task stringclasses 4
values | prompt stringlengths 60 573k | completion stringlengths 60 683k | source_language stringclasses 2
values | target_language stringclasses 4
values | run_name stringclasses 2
values | example_index int64 1 100k | source_metadata dict | hashes dict | source_compile_ok bool 1
class | roundtrip_compile_ok bool 1
class | runtime_signature_match null |
|---|---|---|---|---|---|---|---|---|---|---|---|
python_to_en_plaincode | class Solution:
def finalPrices(self, prices: List[int]) -> List[int]:
res = []
for i in range(len(prices)):
for j in range(i+1,len(prices)):
if prices[j]<=prices[i]:
res.append(prices[i]-prices[j])
break
if j==len(p... | Define class Solution:
Define method finalPrices with parameters self, prices (type: List of int); return type List of int:
Set res to an empty list.
For each i in the range starting at 0 and stopping before len with prices:
For each j in the range starting at i plus 1 and stopping befor... | python | en | run_002_20260417_060406 | 1 | {
"max_stars_repo_path": "coding_intereview/1475. Final Prices With a Special Discount in a Shop.py",
"max_stars_repo_name": "Jahidul007/Python-Bootcamp",
"max_stars_count": 2,
"id": "3",
"raw_source_hash": "a7d86c06e5f0bd5932f94342ef1cd1419c14922f3e3bfeae0ce44b4dcda06eae",
"sanitize_meta": {
"triple_bl... | {
"raw_source_hash": "a7d86c06e5f0bd5932f94342ef1cd1419c14922f3e3bfeae0ce44b4dcda06eae",
"normalized_source_hash": "fb41c52b1740ad3039a1bbc7a3f7e79c56a36e746967aa1e1e153776a73f8193",
"source_ast_hash": "e28d606b7dbd1a2470550f821bcef517258cae14c641f9a7eb001a4363f416c1",
"artifact_hash": "44830b93a9ddbbf7631cb76f... | true | true | null |
python_to_es_plaincode | class Solution:
def finalPrices(self, prices: List[int]) -> List[int]:
res = []
for i in range(len(prices)):
for j in range(i+1,len(prices)):
if prices[j]<=prices[i]:
res.append(prices[i]-prices[j])
break
if j==len(p... | Definir clase Solution:
Definir método finalPrices con parámetros self, prices (tipo: List de int); tipo de retorno List de int:
Establecer res como una lista vacía.
Para cada i en el rango que comienza en 0 y también deteniéndose antes de len con prices:
Para cada j en el rango que comi... | python | es | run_002_20260417_060406 | 1 | {
"max_stars_repo_path": "coding_intereview/1475. Final Prices With a Special Discount in a Shop.py",
"max_stars_repo_name": "Jahidul007/Python-Bootcamp",
"max_stars_count": 2,
"id": "3",
"raw_source_hash": "a7d86c06e5f0bd5932f94342ef1cd1419c14922f3e3bfeae0ce44b4dcda06eae",
"sanitize_meta": {
"triple_bl... | {
"raw_source_hash": "a7d86c06e5f0bd5932f94342ef1cd1419c14922f3e3bfeae0ce44b4dcda06eae",
"normalized_source_hash": "fb41c52b1740ad3039a1bbc7a3f7e79c56a36e746967aa1e1e153776a73f8193",
"source_ast_hash": "e28d606b7dbd1a2470550f821bcef517258cae14c641f9a7eb001a4363f416c1",
"artifact_hash": "44830b93a9ddbbf7631cb76f... | true | true | null |
python_to_fr_plaincode | class Solution:
def finalPrices(self, prices: List[int]) -> List[int]:
res = []
for i in range(len(prices)):
for j in range(i+1,len(prices)):
if prices[j]<=prices[i]:
res.append(prices[i]-prices[j])
break
if j==len(p... | Définir classe Solution:
Définir méthode finalPrices avec paramètres self, prices (type : List de int); type de retour List de int:
Affecter res à une liste vide.
Pour chaque i dans la plage commençant à 0 et s'arrêtant avant len avec prices:
Pour chaque j dans la plage commençant à i pl... | python | fr | run_002_20260417_060406 | 1 | {
"max_stars_repo_path": "coding_intereview/1475. Final Prices With a Special Discount in a Shop.py",
"max_stars_repo_name": "Jahidul007/Python-Bootcamp",
"max_stars_count": 2,
"id": "3",
"raw_source_hash": "a7d86c06e5f0bd5932f94342ef1cd1419c14922f3e3bfeae0ce44b4dcda06eae",
"sanitize_meta": {
"triple_bl... | {
"raw_source_hash": "a7d86c06e5f0bd5932f94342ef1cd1419c14922f3e3bfeae0ce44b4dcda06eae",
"normalized_source_hash": "fb41c52b1740ad3039a1bbc7a3f7e79c56a36e746967aa1e1e153776a73f8193",
"source_ast_hash": "e28d606b7dbd1a2470550f821bcef517258cae14c641f9a7eb001a4363f416c1",
"artifact_hash": "44830b93a9ddbbf7631cb76f... | true | true | null |
en_plaincode_to_python | Define class Solution:
Define method finalPrices with parameters self, prices (type: List of int); return type List of int:
Set res to an empty list.
For each i in the range starting at 0 and stopping before len with prices:
For each j in the range starting at i plus 1 and stopping befor... | class Solution:
def finalPrices(self, prices: List[int]) -> List[int]:
res = []
for i in range(len(prices)):
for j in range(i+1,len(prices)):
if prices[j]<=prices[i]:
res.append(prices[i]-prices[j])
break
if j==len(p... | en | python | run_002_20260417_060406 | 1 | {
"max_stars_repo_path": "coding_intereview/1475. Final Prices With a Special Discount in a Shop.py",
"max_stars_repo_name": "Jahidul007/Python-Bootcamp",
"max_stars_count": 2,
"id": "3",
"raw_source_hash": "a7d86c06e5f0bd5932f94342ef1cd1419c14922f3e3bfeae0ce44b4dcda06eae",
"sanitize_meta": {
"triple_bl... | {
"raw_source_hash": "a7d86c06e5f0bd5932f94342ef1cd1419c14922f3e3bfeae0ce44b4dcda06eae",
"normalized_source_hash": "fb41c52b1740ad3039a1bbc7a3f7e79c56a36e746967aa1e1e153776a73f8193",
"source_ast_hash": "e28d606b7dbd1a2470550f821bcef517258cae14c641f9a7eb001a4363f416c1",
"artifact_hash": "44830b93a9ddbbf7631cb76f... | true | true | null |
python_to_en_plaincode | from __future__ import unicode_literals
from . import __version__ as app_version
app_name = "pos_kiosk"
app_title = "Pos Kiosk"
app_publisher = "9t9it"
app_description = "Kiosk App"
app_icon = "octicon octicon-file-directory"
app_color = "grey"
app_email = "<EMAIL>"
app_license = "MIT"
# Includes in <head>
# --------... | Load unicode_literals from __future__.
Load __version__ referred to as app_version from the current package.
Set app_name to "pos_kiosk".
Set app_title to "Pos Kiosk".
Set app_publisher to "9t9it".
Set app_description to "Kiosk App".
Set app_icon to "octicon octicon-file-directory".
Set app_color to "grey".
Set app_ema... | python | en | run_002_20260417_060406 | 2 | {
"max_stars_repo_path": "pos_kiosk/hooks.py",
"max_stars_repo_name": "Muzzy73/pos_kiosk",
"max_stars_count": 1,
"id": "6",
"raw_source_hash": "a5c711a4abcb2ecb962e46063669e0cb75044793206ec6adde1964cb67cf8b9f",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_triple_... | {
"raw_source_hash": "a5c711a4abcb2ecb962e46063669e0cb75044793206ec6adde1964cb67cf8b9f",
"normalized_source_hash": "7029af563df358ab5cbc6d3961ae61ab13a4c79088f55f833d1993f758155b84",
"source_ast_hash": "00979410a8f5f72e075bf9d5bf06abaa21337279a8a1aac9efa32b2fba7dbfc2",
"artifact_hash": "c4b5525b6aa01ca71066a244... | true | true | null |
python_to_es_plaincode | from __future__ import unicode_literals
from . import __version__ as app_version
app_name = "pos_kiosk"
app_title = "Pos Kiosk"
app_publisher = "9t9it"
app_description = "Kiosk App"
app_icon = "octicon octicon-file-directory"
app_color = "grey"
app_email = "<EMAIL>"
app_license = "MIT"
# Includes in <head>
# --------... | Importar unicode_literals desde __future__.
Importar __version__ referido como app_version desde el paquete actual.
Establecer app_name como "pos_kiosk".
Establecer app_title como "Pos Kiosk".
Establecer app_publisher como "9t9it".
Establecer app_description como "Kiosk App".
Establecer app_icon como "octicon octicon-f... | python | es | run_002_20260417_060406 | 2 | {
"max_stars_repo_path": "pos_kiosk/hooks.py",
"max_stars_repo_name": "Muzzy73/pos_kiosk",
"max_stars_count": 1,
"id": "6",
"raw_source_hash": "a5c711a4abcb2ecb962e46063669e0cb75044793206ec6adde1964cb67cf8b9f",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_triple_... | {
"raw_source_hash": "a5c711a4abcb2ecb962e46063669e0cb75044793206ec6adde1964cb67cf8b9f",
"normalized_source_hash": "7029af563df358ab5cbc6d3961ae61ab13a4c79088f55f833d1993f758155b84",
"source_ast_hash": "00979410a8f5f72e075bf9d5bf06abaa21337279a8a1aac9efa32b2fba7dbfc2",
"artifact_hash": "c4b5525b6aa01ca71066a244... | true | true | null |
python_to_fr_plaincode | from __future__ import unicode_literals
from . import __version__ as app_version
app_name = "pos_kiosk"
app_title = "Pos Kiosk"
app_publisher = "9t9it"
app_description = "Kiosk App"
app_icon = "octicon octicon-file-directory"
app_color = "grey"
app_email = "<EMAIL>"
app_license = "MIT"
# Includes in <head>
# --------... | Charger unicode_literals depuis __future__.
Charger __version__ référé comme app_version depuis le paquet actuel.
