):
"""Parse JWT token, get headers, claims and signature.
Return:
tuple (headers, claims, signing_input, signature)
"""
return JWTUtils.parse_token(token)
| (self, token) | [
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24,410 | okta_jwt_verifier.jwt_verifier | verify_access_token | Verify acess token.
Algorithm:
1. Retrieve and parse your Okta JSON Web Keys (JWK),
which should be checked periodically and cached by your application.
2. Decode the access token, which is in JSON Web Token format
3. Verify the signature used to sign the access token
4. Verify the claims found inside the access token
Default claims to verify for access token:
'exp' Expiration - The time after which the token is invalid.
'iss' Issuer - The principal that issued the JWT.
'aud' Audience - The recipient that the JWT is intended for.
Raise an Exception if any validation is failed, return None otherwise.
| def parse_token(self, token):
"""Parse JWT token, get headers, claims and signature.
Return:
tuple (headers, claims, signing_input, signature)
"""
return JWTUtils.parse_token(token)
| (self, token, claims_to_verify=('iss', 'aud', 'exp')) | [
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24,411 | okta_jwt_verifier.jwt_verifier | verify_claims | Verify claims are present and valid. | def verify_claims(self, claims, claims_to_verify, leeway=LEEWAY):
"""Verify claims are present and valid."""
JWTUtils.verify_claims(claims,
claims_to_verify,
self.audience,
self.issuer,
leeway)
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24,412 | okta_jwt_verifier.jwt_verifier | verify_client_id | Verify client_id match aud or one of its elements. | def verify_client_id(self, aud):
"""Verify client_id match aud or one of its elements."""
if isinstance(aud, str):
if aud != self.client_id:
raise JWTValidationException('Claim "aud" does not match Client ID.')
elif isinstance(aud, list):
for elem in aud:
if elem == self.client_id:
return
raise JWTValidationException('Claim "aud" does not contain Client ID.')
else:
raise JWTValidationException('Claim "aud" has unsupported format.')
| (self, aud) | [
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24,413 | okta_jwt_verifier.jwt_verifier | verify_expiration | Verify if token is not expired. | def verify_expiration(self, token, leeway=LEEWAY):
"""Verify if token is not expired."""
JWTUtils.verify_expiration(token, leeway)
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24,414 | okta_jwt_verifier.jwt_verifier | verify_id_token | Verify id token.
Algorithm:
1. Retrieve and parse your Okta JSON Web Keys (JWK),
which should be checked periodically and cached by your application.
2. Decode the access token, which is in JSON Web Token format.
3. Verify the signature used to sign the access token.
4. Verify the claims found inside the access token.
5. Verify claim "cid" matches provided client_id.
6. If claim "nonce" was provided for token generation, it should be validated too.
Default claims to verify for id token:
'exp' Expiration - The time after which the token is invalid.
'iss' Issuer - The principal that issued the JWT.
'aud' Audience - The recipient that the JWT is intended for.
For ID token 'aud' should match Client ID
Raise an Exception if any validation is failed, return None otherwise.
| def parse_token(self, token):
"""Parse JWT token, get headers, claims and signature.
Return:
tuple (headers, claims, signing_input, signature)
"""
return JWTUtils.parse_token(token)
| (self, token, claims_to_verify=('iss', 'exp'), nonce=None) | [
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24,415 | okta_jwt_verifier.jwt_verifier | verify_signature | Verify token signature using received jwk. | def verify_signature(self, token, okta_jwk):
"""Verify token signature using received jwk."""
JWTUtils.verify_signature(token, okta_jwk)
| (self, token, okta_jwk) | [
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24,416 | okta_jwt_verifier.jwt_verifier | IDTokenVerifier | null | class IDTokenVerifier():
def __init__(self,
issuer=None,
client_id='client_id_stub',
audience='api://default',
request_executor=RequestExecutor,
max_retries=MAX_RETRIES,
request_timeout=REQUEST_TIMEOUT,
max_requests=MAX_REQUESTS,
leeway=LEEWAY,
cache_jwks=True,
proxy=None):
"""
Args:
issuer: string, full URI of the token issuer, required
client_id: string, expected client_id, required
audience: string, expected audience, optional
request_executor: RequestExecutor class or its subclass, optional
max_retries: int, number of times to retry a failed network request, optional
request_timeout: int, max request timeout, optional
max_requests: int, max number of concurrent requests
leeway: int, amount of time to expand the window for token expiration (to work around clock skew)
cache_jwks: bool, optional
"""
self._jwt_verifier = BaseJWTVerifier(issuer,
client_id,
audience,
request_executor,
max_retries,
request_timeout,
max_requests,
leeway,
cache_jwks,
proxy)
async def verify(self, token, claims_to_verify=('iss', 'exp'), nonce=None):
await self._jwt_verifier.verify_id_token(token, claims_to_verify, nonce)
| (issuer=None, client_id='client_id_stub', audience='api://default', request_executor=<class 'okta_jwt_verifier.request_executor.RequestExecutor'>, max_retries=1, request_timeout=30, max_requests=10, leeway=120, cache_jwks=True, proxy=None) | [
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24,417 | okta_jwt_verifier.jwt_verifier | __init__ |
Args:
issuer: string, full URI of the token issuer, required
client_id: string, expected client_id, required
audience: string, expected audience, optional
request_executor: RequestExecutor class or its subclass, optional
max_retries: int, number of times to retry a failed network request, optional
request_timeout: int, max request timeout, optional
max_requests: int, max number of concurrent requests
leeway: int, amount of time to expand the window for token expiration (to work around clock skew)
cache_jwks: bool, optional
| def __init__(self,
issuer=None,
client_id='client_id_stub',
audience='api://default',
request_executor=RequestExecutor,
max_retries=MAX_RETRIES,
request_timeout=REQUEST_TIMEOUT,
max_requests=MAX_REQUESTS,
leeway=LEEWAY,
cache_jwks=True,
proxy=None):
"""
Args:
issuer: string, full URI of the token issuer, required
client_id: string, expected client_id, required
audience: string, expected audience, optional
request_executor: RequestExecutor class or its subclass, optional
max_retries: int, number of times to retry a failed network request, optional
request_timeout: int, max request timeout, optional
max_requests: int, max number of concurrent requests
leeway: int, amount of time to expand the window for token expiration (to work around clock skew)
cache_jwks: bool, optional
"""
self._jwt_verifier = BaseJWTVerifier(issuer,
client_id,
audience,
request_executor,
max_retries,
request_timeout,
max_requests,
leeway,
cache_jwks,
proxy)
| (self, issuer=None, client_id='client_id_stub', audience='api://default', request_executor=<class 'okta_jwt_verifier.request_executor.RequestExecutor'>, max_retries=1, request_timeout=30, max_requests=10, leeway=120, cache_jwks=True, proxy=None) | [
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24,418 | okta_jwt_verifier.jwt_verifier | verify | null | def __init__(self,
issuer=None,
client_id='client_id_stub',
audience='api://default',
request_executor=RequestExecutor,
max_retries=MAX_RETRIES,
request_timeout=REQUEST_TIMEOUT,
max_requests=MAX_REQUESTS,
leeway=LEEWAY,
cache_jwks=True,
proxy=None):
"""
Args:
issuer: string, full URI of the token issuer, required
client_id: string, expected client_id, required
audience: string, expected audience, optional
request_executor: RequestExecutor class or its subclass, optional
max_retries: int, number of times to retry a failed network request, optional
request_timeout: int, max request timeout, optional
max_requests: int, max number of concurrent requests
leeway: int, amount of time to expand the window for token expiration (to work around clock skew)
cache_jwks: bool, optional
"""
self._jwt_verifier = BaseJWTVerifier(issuer,
client_id,
audience,
request_executor,
max_retries,
request_timeout,
max_requests,
leeway,
cache_jwks,
proxy)
| (self, token, claims_to_verify=('iss', 'exp'), nonce=None) | [
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24,419 | okta_jwt_verifier.jwt_utils | JWTUtils | Contains different utils and common methods for jwt verification. | class JWTUtils:
"""Contains different utils and common methods for jwt verification."""
@staticmethod
def parse_token(token):
"""Parse JWT token, get headers, claims and signature.
Return:
tuple (headers, claims, signing_input, signature)
"""
headers, payload, signing_input, signature = jws._load(token)
claims = json.loads(payload.decode('utf-8'))
return (headers, claims, signing_input, signature)
@staticmethod
def verify_claims(claims,
claims_to_verify,
audience,
issuer,
leeway=LEEWAY):
"""Verify claims are present and valid."""
# Check if required claims are present, because library "jose" doesn't raise an exception
for claim in claims_to_verify:
if claim not in claims:
raise JWTValidationException(f'Required claim "{claim}" is not present.')
# Overwrite defaults in python-jose library
options = {'verify_aud': 'aud' in claims_to_verify,
'verify_iat': 'iat' in claims_to_verify,
'verify_exp': 'exp' in claims_to_verify,
'verify_nbf': 'nbf' in claims_to_verify,
'verify_iss': 'iss' in claims_to_verify,
'verify_sub': 'sub' in claims_to_verify,
'verify_jti': 'jti' in claims_to_verify,
'leeway': leeway}
# Validate claims
jwt._validate_claims(claims,
audience=audience,
issuer=issuer,
options=options)
@staticmethod
def verify_signature(token, okta_jwk):
"""Verify token signature using received jwk."""
headers, claims, signing_input, signature = JWTUtils.parse_token(token)
jws._verify_signature(signing_input=signing_input,
header=headers,
signature=signature,
key=okta_jwk,
algorithms=['RS256'])
@staticmethod
def verify_expiration(token, leeway=LEEWAY):
"""Verify if token is not expired."""
headers, claims, signing_input, signature = JWTUtils.parse_token(token)
try:
JWTUtils.verify_claims(claims,
claims_to_verify=('exp',),
audience=None,
issuer=None,
leeway=LEEWAY)
except ExpiredSignatureError:
raise JWTValidationException('Signature has expired.')
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] |
24,420 | okta_jwt_verifier.jwt_utils | parse_token | Parse JWT token, get headers, claims and signature.
Return:
tuple (headers, claims, signing_input, signature)
| @staticmethod
def parse_token(token):
"""Parse JWT token, get headers, claims and signature.
Return:
tuple (headers, claims, signing_input, signature)
"""
headers, payload, signing_input, signature = jws._load(token)
claims = json.loads(payload.decode('utf-8'))
return (headers, claims, signing_input, signature)
| (token) | [
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] |
24,421 | okta_jwt_verifier.jwt_utils | verify_claims | Verify claims are present and valid. | @staticmethod
def verify_claims(claims,
claims_to_verify,
audience,
issuer,
leeway=LEEWAY):
"""Verify claims are present and valid."""
# Check if required claims are present, because library "jose" doesn't raise an exception
for claim in claims_to_verify:
if claim not in claims:
raise JWTValidationException(f'Required claim "{claim}" is not present.')
