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 |
|---|---|---|---|---|---|---|
729,564 | collections | _replace | Return a new TuyaMessage object replacing specified fields with new values | def namedtuple(typename, field_names, *, rename=False, defaults=None, module=None):
"""Returns a new subclass of tuple with named fields.
>>> Point = namedtuple('Point', ['x', 'y'])
>>> Point.__doc__ # docstring for the new class
'Point(x, y)'
>>> p = Point(11, y=22) #... | (self, /, **kwds) | [
0.0541859045624733,
0.0014151688665151596,
-0.015421349555253983,
-0.03568440303206444,
-0.032841190695762634,
-0.03333566337823868,
0.0027891318313777447,
0.021468330174684525,
0.021015064790844917,
-0.04615073278546333,
-0.04219495505094528,
0.05707032233476639,
0.004501756746321917,
0.0... |
729,565 | tinytuya.core | XenonDevice | null | class XenonDevice(object):
def __init__(
self, dev_id, address=None, local_key="", dev_type="default", connection_timeout=5, version=3.1, persist=False, cid=None, node_id=None, parent=None, connection_retry_limit=5, connection_retry_delay=5, port=TCPPORT # pylint: disable=W0621
):
"""
... | (dev_id, address=None, local_key='', dev_type='default', connection_timeout=5, version=3.1, persist=False, cid=None, node_id=None, parent=None, connection_retry_limit=5, connection_retry_delay=5, port=6668) | [
0.027121014893054962,
-0.05033116415143013,
-0.022678779438138008,
0.03154199570417404,
-0.00004591350443661213,
-0.03995886072516441,
-0.08272334933280945,
0.04744052141904831,
-0.04569763317704201,
-0.09777168184518814,
-0.014315050095319748,
0.017513884231448174,
0.0064986287616193295,
... |
729,602 | tinytuya.core | appenddevice | null | def appenddevice(newdevice, devices):
if newdevice["ip"] in devices:
return True
devices[newdevice["ip"]] = newdevice
return False
| (newdevice, devices) | [
0.010829346254467964,
-0.01377464085817337,
-0.06788545101881027,
0.016261978074908257,
-0.024711742997169495,
-0.004388758912682533,
-0.021856242790818214,
0.011933831498026848,
0.026920713484287262,
-0.027531323954463005,
-0.01725870929658413,
-0.05908548831939697,
0.0025524392258375883,
... |
729,603 | tinytuya.core | assign_dp_mappings | Adds mappings to all the devices in the tuyadevices list
Parameters:
tuyadevices = list of devices
mappings = dict containing the mappings
Response:
Nothing, modifies tuyadevices in place
| def assign_dp_mappings( tuyadevices, mappings ):
""" Adds mappings to all the devices in the tuyadevices list
Parameters:
tuyadevices = list of devices
mappings = dict containing the mappings
Response:
Nothing, modifies tuyadevices in place
"""
if type(mappings) != dict:
... | (tuyadevices, mappings) | [
0.04867133870720863,
0.01078788097947836,
-0.050685327500104904,
-0.01459207758307457,
-0.043972037732601166,
0.018694642931222916,
-0.023496508598327637,
-0.03060140460729599,
0.0067972042597830296,
0.030265741050243378,
-0.03875059261918068,
0.004163171164691448,
-0.0024242429062724113,
... |
729,605 | tinytuya.core | bin2hex | null | def bin2hex(x, pretty=False):
if pretty:
space = " "
else:
space = ""
if IS_PY2:
result = "".join("%02X%s" % (ord(y), space) for y in x)
else:
result = "".join("%02X%s" % (y, space) for y in x)
return result
| (x, pretty=False) | [
-0.016537640243768692,
0.01622174307703972,
0.024759503081440926,
-0.00900733657181263,
0.03630255535244942,
-0.04402069002389908,
-0.005365982186049223,
0.009630593471229076,
0.06840453296899796,
-0.022881196811795235,
0.09507649391889572,
0.03362169861793518,
0.026569508016109467,
-0.017... |
729,608 | tinytuya.core | decrypt | null | def decrypt(msg, key):
return AESCipher( key ).decrypt( msg, use_base64=False, decode_text=True )
| (msg, key) | [
0.06981678307056427,
-0.030133523046970367,
0.03970114141702652,
0.054365526884794235,
-0.00046496832510456443,
-0.05940864235162735,
0.0044395532459020615,
0.025465955957770348,
0.07403726130723953,
0.030240824446082115,
0.021102407947182655,
0.027969632297754288,
-0.022139644250273705,
0... |
729,609 | tinytuya.core | decrypt_udp | null | def decrypt_udp(msg):
try:
header = parse_header(msg)
except:
header = None
if not header:
return decrypt(msg, udpkey)
if header.prefix == PREFIX_55AA_VALUE:
payload = unpack_message(msg).payload
try:
if payload[:1] == b'{' and payload[-1:] == b'}':
... | (msg) | [
0.03800623491406441,
0.032130271196365356,
-0.001140254084020853,
-0.014314848929643631,
-0.026343608275055885,
-0.03982796147465706,
0.025772085413336754,
0.04943668097257614,
0.006425161380320787,
-0.02921907976269722,
-0.001214484916999936,
0.014493449591100216,
-0.02311093360185623,
0.... |
729,610 | tinytuya.core | deviceScan | Scans your network for Tuya devices and returns dictionary of devices discovered
devices = tinytuya.deviceScan(verbose)
Parameters:
verbose = True or False, print formatted output to stdout [Default: False]
maxretry = The number of loops to wait to pick up UDP from all devices
color... | def deviceScan(verbose=False, maxretry=None, color=True, poll=True, forcescan=False, byID=False):
"""Scans your network for Tuya devices and returns dictionary of devices discovered
devices = tinytuya.deviceScan(verbose)
Parameters:
verbose = True or False, print formatted output to stdout [Def... | (verbose=False, maxretry=None, color=True, poll=True, forcescan=False, byID=False) | [
0.06054094806313515,
-0.022680792957544327,
-0.0008019910892471671,
-0.0430317297577858,
0.025593113154172897,
0.016176613047719002,
-0.04126668721437454,
-0.0452909842133522,
-0.021004002541303635,
-0.03247677907347679,
-0.024798844009637833,
0.009584179148077965,
-0.002490915823727846,
0... |
729,611 | tinytuya.core | device_info | Searches the devices.json file for devices with ID = dev_id
Parameters:
dev_id = The specific Device ID you are looking for
Response:
{dict} containing the the device info, or None if not found
| def device_info( dev_id ):
"""Searches the devices.json file for devices with ID = dev_id
Parameters:
dev_id = The specific Device ID you are looking for
Response:
{dict} containing the the device info, or None if not found
"""
devinfo = None
try:
# Load defaults
... | (dev_id) | [
0.061090197414159775,
-0.024954665452241898,
0.006229471415281296,
-0.018288441002368927,
0.029110711067914963,
-0.010242998600006104,
0.011134892702102661,
-0.006450146436691284,
-0.022380122914910316,
-0.02480754815042019,
-0.05446994677186012,
-0.024917885661125183,
-0.019382622092962265,... |
729,612 | tinytuya.core | encrypt | null | def encrypt(msg, key):
return AESCipher( key ).encrypt( msg, use_base64=False, pad=True )
| (msg, key) | [
0.002321253763511777,
-0.06916942447423935,
0.025675999000668526,
0.07603035867214203,
0.029719049111008644,
-0.04585624858736992,
-0.018079964444041252,
0.004817531444132328,
0.09024229645729065,
0.01836000196635723,
0.053802330046892166,
-0.01273298542946577,
0.001334556844085455,
0.0517... |
729,613 | tinytuya.core | error_json | Return error details in JSON | def error_json(number=None, payload=None):
"""Return error details in JSON"""
try:
spayload = json.dumps(payload)
# spayload = payload.replace('\"','').replace('\'','')
except:
spayload = '""'
vals = (error_codes[number], str(number), spayload)
log.debug("ERROR %s - %s - pay... | (number=None, payload=None) | [
-0.041698064655065536,
-0.016370024532079697,
0.009876787662506104,
0.019665231928229332,
-0.012686106376349926,
-0.009355561807751656,
-0.06752966344356537,
-0.0030765573028475046,
-0.007288326974958181,
-0.08374950289726257,
0.06092157959938049,
0.04434836655855179,
0.027351103723049164,
... |
729,614 | tinytuya.core | find_device | Scans network for Tuya devices with either ID = dev_id or IP = address
Parameters:
dev_id = The specific Device ID you are looking for
address = The IP address you are tring to find the Device ID for
Response:
{'ip':<ip>, 'version':<version>, 'id':<id>, 'product_id':<product_id>, 'data... | def find_device(dev_id=None, address=None):
"""Scans network for Tuya devices with either ID = dev_id or IP = address
Parameters:
dev_id = The specific Device ID you are looking for
address = The IP address you are tring to find the Device ID for
Response:
{'ip':<ip>, 'version':<ve... | (dev_id=None, address=None) | [
0.05377412214875221,
-0.03381526097655296,
-0.06525398790836334,
-0.013342829421162605,
-0.023000016808509827,
-0.027310002595186234,
-0.03607095405459404,
-0.01196323148906231,
-0.04048164188861847,
-0.06646239757537842,
-0.05542561039328575,
-0.015417261980473995,
-0.02624257653951645,
0... |
729,615 | tinytuya.core | has_suffix | Check to see if payload has valid Tuya suffix | def has_suffix(payload):
"""Check to see if payload has valid Tuya suffix"""
if len(payload) < 4:
return False
log.debug("buffer %r = %r", payload[-4:], SUFFIX_BIN)
return payload[-4:] == SUFFIX_BIN
| (payload) | [
0.00467224046587944,
0.013796699233353138,
-0.011216828599572182,
0.02410755306482315,
-0.01763630472123623,
0.006902663502842188,
-0.012847582809627056,
0.06747353821992874,
0.017394712194800377,
-0.0827629342675209,
0.05363369733095169,
0.05083811655640602,
0.007398792542517185,
-0.05746... |
729,616 | tinytuya.core | hex2bin | null | def hex2bin(x):
if IS_PY2:
return x.decode("hex")
else:
return bytes.fromhex(x)
| (x) | [
0.009174341335892677,
0.010345346294343472,
0.00847437884658575,
0.007263753563165665,
0.021007655188441277,
-0.029671333730220795,
-0.008553620427846909,
0.07966356724500656,
0.02585015818476677,
-0.041064418852329254,
0.0886089876294136,
0.0406770221889019,
0.004706032108515501,
0.001800... |
729,622 | tinytuya.core | pack_message | Pack a TuyaMessage into bytes. | def pack_message(msg, hmac_key=None):
"""Pack a TuyaMessage into bytes."""