Affecter app_name à "pos_kiosk".
Affecter app_title à "Pos Kiosk".
Affecter app_publisher à "9t9it".
Affecter app_description à "Kiosk App".
Affecter app_icon à "octicon octicon-file-directory".
Affecter ap... | python | fr | run_002_20260417_060406 | 2 | {
"max_stars_repo_path": "pos_kiosk/hooks.py",
"max_stars_repo_name": "Muzzy73/pos_kiosk",
"max_stars_count": 1,
"id": "6",
"raw_source_hash": "a5c711a4abcb2ecb962e46063669e0cb75044793206ec6adde1964cb67cf8b9f",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_triple_... | {
"raw_source_hash": "a5c711a4abcb2ecb962e46063669e0cb75044793206ec6adde1964cb67cf8b9f",
"normalized_source_hash": "7029af563df358ab5cbc6d3961ae61ab13a4c79088f55f833d1993f758155b84",
"source_ast_hash": "00979410a8f5f72e075bf9d5bf06abaa21337279a8a1aac9efa32b2fba7dbfc2",
"artifact_hash": "c4b5525b6aa01ca71066a244... | true | true | null |
en_plaincode_to_python | Load unicode_literals from __future__.
Load __version__ referred to as app_version from the current package.
Set app_name to "pos_kiosk".
Set app_title to "Pos Kiosk".
Set app_publisher to "9t9it".
Set app_description to "Kiosk App".
Set app_icon to "octicon octicon-file-directory".
Set app_color to "grey".
Set app_ema... | from __future__ import unicode_literals
from . import __version__ as app_version
app_name = "pos_kiosk"
app_title = "Pos Kiosk"
app_publisher = "9t9it"
app_description = "Kiosk App"
app_icon = "octicon octicon-file-directory"
app_color = "grey"
app_email = "<EMAIL>"
app_license = "MIT"
# Includes in <head>
# --------... | en | python | run_002_20260417_060406 | 2 | {
"max_stars_repo_path": "pos_kiosk/hooks.py",
"max_stars_repo_name": "Muzzy73/pos_kiosk",
"max_stars_count": 1,
"id": "6",
"raw_source_hash": "a5c711a4abcb2ecb962e46063669e0cb75044793206ec6adde1964cb67cf8b9f",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_triple_... | {
"raw_source_hash": "a5c711a4abcb2ecb962e46063669e0cb75044793206ec6adde1964cb67cf8b9f",
"normalized_source_hash": "7029af563df358ab5cbc6d3961ae61ab13a4c79088f55f833d1993f758155b84",
"source_ast_hash": "00979410a8f5f72e075bf9d5bf06abaa21337279a8a1aac9efa32b2fba7dbfc2",
"artifact_hash": "c4b5525b6aa01ca71066a244... | true | true | null |
python_to_en_plaincode | from keras import Model, Input
from keras.layers import Dense, concatenate, LSTM, Reshape, Permute, Embedding, Dropout, Convolution1D, Flatten
from keras.optimizers import Adam
from pypagai.models.base import KerasModel
class SimpleLSTM(KerasModel):
"""
Use a simple lstm neural network
"""
@staticmet... | Load Model, Input from keras.
Load Dense, concatenate, LSTM, Reshape, Permute, Embedding, Dropout, Convolution1D, Flatten from keras.layers.
Load Adam from keras.optimizers.
Load KerasModel from pypagai.models.base.
Define class SimpleLSTM inheriting from KerasModel:
Text block:
""
" Use a simple lstm ne... | python | en | run_002_20260417_060406 | 3 | {
"max_stars_repo_path": "pypagai/models/model_lstm.py",
"max_stars_repo_name": "gcouti/pypagAI",
"max_stars_count": 1,
"id": "7",
"raw_source_hash": "6ff5eb1643faabfe79e7cf12b3b77bdafbf223256b942b1d5db7a26437ee9a32",
"sanitize_meta": {
"triple_block_count": 3,
"total_triple_chars": 144,
"larges... | {
"raw_source_hash": "6ff5eb1643faabfe79e7cf12b3b77bdafbf223256b942b1d5db7a26437ee9a32",
"normalized_source_hash": "85eb10c40cbf0b55fd2e8845ce3f9f0ef240c6c527f9c39a923b896640d00f57",
"source_ast_hash": "3947ecf078c1470508bc0f6ef53482e2d7796c6ee7babb8a53c9c99a71189db0",
"artifact_hash": "8b70f39afd85f9911ab0240d... | true | true | null |
python_to_es_plaincode | from keras import Model, Input
from keras.layers import Dense, concatenate, LSTM, Reshape, Permute, Embedding, Dropout, Convolution1D, Flatten
from keras.optimizers import Adam
from pypagai.models.base import KerasModel
class SimpleLSTM(KerasModel):
"""
Use a simple lstm neural network
"""
@staticmet... | Importar Model, Input desde keras.
Importar Dense, concatenate, LSTM, Reshape, Permute, Embedding, Dropout, Convolution1D, Flatten desde keras.layers.
Importar Adam desde keras.optimizers.
Importar KerasModel desde pypagai.models.base.
Definir clase SimpleLSTM heredando de KerasModel:
Texto literal:
""
" ... | python | es | run_002_20260417_060406 | 3 | {
"max_stars_repo_path": "pypagai/models/model_lstm.py",
"max_stars_repo_name": "gcouti/pypagAI",
"max_stars_count": 1,
"id": "7",
"raw_source_hash": "6ff5eb1643faabfe79e7cf12b3b77bdafbf223256b942b1d5db7a26437ee9a32",
"sanitize_meta": {
"triple_block_count": 3,
"total_triple_chars": 144,
"larges... | {
"raw_source_hash": "6ff5eb1643faabfe79e7cf12b3b77bdafbf223256b942b1d5db7a26437ee9a32",
"normalized_source_hash": "85eb10c40cbf0b55fd2e8845ce3f9f0ef240c6c527f9c39a923b896640d00f57",
"source_ast_hash": "3947ecf078c1470508bc0f6ef53482e2d7796c6ee7babb8a53c9c99a71189db0",
"artifact_hash": "8b70f39afd85f9911ab0240d... | true | true | null |
python_to_fr_plaincode | from keras import Model, Input
from keras.layers import Dense, concatenate, LSTM, Reshape, Permute, Embedding, Dropout, Convolution1D, Flatten
from keras.optimizers import Adam
from pypagai.models.base import KerasModel
class SimpleLSTM(KerasModel):
"""
Use a simple lstm neural network
"""
@staticmet... | Charger Model, Input depuis keras.
Charger Dense, concatenate, LSTM, Reshape, Permute, Embedding, Dropout, Convolution1D, Flatten depuis keras.layers.
Charger Adam depuis keras.optimizers.
Charger KerasModel depuis pypagai.models.base.
Définir classe SimpleLSTM héritant de KerasModel:
Texte littéral:
""
" ... | python | fr | run_002_20260417_060406 | 3 | {
"max_stars_repo_path": "pypagai/models/model_lstm.py",
"max_stars_repo_name": "gcouti/pypagAI",
"max_stars_count": 1,
"id": "7",
"raw_source_hash": "6ff5eb1643faabfe79e7cf12b3b77bdafbf223256b942b1d5db7a26437ee9a32",
"sanitize_meta": {
"triple_block_count": 3,
"total_triple_chars": 144,
"larges... | {
"raw_source_hash": "6ff5eb1643faabfe79e7cf12b3b77bdafbf223256b942b1d5db7a26437ee9a32",
"normalized_source_hash": "85eb10c40cbf0b55fd2e8845ce3f9f0ef240c6c527f9c39a923b896640d00f57",
"source_ast_hash": "3947ecf078c1470508bc0f6ef53482e2d7796c6ee7babb8a53c9c99a71189db0",
"artifact_hash": "8b70f39afd85f9911ab0240d... | true | true | null |
en_plaincode_to_python | Load Model, Input from keras.
Load Dense, concatenate, LSTM, Reshape, Permute, Embedding, Dropout, Convolution1D, Flatten from keras.layers.
Load Adam from keras.optimizers.
Load KerasModel from pypagai.models.base.
Define class SimpleLSTM inheriting from KerasModel:
Text block:
""
" Use a simple lstm ne... | from keras import Model, Input
from keras.layers import Dense, concatenate, LSTM, Reshape, Permute, Embedding, Dropout, Convolution1D, Flatten
from keras.optimizers import Adam
from pypagai.models.base import KerasModel
class SimpleLSTM(KerasModel):
"""
Use a simple lstm neural network
"""
@staticmet... | en | python | run_002_20260417_060406 | 3 | {
"max_stars_repo_path": "pypagai/models/model_lstm.py",
"max_stars_repo_name": "gcouti/pypagAI",
"max_stars_count": 1,
"id": "7",
"raw_source_hash": "6ff5eb1643faabfe79e7cf12b3b77bdafbf223256b942b1d5db7a26437ee9a32",
"sanitize_meta": {
"triple_block_count": 3,
"total_triple_chars": 144,
"larges... | {
"raw_source_hash": "6ff5eb1643faabfe79e7cf12b3b77bdafbf223256b942b1d5db7a26437ee9a32",
"normalized_source_hash": "85eb10c40cbf0b55fd2e8845ce3f9f0ef240c6c527f9c39a923b896640d00f57",
"source_ast_hash": "3947ecf078c1470508bc0f6ef53482e2d7796c6ee7babb8a53c9c99a71189db0",
"artifact_hash": "8b70f39afd85f9911ab0240d... | true | true | null |
python_to_en_plaincode | # Author:
''' PNASNet in PyTorch.
Paper: Progressive Neural Architecture Search
'''
from easyai.base_name.block_name import NormalizationType, ActivationType
from easyai.base_name.backbone_name import BackboneName
from easyai.model.backbone.utility.base_backbone import *
from easyai.model.base_block.utility.utility_bl... | # Author:
Text block:
" PNASNet in PyTorch."
"Paper: Progressive Neural Architecture Search"
ending with a newline.