# Overwrite defaults in python-jose library
options = {'verify_aud': 'aud' in claims_to_verify,
'verify_iat': 'iat' in claims_to_verify,
'verify_exp': 'exp' in claims_to_verify,
'verify_nbf': 'nbf' in claims_to_verify,
'verify_iss': 'iss' in claims_to_verify,
'verify_sub': 'sub' in claims_to_verify,
'verify_jti': 'jti' in claims_to_verify,
'leeway': leeway}
# Validate claims
jwt._validate_claims(claims,
audience=audience,
issuer=issuer,
options=options)
| (claims, claims_to_verify, audience, issuer, leeway=120) | [
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] |
24,422 | okta_jwt_verifier.jwt_utils | verify_expiration | Verify if token is not expired. | @staticmethod
def verify_expiration(token, leeway=LEEWAY):
"""Verify if token is not expired."""
headers, claims, signing_input, signature = JWTUtils.parse_token(token)
try:
JWTUtils.verify_claims(claims,
claims_to_verify=('exp',),
audience=None,
issuer=None,
leeway=LEEWAY)
except ExpiredSignatureError:
raise JWTValidationException('Signature has expired.')
| (token, leeway=120) | [
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] |
24,423 | okta_jwt_verifier.jwt_utils | verify_signature | Verify token signature using received jwk. | @staticmethod
def verify_signature(token, okta_jwk):
"""Verify token signature using received jwk."""
headers, claims, signing_input, signature = JWTUtils.parse_token(token)
jws._verify_signature(signing_input=signing_input,
header=headers,
signature=signature,
key=okta_jwk,
algorithms=['RS256'])
| (token, okta_jwk) | [
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24,424 | okta_jwt_verifier.jwt_verifier | JWTVerifier | null | class JWTVerifier(BaseJWTVerifier):
def __init__(self,
issuer=None,
client_id='client_id_stub',
audience='api://default',
request_executor=RequestExecutor,
max_retries=MAX_RETRIES,
request_timeout=REQUEST_TIMEOUT,
max_requests=MAX_REQUESTS,
leeway=LEEWAY,
cache_jwks=True,
proxy=None):
"""
Args:
issuer: string, full URI of the token issuer, required
client_id: string, expected client_id, required
audience: string, expected audience, optional
request_executor: RequestExecutor class or its subclass, optional
max_retries: int, number of times to retry a failed network request, optional
request_timeout: int, max request timeout, optional
max_requests: int, max number of concurrent requests
leeway: int, amount of time to expand the window for token expiration (to work around clock skew)
cache_jwks: bool, optional
"""
warnings.simplefilter('module')
warnings.warn('JWTVerifier will be deprecated soon. '
'For token verification use IDTokenVerifier or AccessTokenVerifier. '
'For different jwt utils use JWTUtils.', DeprecationWarning)
super().__init__(issuer=issuer,
client_id=client_id,
audience=audience,
request_executor=request_executor,
max_retries=max_retries,
request_timeout=request_timeout,
max_requests=max_requests,
leeway=leeway,
cache_jwks=cache_jwks,
proxy=proxy)
| (issuer=None, client_id='client_id_stub', audience='api://default', request_executor=<class 'okta_jwt_verifier.request_executor.RequestExecutor'>, max_retries=1, request_timeout=30, max_requests=10, leeway=120, cache_jwks=True, proxy=None) | [
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24,425 | okta_jwt_verifier.jwt_verifier | __init__ |
Args:
issuer: string, full URI of the token issuer, required
client_id: string, expected client_id, required
audience: string, expected audience, optional
request_executor: RequestExecutor class or its subclass, optional
max_retries: int, number of times to retry a failed network request, optional
request_timeout: int, max request timeout, optional
max_requests: int, max number of concurrent requests
leeway: int, amount of time to expand the window for token expiration (to work around clock skew)
cache_jwks: bool, optional
| def __init__(self,
issuer=None,
client_id='client_id_stub',
audience='api://default',
request_executor=RequestExecutor,
max_retries=MAX_RETRIES,
request_timeout=REQUEST_TIMEOUT,
max_requests=MAX_REQUESTS,
leeway=LEEWAY,
cache_jwks=True,
proxy=None):
"""
Args:
issuer: string, full URI of the token issuer, required
client_id: string, expected client_id, required
audience: string, expected audience, optional
request_executor: RequestExecutor class or its subclass, optional
max_retries: int, number of times to retry a failed network request, optional
request_timeout: int, max request timeout, optional
max_requests: int, max number of concurrent requests
leeway: int, amount of time to expand the window for token expiration (to work around clock skew)
cache_jwks: bool, optional
"""
warnings.simplefilter('module')
warnings.warn('JWTVerifier will be deprecated soon. '
'For token verification use IDTokenVerifier or AccessTokenVerifier. '
'For different jwt utils use JWTUtils.', DeprecationWarning)
super().__init__(issuer=issuer,
client_id=client_id,
audience=audience,
request_executor=request_executor,
max_retries=max_retries,
request_timeout=request_timeout,
max_requests=max_requests,
leeway=leeway,
cache_jwks=cache_jwks,
proxy=proxy)
| (self, issuer=None, client_id='client_id_stub', audience='api://default', request_executor=<class 'okta_jwt_verifier.request_executor.RequestExecutor'>, max_retries=1, request_timeout=30, max_requests=10, leeway=120, cache_jwks=True, proxy=None) | [
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] |
24,445 | encodings.utf_8 | IncrementalDecoder | null | class IncrementalDecoder(codecs.BufferedIncrementalDecoder):
_buffer_decode = codecs.utf_8_decode
| (errors='strict') | [
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24,446 | codecs | __init__ | null | def __init__(self, errors='strict'):
IncrementalDecoder.__init__(self, errors)
# undecoded input that is kept between calls to decode()
self.buffer = b""
| (self, errors='strict') | [
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24,447 | codecs | decode | null | def decode(self, input, final=False):
# decode input (taking the buffer into account)
data = self.buffer + input
(result, consumed) = self._buffer_decode(data, self.errors, final)
# keep undecoded input until the next call
self.buffer = data[consumed:]
return result
| (self, input, final=False) | [
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24,448 | codecs | getstate | null | def getstate(self):
# additional state info is always 0
return (self.buffer, 0)
| (self) | [
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24,449 | codecs | reset | null | def reset(self):
IncrementalDecoder.reset(self)
self.buffer = b""
| (self) | [
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24,450 | codecs | setstate | null | def setstate(self, state):
# ignore additional state info
self.buffer = state[0]
| (self, state) | [
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24,451 | encodings.utf_8 | StreamReader | null | class StreamReader(codecs.StreamReader):
decode = codecs.utf_8_decode
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24,453 | codecs | __exit__ | null | def __exit__(self, type, value, tb):
self.stream.close()
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24,454 | codecs | __getattr__ | Inherit all other methods from the underlying stream.
| def __getattr__(self, name,
getattr=getattr):
""" Inherit all other methods from the underlying stream.
"""
return getattr(self.stream, name)
| (self, name, getattr=<built-in function getattr>) | [
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] |
24,455 | codecs | __init__ | Creates a StreamReader instance.
stream must be a file-like object open for reading.
The StreamReader may use different error handling
schemes by providing the errors keyword argument. These
parameters are predefined:
'strict' - raise a ValueError (or a subclass)
'ignore' - ignore the character and continue with the next
'replace'- replace with a suitable replacement character
'backslashreplace' - Replace with backslashed escape sequences;
The set of allowed parameter values can be extended via
register_error.
| def __init__(self, stream, errors='strict'):
""" Creates a StreamReader instance.
stream must be a file-like object open for reading.
The StreamReader may use different error handling
schemes by providing the errors keyword argument. These
parameters are predefined:
'strict' - raise a ValueError (or a subclass)
'ignore' - ignore the character and continue with the next
'replace'- replace with a suitable replacement character
'backslashreplace' - Replace with backslashed escape sequences;
The set of allowed parameter values can be extended via
register_error.
"""
self.stream = stream
self.errors = errors
self.bytebuffer = b""
self._empty_charbuffer = self.charbuffertype()
self.charbuffer = self._empty_charbuffer
self.linebuffer = None
| (self, stream, errors='strict') | [
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] |
24,457 | codecs | __next__ | Return the next decoded line from the input stream. | def __next__(self):
""" Return the next decoded line from the input stream."""
line = self.readline()
if line:
return line
raise StopIteration
| (self) | [
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] |
24,458 | codecs | encode | Encodes the object input and returns a tuple (output
object, length consumed).
errors defines the error handling to apply. It defaults to
'strict' handling.
The method may not store state in the Codec instance. Use
StreamWriter for codecs which have to keep state in order to
make encoding efficient.
The encoder must be able to handle zero length input and
return an empty object of the output object type in this
situation.
| def encode(self, input, errors='strict'):
""" Encodes the object input and returns a tuple (output
object, length consumed).
errors defines the error handling to apply. It defaults to
'strict' handling.
The method may not store state in the Codec instance. Use
StreamWriter for codecs which have to keep state in order to
make encoding efficient.
The encoder must be able to handle zero length input and
return an empty object of the output object type in this
situation.
"""
raise NotImplementedError
| (self, input, errors='strict') | [
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] |
24,459 | codecs | read | Decodes data from the stream self.stream and returns the
resulting object.
chars indicates the number of decoded code points or bytes to
return. read() will never return more data than requested,
but it might return less, if there is not enough available.
size indicates the approximate maximum number of decoded
bytes or code points to read for decoding. The decoder
can modify this setting as appropriate. The default value
-1 indicates to read and decode as much as possible. size
is intended to prevent having to decode huge files in one
step.
If firstline is true, and a UnicodeDecodeError happens
after the first line terminator in the input only the first line
will be returned, the rest of the input will be kept until the
next call to read().
The method should use a greedy read strategy, meaning that
it should read as much data as is allowed within the
definition of the encoding and the given size, e.g. if
optional encoding endings or state markers are available
on the stream, these should be read too.
| def read(self, size=-1, chars=-1, firstline=False):
""" Decodes data from the stream self.stream and returns the
resulting object.
chars indicates the number of decoded code points or bytes to
return. read() will never return more data than requested,
but it might return less, if there is not enough available.
size indicates the approximate maximum number of decoded
bytes or code points to read for decoding. The decoder
can modify this setting as appropriate. The default value
-1 indicates to read and decode as much as possible. size
is intended to prevent having to decode huge files in one
step.
If firstline is true, and a UnicodeDecodeError happens
after the first line terminator in the input only the first line
will be returned, the rest of the input will be kept until the
next call to read().
The method should use a greedy read strategy, meaning that
it should read as much data as is allowed within the
definition of the encoding and the given size, e.g. if
optional encoding endings or state markers are available
on the stream, these should be read too.
"""
# If we have lines cached, first merge them back into characters
if self.linebuffer:
self.charbuffer = self._empty_charbuffer.join(self.linebuffer)
self.linebuffer = None
if chars < 0:
# For compatibility with other read() methods that take a
# single argument
chars = size
# read until we get the required number of characters (if available)
while True:
# can the request be satisfied from the character buffer?
if chars >= 0:
if len(self.charbuffer) >= chars:
break
# we need more data
if size < 0:
newdata = self.stream.read()
else:
newdata = self.stream.read(size)
# decode bytes (those remaining from the last call included)
data = self.bytebuffer + newdata
if not data:
break
try:
newchars, decodedbytes = self.decode(data, self.errors)
except UnicodeDecodeError as exc:
if firstline:
newchars, decodedbytes = \
self.decode(data[:exc.start], self.errors)
lines = newchars.splitlines(keepends=True)
if len(lines)<=1:
raise
else:
raise
# keep undecoded bytes until the next call
self.bytebuffer = data[decodedbytes:]
# put new characters in the character buffer
self.charbuffer += newchars
# there was no data available
if not newdata:
break
if chars < 0:
# Return everything we've got
result = self.charbuffer
self.charbuffer = self._empty_charbuffer
else:
# Return the first chars characters
result = self.charbuffer[:chars]
self.charbuffer = self.charbuffer[chars:]
return result
| (self, size=-1, chars=-1, firstline=False) | [
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] |
24,460 | codecs | readline | Read one line from the input stream and return the
decoded data.
size, if given, is passed as size argument to the
read() method.
| def readline(self, size=None, keepends=True):
""" Read one line from the input stream and return the
decoded data.
size, if given, is passed as size argument to the
read() method.
"""
# If we have lines cached from an earlier read, return
# them unconditionally
if self.linebuffer:
line = self.linebuffer[0]
del self.linebuffer[0]
if len(self.linebuffer) == 1:
# revert to charbuffer mode; we might need more data
# next time
self.charbuffer = self.linebuffer[0]
self.linebuffer = None
if not keepends:
line = line.splitlines(keepends=False)[0]
return line
readsize = size or 72
line = self._empty_charbuffer
# If size is given, we call read() only once
while True:
data = self.read(readsize, firstline=True)
if data:
# If we're at a "\r" read one extra character (which might
# be a "\n") to get a proper line ending. If the stream is
# temporarily exhausted we return the wrong line ending.
if (isinstance(data, str) and data.endswith("\r")) or \
(isinstance(data, bytes) and data.endswith(b"\r")):
data += self.read(size=1, chars=1)
line += data
lines = line.splitlines(keepends=True)
if lines:
if len(lines) > 1:
# More than one line result; the first line is a full line
# to return
line = lines[0]
del lines[0]
if len(lines) > 1:
# cache the remaining lines
lines[-1] += self.charbuffer
self.linebuffer = lines
self.charbuffer = None
else:
# only one remaining line, put it back into charbuffer
self.charbuffer = lines[0] + self.charbuffer
if not keepends:
line = line.splitlines(keepends=False)[0]
break
line0withend = lines[0]
line0withoutend = lines[0].splitlines(keepends=False)[0]
if line0withend != line0withoutend: # We really have a line end
# Put the rest back together and keep it until the next call
self.charbuffer = self._empty_charbuffer.join(lines[1:]) + \
self.charbuffer
if keepends:
line = line0withend
else:
line = line0withoutend
break
# we didn't get anything or this was our only try
if not data or size is not None:
if line and not keepends:
line = line.splitlines(keepends=False)[0]
break
if readsize < 8000:
readsize *= 2
return line
| (self, size=None, keepends=True) | [
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] |
24,461 | codecs | readlines | Read all lines available on the input stream
and return them as a list.