if msg.prefix == PREFIX_55AA_VALUE:
header_fmt = MESSAGE_HEADER_FMT_55AA
end_fmt = MESSAGE_END_FMT_HMAC if hmac_key else MESSAGE_END_FMT_55AA
msg_len = len(msg.payload) + struct.calcsize(end_fmt)
header_da... | (msg, hmac_key=None) | [
-0.017398707568645477,
-0.003759038867428899,
-0.029345372691750526,
-0.014060527086257935,
-0.016250908374786377,
-0.03426177427172661,
-0.017389141023159027,
0.02825496345758438,
-0.029307112097740173,
-0.04939357936382294,
0.047097984701395035,
0.06025940179824829,
-0.013477062806487083,
... |
729,623 | tinytuya.core | pad | null | def pad(s):
return s + (16 - len(s) % 16) * chr(16 - len(s) % 16)
| (s) | [
-0.03781580924987793,
0.040984537452459335,
0.028031056746840477,
0.050734471529722214,
-0.011517108418047428,
-0.011351707391440868,
-0.007786888163536787,
-0.00014758198813069612,
0.04993358626961708,
0.0018977548461407423,
0.03952204808592796,
0.03330646827816963,
0.03812920302152634,
0... |
729,624 | tinytuya.core | parse_header | null | def parse_header(data):
if( data[:4] == PREFIX_6699_BIN ):
fmt = MESSAGE_HEADER_FMT_6699
else:
fmt = MESSAGE_HEADER_FMT_55AA
header_len = struct.calcsize(fmt)
if len(data) < header_len:
raise DecodeError('Not enough data to unpack header')
unpacked = struct.unpack( fmt, da... | (data) | [
-0.06376742571592331,
0.07711320370435715,
-0.03349905088543892,
-0.0363643541932106,
-0.027922285720705986,
-0.013499617576599121,
0.02742229960858822,
0.045306410640478134,
-0.03407595679163933,
-0.051344700157642365,
0.027845365926623344,
0.04676790535449982,
-0.020595571026206017,
0.00... |
729,625 | tinytuya.core | scan | Scans your network for Tuya devices with output to stdout | def scan(maxretry=None, color=True, forcescan=False):
"""Scans your network for Tuya devices with output to stdout"""
from . import scanner
scanner.scan(scantime=maxretry, color=color, forcescan=forcescan)
| (maxretry=None, color=True, forcescan=False) | [
0.021504735574126244,
-0.03920025750994682,
0.006012495141476393,
-0.006808966863900423,
0.012769518420100212,
0.04134726896882057,
-0.05672263354063034,
-0.05409081652760506,
-0.01927115209400654,
-0.030439069494605064,
0.008873732760548592,
0.0431479848921299,
0.020413914695382118,
0.003... |
729,627 | tinytuya.core | set_debug | Enable tinytuya verbose logging | def set_debug(toggle=True, color=True):
"""Enable tinytuya verbose logging"""
if toggle:
if color:
logging.basicConfig(
format="\x1b[31;1m%(levelname)s:%(message)s\x1b[0m", level=logging.DEBUG
)
else:
logging.basicConfig(format="%(levelname)s:%... | (toggle=True, color=True) | [
0.012692468240857124,
-0.027477404102683067,
0.06971221417188644,
0.04511654004454613,
0.05069645494222641,
-0.046181127429008484,
-0.0656006932258606,
0.0009917424758896232,
-0.03983030468225479,
0.003618225222453475,
-0.035994116216897964,
-0.030781300738453865,
-0.011269957758486271,
0.... |
729,631 | tinytuya.core | termcolor | null | def termcolor(color=True):
if color is False:
# Disable Terminal Color Formatting
bold = subbold = normal = dim = alert = alertdim = cyan = red = yellow = ""
else:
# Terminal Color Formatting
bold = "\033[0m\033[97m\033[1m"
subbold = "\033[0m\033[32m"
normal = "\0... | (color=True) | [
0.004861247260123491,
0.01817113533616066,
0.008312826044857502,
-0.0008886528667062521,
0.06290584802627563,
-0.01685045100748539,
-0.05608699098229408,
-0.03298904001712799,
0.037784721702337265,
0.025964118540287018,
0.009249483235180378,
-0.010668517090380192,
0.0014354260638356209,
-0... |
729,633 | tinytuya.core | unpack_message | Unpack bytes into a TuyaMessage. | def unpack_message(data, hmac_key=None, header=None, no_retcode=False):
"""Unpack bytes into a TuyaMessage."""
if header is None:
header = parse_header(data)
if header.prefix == PREFIX_55AA_VALUE:
# 4-word header plus return code
header_len = struct.calcsize(MESSAGE_HEADER_FMT_55AA)... | (data, hmac_key=None, header=None, no_retcode=False) | [
0.01750248111784458,
0.026754364371299744,
-0.01108423713594675,
-0.007134163286536932,
-0.025552822276949883,
-0.0421341210603714,
0.010333272628486156,
0.05230718478560448,
-0.008380765095353127,
-0.0434558168053627,
0.03294231370091438,
0.06924894452095032,
-0.012045471929013729,
-0.002... |
729,634 | tinytuya.core | unpad | null | def unpad(s):
return s[: -ord(s[len(s) - 1 :])]
| (s) | [
-0.044903554022312164,
0.10505086183547974,
0.024538308382034302,
0.025090118870139122,
-0.03945442661643028,
-0.0202445350587368,
-0.0035156344529241323,
0.018813278526067734,
0.03890261799097061,
-0.031660109758377075,
-0.011820808984339237,
0.025090118870139122,
-0.007863295264542103,
0... |
729,635 | avltree._avl_tree | AvlTree | Lightweight, pure-python AVL tree.
This class implements the MutableMapping interface and can be used in almost every
way that a built-in dictionary can.
# Sorting
The AVL tree data structure makes it possible to easily iterate on keys in
sort-order, and any method which returns an iterable of key... | class AvlTree(MutableMapping[_K, _V]):
"""Lightweight, pure-python AVL tree.
This class implements the MutableMapping interface and can be used in almost every
way that a built-in dictionary can.
# Sorting
The AVL tree data structure makes it possible to easily iterate on keys in
sort-order, a... | (mapping: 'Mapping[_K, _V] | None' = None) -> 'None' | [
0.053404469043016434,
-0.03112207166850567,
-0.0495571494102478,
0.02448086440563202,
0.023656439036130905,
0.01165073923766613,
-0.05367927625775337,
-0.0006501656025648117,
0.031442683190107346,
-0.06577085703611374,
-0.0508853904902935,
0.007608762942254543,
0.048137303441762924,
0.0459... |
729,636 | avltree._avl_tree | __calculate_balance | Calculates the balance factor of the given node.
Args:
node (AvlTreeNode[_K, _V]): The node.
Returns:
int: The balance factor of the given node.
| def __calculate_balance(self, node: AvlTreeNode[_K, _V]) -> int:
"""Calculates the balance factor of the given node.
Args:
node (AvlTreeNode[_K, _V]): The node.
Returns:
int: The balance factor of the given node.
"""
return (
-1
if node.greater_child_key is None
... | (self, node: avltree._avl_tree_node.AvlTreeNode[~_K, ~_V]) -> int | [
0.030179355293512344,
-0.04302047938108444,
0.045946307480335236,
0.06978636980056763,
0.006592139136046171,
-0.034568093717098236,
0.004619012586772442,
0.03404433652758598,
-0.0150806475430727,
-0.0481497086584568,
-0.010032693855464458,
0.024995947256684303,
0.053278934210538864,
-0.012... |
729,637 | avltree._avl_tree | __enforce_avl | Enforces the AVL property on this tree.
Args:
stack (list[_K]): The stack to traverse in reverse order.
| def __enforce_avl(self, stack: list[_K]) -> None:
"""Enforces the AVL property on this tree.
Args:
stack (list[_K]): The stack to traverse in reverse order.
"""
while len(stack) > 0:
key: _K = stack.pop(-1)
node: AvlTreeNode[_K, _V] = self.__nodes[key]
balance: int = self... | (self, stack: list[~_K]) -> NoneType | [
0.02208845131099224,
0.02593611739575863,
-0.06145577132701874,
0.06220392882823944,
0.03744348883628845,
-0.024404175579547882,
-0.0262389425188303,
-0.03658844903111458,
0.008750767447054386,
-0.02536609210073948,
-0.007521652150899172,
0.005143580958247185,
0.04481818154454231,
-0.02477... |
729,638 | avltree._avl_tree | __get_closer_key | Gets the next closest key to the given key.
Args:
key (_K): The key to search for.
current_key (_K): The current key.