Load NormalizationType, ActivationType from easyai.base_name.block_name.
Load BackboneName from easyai.base_name.backbone_name.
Load everything from easyai.model.backbone.utility.base_backbone.
Load ConvB... | python | en | run_002_20260417_060406 | 4 | {
"max_stars_repo_path": "easyai/model/backbone/cls/pnasnet.py",
"max_stars_repo_name": "lpj0822/image_point_cloud_det",
"max_stars_count": 1,
"id": "9",
"raw_source_hash": "1e7ae79e5a84953e5230479e541e934f228111b32411a607f7b5903ae33da37f",
"sanitize_meta": {
"triple_block_count": 1,
"total_triple_c... | {
"raw_source_hash": "1e7ae79e5a84953e5230479e541e934f228111b32411a607f7b5903ae33da37f",
"normalized_source_hash": "824e0336848577e6a1b3741ebb94a816e1d6ba123bedc819b84655610998cec7",
"source_ast_hash": "71ba39b897ee88d72350b3bd41d5e4fcd8ec68a55fbaf588cf46099332400597",
"artifact_hash": "8d55ceb200088270bb9f0dc4... | true | true | null |
python_to_es_plaincode | # Author:
''' PNASNet in PyTorch.
Paper: Progressive Neural Architecture Search
'''
from easyai.base_name.block_name import NormalizationType, ActivationType
from easyai.base_name.backbone_name import BackboneName
from easyai.model.backbone.utility.base_backbone import *
from easyai.model.base_block.utility.utility_bl... | # Author:
Texto literal:
" PNASNet in PyTorch."
"Paper: Progressive Neural Architecture Search"
terminando con una nueva línea.
Importar NormalizationType, ActivationType desde easyai.base_name.block_name.
Importar BackboneName desde easyai.base_name.backbone_name.
Importar todo desde easyai.model.backbone.utility.base... | python | es | run_002_20260417_060406 | 4 | {
"max_stars_repo_path": "easyai/model/backbone/cls/pnasnet.py",
"max_stars_repo_name": "lpj0822/image_point_cloud_det",
"max_stars_count": 1,
"id": "9",
"raw_source_hash": "1e7ae79e5a84953e5230479e541e934f228111b32411a607f7b5903ae33da37f",
"sanitize_meta": {
"triple_block_count": 1,
"total_triple_c... | {
"raw_source_hash": "1e7ae79e5a84953e5230479e541e934f228111b32411a607f7b5903ae33da37f",
"normalized_source_hash": "824e0336848577e6a1b3741ebb94a816e1d6ba123bedc819b84655610998cec7",
"source_ast_hash": "71ba39b897ee88d72350b3bd41d5e4fcd8ec68a55fbaf588cf46099332400597",
"artifact_hash": "8d55ceb200088270bb9f0dc4... | true | true | null |
python_to_fr_plaincode | # Author:
''' PNASNet in PyTorch.
Paper: Progressive Neural Architecture Search
'''
from easyai.base_name.block_name import NormalizationType, ActivationType
from easyai.base_name.backbone_name import BackboneName
from easyai.model.backbone.utility.base_backbone import *
from easyai.model.base_block.utility.utility_bl... | # Author:
Texte littéral:
" PNASNet in PyTorch."
"Paper: Progressive Neural Architecture Search"
se terminant par une nouvelle ligne.
Charger NormalizationType, ActivationType depuis easyai.base_name.block_name.
Charger BackboneName depuis easyai.base_name.backbone_name.
Charger tout depuis easyai.model.backbone.utilit... | python | fr | run_002_20260417_060406 | 4 | {
"max_stars_repo_path": "easyai/model/backbone/cls/pnasnet.py",
"max_stars_repo_name": "lpj0822/image_point_cloud_det",
"max_stars_count": 1,
"id": "9",
"raw_source_hash": "1e7ae79e5a84953e5230479e541e934f228111b32411a607f7b5903ae33da37f",
"sanitize_meta": {
"triple_block_count": 1,
"total_triple_c... | {
"raw_source_hash": "1e7ae79e5a84953e5230479e541e934f228111b32411a607f7b5903ae33da37f",
"normalized_source_hash": "824e0336848577e6a1b3741ebb94a816e1d6ba123bedc819b84655610998cec7",
"source_ast_hash": "71ba39b897ee88d72350b3bd41d5e4fcd8ec68a55fbaf588cf46099332400597",
"artifact_hash": "8d55ceb200088270bb9f0dc4... | true | true | null |
en_plaincode_to_python | # Author:
Text block:
" PNASNet in PyTorch."
"Paper: Progressive Neural Architecture Search"
ending with a newline.
Load NormalizationType, ActivationType from easyai.base_name.block_name.
Load BackboneName from easyai.base_name.backbone_name.
Load everything from easyai.model.backbone.utility.base_backbone.
Load ConvB... | # Author:
''' PNASNet in PyTorch.
Paper: Progressive Neural Architecture Search
'''
from easyai.base_name.block_name import NormalizationType, ActivationType
from easyai.base_name.backbone_name import BackboneName
from easyai.model.backbone.utility.base_backbone import *
from easyai.model.base_block.utility.utility_bl... | en | python | run_002_20260417_060406 | 4 | {
"max_stars_repo_path": "easyai/model/backbone/cls/pnasnet.py",
"max_stars_repo_name": "lpj0822/image_point_cloud_det",
"max_stars_count": 1,
"id": "9",
"raw_source_hash": "1e7ae79e5a84953e5230479e541e934f228111b32411a607f7b5903ae33da37f",
"sanitize_meta": {
"triple_block_count": 1,
"total_triple_c... | {
"raw_source_hash": "1e7ae79e5a84953e5230479e541e934f228111b32411a607f7b5903ae33da37f",
"normalized_source_hash": "824e0336848577e6a1b3741ebb94a816e1d6ba123bedc819b84655610998cec7",
"source_ast_hash": "71ba39b897ee88d72350b3bd41d5e4fcd8ec68a55fbaf588cf46099332400597",
"artifact_hash": "8d55ceb200088270bb9f0dc4... | true | true | null |
python_to_en_plaincode | import json
import os
import math
import logging
import requests
import time
from map_download.cmd.BaseDownloader import DownloadEngine, BaseDownloaderThread, latlng2tile_terrain, BoundBox
def get_access_token(token):
resp = None
request_count = 0
url = "https://api.cesium.com/v1/assets/1/endpoint"
w... | Load json.
Load os.
Load math.
Load logging.
Load requests.
Load time.
Load DownloadEngine, BaseDownloaderThread, latlng2tile_terrain, BoundBox from map_download.cmd.BaseDownloader.
Define function get_access_token with parameter token:
Set resp to None.
Set request_count to 0.
Set url to "https://api.cesiu... | python | en | run_002_20260417_060406 | 5 | {
"max_stars_repo_path": "map_download/cmd/TerrainDownloader.py",
"max_stars_repo_name": "cugxy/map_download",
"max_stars_count": 27,
"id": "10",
"raw_source_hash": "8ba343fa3627630456d4d8758a7ce2f4bc8e55f923f2ee88df259080c5cad8d4",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0... | {
"raw_source_hash": "8ba343fa3627630456d4d8758a7ce2f4bc8e55f923f2ee88df259080c5cad8d4",
"normalized_source_hash": "735d910720bc9acc94329223be31bf3b0b8f4817bb6aaa80c0fa5192533c2028",
"source_ast_hash": "8fd78bde1199004c7b06339b47de5eab9bb9ad06dc8980f9df96eef79a5d73fe",
"artifact_hash": "7544fde26507442a0aac483d... | true | true | null |
python_to_es_plaincode | import json
import os
import math
import logging
import requests
import time
from map_download.cmd.BaseDownloader import DownloadEngine, BaseDownloaderThread, latlng2tile_terrain, BoundBox
def get_access_token(token):
resp = None
request_count = 0
url = "https://api.cesium.com/v1/assets/1/endpoint"
w... | Importar json.
Importar os.
Importar math.
Importar logging.
Importar requests.
Importar time.
Importar DownloadEngine, BaseDownloaderThread, latlng2tile_terrain, BoundBox desde map_download.cmd.BaseDownloader.
Definir función get_access_token con parámetro token:
Establecer resp como None.
Establecer request_c... | python | es | run_002_20260417_060406 | 5 | {
"max_stars_repo_path": "map_download/cmd/TerrainDownloader.py",
"max_stars_repo_name": "cugxy/map_download",
"max_stars_count": 27,
"id": "10",
"raw_source_hash": "8ba343fa3627630456d4d8758a7ce2f4bc8e55f923f2ee88df259080c5cad8d4",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0... | {
"raw_source_hash": "8ba343fa3627630456d4d8758a7ce2f4bc8e55f923f2ee88df259080c5cad8d4",
"normalized_source_hash": "735d910720bc9acc94329223be31bf3b0b8f4817bb6aaa80c0fa5192533c2028",
"source_ast_hash": "8fd78bde1199004c7b06339b47de5eab9bb9ad06dc8980f9df96eef79a5d73fe",
"artifact_hash": "7544fde26507442a0aac483d... | true | true | null |
python_to_fr_plaincode | import json
import os
import math
import logging
import requests
import time
from map_download.cmd.BaseDownloader import DownloadEngine, BaseDownloaderThread, latlng2tile_terrain, BoundBox
def get_access_token(token):
resp = None
request_count = 0
url = "https://api.cesium.com/v1/assets/1/endpoint"
w... | Charger json.
Charger os.
Charger math.
Charger logging.
Charger requests.
Charger time.
Charger DownloadEngine, BaseDownloaderThread, latlng2tile_terrain, BoundBox depuis map_download.cmd.BaseDownloader.
Définir fonction get_access_token avec paramètre token:
Affecter resp à None.
Affecter request_count à 0.