Line breaks are implemented using the codec's decoder
method and are included in the list entries.
sizehint, if given, is ignored since there is no efficient
way to finding the true end-of-line.
| def readlines(self, sizehint=None, keepends=True):
""" Read all lines available on the input stream
and return them as a list.
Line breaks are implemented using the codec's decoder
method and are included in the list entries.
sizehint, if given, is ignored since there is no efficient
way to finding the true end-of-line.
"""
data = self.read()
return data.splitlines(keepends)
| (self, sizehint=None, keepends=True) | [
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] |
24,462 | codecs | reset | Resets the codec buffers used for keeping internal state.
Note that no stream repositioning should take place.
This method is primarily intended to be able to recover
from decoding errors.
| def reset(self):
""" Resets the codec buffers used for keeping internal state.
Note that no stream repositioning should take place.
This method is primarily intended to be able to recover
from decoding errors.
"""
self.bytebuffer = b""
self.charbuffer = self._empty_charbuffer
self.linebuffer = None
| (self) | [
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24,463 | codecs | seek | Set the input stream's current position.
Resets the codec buffers used for keeping state.
| def seek(self, offset, whence=0):
""" Set the input stream's current position.
Resets the codec buffers used for keeping state.
"""
self.stream.seek(offset, whence)
self.reset()
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24,464 | future_fstrings | TokenSyntaxError | null | class TokenSyntaxError(SyntaxError):
def __init__(self, e, token):
super(TokenSyntaxError, self).__init__(e)
self.e = e
self.token = token
| (e, token) | [
-0.0073152827098965645,
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24,465 | future_fstrings | __init__ | null | def __init__(self, e, token):
super(TokenSyntaxError, self).__init__(e)
self.e = e
self.token = token
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] |
24,466 | future_fstrings | _find_expr | Roughly Python/ast.c:fstring_find_expr | def _find_expr(s, start, level, parts, exprs):
"""Roughly Python/ast.c:fstring_find_expr"""
i = start
nested_depth = 0
quote_char = None
triple_quoted = None
def _check_end():
if i == len(s):
raise SyntaxError("f-string: expecting '}'")
if level >= 2:
raise SyntaxError("f-string: expressions nested too deeply")
parts.append(s[i])
i += 1
while i < len(s):
ch = s[i]
if ch == '\\':
raise SyntaxError(
'f-string expression part cannot include a backslash',
)
if quote_char is not None:
if ch == quote_char:
if triple_quoted:
if i + 2 < len(s) and s[i + 1] == ch and s[i + 2] == ch:
i += 2
quote_char = None
triple_quoted = None
else:
quote_char = None
triple_quoted = None
elif ch in ('"', "'"):
quote_char = ch
if i + 2 < len(s) and s[i + 1] == ch and s[i + 2] == ch:
triple_quoted = True
i += 2
else:
triple_quoted = False
elif ch in ('[', '{', '('):
nested_depth += 1
elif nested_depth and ch in (']', '}', ')'):
nested_depth -= 1
elif ch == '#':
raise SyntaxError("f-string expression cannot include '#'")
elif nested_depth == 0 and ch in ('!', ':', '}'):
if ch == '!' and i + 1 < len(s) and s[i + 1] == '=':
# Allow != at top level as `=` isn't a valid conversion
pass
else:
break
i += 1
if quote_char is not None:
raise SyntaxError('f-string: unterminated string')
elif nested_depth:
raise SyntaxError("f-string: mismatched '(', '{', or '['")
_check_end()
exprs.append(s[start + 1:i])
if s[i] == '!':
parts.append(s[i])
i += 1
_check_end()
parts.append(s[i])
i += 1
_check_end()
if s[i] == ':':
parts.append(s[i])
i += 1
_check_end()
i = _fstring_parse(s, i, level + 1, parts, exprs)
_check_end()
if s[i] != '}':
raise SyntaxError("f-string: expecting '}'")
parts.append(s[i])
i += 1
return i
| (s, start, level, parts, exprs) | [
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] |
24,467 | future_fstrings | _find_literal | Roughly Python/ast.c:fstring_find_literal | def _find_literal(s, start, level, parts, exprs):
"""Roughly Python/ast.c:fstring_find_literal"""
i = start
parse_expr = True
while i < len(s):
ch = s[i]
if ch in ('{', '}'):
if level == 0:
if i + 1 < len(s) and s[i + 1] == ch:
i += 2
parse_expr = False
break
elif ch == '}':
raise SyntaxError("f-string: single '}' is not allowed")
break
i += 1
parts.append(s[start:i])
return i, parse_expr and i < len(s)
| (s, start, level, parts, exprs) | [
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] |
24,468 | future_fstrings | _fstring_parse | Roughly Python/ast.c:fstring_find_literal_and_expr | def _fstring_parse(s, i, level, parts, exprs):
"""Roughly Python/ast.c:fstring_find_literal_and_expr"""
while True:
i, parse_expr = _find_literal(s, i, level, parts, exprs)
if i == len(s) or s[i] == '}':
return i
if parse_expr:
i = _find_expr(s, i, level, parts, exprs)
| (s, i, level, parts, exprs) | [
0.000093326554633677,
-0.029220446944236755,
0.009598987177014351,
0.01203402504324913,
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] |
24,469 | future_fstrings | _fstring_parse_outer | null | def _fstring_parse_outer(s, i, level, parts, exprs):
for q in ('"' * 3, "'" * 3, '"', "'"):
if s.startswith(q):
s = s[len(q):len(s) - len(q)]
break
else:
raise AssertionError('unreachable')
parts.append(q)
ret = _fstring_parse(s, i, level, parts, exprs)
parts.append(q)
return ret
| (s, i, level, parts, exprs) | [
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24,470 | future_fstrings | _is_f | null | def _is_f(token):
import tokenize_rt
prefix, _ = tokenize_rt.parse_string_literal(token.src)
return 'f' in prefix.lower()
| (token) | [
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24,471 | future_fstrings | _make_fstring | null | def _make_fstring(tokens):
import tokenize_rt
new_tokens = []
exprs = []
for i, token in enumerate(tokens):
if token.name == 'STRING' and _is_f(token):
prefix, s = tokenize_rt.parse_string_literal(token.src)
parts = []
try:
_fstring_parse_outer(s, 0, 0, parts, exprs)
except SyntaxError as e:
raise TokenSyntaxError(e, tokens[i - 1])
if 'r' in prefix.lower():
parts = [s.replace('\\', '\\\\') for s in parts]
token = token._replace(src=''.join(parts))
elif token.name == 'STRING':
new_src = token.src.replace('{', '{{').replace('}', '}}')
token = token._replace(src=new_src)
new_tokens.append(token)
exprs = ('({})'.format(expr) for expr in exprs)
format_src = '.format({})'.format(', '.join(exprs))
new_tokens.append(tokenize_rt.Token('FORMAT', src=format_src))
return new_tokens
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24,472 | future_fstrings | _natively_supports_fstrings | null | def _natively_supports_fstrings():
try:
return eval('f"hi"') == 'hi'
except SyntaxError:
return False
| () | [
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] |
24,475 | encodings.utf_8 | decode | null | def decode(input, errors='strict'):
return codecs.utf_8_decode(input, errors, True)
| (input, errors='strict') | [
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24,477 | future_fstrings | decode | null | def decode(b, errors='strict'):
import tokenize_rt # pip install future-fstrings[rewrite]
u, length = utf_8.decode(b, errors)
tokens = tokenize_rt.src_to_tokens(u)
to_replace = []
start = end = seen_f = None
for i, token in enumerate(tokens):
if start is None:
if token.name == 'STRING':
start, end = i, i + 1
seen_f = _is_f(token)
elif token.name == 'STRING':
end = i + 1
seen_f |= _is_f(token)
elif token.name not in tokenize_rt.NON_CODING_TOKENS:
if seen_f:
to_replace.append((start, end))
start = end = seen_f = None
for start, end in reversed(to_replace):
try:
tokens[start:end] = _make_fstring(tokens[start:end])
except TokenSyntaxError as e:
msg = str(e.e)
line = u.splitlines()[e.token.line - 1]
bts = line.encode('UTF-8')[:e.token.utf8_byte_offset]
indent = len(bts.decode('UTF-8'))
raise SyntaxError(msg + '\n\n' + line + '\n' + ' ' * indent + '^')
return tokenize_rt.tokens_to_src(tokens), length
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24,479 | future_fstrings | main | null | def main(argv=None):
parser = argparse.ArgumentParser(description='Prints transformed source.')
parser.add_argument('filename')
args = parser.parse_args(argv)
with open(args.filename, 'rb') as f:
text, _ = fstring_decode(f.read())
getattr(sys.stdout, 'buffer', sys.stdout).write(text.encode('UTF-8'))
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] |
24,480 | future_fstrings | register | null | def register(): # pragma: no cover
codecs.register(codec_map.get)
| () | [
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] |
24,490 | aws_lambda_context | LambdaClientContext | null | class LambdaClientContext:
client: LambdaClientContextMobileClient
custom: LambdaDict
env: LambdaDict
| () | [
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24,491 | aws_lambda_context | LambdaClientContextMobileClient | null | class LambdaClientContextMobileClient:
installation_id: str
app_title: str
app_version_name: str
app_version_code: str
app_package_name: str
| () | [
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] |
24,492 | aws_lambda_context | LambdaCognitoIdentity | null | class LambdaCognitoIdentity:
cognito_identity_id: str
cognito_identity_pool_id: str
| () | [
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24,493 | aws_lambda_context | LambdaContext | null | class LambdaContext:
function_name: str
function_version: str
invoked_function_arn: str
memory_limit_in_mb: int
aws_request_id: str
log_group_name: str
log_stream_name: str
identity: LambdaCognitoIdentity
client_context: LambdaClientContext
@staticmethod
def get_remaining_time_in_millis() -> int:
return 0
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] |
24,494 | aws_lambda_context | get_remaining_time_in_millis | null | @staticmethod
def get_remaining_time_in_millis() -> int:
return 0
| () -> int | [
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24,495 | knockknock.chime_sender | chime_sender |
Chime sender wrapper: execute func, send a chime notification with the end status
(successfully finished or crashed) at the end. Also send a Chime notification before
executing func.
`webhook_url`: str
The webhook URL to access your chime room.
Visit https://docs.aws.amazon.com/chime/latest/dg/webhooks.html for more details.
`user_mentions`: List[str] (default=[])
Optional users alias or full email address to notify.
| def chime_sender(webhook_url: str, user_mentions: List[str] = []):
"""
Chime sender wrapper: execute func, send a chime notification with the end status
(successfully finished or crashed) at the end. Also send a Chime notification before
executing func.
`webhook_url`: str
The webhook URL to access your chime room.
Visit https://docs.aws.amazon.com/chime/latest/dg/webhooks.html for more details.
`user_mentions`: List[str] (default=[])
Optional users alias or full email address to notify.