Returns:
_K: The next closest key to the given key.
Raises:
KeyError: If the given key is not present in this tree.
| def __get_closer_key(self, key: _K, current_key: _K) -> _K:
"""Gets the next closest key to the given key.
Args:
key (_K): The key to search for.
current_key (_K): The current key.
Returns:
_K: The next closest key to the given key.
Raises:
KeyError: If the given key is n... | (self, key: ~_K, current_key: ~_K) -> ~_K | [
0.06842037290334702,
-0.03576922044157982,
-0.06508971005678177,
0.06785345077514648,
-0.010505769401788712,
0.011329577304422855,
0.03421018645167351,
-0.0014361280482262373,
0.04623955860733986,
-0.02997598983347416,
-0.04868440702557564,
-0.05956222116947174,
0.05304262042045593,
-0.003... |
729,639 | avltree._avl_tree | __rotate | Performs a rotation at the given key.
Args:
key (_K): The key to perform a right rotation on.
direction (Literal["left", "right"]): The direction of the rotation.
Returns:
_K: The new root key of this subtree.
Raises:
ValueError: If the shape of... | def __rotate(self, key: _K, direction: Literal["left", "right"]) -> _K:
"""Performs a rotation at the given key.
Args:
key (_K): The key to perform a right rotation on.
direction (Literal["left", "right"]): The direction of the rotation.
Returns:
_K: The new root key of this subtree.... | (self, key: ~_K, direction: Literal['left', 'right']) -> ~_K | [
0.050574298948049545,
0.007131932303309441,
0.02840377204120159,
0.0688844621181488,
0.030705824494361877,
-0.006999121513217688,
-0.03472556173801422,
0.043809808790683746,
0.044943127781152725,
-0.04005569592118263,
0.01885911263525486,
0.02208198606967926,
0.06548450887203217,
0.0435264... |
729,640 | avltree._avl_tree | __update_height | Updates the height of the given node.
Args:
node (AvlTreeNode[_K, _V]): The node.
| def __update_height(self, node: AvlTreeNode[_K, _V]) -> None:
"""Updates the height of the given node.
Args:
node (AvlTreeNode[_K, _V]): The node.
"""
node.height = 1 + max(
(
-1
if node.greater_child_key is None
else self.__nodes[node.greater_child_ke... | (self, node: avltree._avl_tree_node.AvlTreeNode[~_K, ~_V]) -> NoneType | [
0.05324268341064453,
-0.023579925298690796,
0.02232757769525051,
0.05653456971049309,
-0.03957419842481613,
-0.010394489392638206,
-0.028177831321954727,
0.03118346631526947,
-0.023293673992156982,
-0.020431164652109146,
-0.024420786648988724,
-0.03567402809858322,
0.04991501569747925,
0.0... |
729,642 | avltree._avl_tree | __delitem__ | Deletes the given key from this tree.
This method has an amortized and worst-case time complexity of O[log(n)].
Example usage:
```
>>> from avltree import AvlTree
>>> avl_tree = AvlTree[int, str]({0: 'a', 1: 'b'})
>>> del avl_tree[0]
>>> avl_tree
AvlTree... | def __delitem__(self, __k: _K) -> None: # noqa: C901, PLR0912
"""Deletes the given key from this tree.
This method has an amortized and worst-case time complexity of O[log(n)].
Example usage:
```
>>> from avltree import AvlTree
>>> avl_tree = AvlTree[int, str]({0: 'a', 1: 'b'})
>>> del avl_... | (self, _AvlTree__k: ~_K) -> NoneType | [
0.05854947865009308,
-0.01511321309953928,
-0.04928086698055267,
0.008989309892058372,
-0.00970824807882309,
-0.010592697188258171,
-0.042991455644369125,
0.04007432609796524,
0.0547427274286747,
-0.04870158061385155,
-0.02768169716000557,
-0.009940997697412968,
0.03597792983055115,
0.0136... |
729,644 | avltree._avl_tree | __getitem__ | Gets the value associated with the given key.
This method has an amortized and worst-case time complexity of O[log(n)].
Example usage:
```
>>> from avltree import AvlTree
>>> avl_tree = AvlTree[int, str]({0: 'a', 1: 'b'})
>>> avl_tree[0]
'a'
>>> avl_tree... | def __getitem__(self, __k: _K) -> _V:
"""Gets the value associated with the given key.
This method has an amortized and worst-case time complexity of O[log(n)].
Example usage:
```
>>> from avltree import AvlTree
>>> avl_tree = AvlTree[int, str]({0: 'a', 1: 'b'})
>>> avl_tree[0]
'a'
>... | (self, _AvlTree__k: ~_K) -> ~_V | [
0.07337706536054611,
-0.05779154598712921,
-0.06947120279073715,
0.04979022219777107,
0.059990961104631424,
0.021577028557658195,
0.0063090999610722065,
-0.04497426003217697,
0.08410869538784027,
-0.062076617032289505,
-0.059422146528959274,
-0.010039574466645718,
0.050852011889219284,
-0.... |
729,645 | avltree._avl_tree | __init__ | Constructor.
Inserting the elements of a passed-in mapping has an amortized and worst-case
time complexity of O[n*log(n)].
Example usage:
```
>>> from avltree import AvlTree
>>> avl_tree = AvlTree[int, str]({0: 'a', 1: 'b'})
>>> avl_tree
AvlTree({0: 'a',... | def __init__(self, mapping: Mapping[_K, _V] | None = None) -> None:
"""Constructor.
Inserting the elements of a passed-in mapping has an amortized and worst-case
time complexity of O[n*log(n)].
Example usage:
```
>>> from avltree import AvlTree
>>> avl_tree = AvlTree[int, str]({0: 'a', 1: 'b... | (self, mapping: Optional[Mapping[~_K, ~_V]] = None) -> NoneType | [
0.006278782617300749,
-0.0005788328126072884,
-0.00121075299102813,
0.0007329670479521155,
0.010723640210926533,
0.03928462043404579,
-0.016708029434084892,
-0.0023672122042626143,
0.005067426711320877,
-0.048338424414396286,
-0.03826148435473442,
0.04335786774754524,
0.014111576601862907,
... |
729,646 | avltree._avl_tree | __iter__ | Iterates over all keys contained in this tree in sort order.
Getting the first key has an amortized and worst-case time complexity of
O[log(n)]. Iterating over all keys has an amortized and worst-case time
complexity of O[n].
Example usage:
```
>>> from avltree import A... | def __iter__(self) -> Iterator[_K]:
"""Iterates over all keys contained in this tree in sort order.
Getting the first key has an amortized and worst-case time complexity of
O[log(n)]. Iterating over all keys has an amortized and worst-case time
complexity of O[n].
Example usage:
```
>>> from... | (self) -> Iterator[~_K] | [
0.01625014655292034,
-0.007285820320248604,
-0.07769082486629486,
-0.0032601740676909685,
0.039361875504255295,
0.016277814283967018,
-0.008291078731417656,
-0.02209724672138691,
0.0733746662735939,
-0.046592358499765396,
-0.028239469975233078,
-0.011537418700754642,
0.012902357615530491,
... |
729,647 | avltree._avl_tree | __len__ | Returns the number of items contained in this tree.
This method has an amortized and worst-case time complexity of O[1].
Example usage:
```
>>> from avltree import AvlTree
>>> avl_tree = AvlTree[int, str]({0: 'a', 1: 'b'})
>>> len(avl_tree)
2
```
... | def __len__(self) -> int:
"""Returns the number of items contained in this tree.
This method has an amortized and worst-case time complexity of O[1].
Example usage:
```
>>> from avltree import AvlTree
>>> avl_tree = AvlTree[int, str]({0: 'a', 1: 'b'})
>>> len(avl_tree)
2
```
Retu... | (self) -> int | [
-0.043786048889160156,
-0.026344604790210724,
0.008355837315320969,
0.01251551229506731,
0.03050428070127964,
0.06068016588687897,
-0.026964908465743065,
-0.036087002605199814,
0.0323469415307045,
-0.029920466244220734,
-0.012086773291230202,
-0.02601620927453041,
0.022330883890390396,
0.0... |
729,648 | avltree._avl_tree | __repr__ | Builds a developer-friendly string representation of this AvlTree.
Example usage:
```
>>> from avltree import AvlTree
>>> avl_tree = AvlTree[int, str]({0: 'a', 1: 'b'})
>>> repr(avl_tree)
"AvlTree({0: 'a', 1: 'b'})"
```
Returns:
str: A string... | def __repr__(self) -> str:
"""Builds a developer-friendly string representation of this AvlTree.
Example usage:
```
>>> from avltree import AvlTree
>>> avl_tree = AvlTree[int, str]({0: 'a', 1: 'b'})
>>> repr(avl_tree)
"AvlTree({0: 'a', 1: 'b'})"
```
Returns:
str: A string rep... | (self) -> str | [
0.034442782402038574,
-0.030415276065468788,
0.06478206813335419,
-0.022664224728941917,
0.035829611122608185,
-0.042706768959760666,
-0.01884569227695465,
-0.05927274376153946,
0.029009448364377022,
-0.046962250024080276,
-0.039211198687553406,
-0.0017074159113690257,
-0.008221243508160114,... |
729,649 | avltree._avl_tree | __setitem__ | Maps the given key to the given value in this tree.
This method has an amortized and worst-case time complexity of O[log(n)].
Example usage:
```
>>> from avltree import AvlTree
>>> avl_tree = AvlTree[int, str]({0: 'a', 1: 'b'})
>>> avl_tree[0] = 'foo'
>>> avl_tr... | def __setitem__(self, __k: _K, __v: _V) -> None:
"""Maps the given key to the given value in this tree.