... | python | fr | run_002_20260417_060406 | 5 | {
"max_stars_repo_path": "map_download/cmd/TerrainDownloader.py",
"max_stars_repo_name": "cugxy/map_download",
"max_stars_count": 27,
"id": "10",
"raw_source_hash": "8ba343fa3627630456d4d8758a7ce2f4bc8e55f923f2ee88df259080c5cad8d4",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0... | {
"raw_source_hash": "8ba343fa3627630456d4d8758a7ce2f4bc8e55f923f2ee88df259080c5cad8d4",
"normalized_source_hash": "735d910720bc9acc94329223be31bf3b0b8f4817bb6aaa80c0fa5192533c2028",
"source_ast_hash": "8fd78bde1199004c7b06339b47de5eab9bb9ad06dc8980f9df96eef79a5d73fe",
"artifact_hash": "7544fde26507442a0aac483d... | true | true | null |
en_plaincode_to_python | Load json.
Load os.
Load math.
Load logging.
Load requests.
Load time.
Load DownloadEngine, BaseDownloaderThread, latlng2tile_terrain, BoundBox from map_download.cmd.BaseDownloader.
Define function get_access_token with parameter token:
Set resp to None.
Set request_count to 0.
Set url to "https://api.cesiu... | import json
import os
import math
import logging
import requests
import time
from map_download.cmd.BaseDownloader import DownloadEngine, BaseDownloaderThread, latlng2tile_terrain, BoundBox
def get_access_token(token):
resp = None
request_count = 0
url = "https://api.cesium.com/v1/assets/1/endpoint"
w... | en | python | run_002_20260417_060406 | 5 | {
"max_stars_repo_path": "map_download/cmd/TerrainDownloader.py",
"max_stars_repo_name": "cugxy/map_download",
"max_stars_count": 27,
"id": "10",
"raw_source_hash": "8ba343fa3627630456d4d8758a7ce2f4bc8e55f923f2ee88df259080c5cad8d4",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0... | {
"raw_source_hash": "8ba343fa3627630456d4d8758a7ce2f4bc8e55f923f2ee88df259080c5cad8d4",
"normalized_source_hash": "735d910720bc9acc94329223be31bf3b0b8f4817bb6aaa80c0fa5192533c2028",
"source_ast_hash": "8fd78bde1199004c7b06339b47de5eab9bb9ad06dc8980f9df96eef79a5d73fe",
"artifact_hash": "7544fde26507442a0aac483d... | true | true | null |
python_to_en_plaincode | """
Experiment summary
------------------
Treat each province/state in a country cases over time
as a vector, do a simple K-Nearest Neighbor between
countries. What country has the most similar trajectory
to a given country?
Plots similar countries
"""
import sys
sys.path.insert(0, '..')
from utils import data
impor... | Text block:
""
"Experiment summary"
"------------------"
"Treat each province/state in a country cases over time"
"as a vector, do a simple K-Nearest Neighbor between"
"countries. What country has the most similar trajectory"
"to a given country?"
""
"Plots similar countries"
ending with a newline.
Load sys.
Call sys d... | python | en | run_002_20260417_060406 | 6 | {
"max_stars_repo_path": "exp/viz_raw_manhattan.py",
"max_stars_repo_name": "ellencwade/coronavirus-2020",
"max_stars_count": 0,
"id": "12",
"raw_source_hash": "3892bbaa446c6859124ea678a66a873eb57e72ef3d4e82ef6011a9599473cb90",
"sanitize_meta": {
"triple_block_count": 1,
"total_triple_chars": 253,
... | {
"raw_source_hash": "3892bbaa446c6859124ea678a66a873eb57e72ef3d4e82ef6011a9599473cb90",
"normalized_source_hash": "c23ce8757687a2edb3dd35d5f0165a08d25d6b76a867a06feb2a7303df4437b4",
"source_ast_hash": "de3a6bd293e51f162227c85ed75e7f424d6638f345393a6f47e78fd2d564117c",
"artifact_hash": "9de591488a4a51f2bf9d65f1... | true | true | null |
python_to_es_plaincode | """
Experiment summary
------------------
Treat each province/state in a country cases over time
as a vector, do a simple K-Nearest Neighbor between
countries. What country has the most similar trajectory
to a given country?
Plots similar countries
"""
import sys
sys.path.insert(0, '..')
from utils import data
impor... | Texto literal:
""
"Experiment summary"
"------------------"
"Treat each province/state in a country cases over time"
"as a vector, do a simple K-Nearest Neighbor between"
"countries. What country has the most similar trajectory"
"to a given country?"
""
"Plots similar countries"
terminando con una nueva línea.
Importar... | python | es | run_002_20260417_060406 | 6 | {
"max_stars_repo_path": "exp/viz_raw_manhattan.py",
"max_stars_repo_name": "ellencwade/coronavirus-2020",
"max_stars_count": 0,
"id": "12",
"raw_source_hash": "3892bbaa446c6859124ea678a66a873eb57e72ef3d4e82ef6011a9599473cb90",
"sanitize_meta": {
"triple_block_count": 1,
"total_triple_chars": 253,
... | {
"raw_source_hash": "3892bbaa446c6859124ea678a66a873eb57e72ef3d4e82ef6011a9599473cb90",
"normalized_source_hash": "c23ce8757687a2edb3dd35d5f0165a08d25d6b76a867a06feb2a7303df4437b4",
"source_ast_hash": "de3a6bd293e51f162227c85ed75e7f424d6638f345393a6f47e78fd2d564117c",
"artifact_hash": "9de591488a4a51f2bf9d65f1... | true | true | null |
python_to_fr_plaincode | """
Experiment summary
------------------
Treat each province/state in a country cases over time
as a vector, do a simple K-Nearest Neighbor between
countries. What country has the most similar trajectory
to a given country?
Plots similar countries
"""
import sys
sys.path.insert(0, '..')
from utils import data
impor... | Texte littéral:
""
"Experiment summary"
"------------------"
"Treat each province/state in a country cases over time"
"as a vector, do a simple K-Nearest Neighbor between"
"countries. What country has the most similar trajectory"
"to a given country?"
""
"Plots similar countries"
se terminant par une nouvelle ligne.
Ch... | python | fr | run_002_20260417_060406 | 6 | {
"max_stars_repo_path": "exp/viz_raw_manhattan.py",
"max_stars_repo_name": "ellencwade/coronavirus-2020",
"max_stars_count": 0,
"id": "12",
"raw_source_hash": "3892bbaa446c6859124ea678a66a873eb57e72ef3d4e82ef6011a9599473cb90",
"sanitize_meta": {
"triple_block_count": 1,
"total_triple_chars": 253,
... | {
"raw_source_hash": "3892bbaa446c6859124ea678a66a873eb57e72ef3d4e82ef6011a9599473cb90",
"normalized_source_hash": "c23ce8757687a2edb3dd35d5f0165a08d25d6b76a867a06feb2a7303df4437b4",
"source_ast_hash": "de3a6bd293e51f162227c85ed75e7f424d6638f345393a6f47e78fd2d564117c",
"artifact_hash": "9de591488a4a51f2bf9d65f1... | true | true | null |
en_plaincode_to_python | Text block:
""
"Experiment summary"
"------------------"
"Treat each province/state in a country cases over time"
"as a vector, do a simple K-Nearest Neighbor between"
"countries. What country has the most similar trajectory"
"to a given country?"
""
"Plots similar countries"
ending with a newline.
Load sys.
Call sys d... | """
Experiment summary
------------------
Treat each province/state in a country cases over time
as a vector, do a simple K-Nearest Neighbor between
countries. What country has the most similar trajectory
to a given country?
Plots similar countries
"""
import sys
sys.path.insert(0, '..')
from utils import data
impor... | en | python | run_002_20260417_060406 | 6 | {
"max_stars_repo_path": "exp/viz_raw_manhattan.py",
"max_stars_repo_name": "ellencwade/coronavirus-2020",
"max_stars_count": 0,
"id": "12",
"raw_source_hash": "3892bbaa446c6859124ea678a66a873eb57e72ef3d4e82ef6011a9599473cb90",
"sanitize_meta": {
"triple_block_count": 1,
"total_triple_chars": 253,
... | {
"raw_source_hash": "3892bbaa446c6859124ea678a66a873eb57e72ef3d4e82ef6011a9599473cb90",
"normalized_source_hash": "c23ce8757687a2edb3dd35d5f0165a08d25d6b76a867a06feb2a7303df4437b4",
"source_ast_hash": "de3a6bd293e51f162227c85ed75e7f424d6638f345393a6f47e78fd2d564117c",
"artifact_hash": "9de591488a4a51f2bf9d65f1... | true | true | null |
python_to_en_plaincode | """Utils for criterion."""
import torch
import torch.nn.functional as F
def normalize(x, axis=-1):
"""Performs L2-Norm."""
num = x
denom = torch.norm(x, 2, axis, keepdim=True).expand_as(x) + 1e-12
return num / denom
# Source : https://github.com/earhian/Humpback-Whale-Identification-1st-/blob/master... | Evaluate "Utils for criterion.".
Load torch.
Load torch.nn.functional, referred to as F.
Define function normalize with parameters x, axis (default: negative 1):
Evaluate "Performs L2-Norm.".
Set num to x.
Set denom to ((torch dot norm with x, 2, axis, and keepdim set to True) dot expand_as with x) plus 1e-... | python | en | run_002_20260417_060406 | 7 | {
"max_stars_repo_path": "torchflare/criterion/utils.py",
"max_stars_repo_name": "Neklaustares-tPtwP/torchflare",
"max_stars_count": 1,
"id": "14",
"raw_source_hash": "78ce00ca6c55feba8354953695d1668c7ac148d1556ceb77b93e26fb811a80c0",
"sanitize_meta": {
"triple_block_count": 4,
"total_triple_chars":... | {
"raw_source_hash": "78ce00ca6c55feba8354953695d1668c7ac148d1556ceb77b93e26fb811a80c0",
"normalized_source_hash": "8f3e316ea3a2763d240bf3d66dc3696333d6ac246616a64052dbbb8a098abf35",
"source_ast_hash": "7478e56a42e6cf2177f2d017e8c1f69a8884f7dbd36cb169cf95fcaadff73f57",
"artifact_hash": "cf21d2ebddc343a410332192... | true | true | null |
python_to_es_plaincode | """Utils for criterion."""
import torch
import torch.nn.functional as F
def normalize(x, axis=-1):
"""Performs L2-Norm."""
num = x
denom = torch.norm(x, 2, axis, keepdim=True).expand_as(x) + 1e-12
return num / denom
# Source : https://github.com/earhian/Humpback-Whale-Identification-1st-/blob/master... | Evaluar "Utils for criterion.".