"""
dump = {}
def decorator_sender(func):
@functools.wraps(func)
def wrapper_sender(*args, **kwargs):
start_time = datetime.datetime.now()
host_name = socket.gethostname()
func_name = func.__name__
# Handling distributed training edge case.
# In PyTorch, the launch of `torch.distributed.launch` sets up a RANK environment variable for each process.
# This can be used to detect the master process.
# See https://github.com/pytorch/pytorch/blob/master/torch/distributed/launch.py#L211
# Except for errors, only the master process will send notifications.
if 'RANK' in os.environ:
master_process = (int(os.environ['RANK']) == 0)
host_name += ' - RANK: %s' % os.environ['RANK']
else:
master_process = True
if master_process:
contents = [
'Your training has started 🎬',
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
' '.join(user_mentions)
]
dump['Content'] = '\n'.join(contents)
requests.post(url=webhook_url, json=dump)
try:
value = func(*args, **kwargs)
if master_process:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = [
"Your training is complete 🎉",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'End date: %s' % end_time.strftime(DATE_FORMAT),
'Training duration: %s' % str(elapsed_time)
]
try:
str_value = str(value)
contents.append('Main call returned value: %s' % str_value)
except:
contents.append('Main call returned value: %s' %
"ERROR - Couldn't str the returned value.")
contents.append(' '.join(user_mentions))
dump['Content'] = '\n'.join(contents)
requests.post(url=webhook_url, json=dump)
return value
except Exception as ex:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = [
"Your training has crashed ☠️",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'Crash date: %s' % end_time.strftime(DATE_FORMAT),
'Crashed training duration: %s\n\n' % str(elapsed_time),
"Here's the error:", '%s\n\n' % ex,
"Traceback:", '%s' % traceback.format_exc(),
' '.join(user_mentions)
]
dump['Content'] = '\n'.join(contents)
requests.post(url=webhook_url, json=dump)
raise ex
return wrapper_sender
return decorator_sender
| (webhook_url: str, user_mentions: List[str] = []) | [
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24,496 | knockknock.desktop_sender | desktop_sender | null | def desktop_sender(title: str = "knockknock"):
def show_notification(text: str, title: str):
# Check the OS
if platform.system() == "Darwin":
subprocess.run(["sh", "-c", "osascript -e 'display notification \"%s\" with title \"%s\"'" % (text, title)])
elif platform.system() == "Linux":
subprocess.run(["notify-send", title, text])
elif platform.system() == "Windows":
try:
from win10toast import ToastNotifier
except ImportError as err:
print('Error: to use Windows Desktop Notifications, you need to install `win10toast` first. Please run `pip install win10toast==0.9`.')
toaster = ToastNotifier()
toaster.show_toast(title,
text,
icon_path=None,
duration=5)
def decorator_sender(func):
@functools.wraps(func)
def wrapper_sender(*args, **kwargs):
start_time = datetime.datetime.now()
host_name = socket.gethostname()
func_name = func.__name__
# Handling distributed training edge case.
# In PyTorch, the launch of `torch.distributed.launch` sets up a RANK environment variable for each process.
# This can be used to detect the master process.
# See https://github.com/pytorch/pytorch/blob/master/torch/distributed/launch.py#L211
# Except for errors, only the master process will send notifications.
if 'RANK' in os.environ:
master_process = (int(os.environ['RANK']) == 0)
host_name += ' - RANK: %s' % os.environ['RANK']
else:
master_process = True
if master_process:
contents = ['Your training has started 🎬',
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT)]
text = '\n'.join(contents)
show_notification(text, title)
try:
value = func(*args, **kwargs)
if master_process:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training is complete 🎉",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'End date: %s' % end_time.strftime(DATE_FORMAT),
'Training duration: %s' % str(elapsed_time)]
try:
str_value = str(value)
contents.append('Main call returned value: %s'% str_value)
except:
contents.append('Main call returned value: %s'% "ERROR - Couldn't str the returned value.")
text = '\n'.join(contents)
show_notification(text, title)
return value
except Exception as ex:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training has crashed ☠️",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'Crash date: %s' % end_time.strftime(DATE_FORMAT),
'Crashed training duration: %s\n\n' % str(elapsed_time),
"Here's the error:",
'%s\n\n' % ex,
"Traceback:",
'%s' % traceback.format_exc()]
text = '\n'.join(contents)
show_notification(text, title)
raise ex
return wrapper_sender
return decorator_sender
| (title: str = 'knockknock') | [
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24,497 | knockknock.dingtalk_sender | dingtalk_sender |
DingTalk sender wrapper: execute func, send a DingTalk notification with the end status
(sucessfully finished or crashed) at the end. Also send a DingTalk notification before
executing func.
`webhook_url`: str
The webhook URL to access your DingTalk chatroom.
Visit https://ding-doc.dingtalk.com/doc#/serverapi2/qf2nxq for more details.
`user_mentions`: List[str] (default=[])
Optional users phone number to notify.
Visit https://ding-doc.dingtalk.com/doc#/serverapi2/qf2nxq for more details.
`secret`: str (default='')
DingTalk chatroom robot are set with at least one of those three security methods
(ip / keyword / secret), the chatroom will only accect messages that:
are from authorized ips set by user (ip),
contain any keyword set by user (keyword),
are posted through a encrypting way (secret).
Vist https://ding-doc.dingtalk.com/doc#/serverapi2/qf2nxq from more details.
`keywords`: List[str] (default=[])
see `secret`
| def dingtalk_sender(webhook_url: str,
user_mentions: List[str] = [],
secret: str = '',
keywords: List[str] = []):
"""
DingTalk sender wrapper: execute func, send a DingTalk notification with the end status
(sucessfully finished or crashed) at the end. Also send a DingTalk notification before
executing func.
`webhook_url`: str
The webhook URL to access your DingTalk chatroom.
Visit https://ding-doc.dingtalk.com/doc#/serverapi2/qf2nxq for more details.
`user_mentions`: List[str] (default=[])
Optional users phone number to notify.
Visit https://ding-doc.dingtalk.com/doc#/serverapi2/qf2nxq for more details.
`secret`: str (default='')
DingTalk chatroom robot are set with at least one of those three security methods
(ip / keyword / secret), the chatroom will only accect messages that:
are from authorized ips set by user (ip),
contain any keyword set by user (keyword),
are posted through a encrypting way (secret).
Vist https://ding-doc.dingtalk.com/doc#/serverapi2/qf2nxq from more details.
`keywords`: List[str] (default=[])
see `secret`
"""
msg_template = {
"msgtype": "text",
"text": {
"content": ""
},
"at": {
"atMobiles": user_mentions,
"isAtAll": False
}
}
def _construct_encrypted_url():
'''
Visit https://ding-doc.dingtalk.com/doc#/serverapi2/qf2nxq for details
'''
timestamp = round(datetime.datetime.now().timestamp() * 1000)
secret_enc = secret.encode('utf-8')
string_to_sign = '{}\n{}'.format(timestamp, secret)
string_to_sign_enc = string_to_sign.encode('utf-8')
hmac_code = hmac.new(secret_enc, string_to_sign_enc, digestmod=hashlib.sha256).digest()
sign = urllib.parse.quote_plus(base64.b64encode(hmac_code))
encrypted_url = webhook_url + '×tamp={}'.format(timestamp) \
+ '&sign={}'.format(sign)
return encrypted_url
def decorator_sender(func):
@functools.wraps(func)
def wrapper_sender(*args, **kwargs):
start_time = datetime.datetime.now()
host_name = socket.gethostname()
func_name = func.__name__
# Handling distributed training edge case.
# In PyTorch, the launch of `torch.distributed.launch` sets up a RANK environment variable for each process.
# This can be used to detect the master process.
# See https://github.com/pytorch/pytorch/blob/master/torch/distributed/launch.py#L211
# Except for errors, only the master process will send notifications.
if 'RANK' in os.environ:
master_process = (int(os.environ['RANK']) == 0)
host_name += ' - RANK: %s' % os.environ['RANK']
else:
master_process = True
if master_process:
contents = ['Your training has started 🎬',
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT)]
contents.extend(['@{}'.format(i) for i in user_mentions])
contents.extend(keywords)
msg_template['text']['content'] = '\n'.join(contents)
if secret:
postto = _construct_encrypted_url()
requests.post(postto, json=msg_template)
else:
requests.post(webhook_url, json=msg_template)
try:
value = func(*args, **kwargs)
if master_process:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training is complete 🎉",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'End date: %s' % end_time.strftime(DATE_FORMAT),
'Training duration: %s' % str(elapsed_time)]
try:
str_value = str(value)
contents.append('Main call returned value: %s'% str_value)
except:
contents.append('Main call returned value: %s'% "ERROR - Couldn't str the returned value.")
contents.extend(['@{}'.format(i) for i in user_mentions])
contents.extend(keywords)
msg_template['text']['content'] = '\n'.join(contents)
if secret:
postto = _construct_encrypted_url()
requests.post(postto, json=msg_template)
else:
requests.post(webhook_url, json=msg_template)
print(msg_template)
return value
except Exception as ex:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training has crashed ☠️",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'Crash date: %s' % end_time.strftime(DATE_FORMAT),
'Crashed training duration: %s\n\n' % str(elapsed_time),
"Here's the error:",
'%s\n\n' % ex,
"Traceback:",
'%s' % traceback.format_exc()]
contents.extend(['@{}'.format(i) for i in user_mentions])
contents.extend(keywords)
msg_template['text']['content'] = '\n'.join(contents)
if secret:
postto = _construct_encrypted_url()
requests.post(postto, json=msg_template)
else:
requests.post(webhook_url, json=msg_template)
print(msg_template)
raise ex
return wrapper_sender
return decorator_sender
| (webhook_url: str, user_mentions: List[str] = [], secret: str = '', keywords: List[str] = []) | [
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24,498 | knockknock.discord_sender | discord_sender |
Discord sender wrapper: execute func, send a Discord message with the end status
(sucessfully finished or crashed) at the end. Also send a Discord message before
executing func.
`webhook_url`: str
The Discord webhook URL for posting messages.
Visit https://support.discordapp.com/hc/en-us/articles/228383668-Intro-to-Webhooks to
set up your webhook and get your URL.
| def discord_sender(webhook_url: str):
"""
Discord sender wrapper: execute func, send a Discord message with the end status
(sucessfully finished or crashed) at the end. Also send a Discord message before
executing func.
`webhook_url`: str
The Discord webhook URL for posting messages.
Visit https://support.discordapp.com/hc/en-us/articles/228383668-Intro-to-Webhooks to
set up your webhook and get your URL.
"""
def decorator_sender(func):
def send_message(text: str):
headers = {'Content-Type': 'application/json'}
payload = json.dumps({'content': text})
r = requests.post(url=webhook_url, data=payload, headers=headers)
@functools.wraps(func)
def wrapper_sender(*args, **kwargs):
start_time = datetime.datetime.now()
host_name = socket.gethostname()
func_name = func.__name__
# Handling distributed training edge case.
# In PyTorch, the launch of `torch.distributed.launch` sets up a RANK environment variable for each process.
# This can be used to detect the master process.
# See https://github.com/pytorch/pytorch/blob/master/torch/distributed/launch.py#L211
# Except for errors, only the master process will send notifications.
if 'RANK' in os.environ:
master_process = (int(os.environ['RANK']) == 0)
host_name += ' - RANK: %s' % os.environ['RANK']
else:
master_process = True
if master_process:
contents = ['Your training has started 🎬',
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT)]
text = '\n'.join(contents)
send_message(text=text)
try:
value = func(*args, **kwargs)
if master_process:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training is complete 🎉",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'End date: %s' % end_time.strftime(DATE_FORMAT),
'Training duration: %s' % str(elapsed_time)]
try:
str_value = str(value)
contents.append('Main call returned value: %s'% str_value)
except:
contents.append('Main call returned value: %s'% "ERROR - Couldn't str the returned value.")
text = '\n'.join(contents)
send_message(text=text)
return value
except Exception as ex:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training has crashed ☠️",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'Crash date: %s' % end_time.strftime(DATE_FORMAT),
'Crashed training duration: %s\n\n' % str(elapsed_time),
"Here's the error:",
'%s\n\n' % ex,
"Traceback:",
'%s' % traceback.format_exc()]
text = '\n'.join(contents)
send_message(text=text)
raise ex
return wrapper_sender
return decorator_sender
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24,499 | knockknock.email_sender | email_sender |
Email sender wrapper: execute func, send an email with the end status
(sucessfully finished or crashed) at the end. Also send an email before
executing func.
`recipient_emails`: list[str]
A list of email addresses to notify.
`sender_email`: str (default=None)
The email adress to send the messages. If None, use the same
address as the first recipient email in `recipient_emails`
if length of `recipient_emails` is more than 0.
| def email_sender(recipient_emails: list, sender_email: str = None):
"""
Email sender wrapper: execute func, send an email with the end status
(sucessfully finished or crashed) at the end. Also send an email before
executing func.
`recipient_emails`: list[str]
A list of email addresses to notify.
`sender_email`: str (default=None)
The email adress to send the messages. If None, use the same
address as the first recipient email in `recipient_emails`
if length of `recipient_emails` is more than 0.