This method has an amortized and worst-case time complexity of O[log(n)].
Example usage:
```
>>> from avltree import AvlTree
>>> avl_tree = AvlTree[int, str]({0: 'a', 1: 'b'})
>>> avl_tree... | (self, _AvlTree__k: ~_K, _AvlTree__v: ~_V) -> NoneType | [
0.05582147464156151,
-0.008941666223108768,
-0.0482550784945488,
0.04234865680336952,
0.039086613804101944,
0.03223439306020737,
-0.026366574689745903,
-0.0272158645093441,
-0.00037669119774363935,
-0.052385713905096054,
-0.0374845452606678,
-0.011368895880877972,
0.05887119472026825,
0.02... |
729,650 | avltree._avl_tree | between | Iterates over all keys between the given start and stop in sort order.
Getting the first key has an amortized and worst-case time complexity of
O[log(n)]. Iterating over all keys has an amortized and worst-case time
complexity of O[k], where k is the number of items in only the interval between... | def between( # noqa: C901, PLR0912
self,
start: _K | None = None,
stop: _K | None = None,
treatment: Literal["inclusive", "exclusive"] = "inclusive",
) -> Iterator[_K]:
"""Iterates over all keys between the given start and stop in sort order.
Getting the first key has an amortized and worst-cas... | (self, start: Optional[~_K] = None, stop: Optional[~_K] = None, treatment: Literal['inclusive', 'exclusive'] = 'inclusive') -> Iterator[~_K] | [
0.03893772512674332,
0.0026554346550256014,
-0.07214687019586563,
-0.016998931765556335,
0.012266629375517368,
0.03800371661782265,
-0.010538715869188309,
-0.016978176310658455,
-0.012526075355708599,
-0.06953164935112,
-0.03266949951648712,
0.021668968722224236,
0.06529748439788818,
0.023... |
729,655 | avltree._avl_tree | maximum | Gets the maximum key contained in this tree.
This method has an amortized and worst-case time complexity of O[log(n)].
Example usage:
```
>>> from avltree import AvlTree
>>> avl_tree = AvlTree[int, str]({0: 'a', 1: 'b'})
>>> avl_tree.maximum()
1
```
... | def maximum(self) -> _K:
"""Gets the maximum key contained in this tree.
This method has an amortized and worst-case time complexity of O[log(n)].
Example usage:
```
>>> from avltree import AvlTree
>>> avl_tree = AvlTree[int, str]({0: 'a', 1: 'b'})
>>> avl_tree.maximum()
1
```
Re... | (self) -> ~_K | [
0.0841929167509079,
0.01955130323767662,
-0.011482511647045612,
0.04403150826692581,
0.023421403020620346,
-0.0032311677932739258,
0.006161124911159277,
-0.025027858093380928,
0.045710984617471695,
-0.06349153071641922,
-0.029719442129135132,
0.0027679423801600933,
0.006832003127783537,
-0... |
729,656 | avltree._avl_tree | minimum | Gets the minimum key contained in this tree.
This method has an amortized and worst-case time complexity of O[log(n)].
Example usage:
```
>>> from avltree import AvlTree
>>> avl_tree = AvlTree[int, str]({0: 'a', 1: 'b'})
>>> avl_tree.minimum()
0
```
... | def minimum(self) -> _K:
"""Gets the minimum key contained in this tree.
This method has an amortized and worst-case time complexity of O[log(n)].
Example usage:
```
>>> from avltree import AvlTree
>>> avl_tree = AvlTree[int, str]({0: 'a', 1: 'b'})
>>> avl_tree.minimum()
0
```
Re... | (self) -> ~_K | [
0.06188405677676201,
0.007775749545544386,
0.014675106853246689,
0.040564462542533875,
0.06825131922960281,
0.02173096314072609,
0.06635545194149017,
-0.01724168471992016,
0.05501599982380867,
-0.04392695054411888,
-0.03625404089689255,
-0.03852550685405731,
0.0267746914178133,
-0.00444903... |
729,665 | allpairspy.allpairs | AllPairs | null | class AllPairs:
def __init__(self, parameters, filter_func=lambda x: True, previously_tested=None, n=2):
"""
TODO: check that input arrays are:
- (optional) has no duplicated values inside single array / or compress such values
"""
if not previously_tested:
p... | (parameters, filter_func=<function AllPairs.<lambda> at 0x7f625a34cca0>, previously_tested=None, n=2) | [
0.06454934924840927,
-0.0011813208693638444,
-0.1150873601436615,
0.013100196607410908,
0.0013958188937976956,
-0.04887770488858223,
-0.05665278434753418,
-0.02318350225687027,
0.03195071220397949,
-0.02917679026722908,
-0.039908017963171005,
0.03101932257413864,
-0.0038900701329112053,
0.... |
729,666 | allpairspy.allpairs | __extract_param_name_list | null | def __extract_param_name_list(self, parameters):
if not self.__is_ordered_dict_param:
return []
return list(parameters)
| (self, parameters) | [
0.020596181973814964,
0.04070114344358444,
-0.013491025194525719,
-0.05024486035108566,
0.007956020534038544,
0.02440314181149006,
0.007631464395672083,
-0.010534930042922497,
0.0711568295955658,
0.015464680269360542,
-0.008618291467428207,
-0.03957835212349892,
-0.04277128726243973,
-0.04... |
729,667 | allpairspy.allpairs | __extract_value_matrix | null | def __extract_value_matrix(self, parameters):
if not self.__is_ordered_dict_param:
return parameters
return [v for v in parameters.values()]
| (self, parameters) | [
0.07692839205265045,
0.017264002934098244,
0.0034161144867539406,
-0.04647469520568848,
0.01014260109513998,
0.00022996190818957984,
-0.014622610062360764,
-0.002995304297655821,
0.06128720939159393,
0.06253021955490112,
-0.03290518745779991,
0.03440715745091438,
-0.03725571557879448,
-0.0... |
729,668 | allpairspy.allpairs | __get_iteration_value | null | def __get_iteration_value(self, item_list):
if not self.__param_name_list:
return [item.value for item in item_list]
return self.__pairs_class(*[item.value for item in item_list])
| (self, item_list) | [
0.07912025600671768,
-0.037362340837717056,
-0.06806043535470963,
-0.013957706280052662,
0.0005799094797112048,
0.0006746224826201797,
0.026249349117279053,
-0.021056197583675385,
0.09819135814905167,
0.012717021629214287,
0.0078163156285882,
0.03286042809486389,
0.012504332698881626,
0.00... |
729,669 | allpairspy.allpairs | __get_values | null | @staticmethod
def __get_values(item_list):
return [item.value for item in item_list]
| (item_list) | [
0.06310777366161346,
-0.0922045186161995,
-0.07254742085933685,
-0.02674567513167858,
-0.00929823238402605,
0.00833924114704132,
0.02107127755880356,
-0.05253677815198898,
0.1138414740562439,
0.00891817081719637,
-0.009377779439091682,
0.042354684323072433,
0.02361680194735527,
-0.01302813... |
729,670 | allpairspy.allpairs | __get_working_item_matrix | null | def __get_working_item_matrix(self, parameter_matrix):
return [
[
Item(f"a{param_idx:d}v{value_idx:d}", value)
for value_idx, value in enumerate(value_list)
]
for param_idx, value_list in enumerate(parameter_matrix)
]
| (self, parameter_matrix) | [
0.07411634176969528,
-0.04497181624174118,
-0.041102148592472076,
-0.0069287968799471855,
-0.010214528068900108,
-0.029806900769472122,
-0.005303362384438515,
-0.0042771161533892155,
0.05030568316578865,
0.05567441135644913,
-0.025658337399363518,
0.04929468780755997,
-0.03688386082649231,
... |
729,671 | allpairspy.allpairs | __resort_working_array | null | def __resort_working_array(self, chosen_item_list, num):
for item in self.__working_item_matrix[num]:
data_node = self.__pairs.get_node_info(item)
new_combs = [
# numbers of new combinations to be created if this item is
# appended to array
{key(z) for z in combin... | (self, chosen_item_list, num) | [
0.03783199191093445,
0.01029890961945057,
-0.08731015771627426,
0.03826601058244705,
0.011429167352616787,
-0.05598845332860947,
-0.014123701490461826,
-0.01528108585625887,
0.012478046119213104,
-0.02652941271662712,
-0.0363490916788578,
0.014548678882420063,
-0.0031782849691808224,
-0.00... |
729,672 | allpairspy.allpairs | __validate_parameter | null | def __validate_parameter(self, value):
if isinstance(value, OrderedDict):
for parameter_list in value.values():
if not parameter_list:
raise ValueError("each parameter arrays must have at least one item")
return
if len(value) < 2:
raise ValueError("must provid... | (self, value) | [
0.05088719353079796,
0.01629222184419632,
-0.03709080070257187,
-0.010997248813509941,
-0.01699417270720005,
-0.030279265716671944,
-0.04177048057317734,
-0.03402300924062729,
0.032948415726423264,
0.0040557230822741985,
0.004179214593023062,
0.026726175099611282,
-0.0024568322114646435,
-... |
729,673 | allpairspy.allpairs | __init__ |
TODO: check that input arrays are:
- (optional) has no duplicated values inside single array / or compress such values
| def __init__(self, parameters, filter_func=lambda x: True, previously_tested=None, n=2):
"""
TODO: check that input arrays are:
- (optional) has no duplicated values inside single array / or compress such values
"""
if not previously_tested:
previously_tested = [[]]
self.__validate_p... | (self, parameters, filter_func=<function AllPairs.<lambda> at 0x7f625a34cca0>, previously_tested=None, n=2) | [
0.045276153832674026,
0.01676124706864357,
-0.08034816384315491,
0.018679248169064522,
0.012528417631983757,
-0.037434082478284836,
-0.07483036816120148,
-0.02885504439473152,
-0.00574455363675952,
-0.02227904088795185,
-0.0339004248380661,
0.07607754319906235,
-0.013577176257967949,
0.020... |
729,675 | allpairspy.allpairs | __next__ | null | def __next__(self):
assert len(self.__pairs) <= self.__max_unique_pairs_expected
if len(self.__pairs) == self.__max_unique_pairs_expected:
# no reasons to search further - all pairs are found
raise StopIteration()
previous_unique_pairs_count = len(self.__pairs)
chosen_item_list = [None] ... | (self) | [
0.02988700196146965,
-0.03553081676363945,
-0.0936368927359581,
0.01593262329697609,
-0.017746014520525932,
-0.03576355054974556,
-0.0269390307366848,
0.015447760000824928,
0.05166708305478096,
-0.006051099859178066,
-0.023894086480140686,
0.018579980358481407,
0.009663335047662258,
0.0699... |
729,679 | scs | SCS | null | class SCS(object):
def __init__(self, data, cone, **settings):
"""Initialize the SCS solver.