Importar torch.
Importar torch.nn.functional, referido como F.
Definir función normalize con parámetros x, axis (predeterminado: negativo 1):
Evaluar "Performs L2-Norm.".
Establecer num como x.
Establecer denom como ((torch punto norm con x, 2, axis, y también keepdim estable... | python | es | run_002_20260417_060406 | 7 | {
"max_stars_repo_path": "torchflare/criterion/utils.py",
"max_stars_repo_name": "Neklaustares-tPtwP/torchflare",
"max_stars_count": 1,
"id": "14",
"raw_source_hash": "78ce00ca6c55feba8354953695d1668c7ac148d1556ceb77b93e26fb811a80c0",
"sanitize_meta": {
"triple_block_count": 4,
"total_triple_chars":... | {
"raw_source_hash": "78ce00ca6c55feba8354953695d1668c7ac148d1556ceb77b93e26fb811a80c0",
"normalized_source_hash": "8f3e316ea3a2763d240bf3d66dc3696333d6ac246616a64052dbbb8a098abf35",
"source_ast_hash": "7478e56a42e6cf2177f2d017e8c1f69a8884f7dbd36cb169cf95fcaadff73f57",
"artifact_hash": "cf21d2ebddc343a410332192... | true | true | null |
python_to_fr_plaincode | """Utils for criterion."""
import torch
import torch.nn.functional as F
def normalize(x, axis=-1):
"""Performs L2-Norm."""
num = x
denom = torch.norm(x, 2, axis, keepdim=True).expand_as(x) + 1e-12
return num / denom
# Source : https://github.com/earhian/Humpback-Whale-Identification-1st-/blob/master... | Évaluer "Utils for criterion.".
Charger torch.
Charger torch.nn.functional, référé comme F.
Définir fonction normalize avec paramètres x, axis (par défaut: négatif 1):
Évaluer "Performs L2-Norm.".
Affecter num à x.
Affecter denom à ((torch point de norm avec x, 2, axis, et keepdim défini à True) point de ex... | python | fr | run_002_20260417_060406 | 7 | {
"max_stars_repo_path": "torchflare/criterion/utils.py",
"max_stars_repo_name": "Neklaustares-tPtwP/torchflare",
"max_stars_count": 1,
"id": "14",
"raw_source_hash": "78ce00ca6c55feba8354953695d1668c7ac148d1556ceb77b93e26fb811a80c0",
"sanitize_meta": {
"triple_block_count": 4,
"total_triple_chars":... | {
"raw_source_hash": "78ce00ca6c55feba8354953695d1668c7ac148d1556ceb77b93e26fb811a80c0",
"normalized_source_hash": "8f3e316ea3a2763d240bf3d66dc3696333d6ac246616a64052dbbb8a098abf35",
"source_ast_hash": "7478e56a42e6cf2177f2d017e8c1f69a8884f7dbd36cb169cf95fcaadff73f57",
"artifact_hash": "cf21d2ebddc343a410332192... | true | true | null |
en_plaincode_to_python | Evaluate "Utils for criterion.".
Load torch.
Load torch.nn.functional, referred to as F.
Define function normalize with parameters x, axis (default: negative 1):
Evaluate "Performs L2-Norm.".
Set num to x.
Set denom to ((torch dot norm with x, 2, axis, and keepdim set to True) dot expand_as with x) plus 1e-... | """Utils for criterion."""
import torch
import torch.nn.functional as F
def normalize(x, axis=-1):
"""Performs L2-Norm."""
num = x
denom = torch.norm(x, 2, axis, keepdim=True).expand_as(x) + 1e-12
return num / denom
# Source : https://github.com/earhian/Humpback-Whale-Identification-1st-/blob/master... | en | python | run_002_20260417_060406 | 7 | {
"max_stars_repo_path": "torchflare/criterion/utils.py",
"max_stars_repo_name": "Neklaustares-tPtwP/torchflare",
"max_stars_count": 1,
"id": "14",
"raw_source_hash": "78ce00ca6c55feba8354953695d1668c7ac148d1556ceb77b93e26fb811a80c0",
"sanitize_meta": {
"triple_block_count": 4,
"total_triple_chars":... | {
"raw_source_hash": "78ce00ca6c55feba8354953695d1668c7ac148d1556ceb77b93e26fb811a80c0",
"normalized_source_hash": "8f3e316ea3a2763d240bf3d66dc3696333d6ac246616a64052dbbb8a098abf35",
"source_ast_hash": "7478e56a42e6cf2177f2d017e8c1f69a8884f7dbd36cb169cf95fcaadff73f57",
"artifact_hash": "cf21d2ebddc343a410332192... | true | true | null |
python_to_en_plaincode | #! /usr/bin/env python2.7
# -*- coding: latin-1 -*-
from flask import Blueprint
from flask import current_app
from flask import render_template
from flask_login import login_required
homestack = Blueprint("homestack", __name__, url_prefix="/homestack")
@homestack.route("/", methods=["GET"])
@login_required
def hom... | # ! /usr/bin/env python2.7
# -*- coding: latin-1 -*-
Load Blueprint from flask.
Load current_app from flask.
Load render_template from flask.
Load login_required from flask_login.
Set homestack to Blueprint with "homestack", __name__, and url_prefix set to "/homestack".
Apply homestack dot route with "/" and methods se... | python | en | run_002_20260417_060406 | 8 | {
"max_stars_repo_path": "app/views/web/homestack.py",
"max_stars_repo_name": "geudrik/hautomation",
"max_stars_count": 0,
"id": "16",
"raw_source_hash": "a0838d3a04f088d52fb7f7ff2895f2afb5516d976530b1b023edd8a5b5c1e563",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"larg... | {
"raw_source_hash": "a0838d3a04f088d52fb7f7ff2895f2afb5516d976530b1b023edd8a5b5c1e563",
"normalized_source_hash": "51f4b7e693e09b160f130cfe54ad310af3d0092af4126dcb93b4c9a7edd5c6b0",
"source_ast_hash": "f2d83c5d1e51a2434e03ff70f9d625c17ac71fd8e43236129a9c962eeae5bd9a",
"artifact_hash": "f9f1bf3b00cdae2fe6c77791... | true | true | null |
python_to_es_plaincode | #! /usr/bin/env python2.7
# -*- coding: latin-1 -*-
from flask import Blueprint
from flask import current_app
from flask import render_template
from flask_login import login_required
homestack = Blueprint("homestack", __name__, url_prefix="/homestack")
@homestack.route("/", methods=["GET"])
@login_required
def hom... | # ! /usr/bin/env python2.7
# -*- coding: latin-1 -*-
Importar Blueprint desde flask.
Importar current_app desde flask.
Importar render_template desde flask.
Importar login_required desde flask_login.
Establecer homestack como Blueprint con "homestack", __name__, y también url_prefix establecido a "/homestack".
Aplicar ... | python | es | run_002_20260417_060406 | 8 | {
"max_stars_repo_path": "app/views/web/homestack.py",
"max_stars_repo_name": "geudrik/hautomation",
"max_stars_count": 0,
"id": "16",
"raw_source_hash": "a0838d3a04f088d52fb7f7ff2895f2afb5516d976530b1b023edd8a5b5c1e563",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"larg... | {
"raw_source_hash": "a0838d3a04f088d52fb7f7ff2895f2afb5516d976530b1b023edd8a5b5c1e563",
"normalized_source_hash": "51f4b7e693e09b160f130cfe54ad310af3d0092af4126dcb93b4c9a7edd5c6b0",
"source_ast_hash": "f2d83c5d1e51a2434e03ff70f9d625c17ac71fd8e43236129a9c962eeae5bd9a",
"artifact_hash": "f9f1bf3b00cdae2fe6c77791... | true | true | null |
python_to_fr_plaincode | #! /usr/bin/env python2.7
# -*- coding: latin-1 -*-
from flask import Blueprint
from flask import current_app
from flask import render_template
from flask_login import login_required
homestack = Blueprint("homestack", __name__, url_prefix="/homestack")
@homestack.route("/", methods=["GET"])
@login_required
def hom... | # ! /usr/bin/env python2.7
# -*- coding: latin-1 -*-
Charger Blueprint depuis flask.
Charger current_app depuis flask.
Charger render_template depuis flask.
Charger login_required depuis flask_login.
Affecter homestack à Blueprint avec "homestack", __name__, et url_prefix défini à "/homestack".
Appliquer homestack poin... | python | fr | run_002_20260417_060406 | 8 | {
"max_stars_repo_path": "app/views/web/homestack.py",
"max_stars_repo_name": "geudrik/hautomation",
"max_stars_count": 0,
"id": "16",
"raw_source_hash": "a0838d3a04f088d52fb7f7ff2895f2afb5516d976530b1b023edd8a5b5c1e563",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"larg... | {
"raw_source_hash": "a0838d3a04f088d52fb7f7ff2895f2afb5516d976530b1b023edd8a5b5c1e563",
"normalized_source_hash": "51f4b7e693e09b160f130cfe54ad310af3d0092af4126dcb93b4c9a7edd5c6b0",
"source_ast_hash": "f2d83c5d1e51a2434e03ff70f9d625c17ac71fd8e43236129a9c962eeae5bd9a",
"artifact_hash": "f9f1bf3b00cdae2fe6c77791... | true | true | null |
en_plaincode_to_python | # ! /usr/bin/env python2.7
# -*- coding: latin-1 -*-
Load Blueprint from flask.
Load current_app from flask.
Load render_template from flask.
Load login_required from flask_login.
Set homestack to Blueprint with "homestack", __name__, and url_prefix set to "/homestack".