"""
if sender_email is None and len(recipient_emails) > 0:
sender_email = recipient_emails[0]
yag_sender = yagmail.SMTP(sender_email)
def decorator_sender(func):
@functools.wraps(func)
def wrapper_sender(*args, **kwargs):
start_time = datetime.datetime.now()
host_name = socket.gethostname()
func_name = func.__name__
# Handling distributed training edge case.
# In PyTorch, the launch of `torch.distributed.launch` sets up a RANK environment variable for each process.
# This can be used to detect the master process.
# See https://github.com/pytorch/pytorch/blob/master/torch/distributed/launch.py#L211
# Except for errors, only the master process will send notifications.
if 'RANK' in os.environ:
master_process = (int(os.environ['RANK']) == 0)
host_name += ' - RANK: %s' % os.environ['RANK']
else:
master_process = True
if master_process:
contents = ['Your training has started.',
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT)]
for i in range(len(recipient_emails)):
current_recipient = recipient_emails[i]
yag_sender.send(current_recipient, 'Training has started 🎬', contents)
try:
value = func(*args, **kwargs)
if master_process:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training is complete.",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'End date: %s' % end_time.strftime(DATE_FORMAT),
'Training duration: %s' % str(elapsed_time)]
try:
str_value = str(value)
contents.append('Main call returned value: %s'% str_value)
except:
contents.append('Main call returned value: %s'% "ERROR - Couldn't str the returned value.")
for i in range(len(recipient_emails)):
current_recipient = recipient_emails[i]
yag_sender.send(current_recipient, 'Training has sucessfully finished 🎉', contents)
return value
except Exception as ex:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training has crashed.",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'Crash date: %s' % end_time.strftime(DATE_FORMAT),
'Crashed training duration: %s\n\n' % str(elapsed_time),
"Here's the error:",
'%s\n\n' % ex,
"Traceback:",
'%s' % traceback.format_exc()]
for i in range(len(recipient_emails)):
current_recipient = recipient_emails[i]
yag_sender.send(current_recipient, 'Training has crashed ☠️', contents)
raise ex
return wrapper_sender
return decorator_sender
| (recipient_emails: list, sender_email: Optional[str] = None) | [
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24,500 | knockknock.matrix_sender | matrix_sender |
Matrix sender wrapper: execute func, send a Matrix message with the end status
(sucessfully finished or crashed) at the end. Also send a Matrix message before
executing func.
`homeserver`: str
The homeserver address which was used to register the BOT.
It is e.g. 'https://matrix-client.matrix.org'. It can be also looked up
in Riot by looking in the riot settings, "Help & About" at the bottom.
Specifying the schema (`http` or `https`) is required.
`token`: str
The access TOKEN of the user that will send the messages.
It can be obtained in Riot by looking in the riot settings, "Help & About" ,
down the bottom is: Access Token:<click to reveal>
`room`: str
The alias of the room to which messages will be send by the BOT.
After creating a room, an alias can be set. In Riot, this can be done
by opening the room settings under 'Room Addresses'.
| def matrix_sender(homeserver: str, token: str, room: str):
"""
Matrix sender wrapper: execute func, send a Matrix message with the end status
(sucessfully finished or crashed) at the end. Also send a Matrix message before
executing func.
`homeserver`: str
The homeserver address which was used to register the BOT.
It is e.g. 'https://matrix-client.matrix.org'. It can be also looked up
in Riot by looking in the riot settings, "Help & About" at the bottom.
Specifying the schema (`http` or `https`) is required.
`token`: str
The access TOKEN of the user that will send the messages.
It can be obtained in Riot by looking in the riot settings, "Help & About" ,
down the bottom is: Access Token:<click to reveal>
`room`: str
The alias of the room to which messages will be send by the BOT.
After creating a room, an alias can be set. In Riot, this can be done
by opening the room settings under 'Room Addresses'.
"""
matrix = MatrixHttpApi(homeserver, token=token)
room_id = matrix.get_room_id(room)
def decorator_sender(func):
@functools.wraps(func)
def wrapper_sender(*args, **kwargs):
start_time = datetime.datetime.now()
host_name = socket.gethostname()
func_name = func.__name__
# Handling distributed training edge case.
# In PyTorch, the launch of `torch.distributed.launch` sets up a RANK environment variable for each process.
# This can be used to detect the master process.
# See https://github.com/pytorch/pytorch/blob/master/torch/distributed/launch.py#L211
# Except for errors, only the master process will send notifications.
if 'RANK' in os.environ:
master_process = (int(os.environ['RANK']) == 0)
host_name += ' - RANK: %s' % os.environ['RANK']
else:
master_process = True
if master_process:
contents = ['Your training has started 🎬',
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT)]
text = '\n'.join(contents)
matrix.send_message(room_id, text)
try:
value = func(*args, **kwargs)
if master_process:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training is complete 🎉",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'End date: %s' % end_time.strftime(DATE_FORMAT),
'Training duration: %s' % str(elapsed_time)]
try:
str_value = str(value)
contents.append('Main call returned value: %s'% str_value)
except:
contents.append('Main call returned value: %s'% "ERROR - Couldn't str the returned value.")
text = '\n'.join(contents)
matrix.send_message(room_id, text)
return value
except Exception as ex:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training has crashed ☠️",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'Crash date: %s' % end_time.strftime(DATE_FORMAT),
'Crashed training duration: %s\n\n' % str(elapsed_time),
"Here's the error:",
'%s\n\n' % ex,
"Traceback:",
'%s' % traceback.format_exc()]
text = '\n'.join(contents)
matrix.send_message(room_id, text)
raise ex
return wrapper_sender
return decorator_sender
| (homeserver: str, token: str, room: str) | [
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24,501 | knockknock.rocketchat_sender | rocketchat_sender |
RocketChat sender wrapper: execute func, post a RocketChat message with the end status
(sucessfully finished or crashed) at the end. Also send a RocketChat message before
executing func.
`rocketchat_server_url`: str
The RocketChat server URL.
E.g. rocketchat.yourcompany.com
`rocketchat_user_id`: str
The RocketChat user id to post messages with (you'll be able to view your user id when you create a personal access token).
`rocketchat_auth_token`: str
The RocketChat personal access token.
Visit https://rocket.chat/docs/developer-guides/rest-api/personal-access-tokens/ for more details.
`channel`: str
The RocketChat channel to log.
`user_mentions`: List[str] (default=[])
Optional list of user names to notify, as comma seperated list.
`alias`: str (default="")
Optional alias to use for the notification.
| def rocketchat_sender(rocketchat_server_url: str,
rocketchat_user_id: str,
rocketchat_auth_token: str,
channel: str,
user_mentions: List[str] = [],
alias: str = ""):
"""
RocketChat sender wrapper: execute func, post a RocketChat message with the end status
(sucessfully finished or crashed) at the end. Also send a RocketChat message before
executing func.
`rocketchat_server_url`: str
The RocketChat server URL.
E.g. rocketchat.yourcompany.com
`rocketchat_user_id`: str
The RocketChat user id to post messages with (you'll be able to view your user id when you create a personal access token).
`rocketchat_auth_token`: str
The RocketChat personal access token.
Visit https://rocket.chat/docs/developer-guides/rest-api/personal-access-tokens/ for more details.
`channel`: str
The RocketChat channel to log.
`user_mentions`: List[str] (default=[])
Optional list of user names to notify, as comma seperated list.
`alias`: str (default="")
Optional alias to use for the notification.
"""
dump = {
"alias": alias,
"channel": channel,
"emoji": ":bell:"
}
headers = {
"Content-type": "application/json",
"X-Auth-Token": rocketchat_auth_token,
"X-User-Id": rocketchat_user_id
}
def decorator_sender(func):
@functools.wraps(func)
def wrapper_sender(*args, **kwargs):
webhook_url = urljoin(rocketchat_server_url,
"/api/v1/chat.postMessage")
start_time = datetime.datetime.now().replace(microsecond=0)
host_name = socket.gethostname()
func_name = func.__name__
# Handling distributed training edge case.
# In PyTorch, the launch of `torch.distributed.launch` sets up a RANK environment variable for each process.
# This can be used to detect the master process.
# See https://github.com/pytorch/pytorch/blob/master/torch/distributed/launch.py#L211
# Except for errors, only the master process will send notifications.
if "RANK" in os.environ:
master_process = (int(os.environ["RANK"]) == 0)
host_name += " - RANK: %s" % os.environ["RANK"]
else:
master_process = True
if master_process:
contents = ["Your training has **started** :clap: %s" % " ".join(["@" + u for u in user_mentions]),
"**Machine name:** %s" % host_name,
"**Main call:** %s" % func_name,
"**Starting date:** %s" % start_time.strftime(
DATE_FORMAT)]
dump["text"] = "\n".join(contents)
requests.post(
url=webhook_url,
data=json.dumps(dump),
headers=headers)
try:
value = func(*args, **kwargs)
if master_process:
end_time = datetime.datetime.now().replace(microsecond=0)
elapsed_time = (end_time - start_time)
contents = ["Your training is **complete** :tada: %s" % " ".join(["@" + u for u in user_mentions]),
"**Machine name:** %s" % host_name,
"**Main call:** %s" % func_name,
"**Starting date:** %s" % start_time.strftime(
DATE_FORMAT),
"**End date:** %s" % end_time.strftime(
DATE_FORMAT),
"**Training duration:** %s" % str(elapsed_time)]
try:
str_value = str(value)
contents.append(
"**Main call returned value:** %s" % str_value)
except:
contents.append("**Main call returned value:** %s" %
"ERROR - Couldn't str the returned value.")
dump["text"] = "\n".join(contents)
requests.post(
url=webhook_url,
data=json.dumps(dump),
headers=headers)
return value
except Exception as ex:
end_time = datetime.datetime.now().replace(microsecond=0)
elapsed_time = end_time - start_time
contents = ["Your training has **crashed** :skull_crossbones: %s" % " ".join(["@" + u for u in user_mentions]),
"**Machine name:** %s" % host_name,
"**Main call:** %s" % func_name,
"**Starting date:** %s" % start_time.strftime(
DATE_FORMAT),
"**Crash date:** %s" % end_time.strftime(
DATE_FORMAT),
"**Crashed training duration:** %s" % str(
elapsed_time),
"**Error message:**",
"\n%s\n" % ex,
"**Traceback:**",
"\n%s\n" % traceback.format_exc()]
dump["text"] = "\n".join(contents)
requests.post(
url=webhook_url,
data=json.dumps(dump),
headers=headers)
raise ex
return wrapper_sender
return decorator_sender
| (rocketchat_server_url: str, rocketchat_user_id: str, rocketchat_auth_token: str, channel: str, user_mentions: List[str] = [], alias: str = '') | [
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24,502 | knockknock.slack_sender | slack_sender |
Slack sender wrapper: execute func, send a Slack notification with the end status
(sucessfully finished or crashed) at the end. Also send a Slack notification before
executing func.
`webhook_url`: str
The webhook URL to access your slack room.
Visit https://api.slack.com/incoming-webhooks#create_a_webhook for more details.
`channel`: str
The slack room to log.
`user_mentions`: List[str] (default=[])
Optional users ids to notify.
Visit https://api.slack.com/methods/users.identity for more details.
| def slack_sender(webhook_url: str, channel: str, user_mentions: List[str] = []):
"""
Slack sender wrapper: execute func, send a Slack notification with the end status
(sucessfully finished or crashed) at the end. Also send a Slack notification before
executing func.
`webhook_url`: str
The webhook URL to access your slack room.
Visit https://api.slack.com/incoming-webhooks#create_a_webhook for more details.
`channel`: str
The slack room to log.
`user_mentions`: List[str] (default=[])
Optional users ids to notify.
Visit https://api.slack.com/methods/users.identity for more details.