@param data Dictionary containing keys `P`, `A`, `b`, `c`.
@param cone Dictionary containing cone information.
@param settings Settings as kwargs, see docs.
"""
self... | (data, cone, **settings) | [
-0.008927764371037483,
-0.03765592351555824,
0.005834599491208792,
0.029255757108330727,
-0.029441967606544495,
-0.015186510048806667,
-0.03422137349843979,
-0.02702122926712036,
0.05664940923452377,
-0.04978030547499657,
-0.055697664618492126,
0.0020871106535196304,
-0.015858937054872513,
... |
729,680 | scs | __init__ | Initialize the SCS solver.
@param data Dictionary containing keys `P`, `A`, `b`, `c`.
@param cone Dictionary containing cone information.
@param settings Settings as kwargs, see docs.
| def __init__(self, data, cone, **settings):
"""Initialize the SCS solver.
@param data Dictionary containing keys `P`, `A`, `b`, `c`.
@param cone Dictionary containing cone information.
@param settings Settings as kwargs, see docs.
"""
self._settings = settings
if not data or not cone... | (self, data, cone, **settings) | [
-0.0257708877325058,
-0.014535893686115742,
0.017488807439804077,
0.027142947539687157,
-0.017031453549861908,
-0.01926851086318493,
-0.013690783642232418,
-0.02585042640566826,
0.06852351874113083,
-0.04227539151906967,
-0.041639070957899094,
0.0162559412419796,
-0.01573893241584301,
0.02... |
729,681 | scs | solve | Solve the optimization problem.
@param warm_start Whether to warm-start. By default the solution of
the previous problem is used as the warm-start. The
warm-start can be overriden to another value by
passing `x`, `y`, `s` arg... | def solve(self, warm_start=True, x=None, y=None, s=None):
"""Solve the optimization problem.
@param warm_start Whether to warm-start. By default the solution of
the previous problem is used as the warm-start. The
warm-start can be overriden to another value by
... | (self, warm_start=True, x=None, y=None, s=None) | [
0.03564241901040077,
-0.06699838489294052,
0.03484996780753136,
0.03222046047449112,
-0.024476023390889168,
-0.014183125458657742,
-0.05125736817717552,
-0.025736745446920395,
-0.0239357128739357,
-0.002940184436738491,
-0.029735036194324493,
0.018676700070500374,
-0.034111544489860535,
0.... |
729,682 | scs | update | Update the `b` vector, `c` vector, or both, before another solve.
After a solve we can reuse the SCS workspace in another solve if the
only problem data that has changed are the `b` and `c` vectors.
@param b New `b` vector.
@param c New `c` vector.
| def update(self, b=None, c=None):
"""Update the `b` vector, `c` vector, or both, before another solve.
After a solve we can reuse the SCS workspace in another solve if the
only problem data that has changed are the `b` and `c` vectors.
@param b New `b` vector.
@param c New `c` vector.
"""
... | (self, b=None, c=None) | [
-0.029297102242708206,
-0.026761775836348534,
-0.03655095398426056,
0.05922803655266762,
-0.08429959416389465,
-0.0012621610658243299,
-0.07479212433099747,
-0.010704710148274899,
0.027061086148023605,
-0.01656765304505825,
-0.03774819150567055,
-0.046586617827415466,
-0.04415693134069443,
... |
729,684 | scs | _select_scs_module | null | def _select_scs_module(stgs):
if stgs.pop("gpu", False): # False by default
if not stgs.pop("use_indirect", _USE_INDIRECT_DEFAULT):
raise NotImplementedError(
"GPU direct solver not yet available, pass `use_indirect=True`."
)
import _scs_gpu
return _... | (stgs) | [
0.04614492505788803,
-0.04244918376207352,
0.009878329932689667,
0.01227019727230072,
-0.016656728461384773,
0.017053933814167976,
0.015413302928209305,
0.033434346318244934,
0.02340058796107769,
-0.0156723503023386,
-0.00969699677079916,
-0.004280753433704376,
-0.0605824813246727,
0.00228... |
729,685 | scs | solve | null | def solve(data, cone, **settings):
solver = SCS(data, cone, **settings)
# Hack out the warm start data from old API
x = y = s = None
if "x" in data:
x = data["x"]
if "y" in data:
y = data["y"]
if "s" in data:
s = data["s"]
return solver.solve(warm_start=True, x=x, y... | (data, cone, **settings) | [
0.017293576151132584,
-0.06231260672211647,
0.005333492066711187,
0.01896546222269535,
-0.015325626358389854,
0.01686689630150795,
-0.01450709905475378,
-0.06684063374996185,
0.06144183129072189,
-0.0517936535179615,
-0.035039953887462616,
0.01938343420624733,
-0.07182145863771439,
-0.0179... |
729,687 | aiconfig_extension_groq.groq | GroqParser | null | class GroqParser(DefaultOpenAIParser):
def __init__(self, model: str):
super().__init__(model_id = model)
# "Model" field is a custom name for the specific model they want to use
# when registering the Groq model parser. See the cookbook for reference:
# https://github.com/lastmile-... | (model: str) | [
-0.009592128917574883,
-0.03497662395238876,
-0.14245952665805817,
-0.022466735914349556,
0.005092399660497904,
0.009355061687529087,
0.016011197119951248,
0.045261722058057785,
0.009619483724236488,
-0.04048389196395874,
0.03433836251497269,
0.028046948835253716,
-0.004337885417044163,
0.... |
729,688 | aiconfig_extension_groq.groq | __init__ | null | def __init__(self, model: str):
super().__init__(model_id = model)
# "Model" field is a custom name for the specific model they want to use
# when registering the Groq model parser. See the cookbook for reference:
# https://github.com/lastmile-ai/aiconfig/blob/main/cookbooks/Groq/aiconfig_model_registry... | (self, model: str) | [
0.013730534352362156,
0.010530184023082256,
-0.02055356837809086,
0.003730613272637129,
0.007099896669387817,
-0.0021409967448562384,
0.027798935770988464,
0.0389673113822937,
0.021060368046164513,
-0.008789231069386005,
-0.010990058071911335,
0.051092978566884995,
0.018732840195298195,
0.... |
729,690 | aiconfig.model_parser | get_model_settings |
Extracts the AI model's settings from the configuration. If both prompt and config level settings are defined, merge them with prompt settings taking precedence.
Args:
prompt: The prompt object.
Returns:
dict: The settings of the model used by the prompt.
| def get_model_settings(
self, prompt: Prompt, aiconfig: "AIConfigRuntime"
) -> Dict[str, Any]:
"""
Extracts the AI model's settings from the configuration. If both prompt and config level settings are defined, merge them with prompt settings taking precedence.
Args:
prompt: The prompt object.
... | (self, prompt: aiconfig.schema.Prompt, aiconfig: 'AIConfigRuntime') -> Dict[str, Any] | [
-0.024231255054473877,
-0.027353648096323013,
-0.045657966285943985,
-0.057810988277196884,
0.014434050768613815,
0.00012905281619168818,
-0.012498915195465088,
-0.04087154567241669,
0.07101104408502579,
-0.015696095302700996,
-0.02079101651906967,
-0.009787856601178646,
-0.04393784701824188... |
729,691 | aiconfig.default_parsers.openai | get_output_text | null | def get_output_text(
self,
prompt: Prompt,
aiconfig: "AIConfigRuntime",
output: Optional[Output] = None,
) -> str:
if not output:
output = aiconfig.get_latest_output(prompt)
if not output:
return ""
if output.output_type == "execute_result":
output_data = output.data
... | (self, prompt: aiconfig.schema.Prompt, aiconfig: 'AIConfigRuntime', output: Union[aiconfig.schema.ExecuteResult, aiconfig.schema.Error, NoneType] = None) -> str | [
0.015308971516788006,
-0.051072556525468826,
0.012164919637143612,
-0.04818441718816757,
0.03911785036325455,
-0.007686474360525608,
-0.014267046935856342,
0.028790006414055824,
0.07567659020423889,
-0.08189157396554947,
0.051255349069833755,
0.0420059897005558,
-0.03937375918030739,
-0.00... |
729,692 | aiconfig.default_parsers.openai | get_prompt_template |
Returns a template for a prompt.
| def get_prompt_template(
self, prompt: Prompt, aiconfig: "AIConfigRuntime"
) -> str:
"""
Returns a template for a prompt.