Apply homestack dot route with "/" and methods se... | #! /usr/bin/env python2.7
# -*- coding: latin-1 -*-
from flask import Blueprint
from flask import current_app
from flask import render_template
from flask_login import login_required
homestack = Blueprint("homestack", __name__, url_prefix="/homestack")
@homestack.route("/", methods=["GET"])
@login_required
def hom... | en | python | run_002_20260417_060406 | 8 | {
"max_stars_repo_path": "app/views/web/homestack.py",
"max_stars_repo_name": "geudrik/hautomation",
"max_stars_count": 0,
"id": "16",
"raw_source_hash": "a0838d3a04f088d52fb7f7ff2895f2afb5516d976530b1b023edd8a5b5c1e563",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"larg... | {
"raw_source_hash": "a0838d3a04f088d52fb7f7ff2895f2afb5516d976530b1b023edd8a5b5c1e563",
"normalized_source_hash": "51f4b7e693e09b160f130cfe54ad310af3d0092af4126dcb93b4c9a7edd5c6b0",
"source_ast_hash": "f2d83c5d1e51a2434e03ff70f9d625c17ac71fd8e43236129a9c962eeae5bd9a",
"artifact_hash": "f9f1bf3b00cdae2fe6c77791... | true | true | null |
python_to_en_plaincode | # !/usr/bin/python
# -*- coding: utf-8 -*-
# @time : 2019/11/2 21:08
# @author : Mo
# @function:
from keras_textclassification.data_preprocess.text_preprocess import load_json, save_json
from keras_textclassification.conf.path_config import path_model_dir
path_fast_text_model_vocab2index = path_model_dir + 'vocab... | # !/usr/bin/python
# -*- coding: utf-8 -*-
# @time : 2019/11/2 21:08
# @author : Mo
# @function:
Load load_json, save_json from keras_textclassification.data_preprocess.text_preprocess.
Load path_model_dir from keras_textclassification.conf.path_config.
Set path_fast_text_model_vocab2index to path_model_dir plus "v... | python | en | run_002_20260417_060406 | 9 | {
"max_stars_repo_path": "keras_textclassification/data_preprocess/generator_preprocess.py",
"max_stars_repo_name": "Vail-qin/Keras-TextClassification",
"max_stars_count": 1,
"id": "19",
"raw_source_hash": "e197c9c464126d62d78c30aec5ad91317d62797304bd554419f3a9f7bf56e9f2",
"sanitize_meta": {
"triple_blo... | {
"raw_source_hash": "e197c9c464126d62d78c30aec5ad91317d62797304bd554419f3a9f7bf56e9f2",
"normalized_source_hash": "e29a8de3c46b4783233df9b9da562c168a2a6b1b29a7ed5c320132a06557df64",
"source_ast_hash": "17d5ee44475fd8f327291146eabf49a726f84f07427dc66d498f1a3e031c919d",
"artifact_hash": "8075dc8a7ecf3dabf68b8393... | true | true | null |
python_to_es_plaincode | # !/usr/bin/python
# -*- coding: utf-8 -*-
# @time : 2019/11/2 21:08
# @author : Mo
# @function:
from keras_textclassification.data_preprocess.text_preprocess import load_json, save_json
from keras_textclassification.conf.path_config import path_model_dir
path_fast_text_model_vocab2index = path_model_dir + 'vocab... | # !/usr/bin/python
# -*- coding: utf-8 -*-
# @time : 2019/11/2 21:08
# @author : Mo
# @function:
Importar load_json, save_json desde keras_textclassification.data_preprocess.text_preprocess.
Importar path_model_dir desde keras_textclassification.conf.path_config.
Establecer path_fast_text_model_vocab2index como pat... | python | es | run_002_20260417_060406 | 9 | {
"max_stars_repo_path": "keras_textclassification/data_preprocess/generator_preprocess.py",
"max_stars_repo_name": "Vail-qin/Keras-TextClassification",
"max_stars_count": 1,
"id": "19",
"raw_source_hash": "e197c9c464126d62d78c30aec5ad91317d62797304bd554419f3a9f7bf56e9f2",
"sanitize_meta": {
"triple_blo... | {
"raw_source_hash": "e197c9c464126d62d78c30aec5ad91317d62797304bd554419f3a9f7bf56e9f2",
"normalized_source_hash": "e29a8de3c46b4783233df9b9da562c168a2a6b1b29a7ed5c320132a06557df64",
"source_ast_hash": "17d5ee44475fd8f327291146eabf49a726f84f07427dc66d498f1a3e031c919d",
"artifact_hash": "8075dc8a7ecf3dabf68b8393... | true | true | null |
python_to_fr_plaincode | # !/usr/bin/python
# -*- coding: utf-8 -*-
# @time : 2019/11/2 21:08
# @author : Mo
# @function:
from keras_textclassification.data_preprocess.text_preprocess import load_json, save_json
from keras_textclassification.conf.path_config import path_model_dir
path_fast_text_model_vocab2index = path_model_dir + 'vocab... | # !/usr/bin/python
# -*- coding: utf-8 -*-
# @time : 2019/11/2 21:08
# @author : Mo
# @function:
Charger load_json, save_json depuis keras_textclassification.data_preprocess.text_preprocess.
Charger path_model_dir depuis keras_textclassification.conf.path_config.
Affecter path_fast_text_model_vocab2index à path_mod... | python | fr | run_002_20260417_060406 | 9 | {
"max_stars_repo_path": "keras_textclassification/data_preprocess/generator_preprocess.py",
"max_stars_repo_name": "Vail-qin/Keras-TextClassification",
"max_stars_count": 1,
"id": "19",
"raw_source_hash": "e197c9c464126d62d78c30aec5ad91317d62797304bd554419f3a9f7bf56e9f2",
"sanitize_meta": {
"triple_blo... | {
"raw_source_hash": "e197c9c464126d62d78c30aec5ad91317d62797304bd554419f3a9f7bf56e9f2",
"normalized_source_hash": "e29a8de3c46b4783233df9b9da562c168a2a6b1b29a7ed5c320132a06557df64",
"source_ast_hash": "17d5ee44475fd8f327291146eabf49a726f84f07427dc66d498f1a3e031c919d",
"artifact_hash": "8075dc8a7ecf3dabf68b8393... | true | true | null |
en_plaincode_to_python | # !/usr/bin/python
# -*- coding: utf-8 -*-
# @time : 2019/11/2 21:08
# @author : Mo
# @function:
Load load_json, save_json from keras_textclassification.data_preprocess.text_preprocess.
Load path_model_dir from keras_textclassification.conf.path_config.
Set path_fast_text_model_vocab2index to path_model_dir plus "v... | # !/usr/bin/python
# -*- coding: utf-8 -*-
# @time : 2019/11/2 21:08
# @author : Mo
# @function:
from keras_textclassification.data_preprocess.text_preprocess import load_json, save_json
from keras_textclassification.conf.path_config import path_model_dir
path_fast_text_model_vocab2index = path_model_dir + 'vocab... | en | python | run_002_20260417_060406 | 9 | {
"max_stars_repo_path": "keras_textclassification/data_preprocess/generator_preprocess.py",
"max_stars_repo_name": "Vail-qin/Keras-TextClassification",
"max_stars_count": 1,
"id": "19",
"raw_source_hash": "e197c9c464126d62d78c30aec5ad91317d62797304bd554419f3a9f7bf56e9f2",
"sanitize_meta": {
"triple_blo... | {
"raw_source_hash": "e197c9c464126d62d78c30aec5ad91317d62797304bd554419f3a9f7bf56e9f2",
"normalized_source_hash": "e29a8de3c46b4783233df9b9da562c168a2a6b1b29a7ed5c320132a06557df64",
"source_ast_hash": "17d5ee44475fd8f327291146eabf49a726f84f07427dc66d498f1a3e031c919d",
"artifact_hash": "8075dc8a7ecf3dabf68b8393... | true | true | null |
python_to_en_plaincode | # Copyright 2014 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
from gpu_tests.gpu_test_expectations import GpuTestExpectations
# See the GpuTestExpectations class for documentation.
class PixelExpectations(GpuTestExpec... | # Copyright 2014 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
Load GpuTestExpectations from gpu_tests.gpu_test_expectations.
# See the GpuTestExpectations class for documentation.
Define class PixelExpectations inheritin... | python | en | run_002_20260417_060406 | 10 | {
"max_stars_repo_path": "content/test/gpu/gpu_tests/pixel_expectations.py",
"max_stars_repo_name": "metux/chromium-deb",
"max_stars_count": 0,
"id": "20",
"raw_source_hash": "75927affe6599410c73b2ae075e3831f3e5edeb2dfa0ae1a7cfb2e0ada7bf1db",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple... | {
"raw_source_hash": "75927affe6599410c73b2ae075e3831f3e5edeb2dfa0ae1a7cfb2e0ada7bf1db",
"normalized_source_hash": "707a6e430e224c58d91c08d6336e01fc7afa8f21eb17a25c9756c73359c62415",
"source_ast_hash": "509eda94b7abb5ee160df0455c781a9168c87e9796e5e25d2615e2e77426fbe5",
"artifact_hash": "cd0bc9813a411c7fb03dd485... | true | true | null |
python_to_es_plaincode | # Copyright 2014 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
from gpu_tests.gpu_test_expectations import GpuTestExpectations
# See the GpuTestExpectations class for documentation.
class PixelExpectations(GpuTestExpec... | # Copyright 2014 The Chromium Authors. All rights reserved.
# Use de this source code es governed por a BSD-style license that can be
# found en the LICENSE file.
Importar GpuTestExpectations desde gpu_tests.gpu_test_expectations.
# See the GpuTestExpectations class for documentation.
Definir clase PixelExpectations he... | python | es | run_002_20260417_060406 | 10 | {
"max_stars_repo_path": "content/test/gpu/gpu_tests/pixel_expectations.py",
"max_stars_repo_name": "metux/chromium-deb",
"max_stars_count": 0,
"id": "20",
"raw_source_hash": "75927affe6599410c73b2ae075e3831f3e5edeb2dfa0ae1a7cfb2e0ada7bf1db",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple... | {
"raw_source_hash": "75927affe6599410c73b2ae075e3831f3e5edeb2dfa0ae1a7cfb2e0ada7bf1db",
"normalized_source_hash": "707a6e430e224c58d91c08d6336e01fc7afa8f21eb17a25c9756c73359c62415",
"source_ast_hash": "509eda94b7abb5ee160df0455c781a9168c87e9796e5e25d2615e2e77426fbe5",
"artifact_hash": "cd0bc9813a411c7fb03dd485... | true | true | null |
python_to_fr_plaincode | # Copyright 2014 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
from gpu_tests.gpu_test_expectations import GpuTestExpectations
# See the GpuTestExpectations class for documentation.
class PixelExpectations(GpuTestExpec... | # Copyright 2014 The Chromium Authors. All rights reserved.