"""
dump = {
"username": "Knock Knock",
"channel": channel,
"icon_emoji": ":clapper:",
}
def decorator_sender(func):
@functools.wraps(func)
def wrapper_sender(*args, **kwargs):
start_time = datetime.datetime.now()
host_name = socket.gethostname()
func_name = func.__name__
# Handling distributed training edge case.
# In PyTorch, the launch of `torch.distributed.launch` sets up a RANK environment variable for each process.
# This can be used to detect the master process.
# See https://github.com/pytorch/pytorch/blob/master/torch/distributed/launch.py#L211
# Except for errors, only the master process will send notifications.
if 'RANK' in os.environ:
master_process = (int(os.environ['RANK']) == 0)
host_name += ' - RANK: %s' % os.environ['RANK']
else:
master_process = True
if master_process:
contents = ['Your training has started 🎬',
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT)]
contents.append(' '.join(user_mentions))
dump['text'] = '\n'.join(contents)
dump['icon_emoji'] = ':clapper:'
requests.post(webhook_url, json.dumps(dump))
try:
value = func(*args, **kwargs)
if master_process:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training is complete 🎉",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'End date: %s' % end_time.strftime(DATE_FORMAT),
'Training duration: %s' % str(elapsed_time)]
try:
str_value = str(value)
contents.append('Main call returned value: %s'% str_value)
except:
contents.append('Main call returned value: %s'% "ERROR - Couldn't str the returned value.")
contents.append(' '.join(user_mentions))
dump['text'] = '\n'.join(contents)
dump['icon_emoji'] = ':tada:'
requests.post(webhook_url, json.dumps(dump))
return value
except Exception as ex:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training has crashed ☠️",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'Crash date: %s' % end_time.strftime(DATE_FORMAT),
'Crashed training duration: %s\n\n' % str(elapsed_time),
"Here's the error:",
'%s\n\n' % ex,
"Traceback:",
'%s' % traceback.format_exc()]
contents.append(' '.join(user_mentions))
dump['text'] = '\n'.join(contents)
dump['icon_emoji'] = ':skull_and_crossbones:'
requests.post(webhook_url, json.dumps(dump))
raise ex
return wrapper_sender
return decorator_sender
| (webhook_url: str, channel: str, user_mentions: List[str] = []) | [
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24,503 | knockknock.sms_sender | sms_sender | null | def sms_sender(account_sid: str, auth_token: str, recipient_number: str, sender_number: str):
client = Client(account_sid, auth_token)
def decorator_sender(func):
@functools.wraps(func)
def wrapper_sender(*args, **kwargs):
start_time = datetime.datetime.now()
host_name = socket.gethostname()
func_name = func.__name__
# Handling distributed training edge case.
# In PyTorch, the launch of `torch.distributed.launch` sets up a RANK environment variable for each process.
# This can be used to detect the master process.
# See https://github.com/pytorch/pytorch/blob/master/torch/distributed/launch.py#L211
# Except for errors, only the master process will send notifications.
if 'RANK' in os.environ:
master_process = (int(os.environ['RANK']) == 0)
host_name += ' - RANK: %s' % os.environ['RANK']
else:
master_process = True
if master_process:
contents = ['Your training has started 🎬',
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT)]
text = '\n'.join(contents)
client.messages.create(body=text, from_=sender_number, to=recipient_number)
try:
value = func(*args, **kwargs)
if master_process:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training is complete 🎉",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'End date: %s' % end_time.strftime(DATE_FORMAT),
'Training duration: %s' % str(elapsed_time)]
try:
str_value = str(value)
contents.append('Main call returned value: %s'% str_value)
except:
contents.append('Main call returned value: %s'% "ERROR - Couldn't str the returned value.")
text = '\n'.join(contents)
client.messages.create(body=text, from_=sender_number, to=recipient_number)
return value
except Exception as ex:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training has crashed ☠️",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'Crash date: %s' % end_time.strftime(DATE_FORMAT),
'Crashed training duration: %s\n\n' % str(elapsed_time),
"Here's the error:",
'%s\n\n' % ex,
"Traceback:",
'%s' % traceback.format_exc()]
text = '\n'.join(contents)
client.messages.create(body=text, from_=sender_number, to=recipient_number)
raise ex
return wrapper_sender
return decorator_sender
| (account_sid: str, auth_token: str, recipient_number: str, sender_number: str) | [
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24,504 | knockknock.teams_sender | teams_sender |
team sender wrapper: execute func, send a team notification with the end status
(sucessfully finished or crashed) at the end. Also send a Slack notification before
executing func.
`webhook_url`: str
The webhook URL to access your slack room.
Visit https://docs.microsoft.com/en-us/microsoftteams/platform/concepts/connectors/connectors-using for more details.
`user_mentions`: List[str] (default=[])
Optional users ids to notify.
| def teams_sender(webhook_url: str, user_mentions: List[str] = []):
"""
team sender wrapper: execute func, send a team notification with the end status
(sucessfully finished or crashed) at the end. Also send a Slack notification before
executing func.
`webhook_url`: str
The webhook URL to access your slack room.
Visit https://docs.microsoft.com/en-us/microsoftteams/platform/concepts/connectors/connectors-using for more details.
`user_mentions`: List[str] (default=[])
Optional users ids to notify.
"""
dump = {
"username": "Knock Knock",
"icon_emoji": ":clapper:",
}
def decorator_sender(func):
@functools.wraps(func)
def wrapper_sender(*args, **kwargs):
start_time = datetime.datetime.now()
host_name = socket.gethostname()
func_name = func.__name__
# Handling distributed training edge case.
# In PyTorch, the launch of `torch.distributed.launch` sets up a RANK environment variable for each process.
# This can be used to detect the master process.
# See https://github.com/pytorch/pytorch/blob/master/torch/distributed/launch.py#L211
# Except for errors, only the master process will send notifications.
if 'RANK' in os.environ:
master_process = (int(os.environ['RANK']) == 0)
host_name += ' - RANK: %s' % os.environ['RANK']
else:
master_process = True
if master_process:
contents = ['Your training has started 🎬',
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT)]
contents.append(' '.join(user_mentions))
dump['text'] = '\n'.join(contents)
dump['icon_emoji'] = ':clapper:'
requests.post(webhook_url, json.dumps(dump))
try:
value = func(*args, **kwargs)
if master_process:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training is complete 🎉",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(
DATE_FORMAT),
'End date: %s' % end_time.strftime(
DATE_FORMAT),
'Training duration: %s' % str(elapsed_time)]
try:
str_value = str(value)
contents.append(
'Main call returned value: %s' % str_value)
except:
contents.append('Main call returned value: %s' %
"ERROR - Couldn't str the returned value.")
contents.append(' '.join(user_mentions))
dump['text'] = '\n'.join(contents)
dump['icon_emoji'] = ':tada:'
requests.post(webhook_url, json.dumps(dump))
return value
except Exception as ex:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training has crashed ☠️",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(
DATE_FORMAT),
'Crash date: %s' % end_time.strftime(DATE_FORMAT),
'Crashed training duration: %s\n\n' % str(
elapsed_time),
"Here's the error:",
'%s\n\n' % ex,
"Traceback:",
'%s' % traceback.format_exc()]
contents.append(' '.join(user_mentions))
dump['text'] = '\n'.join(contents)
dump['icon_emoji'] = ':skull_and_crossbones:'
requests.post(webhook_url, json.dumps(dump))
raise ex
return wrapper_sender
return decorator_sender
| (webhook_url: str, user_mentions: List[str] = []) | [
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] |
24,505 | knockknock.telegram_sender | telegram_sender |
Telegram sender wrapper: execute func, send a Telegram message with the end status
(sucessfully finished or crashed) at the end. Also send a Telegram message before
executing func.
`token`: str
The API access TOKEN required to use the Telegram API.
Visit https://core.telegram.org/bots#6-botfather to obtain your TOKEN.
`chat_id`: int
Your chat room id with your notification BOT.
Visit https://api.telegram.org/bot<YourBOTToken>/getUpdates to get your chat_id
(start a conversation with your bot by sending a message and get the `int` under
message['chat']['id'])
| def telegram_sender(token: str, chat_id: int):
"""
Telegram sender wrapper: execute func, send a Telegram message with the end status
(sucessfully finished or crashed) at the end. Also send a Telegram message before
executing func.
`token`: str
The API access TOKEN required to use the Telegram API.
Visit https://core.telegram.org/bots#6-botfather to obtain your TOKEN.
`chat_id`: int
Your chat room id with your notification BOT.
Visit https://api.telegram.org/bot<YourBOTToken>/getUpdates to get your chat_id
(start a conversation with your bot by sending a message and get the `int` under
message['chat']['id'])
"""
bot = telegram.Bot(token=token)
def decorator_sender(func):
@functools.wraps(func)
def wrapper_sender(*args, **kwargs):
start_time = datetime.datetime.now()
host_name = socket.gethostname()
func_name = func.__name__
# Handling distributed training edge case.
# In PyTorch, the launch of `torch.distributed.launch` sets up a RANK environment variable for each process.
# This can be used to detect the master process.
# See https://github.com/pytorch/pytorch/blob/master/torch/distributed/launch.py#L211
# Except for errors, only the master process will send notifications.
if 'RANK' in os.environ:
master_process = (int(os.environ['RANK']) == 0)
host_name += ' - RANK: %s' % os.environ['RANK']
else:
master_process = True
if master_process:
contents = ['Your training has started 🎬',
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT)]
text = '\n'.join(contents)
bot.send_message(chat_id=chat_id, text=text)
try:
value = func(*args, **kwargs)
if master_process:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training is complete 🎉",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'End date: %s' % end_time.strftime(DATE_FORMAT),
'Training duration: %s' % str(elapsed_time)]
try:
str_value = str(value)
contents.append('Main call returned value: %s'% str_value)
except:
contents.append('Main call returned value: %s'% "ERROR - Couldn't str the returned value.")
text = '\n'.join(contents)
bot.send_message(chat_id=chat_id, text=text)
return value
except Exception as ex:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training has crashed ☠️",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'Crash date: %s' % end_time.strftime(DATE_FORMAT),
'Crashed training duration: %s\n\n' % str(elapsed_time),
"Here's the error:",
'%s\n\n' % ex,
"Traceback:",
'%s' % traceback.format_exc()]
text = '\n'.join(contents)
bot.send_message(chat_id=chat_id, text=text)
raise ex
return wrapper_sender
return decorator_sender
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24,506 | knockknock.wechat_sender | wechat_sender |
WeChat Work sender wrapper: execute func, send a WeChat Work notification with the end status
(sucessfully finished or crashed) at the end. Also send a WeChat Work notification before
executing func. To obtain the webhook, add a Group Robot in your WeChat Work Group. Visit
https://work.weixin.qq.com/api/doc/90000/90136/91770 for more details.
`webhook_url`: str
The webhook URL to access your WeChat Work chatroom.
Visit https://work.weixin.qq.com/api/doc/90000/90136/91770 for more details.
`user_mentions`: List[str] (default=[])
Optional userids to notify (use '@all' for all group members).
Visit https://work.weixin.qq.com/api/doc/90000/90136/91770 for more details.
`user_mentions_mobile`: List[str] (default=[])
Optional user's phone numbers to notify (use '@all' for all group members).
Visit https://work.weixin.qq.com/api/doc/90000/90136/91770 for more details.
| def wechat_sender(webhook_url: str,
user_mentions: List[str] = [],
user_mentions_mobile: List[str] = []):
"""
WeChat Work sender wrapper: execute func, send a WeChat Work notification with the end status
(sucessfully finished or crashed) at the end. Also send a WeChat Work notification before
executing func. To obtain the webhook, add a Group Robot in your WeChat Work Group. Visit
https://work.weixin.qq.com/api/doc/90000/90136/91770 for more details.
`webhook_url`: str
The webhook URL to access your WeChat Work chatroom.
Visit https://work.weixin.qq.com/api/doc/90000/90136/91770 for more details.
`user_mentions`: List[str] (default=[])
Optional userids to notify (use '@all' for all group members).
Visit https://work.weixin.qq.com/api/doc/90000/90136/91770 for more details.
`user_mentions_mobile`: List[str] (default=[])
Optional user's phone numbers to notify (use '@all' for all group members).
Visit https://work.weixin.qq.com/api/doc/90000/90136/91770 for more details.