"""
if isinstance(prompt.input, str):
return prompt.input
elif isinstance(prompt.input, PromptInput) and isinstance(
prompt.input.data, str
):
ret... | (self, prompt: aiconfig.schema.Prompt, aiconfig: 'AIConfigRuntime') -> str | [
0.03799542784690857,
-0.028407461941242218,
0.04954375699162483,
-0.10493296384811401,
0.035429131239652634,
0.0032657890114933252,
0.013392853550612926,
-0.0017999709816649556,
0.07884228974580765,
-0.04220129922032356,
0.040739938616752625,
0.049472469836473465,
-0.0758482813835144,
0.01... |
729,693 | aiconfig.default_parsers.openai | id | null | def id(self) -> str:
return self.model_id
| (self) -> str | [
-0.014817651361227036,
0.009814174845814705,
0.033403243869543076,
0.028443582355976105,
0.048404913395643234,
-0.024868417531251907,
0.05313674733042717,
0.06274061650037766,
0.0007513977470807731,
-0.002567458199337125,
-0.08005562424659729,
-0.03617224469780922,
-0.0008888619486242533,
... |
729,694 | aiconfig_extension_groq.groq | initialize_openai_client | null | def initialize_openai_client(self) -> None:
# Initialize Groq Client
self.client = Groq(
api_key=os.getenv("GROQ_API_KEY"),
)
| (self) -> NoneType | [
-0.06803854554891586,
-0.061305757611989975,
-0.09268802404403687,
-0.017916692420840263,
-0.00826636515557766,
0.008359876461327076,
0.003151318058371544,
0.07088127732276917,
0.022087279707193375,
-0.02270445041358471,
0.006629924289882183,
0.016719752922654152,
0.02016095444560051,
0.03... |
729,695 | aiconfig.default_parsers.parameterized_model_parser | resolve_prompt_template |
Resolves a templated string with the provided parameters (applied from the AIConfig as well as passed in params).
Args:
prompt_template (str): The template string to resolve.
prompt (Prompt): The prompt object that the template string belongs to (if any).
ai_config ... | def resolve_prompt_template(
prompt_template: str,
prompt: Prompt,
ai_config: "AIConfigRuntime",
params: Optional[JSONObject] = {},
):
"""
Resolves a templated string with the provided parameters (applied from the AIConfig as well as passed in params).
Args:
prompt_template (str): Th... | (prompt_template: str, prompt: aiconfig.schema.Prompt, ai_config: 'AIConfigRuntime', params: Optional[Dict[str, Any]] = {}) | [
0.034879740327596664,
-0.013875006698071957,
0.003842275822535157,
-0.11330672353506088,
0.02221049554646015,
-0.0029357695020735264,
0.0015814710641279817,
0.007522909436374903,
0.0494537390768528,
-0.07444272935390472,
0.033901147544384,
0.05703780800104141,
-0.08073366433382034,
0.01352... |
729,696 | aiconfig.default_parsers.parameterized_model_parser | run | null | @abstractmethod
async def run_inference(self) -> List[Output]:
pass
| (self, prompt: aiconfig.schema.Prompt, aiconfig: aiconfig.schema.AIConfig, options: Optional[aiconfig.model_parser.InferenceOptions] = None, parameters: Dict = {}, run_with_dependencies: Optional[bool] = False) -> List[Union[aiconfig.schema.ExecuteResult, aiconfig.schema.Error]] | [
0.007228159345686436,
-0.07212400436401367,
-0.06545569002628326,
0.017699245363473892,
-0.03851700574159622,
0.022576075047254562,
-0.0342705138027668,
-0.04037484526634216,
0.01635562814772129,
-0.003578830510377884,
0.04697681590914726,
0.027369966730475426,
-0.008468101732432842,
0.028... |
729,697 | aiconfig.model_parser | run_batch |
Concurrently runs inference on multiple parameter sets, one set at a time.
Default implementation for the run_batch method. Model Parsers may choose to override this method if they need to implement custom batch execution logic.
For each dictionary of parameters in `params_list``, the `run` met... | @abstractmethod
async def run(
self,
prompt: Prompt,
aiconfig: AIConfig,
options: Optional["InferenceOptions"] = None,
parameters: Dict = {},
run_with_dependencies: Optional[bool] = False,
) -> ExecuteResult:
"""
Execute model inference based on completion data to be constructed in deser... | (self, prompt: aiconfig.schema.Prompt, aiconfig: 'AIConfigRuntime', parameters_list: list[dict[str, typing.Any]], options: Optional[ForwardRef('InferenceOptions')] = None, **kwargs: Any) -> list['AIConfigRuntime'] | [
0.020260704681277275,
-0.031360045075416565,
-0.0735023096203804,
-0.021828705444931984,
0.019696928560733795,
-0.0006964617059566081,
-0.04348123073577881,
-0.045524921268224716,
0.03178287670016289,
-0.020771626383066177,
0.043269816786050797,
0.009593002498149872,
-0.021722998470067978,
... |
729,698 | aiconfig.default_parsers.openai | run_inference |
Invoked to run a prompt in the .aiconfig. This method should perform
the actual model inference based on the provided prompt and inference settings.
Args:
prompt (str): The input prompt.
inference_settings (dict): Model-specific inference settings.
Returns:
... | @abstractmethod
def id(self) -> str:
"""
Returns an identifier for the model (e.g. gpt-3.5, gpt-4, etc.).
"""
return self.id
| (self, prompt: aiconfig.schema.Prompt, aiconfig: 'AIConfigRuntime', options: aiconfig.model_parser.InferenceOptions, parameters) -> List[Union[aiconfig.schema.ExecuteResult, aiconfig.schema.Error]] | [
0.012052255682647228,
-0.038461651653051376,
0.007213759236037731,
0.03598082438111305,
0.0004898977931588888,
-0.07090597599744797,
0.015940647572278976,
0.013363048434257507,
0.014251573011279106,
-0.0016648827586323023,
-0.03140624240040779,
-0.008256235159933567,
0.01692594215273857,
0... |
729,699 | aiconfig.default_parsers.parameterized_model_parser | run_with_dependencies |
Executes the AI model with the resolved dependencies and prompt references and returns the API response.
Args:
prompt: The prompt to be used.
aiconfig: The AIConfig object containing all prompts and parameters.
parameters (dict): The resolved parameters to use for i... | @abstractmethod
async def run_inference(self) -> List[Output]:
pass
| (self, prompt: aiconfig.schema.Prompt, aiconfig: aiconfig.schema.AIConfig, options=None, parameters: Dict = {}) -> List[Union[aiconfig.schema.ExecuteResult, aiconfig.schema.Error]] | [
0.007228159345686436,
-0.07212400436401367,
-0.06545569002628326,
0.017699245363473892,
-0.03851700574159622,
0.022576075047254562,
-0.0342705138027668,
-0.04037484526634216,
0.01635562814772129,
-0.003578830510377884,
0.04697681590914726,
0.027369966730475426,
-0.008468101732432842,
0.028... |
729,700 | aiconfig.default_parsers.openai | serialize |
Defines how prompts and model inference settings get serialized in the .aiconfig.
Args:
prompt (str): The prompt to be serialized.
inference_settings (dict): Model-specific inference settings to be serialized.
Returns:
str: Serialized representation of the ... | @abstractmethod
def id(self) -> str:
"""
Returns an identifier for the model (e.g. gpt-3.5, gpt-4, etc.).