# Use de this source code est governed par a BSD-style license that can be
# found dans the LICENSE file.
Charger GpuTestExpectations depuis gpu_tests.gpu_test_expectations.
# See the GpuTestExpectations class for documentation.
Définir classe PixelExpectation... | python | fr | run_002_20260417_060406 | 10 | {
"max_stars_repo_path": "content/test/gpu/gpu_tests/pixel_expectations.py",
"max_stars_repo_name": "metux/chromium-deb",
"max_stars_count": 0,
"id": "20",
"raw_source_hash": "75927affe6599410c73b2ae075e3831f3e5edeb2dfa0ae1a7cfb2e0ada7bf1db",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple... | {
"raw_source_hash": "75927affe6599410c73b2ae075e3831f3e5edeb2dfa0ae1a7cfb2e0ada7bf1db",
"normalized_source_hash": "707a6e430e224c58d91c08d6336e01fc7afa8f21eb17a25c9756c73359c62415",
"source_ast_hash": "509eda94b7abb5ee160df0455c781a9168c87e9796e5e25d2615e2e77426fbe5",
"artifact_hash": "cd0bc9813a411c7fb03dd485... | true | true | null |
en_plaincode_to_python | # Copyright 2014 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
Load GpuTestExpectations from gpu_tests.gpu_test_expectations.
# See the GpuTestExpectations class for documentation.
Define class PixelExpectations inheritin... | # Copyright 2014 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
from gpu_tests.gpu_test_expectations import GpuTestExpectations
# See the GpuTestExpectations class for documentation.
class PixelExpectations(GpuTestExpec... | en | python | run_002_20260417_060406 | 10 | {
"max_stars_repo_path": "content/test/gpu/gpu_tests/pixel_expectations.py",
"max_stars_repo_name": "metux/chromium-deb",
"max_stars_count": 0,
"id": "20",
"raw_source_hash": "75927affe6599410c73b2ae075e3831f3e5edeb2dfa0ae1a7cfb2e0ada7bf1db",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple... | {
"raw_source_hash": "75927affe6599410c73b2ae075e3831f3e5edeb2dfa0ae1a7cfb2e0ada7bf1db",
"normalized_source_hash": "707a6e430e224c58d91c08d6336e01fc7afa8f21eb17a25c9756c73359c62415",
"source_ast_hash": "509eda94b7abb5ee160df0455c781a9168c87e9796e5e25d2615e2e77426fbe5",
"artifact_hash": "cd0bc9813a411c7fb03dd485... | true | true | null |
python_to_en_plaincode | # Generated by Django 1.11.13 on 2018-06-08 22:54
from __future__ import unicode_literals
from django.conf import settings
import django.contrib.postgres.fields.jsonb
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies... | # Generated by Django 1.11.13 on 2018-06-08 22:54
Load unicode_literals from __future__.
Load settings from django.conf.
Load django.contrib.postgres.fields.jsonb.
Load migrations, models from django.db.
Load django.db.models.deletion.
Define class Migration inheriting from migrations.Migration:
Set initial to True... | python | en | run_002_20260417_060406 | 11 | {
"max_stars_repo_path": "examples/p02_budgets/budget_data_ingest/migrations/0001_initial.py",
"max_stars_repo_name": "18F/data-federation-ingest",
"max_stars_count": 18,
"id": "21",
"raw_source_hash": "b357749685f22bb2ffee48b5c9d83a3cf75fd3a9fbc5e5b3fceb91d9cb13b527",
"sanitize_meta": {
"triple_block_c... | {
"raw_source_hash": "b357749685f22bb2ffee48b5c9d83a3cf75fd3a9fbc5e5b3fceb91d9cb13b527",
"normalized_source_hash": "277e1b1899893e3ab7a6ea1c97ab7bb489348f3330aab9e653670a43dde7ff12",
"source_ast_hash": "4d1fa9d45b22fc1a57d16b77f557760642f1d394040cd222349222647b33baed",
"artifact_hash": "ed2e21210f39f22d035c2751... | true | true | null |
python_to_es_plaincode | # Generated by Django 1.11.13 on 2018-06-08 22:54
from __future__ import unicode_literals
from django.conf import settings
import django.contrib.postgres.fields.jsonb
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies... | # Generated por Django 1.11.13 on 2018-06-08 22:54
Importar unicode_literals desde __future__.
Importar settings desde django.conf.
Importar django.contrib.postgres.fields.jsonb.
Importar migrations, models desde django.db.
Importar django.db.models.deletion.
Definir clase Migration heredando de migrations.Migration:
... | python | es | run_002_20260417_060406 | 11 | {
"max_stars_repo_path": "examples/p02_budgets/budget_data_ingest/migrations/0001_initial.py",
"max_stars_repo_name": "18F/data-federation-ingest",
"max_stars_count": 18,
"id": "21",
"raw_source_hash": "b357749685f22bb2ffee48b5c9d83a3cf75fd3a9fbc5e5b3fceb91d9cb13b527",
"sanitize_meta": {
"triple_block_c... | {
"raw_source_hash": "b357749685f22bb2ffee48b5c9d83a3cf75fd3a9fbc5e5b3fceb91d9cb13b527",
"normalized_source_hash": "277e1b1899893e3ab7a6ea1c97ab7bb489348f3330aab9e653670a43dde7ff12",
"source_ast_hash": "4d1fa9d45b22fc1a57d16b77f557760642f1d394040cd222349222647b33baed",
"artifact_hash": "ed2e21210f39f22d035c2751... | true | true | null |
python_to_fr_plaincode | # Generated by Django 1.11.13 on 2018-06-08 22:54
from __future__ import unicode_literals
from django.conf import settings
import django.contrib.postgres.fields.jsonb
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies... | # Generated par Django 1.11.13 on 2018-06-08 22:54
Charger unicode_literals depuis __future__.
Charger settings depuis django.conf.
Charger django.contrib.postgres.fields.jsonb.
Charger migrations, models depuis django.db.
Charger django.db.models.deletion.
Définir classe Migration héritant de migrations.Migration:
... | python | fr | run_002_20260417_060406 | 11 | {
"max_stars_repo_path": "examples/p02_budgets/budget_data_ingest/migrations/0001_initial.py",
"max_stars_repo_name": "18F/data-federation-ingest",
"max_stars_count": 18,
"id": "21",
"raw_source_hash": "b357749685f22bb2ffee48b5c9d83a3cf75fd3a9fbc5e5b3fceb91d9cb13b527",
"sanitize_meta": {
"triple_block_c... | {
"raw_source_hash": "b357749685f22bb2ffee48b5c9d83a3cf75fd3a9fbc5e5b3fceb91d9cb13b527",
"normalized_source_hash": "277e1b1899893e3ab7a6ea1c97ab7bb489348f3330aab9e653670a43dde7ff12",
"source_ast_hash": "4d1fa9d45b22fc1a57d16b77f557760642f1d394040cd222349222647b33baed",
"artifact_hash": "ed2e21210f39f22d035c2751... | true | true | null |
en_plaincode_to_python | # Generated by Django 1.11.13 on 2018-06-08 22:54
Load unicode_literals from __future__.
Load settings from django.conf.
Load django.contrib.postgres.fields.jsonb.
Load migrations, models from django.db.
Load django.db.models.deletion.