"""
msg_template = {
"msgtype": "text",
"text": {
"content": "",
"mentioned_list":user_mentions,
"mentioned_mobile_list":user_mentions_mobile
}
}
def decorator_sender(func):
@functools.wraps(func)
def wrapper_sender(*args, **kwargs):
start_time = datetime.datetime.now()
host_name = socket.gethostname()
func_name = func.__name__
# Handling distributed training edge case.
# In PyTorch, the launch of `torch.distributed.launch` sets up a RANK environment variable for each process.
# This can be used to detect the master process.
# See https://github.com/pytorch/pytorch/blob/master/torch/distributed/launch.py#L211
# Except for errors, only the master process will send notifications.
if 'RANK' in os.environ:
master_process = (int(os.environ['RANK']) == 0)
host_name += ' - RANK: %s' % os.environ['RANK']
else:
master_process = True
if master_process:
contents = ['Your training has started 🎬',
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT)]
msg_template['text']['content'] = '\n'.join(contents)
requests.post(webhook_url, json=msg_template)
try:
value = func(*args, **kwargs)
if master_process:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training is complete 🎉",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'End date: %s' % end_time.strftime(DATE_FORMAT),
'Training duration: %s' % str(elapsed_time)]
try:
str_value = str(value)
contents.append('Main call returned value: %s'% str_value)
except:
contents.append('Main call returned value: %s'% "ERROR - Couldn't str the returned value.")
msg_template['text']['content'] = '\n'.join(contents)
requests.post(webhook_url, json=msg_template)
print(msg_template)
return value
except Exception as ex:
end_time = datetime.datetime.now()
elapsed_time = end_time - start_time
contents = ["Your training has crashed ☠️",
'Machine name: %s' % host_name,
'Main call: %s' % func_name,
'Starting date: %s' % start_time.strftime(DATE_FORMAT),
'Crash date: %s' % end_time.strftime(DATE_FORMAT),
'Crashed training duration: %s\n\n' % str(elapsed_time),
"Here's the error:",
'%s\n\n' % ex,
"Traceback:",
'%s' % traceback.format_exc()]
msg_template['text']['content'] = '\n'.join(contents)
requests.post(webhook_url, json=msg_template)
print(msg_template)
raise ex
return wrapper_sender
return decorator_sender
| (webhook_url: str, user_mentions: List[str] = [], user_mentions_mobile: List[str] = []) | [
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24,507 | logorestclient.service.logo_service | LogoService | null | class LogoService(TokenService):
def __init__(self, credentials):
if credentials is None:
raise LogoException("Credentials required!")
payload = {
'grant_type': credentials['GRANT_TYPE'],
'username': credentials['USER_NAME'],
'firmno': credentials['CLIENT_NUMBER'],
'password': credentials['PASSWORD']
}
super().__init__(credentials['REST_URL'], **payload)
token = self.token_dict['access_token']
self.headers = {
'Authorization': f'Bearer {token}',
'content-type': 'application/json',
'accept': 'application/json'
}
def runQuery(self, query):
res = self.connect('GET', '/api/v1/queries?tsql=' + query, headers=self.headers)
if 'error' in res:
raise LogoException(res['error'] + ' ' + res['error_description'])
if 'Message' in res and 'ModelState' in res:
if '207' in res['ModelState']:
raise LogoException(res['ModelState']['207'])
if 'LoginError' in res['ModelState']:
token_dict = self.retrieve_access_token()
self.token_dict = token_dict
return self.runQuery(query)
if 'count' in res and res['count'] == 0 or len(res['items']) == 0:
return
return res
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24,508 | logorestclient.service.logo_service | __init__ | null | def __init__(self, credentials):
if credentials is None:
raise LogoException("Credentials required!")
payload = {
'grant_type': credentials['GRANT_TYPE'],
'username': credentials['USER_NAME'],
'firmno': credentials['CLIENT_NUMBER'],
'password': credentials['PASSWORD']
}
super().__init__(credentials['REST_URL'], **payload)
token = self.token_dict['access_token']
self.headers = {
'Authorization': f'Bearer {token}',
'content-type': 'application/json',
'accept': 'application/json'
}
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24,509 | logorestclient.service.http_service | connect | null | def connect(self, method, url, request_body={}, headers=None, is_json=False):
if method == 'GET':
return self.get_request(self.REST_URL + url, headers)
return self.post_request(self.REST_URL + url, request_body, headers, is_json)
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24,510 | logorestclient.service.http_service | get_request | null | def get_request(self, url, headers):
r = requests.get(url, headers=headers)
return self.parse_result(r)
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24,511 | logorestclient.service.http_service | parse_result | null | @staticmethod
def parse_result(r):
res = r.text.encode('utf-8')
res = Serializer.loads(res)
if 'Meta' in res:
del res['Meta']
return res
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24,512 | logorestclient.service.http_service | post_request | null | def post_request(self, url, request_body, headers, is_json):
if is_json is True:
request_body = Serializer.dumps(request_body)
r = requests.post(url, data=request_body, headers=headers)
return self.parse_result(r)
| (self, url, request_body, headers, is_json) | [
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24,513 | logorestclient.service.token_service | retrieve_access_token | null | def retrieve_access_token(self):
res = self.connect('POST', '/api/v1/token', self.payloads)
if 'error' in res:
raise LogoException(res['error'] + ' ' + res['error_description'])
update_token(res)
return res
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24,514 | logorestclient.service.logo_service | runQuery | null | def runQuery(self, query):
res = self.connect('GET', '/api/v1/queries?tsql=' + query, headers=self.headers)
if 'error' in res:
raise LogoException(res['error'] + ' ' + res['error_description'])
if 'Message' in res and 'ModelState' in res:
if '207' in res['ModelState']:
raise LogoException(res['ModelState']['207'])
if 'LoginError' in res['ModelState']:
token_dict = self.retrieve_access_token()
self.token_dict = token_dict
return self.runQuery(query)
if 'count' in res and res['count'] == 0 or len(res['items']) == 0:
return
return res
| (self, query) | [
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24,521 | schedula.utils.blue | BlueDispatcher |
Blueprint object is a blueprint of how to construct or extend a Dispatcher.
**------------------------------------------------------------------------**
**Example**:
Create a BlueDispatcher::
>>> import schedula as sh
>>> blue = sh.BlueDispatcher(name='Dispatcher')
Add data/function/dispatcher nodes to the dispatcher map as usual::
>>> blue.add_data(data_id='a', default_value=3)
<schedula.utils.blue.BlueDispatcher object at ...>
>>> @sh.add_function(blue, True, True, outputs=['c'])
... def diff_function(a, b=2):
... return b - a
...
>>> blue.add_function(function=max, inputs=['c', 'd'], outputs=['e'])
<schedula.utils.blue.BlueDispatcher object at ...>
>>> from math import log
>>> sub_blue = sh.BlueDispatcher(name='Sub-Dispatcher')
>>> sub_blue.add_data(data_id='a', default_value=2).add_function(
... function=log, inputs=['a'], outputs=['b']
... )
<schedula.utils.blue.BlueDispatcher object at ...>
>>> blue.add_dispatcher(sub_blue, ('a',), {'b': 'f'})
<schedula.utils.blue.BlueDispatcher object at ...>
You can set the default values as usual::
>>> blue.set_default_value(data_id='c', value=1, initial_dist=6)
<schedula.utils.blue.BlueDispatcher object at ...>
You can also create a `Blueprint` out of `SubDispatchFunction` and add it to
the `Dispatcher` as follow::
>>> func = sh.SubDispatchFunction(sub_blue, 'func', ['a'], ['b'])
>>> blue.add_from_lists(fun_list=[
... dict(function=func, inputs=['a'], outputs=['d']),
... dict(function=func, inputs=['c'], outputs=['g']),
... ])
<schedula.utils.blue.BlueDispatcher object at ...>
Finally you can create the dispatcher object using the method `new`:
.. dispatcher:: dsp
:opt: graph_attr={'ratio': '1'}
:code:
>>> dsp = blue.register(memo={}); dsp
<schedula.dispatcher.Dispatcher object at ...>
Or dispatch, calling the Blueprint object:
.. dispatcher:: sol
:opt: graph_attr={'ratio': '1'}
:code:
>>> sol = blue({'a': 1}); sol
Solution([('a', 1), ('b', 2), ('c', 1), ('d', 0.0),
('f', 0.0), ('e', 1), ('g', 0.0)])
| class BlueDispatcher(Blueprint):
"""
Blueprint object is a blueprint of how to construct or extend a Dispatcher.
**------------------------------------------------------------------------**
**Example**:
Create a BlueDispatcher::
>>> import schedula as sh
>>> blue = sh.BlueDispatcher(name='Dispatcher')
Add data/function/dispatcher nodes to the dispatcher map as usual::
>>> blue.add_data(data_id='a', default_value=3)
<schedula.utils.blue.BlueDispatcher object at ...>
>>> @sh.add_function(blue, True, True, outputs=['c'])
... def diff_function(a, b=2):
... return b - a
...
>>> blue.add_function(function=max, inputs=['c', 'd'], outputs=['e'])
<schedula.utils.blue.BlueDispatcher object at ...>
>>> from math import log
>>> sub_blue = sh.BlueDispatcher(name='Sub-Dispatcher')
>>> sub_blue.add_data(data_id='a', default_value=2).add_function(
... function=log, inputs=['a'], outputs=['b']
... )
<schedula.utils.blue.BlueDispatcher object at ...>
>>> blue.add_dispatcher(sub_blue, ('a',), {'b': 'f'})
<schedula.utils.blue.BlueDispatcher object at ...>
You can set the default values as usual::
>>> blue.set_default_value(data_id='c', value=1, initial_dist=6)
<schedula.utils.blue.BlueDispatcher object at ...>
You can also create a `Blueprint` out of `SubDispatchFunction` and add it to
the `Dispatcher` as follow::
>>> func = sh.SubDispatchFunction(sub_blue, 'func', ['a'], ['b'])
>>> blue.add_from_lists(fun_list=[
... dict(function=func, inputs=['a'], outputs=['d']),
... dict(function=func, inputs=['c'], outputs=['g']),
... ])
<schedula.utils.blue.BlueDispatcher object at ...>
Finally you can create the dispatcher object using the method `new`:
.. dispatcher:: dsp
:opt: graph_attr={'ratio': '1'}
:code:
>>> dsp = blue.register(memo={}); dsp
<schedula.dispatcher.Dispatcher object at ...>
Or dispatch, calling the Blueprint object:
.. dispatcher:: sol
:opt: graph_attr={'ratio': '1'}
:code:
>>> sol = blue({'a': 1}); sol
Solution([('a', 1), ('b', 2), ('c', 1), ('d', 0.0),
('f', 0.0), ('e', 1), ('g', 0.0)])
"""
def __init__(self, dmap=None, name='', default_values=None, raises=False,
description='', executor=False):
kwargs = {
'dmap': dmap, 'name': name, 'default_values': default_values,
'raises': raises, 'description': description, 'executor': executor
}
super(BlueDispatcher, self).__init__(**kwargs)
def add_data(self, data_id=None, default_value=EMPTY, initial_dist=0.0,
wait_inputs=False, wildcard=None, function=None, callback=None,
description=None, filters=None, await_result=None, **kwargs):
"""
Add a single data node to the dispatcher.
:param data_id:
Data node id. If None will be assigned automatically ('unknown<%d>')
not in dmap.
:type data_id: str, optional
:param default_value:
Data node default value. This will be used as input if it is not
specified as inputs in the ArciDispatch algorithm.
:type default_value: T, optional
:param initial_dist:
Initial distance in the ArciDispatch algorithm when the data node
default value is used.
:type initial_dist: float, int, optional
:param wait_inputs:
If True ArciDispatch algorithm stops on the node until it gets all
input estimations.
:type wait_inputs: bool, optional
:param wildcard:
If True, when the data node is used as input and target in the
ArciDispatch algorithm, the input value will be used as input for
the connected functions, but not as output.
:type wildcard: bool, optional
:param function:
Data node estimation function.
This can be any function that takes only one dictionary
(key=function node id, value=estimation of data node) as input and
return one value that is the estimation of the data node.
:type function: callable, optional
:param callback:
Callback function to be called after node estimation.
This can be any function that takes only one argument that is the
data node estimation output. It does not return anything.
:type callback: callable, optional
:param description:
Data node's description.
:type description: str, optional
:param filters:
A list of functions that are invoked after the invocation of the
main function.
:type filters: list[function], optional
:param await_result:
If True the Dispatcher waits data results before assigning them to
the solution. If a number is defined this is used as `timeout` for
`Future.result` method [default: False]. Note this is used when
asynchronous or parallel execution is enable.
:type await_result: bool|int|float, optional
:param kwargs:
Set additional node attributes using key=value.
:type kwargs: keyword arguments, optional
:return:
Self.
:rtype: BlueDispatcher
"""
kwargs.update({
'data_id': data_id, 'filters': filters, 'wait_inputs': wait_inputs,
'wildcard': wildcard, 'function': function, 'callback': callback,
'initial_dist': initial_dist, 'default_value': default_value,
'description': description, 'await_result': await_result
})
self.deferred.append(('add_data', kwargs))
return self
def add_function(self, function_id=None, function=None, inputs=None,
outputs=None, input_domain=None, weight=None,
inp_weight=None, out_weight=None, description=None,
filters=None, await_domain=None, await_result=None,
**kwargs):
"""
Add a single function node to dispatcher.