"""
return self.id
| (self, prompt_name: str, data: Dict, ai_config: 'AIConfigRuntime', parameters: Optional[Dict], **kwargs) -> List[aiconfig.schema.Prompt] | [
0.012052255682647228,
-0.038461651653051376,
0.007213759236037731,
0.03598082438111305,
0.0004898977931588888,
-0.07090597599744797,
0.015940647572278976,
0.013363048434257507,
0.014251573011279106,
-0.0016648827586323023,
-0.03140624240040779,
-0.008256235159933567,
0.01692594215273857,
0... |
729,707 | dotchain.dot_chain | DotChain | null | class DotChain:
__slots__ = ('__chain__')
def __init__(self, data: t.Any = None,
context: t.Optional[t.Any | list[t.Any]] = [],
parent: t.Optional[Chain] = None,
pipe: t.Optional[bool] = False,
**kwargs):
if 'chain' in kwargs:
... | (data: 't.Any' = None, context: 't.Optional[t.Any | list[t.Any]]' = [], parent: 't.Optional[Chain]' = None, pipe: 't.Optional[bool]' = False, **kwargs) | [
0.0009013913222588599,
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0.02155905030667782,
0.024309687316417694,
-0.007935960777103901,
-0.0003275674534961581,
-0.04375000298023224,
-0.046017419546842575,
0.06661003082990646,
-0.014013382606208324,
0.03310057520866394,
0.021744903177022934,
0.012628771364688873,
0... |
729,708 | dotchain.dot_chain | Call | null | def Call(self, callable: t.Callable) -> DotChain:
attr_chain = GetAttrChain(parent=self.__chain__,
item=callable,
context=self.__chain__.contexts,
pipe=self.__chain__.pipe)
return DotChain(
chain=CallChain(parent=a... | (self, callable: Callable) -> dotchain.dot_chain.DotChain | [
0.026737909764051437,
-0.043799590319395065,
0.025491729378700256,
0.008732428774237633,
-0.02244958095252514,
-0.012498460710048676,
0.001384772709570825,
-0.02551005594432354,
0.04625530168414116,
-0.01951739192008972,
0.0023709507659077644,
0.009694553911685944,
0.04050087928771973,
0.0... |
729,709 | dotchain.dot_chain | Result | null | def Result(self) -> t.Any:
return self.__chain__.result_sync()
| (self) -> Any | [
0.008659306913614273,
-0.06037836894392967,
-0.0085366889834404,
0.05878857150673866,
0.027432411909103394,
-0.022460076957941055,
-0.027601540088653564,
-0.06179903447628021,
0.08639011532068253,
-0.008633937686681747,
0.04776148870587349,
-0.00014243670739233494,
-0.01024064514786005,
0.... |
729,710 | dotchain.dot_chain | With | null | def With(self, *contexts: t.Any | list[t.Any], clear: bool = False) -> t.Self:
self.__chain__.set_contexts(*contexts, clear=clear)
return self
| (self, *contexts: 't.Any | list[t.Any]', clear: 'bool' = False) -> 't.Self' | [
-0.04054044559597969,
-0.045324284583330154,
0.04099438339471817,
-0.006586512550711632,
-0.03900402784347534,
0.015128464438021183,
-0.007490030489861965,
-0.006088923197239637,
0.03324246406555176,
0.03778187930583954,
-0.001439299201592803,
-0.04846695438027382,
-0.054857052862644196,
0... |
729,711 | dotchain.dot_chain | __aiter__ | null | def __aiter__(self):
self.__chain__.__aiter__()
return self
| (self) | [
-0.038104455918073654,
0.0018781159305945039,
0.010317805223166943,
0.05569377541542053,
-0.029929380863904953,
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-0.022735314443707466,
0.0007760943262837827,
0.06946232169866562,
0.011780713684856892,
0.052733536809682846,
0.0010052114957943559,
0.027227303013205528,
... |
729,712 | dotchain.dot_chain | __anext__ | null | def __iter__(self):
self.__chain__.__iter__()
return self
| (self) | [
-0.016319777816534042,
-0.038512952625751495,
-0.031537216156721115,
0.023906966671347618,
-0.06686372309923172,
-0.006217878311872482,
-0.01757713221013546,
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0.1079602763056755,
0.03417249396443367,
0.03734171763062477,
-0.003916315734386444,
0.006093003787100315,
0.... |
729,713 | dotchain.dot_chain | __await__ | null | def __await__(self):
return self.__chain__.__await__()
| (self) | [
0.019938072189688683,
-0.01822333224117756,
-0.0360431931912899,
0.07907984405755997,
0.01333968061953783,
-0.020425597205758095,
0.005430014804005623,
-0.016130337491631508,
0.05978059768676758,
-0.004404532257467508,
0.04582730680704117,
0.004259535577148199,
0.02387189120054245,
0.02590... |
729,714 | dotchain.dot_chain | __call__ | null | def __call__(self, *args, **kwargs) -> DotChain:
return DotChain(
chain=CallChain(self.__chain__,
args=args,
kwargs=kwargs,
context=self.__chain__.contexts,
pipe=self.__chain__.pipe))
| (self, *args, **kwargs) -> dotchain.dot_chain.DotChain | [
-0.02821815386414528,
-0.07414884865283966,
0.06328468024730682,
0.0317499041557312,
-0.04166390746831894,
-0.028182297945022583,
-0.05503794923424721,
-0.029383452609181404,
0.07988569885492325,
-0.015606037341058254,
0.014162859879434109,
0.011177903041243553,
0.016206614673137665,
0.035... |
729,715 | dotchain.dot_chain | __getattr__ | null | def __getattr__(self, item: str) -> DotChain:
# https://github.com/python/cpython/issues/69718#issuecomment-1093697247
if item.startswith('__'):
raise AttributeError(item)
return DotChain(
chain=GetAttrChain(self.__chain__,
item,
context=... | (self, item: str) -> dotchain.dot_chain.DotChain | [
0.022754358127713203,
-0.0181931983679533,
0.06217581033706665,
0.03391719609498978,
0.00023697990400251,
-0.06217581033706665,
0.03974724933505058,
-0.021159665659070015,
0.05624287202954292,
0.013940688222646713,
0.00906230416148901,
0.0605296790599823,
0.039438601583242416,
0.0568258799... |
729,716 | dotchain.dot_chain | __init__ | null | def __init__(self, data: t.Any = None,
context: t.Optional[t.Any | list[t.Any]] = [],
parent: t.Optional[Chain] = None,
pipe: t.Optional[bool] = False,
**kwargs):
if 'chain' in kwargs:
self.__chain__ = kwargs.get('chain')
else:
self.__chain__ =... | (self, data: Optional[Any] = None, context: Union[Any, list[Any], NoneType] = [], parent: Optional[dotchain.chain.Chain] = None, pipe: Optional[bool] = False, **kwargs) | [
-0.03479931503534317,
0.01628200151026249,
0.027038317173719406,
-0.028629858046770096,
-0.033404480665922165,
-0.011945500038564205,
-0.03862616792321205,
-0.012964801862835884,
0.07539255917072296,
-0.02920209802687168,
0.018070250749588013,
0.019474025815725327,
-0.0768231526017189,
0.0... |
729,718 | dotchain.dot_chain | __next__ | null | def __next__(self):
return self.__chain__.__next__()
| (self) | [
-0.017710017040371895,
-0.0374138206243515,
-0.007936133071780205,
0.03824600949883461,
-0.05076351389288902,
0.000024295875846291892,
0.013661765493452549,
-0.032559383660554886,
0.08266407996416092,
0.009067390114068985,
0.02931731566786766,
-0.0012341965921223164,
0.03486524149775505,
0... |
729,721 | addfips.addfips | AddFIPS | Get state or county FIPS codes | class AddFIPS:
"""Get state or county FIPS codes"""
default_county_field = 'county'
default_state_field = 'state'
data = files('addfips')
def __init__(self, vintage=None):
# Handle de-diacreticizing
self.diacretic_pattern = '(' + ('|'.join(DIACRETICS)) + ')'
self.delete_di... | (vintage=None) | [
0.03373221307992935,
-0.04146377369761467,
-0.02037861756980419,
0.029977459460496902,
-0.07230927050113678,
-0.08462323993444443,
-0.056321289390325546,
-0.010098467580974102,
0.07121917605400085,
-0.08720715343952179,
-0.058662962168455124,
0.031471285969018936,
-0.03732547163963318,
0.0... |
729,722 | addfips.addfips | __init__ | null | def __init__(self, vintage=None):
# Handle de-diacreticizing
self.diacretic_pattern = '(' + ('|'.join(DIACRETICS)) + ')'
self.delete_diacretics = lambda x: DIACRETICS[x.group()]
if vintage is None or vintage not in COUNTY_FILES:
vintage = max(COUNTY_FILES.keys())
self._states, self._state_fi... | (self, vintage=None) | [
-0.0004496534529607743,
-0.034084502607584,
-0.03669029474258423,
-0.008544901385903358,
-0.0675603598356247,
-0.050213780254125595,
-0.024212932214140892,
-0.009120267815887928,
0.019724125042557716,
-0.03727992624044418,
-0.058392539620399475,
0.10430771112442017,
-0.0637943223118782,
0.... |
729,723 | addfips.addfips | _delete_diacretics | null | def _delete_diacretics(self, string):
return re.sub(self.diacretic_pattern, self.delete_diacretics, string)
| (self, string) | [
-0.00806625559926033,
0.027030080556869507,
0.06169017404317856,
0.0283815860748291,
-0.04653279855847359,
-0.08964406698942184,
-0.025148240849375725,
0.05005697160959244,
0.040921490639448166,
0.0032504526898264885,
-0.011915476061403751,
0.0563868023455143,
-0.04643015190958977,
-0.0073... |
729,724 | addfips.addfips | _load_county_data | null | def _load_county_data(self, vintage):
with self.data.joinpath(COUNTY_FILES[vintage]).open('rt', encoding='utf-8') as f:
counties = {}
for row in csv.DictReader(f):
if row['statefp'] not in counties:
counties[row['statefp']] = {}
state = counties[row['statefp']... | (self, vintage) | [
-0.0017779755871742964,
-0.04171304032206535,
-0.04463560879230499,
-0.009707106277346611,
-0.07735320925712585,
-0.036114610731601715,
-0.024101709946990013,
0.004519070498645306,
0.056515663862228394,
-0.08281879127025604,
-0.06152578443288803,
0.024974685162305832,
-0.07473427802324295,
... |
729,725 | addfips.addfips | _load_state_data | null | def _load_state_data(self):
with self.data.joinpath(STATES).open('rt', encoding='utf-8') as f:
reader = csv.DictReader(f)
states = {}
state_fips = {}
for row in reader:
states[row['postal'].lower()] = row['fips']
states[row['name'].lower()] = row['fips']
... | (self) | [
0.02849714830517769,
-0.0267731212079525,
-0.017219984903931618,
-0.02628633752465248,
-0.0495302751660347,
-0.028071211650967598,
-0.020546341314911842,
-0.013285147026181221,
0.046244483441114426,
-0.048313312232494354,
-0.03695502132177353,
0.008336176164448261,
-0.045676566660404205,
0... |
729,726 | addfips.addfips | add_county_fips |
Add county FIPS to a dictionary containing a state name, FIPS code, or using a passed state name or FIPS code.
:row dict/list A dictionary with state and county names
:county_field str county name field. default: county
:state_fips_field str state FIPS field containing state fips
... | def add_county_fips(self, row, county_field=None, state_field=None, state=None):
"""
Add county FIPS to a dictionary containing a state name, FIPS code, or using a passed state name or FIPS code.
:row dict/list A dictionary with state and county names
:county_field str county name field. default: county... | (self, row, county_field=None, state_field=None, state=None) | [
-0.014998691156506538,
-0.04081227630376816,
0.03226473182439804,
0.032390695065259933,
-0.0580873116850853,
-0.03575572744011879,
-0.03060920722782612,
-0.003398773493245244,
0.047254424542188644,
-0.08493559807538986,
-0.0062397075816988945,
0.042143892496824265,
-0.027981961145997047,
0... |
729,727 | addfips.addfips | add_state_fips |
Add state FIPS to a dictionary.
:row dict/list A dictionary with state and county names
:state_field str name of state name field. default: state
| def add_state_fips(self, row, state_field=None):
"""
Add state FIPS to a dictionary.
:row dict/list A dictionary with state and county names
:state_field str name of state name field. default: state
"""
if state_field is None:
state_field = self.default_state_field
fips = self.get_st... | (self, row, state_field=None) | [
-0.00007318480493267998,
-0.045505259186029434,
0.011184578761458397,
0.02739080600440502,
-0.04265661537647247,
-0.01970311999320984,
-0.025290843099355698,
-0.01083762850612402,
0.04503048583865166,
-0.07910464704036713,
-0.021529173478484154,
0.03162724897265434,
-0.021583953872323036,
... |
729,728 | addfips.addfips | get_county_fips |
Get a county's FIPS code.
:county str County name
:state str Name, postal abbreviation or FIPS code for a state
| def get_county_fips(self, county, state):
"""
Get a county's FIPS code.
:county str County name
:state str Name, postal abbreviation or FIPS code for a state
"""
state_fips = self.get_state_fips(state)
counties = self._counties.get(state_fips, {})
try:
name = self._delete_diacret... | (self, county, state) | [
-0.02195850759744644,
-0.05754394084215164,
0.030181651934981346,
0.004506915807723999,
-0.0620260052382946,
-0.05389322713017464,
-0.007992716506123543,
-0.03415767848491669,
0.10062960535287857,
-0.1071358323097229,
-0.017169203609228134,
0.0435917042195797,
-0.04641106724739075,
-0.0025... |
729,729 | addfips.addfips | get_state_fips | Get FIPS code from a state name or postal code | def get_state_fips(self, state):
'''Get FIPS code from a state name or postal code'''
if state is None:
return None
# Check if we already have a FIPS code
if state in self._state_fips:
return state
return self._states.get(state.lower())
| (self, state) | [
0.021182727068662643,
-0.048872094601392746,
0.04453433305025101,
0.025574708357453346,
-0.05418584868311882,
-0.06394580751657486,
0.0217610951513052,
-0.044389743357896805,
0.08783963322639465,
-0.10685348510742188,
-0.042690787464380264,
0.032551273703575134,
-0.04070264473557472,
0.018... |
729,731 | minidir | Directory | Directory is a interface that can add, remove and iterate files | class Directory(typing.Protocol):
"""Directory is a interface that can add, remove and iterate files"""
def __iter__(self) -> typing.Iterator[Path]:
pass
def create(self, path: Path) -> File:
pass
def remove(self, path: Path) -> None:
pass
def get(self, path: Path) -> Fil... | (*args, **kwargs) | [
-0.008052605204284191,
0.003021512646228075,
-0.0981360673904419,
-0.02761981636285782,
-0.010314572602510452,
-0.007357347756624222,
-0.04541078582406044,
0.03923918679356575,
0.012543206103146076,
0.007004956714808941,
0.058820683509111404,
-0.04057255759835243,
-0.009790748357772827,
0.... |
729,733 | minidir | __iter__ | null | def __iter__(self) -> typing.Iterator[Path]:
pass
| (self) -> Iterator[minidir.Path] | [
0.03088340349495411,
-0.03812384605407715,
-0.07521824538707733,
-0.0024427915923297405,
-0.027297498658299446,
-0.000664851046167314,
0.004027710761874914,
0.059193190187215805,
0.07068867981433868,
0.022218894213438034,
0.06427179276943207,
-0.008111182600259781,
0.00897334422916174,
0.0... |
729,735 | minidir | create | null | def create(self, path: Path) -> File:
pass
| (self, path: minidir.Path) -> minidir.File | [
-0.006111571099609137,
0.024904971942305565,
-0.025975238531827927,
0.024395320564508438,
-0.01572274975478649,
-0.054124992340803146,
0.008460215292870998,
0.07773884385824203,
-0.019485676661133766,
-0.0036248965188860893,
0.09785309433937073,
0.019519653171300888,
0.018738187849521637,
... |
729,736 | minidir | get | null | def get(self, path: Path) -> File:
pass
| (self, path: minidir.Path) -> minidir.File | [
0.047557249665260315,
-0.021689502522349358,
-0.042393893003463745,
0.06596869975328445,
0.01259417925029993,
-0.04266564920544624,
0.034954577684402466,
0.027005724608898163,
0.02598663978278637,
-0.001118869287893176,
0.08132290095090866,
-0.007503005675971508,
-0.026139503344893456,
0.0... |
729,737 | minidir | remove | null | def remove(self, path: Path) -> None:
pass
| (self, path: minidir.Path) -> NoneType | [
0.04327651113271713,
0.04052671790122986,
-0.026123037561774254,
0.002418345073238015,
-0.008081610314548016,
-0.0487433597445488,
-0.02018151991069317,
0.09447504580020905,
0.02219475992023945,
0.02546832337975502,
0.04720478504896164,
-0.006416184362024069,
0.022702163085341454,
-0.01442... |
729,738 | minidir | FakeDirectory | FakeDirectory implements Directory protocol in memory. | class FakeDirectory:
"""FakeDirectory implements Directory protocol in memory."""
_dir: typing.Dict[str, bytes]
def __init__(self) -> None:
self._dir = {}
pass
def __iter__(self) -> typing.Iterator[Path]:
paths: typing.List[Path] = []
for key in self._dir:
... | () -> None | [
0.026432648301124573,
0.017257902771234512,
-0.08703829348087311,
0.0112225990742445,
0.015985887497663498,
-0.015291241928935051,
-0.0336497537791729,
0.08545053005218506,
-0.011520304717123508,
-0.01957639865577221,
0.059324607253074646,
0.02917514741420746,
-0.021290460601449013,
0.0507... |
729,739 | minidir | __init__ | null | def __init__(self) -> None:
self._dir = {}
pass
| (self) -> NoneType | [
0.0009170864359475672,
0.013269690796732903,
-0.02465616539120674,
-0.010819767601788044,
-0.001291440799832344,
0.0019845685455948114,
-0.0018167357193306088,
0.09478848427534103,
-0.013949739746749401,
0.004202359355986118,
0.007877243682742119,
0.02612088806927204,
-0.005902483593672514,
... |
729,740 | minidir | __iter__ | null | def __iter__(self) -> typing.Iterator[Path]:
paths: typing.List[Path] = []
for key in self._dir:
paths.append(SomePath(key))
return iter(paths)
| (self) -> Iterator[minidir.Path] | [
0.006121609825640917,
-0.04980170726776123,
-0.09859440475702286,
0.003229723544791341,
0.0010287142358720303,
0.017873840406537056,
0.0019831042736768723,
0.05567556992173195,
0.07927913218736649,
0.029909852892160416,
0.03517110273241997,
0.010981961153447628,
0.0016463932115584612,
0.07... |
729,741 | minidir | create | null | def create(self, path: Path) -> File:
if str(path) in self._dir:
raise NameCollision()
self._dir[str(path)] = b""
return _FakeDirectoryFile(self._dir, str(path))
| (self, path: minidir.Path) -> minidir.File | [
-0.002269681077450514,
0.051701951771974564,
-0.031791433691978455,
0.0058042071759700775,
-0.008956100791692734,
-0.047305651009082794,
-0.029738614335656166,
0.07535477727651596,
-0.021291175857186317,
0.002269681077450514,
0.09984326362609863,
0.055371589958667755,
-0.015477885492146015,
... |
729,742 | minidir | get | null | def get(self, path: Path) -> File:
if str(path) not in self._dir:
raise NotFound()
return _FakeDirectoryFile(self._dir, str(path))
| (self, path: minidir.Path) -> minidir.File | [
0.06846857070922852,
0.007476716302335262,
-0.048995181918144226,
0.04386095702648163,
0.02200382575392723,
-0.04734489694237709,
0.040890440344810486,
0.036856405436992645,
-0.007307103369385004,
0.018309015780687332,
0.0870618000626564,
0.03769988566637039,
-0.03161216154694557,
0.009223... |
729,743 | minidir | remove | null | def remove(self, path: Path) -> None:
if str(path) not in self._dir:
raise NotFound()
del self._dir[str(path)]
| (self, path: minidir.Path) -> NoneType | [
0.06048315390944481,
0.0674886554479599,
-0.0182073712348938,
-0.021502038463950157,
0.027501801028847694,
-0.03464602679014206,
-0.00913836620748043,
0.07338438183069229,
-0.0023799636401236057,
0.03613729774951935,
0.042414505034685135,
0.03464602679014206,
0.03187157213687897,
-0.025143... |
729,744 | minidir | File | File is a interface that can read and write content. | class File(typing.Protocol):
"""File is a interface that can read and write content."""
def read(self) -> bytes:
pass
def write(self, content: bytes) -> None:
pass
| (*args, **kwargs) | [
-0.010736407712101936,
-0.048426516354084015,
-0.0530780591070652,
0.006422913633286953,
-0.007842715829610825,
-0.015153569169342518,
-0.049508269876241684,
0.04864286631345749,
0.032362472265958786,
-0.03275911509990692,
0.07932861894369125,
-0.03398510068655014,
-0.015568241477012634,
0... |
729,747 | minidir | read | null | def read(self) -> bytes:
pass
| (self) -> bytes | [
-0.01278314832597971,
-0.03378164395689964,
-0.04206392168998718,
0.041796211153268814,
0.004362835083156824,
-0.013820524327456951,
-0.03219211846590042,
0.05739031359553337,
0.060402050614356995,
-0.06595703214406967,
0.04929208755493164,
0.0147909726947546,
0.008658742532134056,
0.05367... |
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