:param function_id:
Function node id.
If None will be assigned as <fun.__name__>.
:type function_id: str, optional
:param function:
Data node estimation function.
:type function: callable, optional
:param inputs:
Ordered arguments (i.e., data node ids) needed by the function.
:type inputs: list, optional
:param outputs:
Ordered results (i.e., data node ids) returned by the function.
:type outputs: list, optional
:param input_domain:
A function that checks if input values satisfy the function domain.
This can be any function that takes the same inputs of the function
and returns True if input values satisfy the domain, otherwise
False. In this case the dispatch algorithm doesn't pass on the node.
:type input_domain: callable, optional
:param weight:
Node weight. It is a weight coefficient that is used by the dispatch
algorithm to estimate the minimum workflow.
:type weight: float, int, optional
:param inp_weight:
Edge weights from data nodes to the function node.
It is a dictionary (key=data node id) with the weight coefficients
used by the dispatch algorithm to estimate the minimum workflow.
:type inp_weight: dict[str, float | int], optional
:param out_weight:
Edge weights from the function node to data nodes.
It is a dictionary (key=data node id) with the weight coefficients
used by the dispatch algorithm to estimate the minimum workflow.
:type out_weight: dict[str, float | int], optional
:param description:
Function node's description. | (dmap=None, name='', default_values=None, raises=False, description='', executor=False) | [
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24,522 | schedula.utils.blue | __call__ | Calls the registered Blueprint. | def __call__(self, *args, **kwargs):
"""Calls the registered Blueprint."""
return self.register(memo={})(*args, **kwargs)
| (self, *args, **kwargs) | [
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24,523 | schedula.utils.blue | __getstate__ | null | def __getstate__(self):
d, keys = self.__dict__, ('args', 'kwargs', 'deferred', 'cls')
return {k: d[k] for k in keys if k in d}
| (self) | [
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24,524 | schedula.utils.blue | __init__ | null | def __init__(self, dmap=None, name='', default_values=None, raises=False,
description='', executor=False):
kwargs = {
'dmap': dmap, 'name': name, 'default_values': default_values,
'raises': raises, 'description': description, 'executor': executor
}
super(BlueDispatcher, self).__init__(**kwargs)
| (self, dmap=None, name='', default_values=None, raises=False, description='', executor=False) | [
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24,525 | schedula.utils.blue | _set_cls | null | def _set_cls(self, cls):
self.cls = cls
return self
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24,526 | schedula.utils.blue | add_data |
Add a single data node to the dispatcher.
:param data_id:
Data node id. If None will be assigned automatically ('unknown<%d>')
not in dmap.
:type data_id: str, optional
:param default_value:
Data node default value. This will be used as input if it is not
specified as inputs in the ArciDispatch algorithm.
:type default_value: T, optional
:param initial_dist:
Initial distance in the ArciDispatch algorithm when the data node
default value is used.
:type initial_dist: float, int, optional
:param wait_inputs:
If True ArciDispatch algorithm stops on the node until it gets all
input estimations.
:type wait_inputs: bool, optional
:param wildcard:
If True, when the data node is used as input and target in the
ArciDispatch algorithm, the input value will be used as input for
the connected functions, but not as output.
:type wildcard: bool, optional
:param function:
Data node estimation function.
This can be any function that takes only one dictionary
(key=function node id, value=estimation of data node) as input and
return one value that is the estimation of the data node.
:type function: callable, optional
:param callback:
Callback function to be called after node estimation.
This can be any function that takes only one argument that is the
data node estimation output. It does not return anything.
:type callback: callable, optional
:param description:
Data node's description.
:type description: str, optional
:param filters:
A list of functions that are invoked after the invocation of the
main function.
:type filters: list[function], optional
:param await_result:
If True the Dispatcher waits data results before assigning them to
the solution. If a number is defined this is used as `timeout` for
`Future.result` method [default: False]. Note this is used when
asynchronous or parallel execution is enable.
:type await_result: bool|int|float, optional
:param kwargs:
Set additional node attributes using key=value.
:type kwargs: keyword arguments, optional
:return:
Self.
:rtype: BlueDispatcher
| def add_data(self, data_id=None, default_value=EMPTY, initial_dist=0.0,
wait_inputs=False, wildcard=None, function=None, callback=None,
description=None, filters=None, await_result=None, **kwargs):
"""
Add a single data node to the dispatcher.
:param data_id:
Data node id. If None will be assigned automatically ('unknown<%d>')
not in dmap.
:type data_id: str, optional
:param default_value:
Data node default value. This will be used as input if it is not
specified as inputs in the ArciDispatch algorithm.
:type default_value: T, optional
:param initial_dist:
Initial distance in the ArciDispatch algorithm when the data node
default value is used.
:type initial_dist: float, int, optional
:param wait_inputs:
If True ArciDispatch algorithm stops on the node until it gets all
input estimations.
:type wait_inputs: bool, optional
:param wildcard:
If True, when the data node is used as input and target in the
ArciDispatch algorithm, the input value will be used as input for
the connected functions, but not as output.
:type wildcard: bool, optional
:param function:
Data node estimation function.
This can be any function that takes only one dictionary
(key=function node id, value=estimation of data node) as input and
return one value that is the estimation of the data node.
:type function: callable, optional
:param callback:
Callback function to be called after node estimation.
This can be any function that takes only one argument that is the
data node estimation output. It does not return anything.
:type callback: callable, optional
:param description:
Data node's description.
:type description: str, optional
:param filters:
A list of functions that are invoked after the invocation of the
main function.
:type filters: list[function], optional
:param await_result:
If True the Dispatcher waits data results before assigning them to
the solution. If a number is defined this is used as `timeout` for
`Future.result` method [default: False]. Note this is used when
asynchronous or parallel execution is enable.
:type await_result: bool|int|float, optional
:param kwargs:
Set additional node attributes using key=value.
:type kwargs: keyword arguments, optional
:return:
Self.
:rtype: BlueDispatcher
"""
kwargs.update({
'data_id': data_id, 'filters': filters, 'wait_inputs': wait_inputs,
'wildcard': wildcard, 'function': function, 'callback': callback,
'initial_dist': initial_dist, 'default_value': default_value,
'description': description, 'await_result': await_result
})
self.deferred.append(('add_data', kwargs))
return self
| (self, data_id=None, default_value=empty, initial_dist=0.0, wait_inputs=False, wildcard=None, function=None, callback=None, description=None, filters=None, await_result=None, **kwargs) | [
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24,527 | schedula.utils.blue | add_dispatcher |
Add a single sub-dispatcher node to dispatcher.
:param dsp:
Child dispatcher that is added as sub-dispatcher node to the parent
dispatcher.
:type dsp: BlueDispatcher | Dispatcher | dict[str, list]
:param inputs:
Inputs mapping. Data node ids from parent dispatcher to child
sub-dispatcher. If `None` all child dispatcher nodes are used as
inputs.
:type inputs: dict[str, str | list[str]] | tuple[str] |
(str, ..., dict[str, str | list[str]])
:param outputs:
Outputs mapping. Data node ids from child sub-dispatcher to parent
dispatcher. If `None` all child dispatcher nodes are used as
outputs.
:type outputs: dict[str, str | list[str]] | tuple[str] |
(str, ..., dict[str, str | list[str]])
:param dsp_id:
Sub-dispatcher node id.
If None will be assigned as <dsp.name>.
:type dsp_id: str, optional
:param input_domain:
A function that checks if input values satisfy the function domain.
This can be any function that takes the a dictionary with the inputs
of the sub-dispatcher node and returns True if input values satisfy
the domain, otherwise False.
.. note:: This function is invoked every time that a data node reach
the sub-dispatcher node.
:type input_domain: (dict) -> bool, optional
:param weight:
Node weight. It is a weight coefficient that is used by the dispatch
algorithm to estimate the minimum workflow.
:type weight: float, int, optional
:param inp_weight:
Edge weights from data nodes to the sub-dispatcher node.
It is a dictionary (key=data node id) with the weight coefficients
used by the dispatch algorithm to estimate the minimum workflow.
:type inp_weight: dict[str, int | float], optional
:param description:
Sub-dispatcher node's description.
:type description: str, optional
:param include_defaults:
If True the default values of the sub-dispatcher are added to the
current dispatcher.
:type include_defaults: bool, optional
:param await_domain:
If True the Dispatcher waits all input results before executing the
`input_domain` function. If a number is defined this is used as
`timeout` for `Future.result` method [default: True]. Note this is
used when asynchronous or parallel execution is enable.
:type await_domain: bool|int|float, optional
:param inputs_prefix:
Add a prefix to parent dispatcher inputs nodes.
:type inputs_prefix: str
:param outputs_prefix:
Add a prefix to parent dispatcher outputs nodes.
:type outputs_prefix: str
:param kwargs:
Set additional node attributes using key=value.
:type kwargs: keyword arguments, optional
:return:
Self.
:rtype: BlueDispatcher
| def add_dispatcher(self, dsp, inputs=None, outputs=None, dsp_id=None,
input_domain=None, weight=None, inp_weight=None,
description=None, include_defaults=False,
await_domain=None, inputs_prefix='', outputs_prefix='',
**kwargs):
"""
Add a single sub-dispatcher node to dispatcher.
:param dsp:
Child dispatcher that is added as sub-dispatcher node to the parent
dispatcher.
:type dsp: BlueDispatcher | Dispatcher | dict[str, list]
:param inputs:
Inputs mapping. Data node ids from parent dispatcher to child
sub-dispatcher. If `None` all child dispatcher nodes are used as
inputs.
:type inputs: dict[str, str | list[str]] | tuple[str] |
(str, ..., dict[str, str | list[str]])
:param outputs:
Outputs mapping. Data node ids from child sub-dispatcher to parent
dispatcher. If `None` all child dispatcher nodes are used as
outputs.
:type outputs: dict[str, str | list[str]] | tuple[str] |
(str, ..., dict[str, str | list[str]])
:param dsp_id:
Sub-dispatcher node id.
If None will be assigned as <dsp.name>.
:type dsp_id: str, optional
:param input_domain:
A function that checks if input values satisfy the function domain.
This can be any function that takes the a dictionary with the inputs
of the sub-dispatcher node and returns True if input values satisfy
the domain, otherwise False.
.. note:: This function is invoked every time that a data node reach
the sub-dispatcher node.
:type input_domain: (dict) -> bool, optional
:param weight:
Node weight. It is a weight coefficient that is used by the dispatch
algorithm to estimate the minimum workflow.
:type weight: float, int, optional
:param inp_weight:
Edge weights from data nodes to the sub-dispatcher node.
It is a dictionary (key=data node id) with the weight coefficients
used by the dispatch algorithm to estimate the minimum workflow.
:type inp_weight: dict[str, int | float], optional
:param description:
Sub-dispatcher node's description.
:type description: str, optional
:param include_defaults:
If True the default values of the sub-dispatcher are added to the
current dispatcher.
:type include_defaults: bool, optional
:param await_domain:
If True the Dispatcher waits all input results before executing the
`input_domain` function. If a number is defined this is used as
`timeout` for `Future.result` method [default: True]. Note this is
used when asynchronous or parallel execution is enable.
:type await_domain: bool|int|float, optional
:param inputs_prefix:
Add a prefix to parent dispatcher inputs nodes.
:type inputs_prefix: str
:param outputs_prefix:
Add a prefix to parent dispatcher outputs nodes.
:type outputs_prefix: str
:param kwargs:
Set additional node attributes using key=value.
:type kwargs: keyword arguments, optional
:return:
Self.
:rtype: BlueDispatcher
"""
kwargs.update({
'include_defaults': include_defaults, 'await_domain': await_domain,
'weight': weight, 'input_domain': input_domain, 'dsp_id': dsp_id,
'description': description, 'outputs': outputs, 'inputs': inputs,
'inp_weight': inp_weight, 'dsp': dsp,
'inputs_prefix': inputs_prefix, 'outputs_prefix': outputs_prefix
})
self.deferred.append(('add_dispatcher', kwargs))
return self
| (self, dsp, inputs=None, outputs=None, dsp_id=None, input_domain=None, weight=None, inp_weight=None, description=None, include_defaults=False, await_domain=None, inputs_prefix='', outputs_prefix='', **kwargs) | [
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