Define class Migration inheriting from migrations.Migration:
Set initial to True... | # Generated by Django 1.11.13 on 2018-06-08 22:54
from __future__ import unicode_literals
from django.conf import settings
import django.contrib.postgres.fields.jsonb
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies... | en | python | run_002_20260417_060406 | 11 | {
"max_stars_repo_path": "examples/p02_budgets/budget_data_ingest/migrations/0001_initial.py",
"max_stars_repo_name": "18F/data-federation-ingest",
"max_stars_count": 18,
"id": "21",
"raw_source_hash": "b357749685f22bb2ffee48b5c9d83a3cf75fd3a9fbc5e5b3fceb91d9cb13b527",
"sanitize_meta": {
"triple_block_c... | {
"raw_source_hash": "b357749685f22bb2ffee48b5c9d83a3cf75fd3a9fbc5e5b3fceb91d9cb13b527",
"normalized_source_hash": "277e1b1899893e3ab7a6ea1c97ab7bb489348f3330aab9e653670a43dde7ff12",
"source_ast_hash": "4d1fa9d45b22fc1a57d16b77f557760642f1d394040cd222349222647b33baed",
"artifact_hash": "ed2e21210f39f22d035c2751... | true | true | null |
python_to_en_plaincode | import setuptools #enables develop
setuptools.setup(
name='pysvm',
version='0.1',
description='PySVM : A NumPy implementation of SVM based on SMO algorithm',
author_email="<EMAIL>",
packages=['pysvm'],
license='MIT License',
long_description=open('README.md', encoding='utf-8').read(),
... | Load setuptools. # enables develop
Call setuptools dot setup with name set to "pysvm", version set to "0.1", description set to "PySVM : A NumPy implementation of SVM based on SMO algorithm", author_email set to "<EMAIL>", packages set to the list ["pysvm"], license set to "MIT License", long_description set to ((open ... | python | en | run_002_20260417_060406 | 12 | {
"max_stars_repo_path": "setup.py",
"max_stars_repo_name": "Kaslanarian/PythonSVM",
"max_stars_count": 2,
"id": "22",
"raw_source_hash": "7f4bc356b950d8cbeacc269149d7a8e06f2662e7ae7ca35867bc62ddc60482eb",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_triple_block... | {
"raw_source_hash": "7f4bc356b950d8cbeacc269149d7a8e06f2662e7ae7ca35867bc62ddc60482eb",
"normalized_source_hash": "d6de3b9e5c15a8ab3d7921a4484f42055604237475f7c9885dc569941bca02c1",
"source_ast_hash": "2984cdbdb55c34383c4417391697849417ef1a493866d30d52828f37e69abb81",
"artifact_hash": "e7d211cd3c3c2289c327ebe0... | true | true | null |
python_to_es_plaincode | import setuptools #enables develop
setuptools.setup(
name='pysvm',
version='0.1',
description='PySVM : A NumPy implementation of SVM based on SMO algorithm',
author_email="<EMAIL>",
packages=['pysvm'],
license='MIT License',
long_description=open('README.md', encoding='utf-8').read(),
... | Importar setuptools. # enables develop
Llamar setuptools punto setup con name establecido a "pysvm", version establecido a "0.1", description establecido a "PySVM : A NumPy implementation of SVM based on SMO algorithm", author_email establecido a "<EMAIL>", packages establecido a la lista ["pysvm"], license establecido... | python | es | run_002_20260417_060406 | 12 | {
"max_stars_repo_path": "setup.py",
"max_stars_repo_name": "Kaslanarian/PythonSVM",
"max_stars_count": 2,
"id": "22",
"raw_source_hash": "7f4bc356b950d8cbeacc269149d7a8e06f2662e7ae7ca35867bc62ddc60482eb",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_triple_block... | {
"raw_source_hash": "7f4bc356b950d8cbeacc269149d7a8e06f2662e7ae7ca35867bc62ddc60482eb",
"normalized_source_hash": "d6de3b9e5c15a8ab3d7921a4484f42055604237475f7c9885dc569941bca02c1",
"source_ast_hash": "2984cdbdb55c34383c4417391697849417ef1a493866d30d52828f37e69abb81",
"artifact_hash": "e7d211cd3c3c2289c327ebe0... | true | true | null |
python_to_fr_plaincode | import setuptools #enables develop
setuptools.setup(
name='pysvm',
version='0.1',
description='PySVM : A NumPy implementation of SVM based on SMO algorithm',
author_email="<EMAIL>",
packages=['pysvm'],
license='MIT License',
long_description=open('README.md', encoding='utf-8').read(),
... | Charger setuptools. # enables develop
Appeler setuptools point de setup avec name défini à "pysvm", version défini à "0.1", description défini à "PySVM : A NumPy implementation of SVM based on SMO algorithm", author_email défini à "<EMAIL>", packages défini à la liste ["pysvm"], license défini à "MIT License", long_des... | python | fr | run_002_20260417_060406 | 12 | {
"max_stars_repo_path": "setup.py",
"max_stars_repo_name": "Kaslanarian/PythonSVM",
"max_stars_count": 2,
"id": "22",
"raw_source_hash": "7f4bc356b950d8cbeacc269149d7a8e06f2662e7ae7ca35867bc62ddc60482eb",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_triple_block... | {
"raw_source_hash": "7f4bc356b950d8cbeacc269149d7a8e06f2662e7ae7ca35867bc62ddc60482eb",
"normalized_source_hash": "d6de3b9e5c15a8ab3d7921a4484f42055604237475f7c9885dc569941bca02c1",
"source_ast_hash": "2984cdbdb55c34383c4417391697849417ef1a493866d30d52828f37e69abb81",
"artifact_hash": "e7d211cd3c3c2289c327ebe0... | true | true | null |
en_plaincode_to_python | Load setuptools. # enables develop
Call setuptools dot setup with name set to "pysvm", version set to "0.1", description set to "PySVM : A NumPy implementation of SVM based on SMO algorithm", author_email set to "<EMAIL>", packages set to the list ["pysvm"], license set to "MIT License", long_description set to ((open ... | import setuptools #enables develop
setuptools.setup(
name='pysvm',
version='0.1',
description='PySVM : A NumPy implementation of SVM based on SMO algorithm',
author_email="<EMAIL>",
packages=['pysvm'],
license='MIT License',
long_description=open('README.md', encoding='utf-8').read(),
... | en | python | run_002_20260417_060406 | 12 | {
"max_stars_repo_path": "setup.py",
"max_stars_repo_name": "Kaslanarian/PythonSVM",
"max_stars_count": 2,
"id": "22",
"raw_source_hash": "7f4bc356b950d8cbeacc269149d7a8e06f2662e7ae7ca35867bc62ddc60482eb",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_triple_block... | {
"raw_source_hash": "7f4bc356b950d8cbeacc269149d7a8e06f2662e7ae7ca35867bc62ddc60482eb",
"normalized_source_hash": "d6de3b9e5c15a8ab3d7921a4484f42055604237475f7c9885dc569941bca02c1",
"source_ast_hash": "2984cdbdb55c34383c4417391697849417ef1a493866d30d52828f37e69abb81",
"artifact_hash": "e7d211cd3c3c2289c327ebe0... | true | true | null |
python_to_en_plaincode | ######## Image Object Detection Using Tensorflow-trained Classifier #########
#
# Author: <NAME>
# Date: 1/15/18
# Description:
# This program uses a TensorFlow-trained classifier to perform object detection.
# It loads the classifier uses it to perform object detection on an image.
# It draws boxes and scores around ... | # ####### Image Object Detection Using Tensorflow-trained Classifier #########
#
# Author: <NAME>
# Date: 1/15/18
# Description:
# This program uses a TensorFlow-trained classifier to perform object detection.
# It loads the classifier uses it to perform object detection on an image.
# It draws boxes and scores around ... | python | en | run_002_20260417_060406 | 13 | {
"max_stars_repo_path": "Object_detection_image.py",
"max_stars_repo_name": "hiperus0988/pyao",
"max_stars_count": 1,
"id": "23",
"raw_source_hash": "6f10fe3937e35951eeb5bb4ced40684942e59c93a0a0e010b52991db4e9b39fb",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_... | {
"raw_source_hash": "6f10fe3937e35951eeb5bb4ced40684942e59c93a0a0e010b52991db4e9b39fb",
"normalized_source_hash": "407e7f9d1bb635e49146c17ff9c2114196a9bfb41a2fe601cfbdbd4131314577",
"source_ast_hash": "32c8e1b70d7d473326d699b762e40b32ffe93d89c34e56815e4ee970f4ab80e0",
"artifact_hash": "4c1c12475fd6922727adab14... | true | true | null |
python_to_es_plaincode | ######## Image Object Detection Using Tensorflow-trained Classifier #########
#
# Author: <NAME>
# Date: 1/15/18
# Description:
# This program uses a TensorFlow-trained classifier to perform object detection.
# It loads the classifier uses it to perform object detection on an image.
# It draws boxes and scores around ... | # ####### Image Object Detection Using Tensorflow-trained Classifier #########
#
# Author: <NAME>
# Date: 1/15/18
# Description:
# This program uses a TensorFlow-trained classifier como perform object detection.
# It loads the classifier uses it como perform object detection on an image.
# It draws boxes y también scor... | python | es | run_002_20260417_060406 | 13 | {
"max_stars_repo_path": "Object_detection_image.py",
"max_stars_repo_name": "hiperus0988/pyao",
"max_stars_count": 1,
"id": "23",
"raw_source_hash": "6f10fe3937e35951eeb5bb4ced40684942e59c93a0a0e010b52991db4e9b39fb",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_... | {
"raw_source_hash": "6f10fe3937e35951eeb5bb4ced40684942e59c93a0a0e010b52991db4e9b39fb",
"normalized_source_hash": "407e7f9d1bb635e49146c17ff9c2114196a9bfb41a2fe601cfbdbd4131314577",
"source_ast_hash": "32c8e1b70d7d473326d699b762e40b32ffe93d89c34e56815e4ee970f4ab80e0",
"artifact_hash": "4c1c12475fd6922727adab14... | true | true | null |
python_to_fr_plaincode | ######## Image Object Detection Using Tensorflow-trained Classifier #########
#
# Author: <NAME>
# Date: 1/15/18
# Description:
# This program uses a TensorFlow-trained classifier to perform object detection.
# It loads the classifier uses it to perform object detection on an image.
# It draws boxes and scores around ... | # ####### Image Object Detection Using Tensorflow-trained Classifier #########
#
# Author: <NAME>
# Date: 1/15/18
# Description:
# This program uses a TensorFlow-trained classifier à perform object detection.
# It loads the classifier uses it à perform object detection on an image.
# It draws boxes et scores around the... | python | fr | run_002_20260417_060406 | 13 | {
"max_stars_repo_path": "Object_detection_image.py",
"max_stars_repo_name": "hiperus0988/pyao",
"max_stars_count": 1,
"id": "23",
"raw_source_hash": "6f10fe3937e35951eeb5bb4ced40684942e59c93a0a0e010b52991db4e9b39fb",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_... | {
"raw_source_hash": "6f10fe3937e35951eeb5bb4ced40684942e59c93a0a0e010b52991db4e9b39fb",
"normalized_source_hash": "407e7f9d1bb635e49146c17ff9c2114196a9bfb41a2fe601cfbdbd4131314577",
"source_ast_hash": "32c8e1b70d7d473326d699b762e40b32ffe93d89c34e56815e4ee970f4ab80e0",
"artifact_hash": "4c1c12475fd6922727adab14... | true | true | null |
en_plaincode_to_python | # ####### Image Object Detection Using Tensorflow-trained Classifier #########
#
# Author: <NAME>
# Date: 1/15/18
# Description:
# This program uses a TensorFlow-trained classifier to perform object detection.
# It loads the classifier uses it to perform object detection on an image.
# It draws boxes and scores around ... | ######## Image Object Detection Using Tensorflow-trained Classifier #########
#
# Author: <NAME>
# Date: 1/15/18
# Description:
# This program uses a TensorFlow-trained classifier to perform object detection.
# It loads the classifier uses it to perform object detection on an image.
# It draws boxes and scores around ... | en | python | run_002_20260417_060406 | 13 | {
"max_stars_repo_path": "Object_detection_image.py",
"max_stars_repo_name": "hiperus0988/pyao",
"max_stars_count": 1,
"id": "23",
"raw_source_hash": "6f10fe3937e35951eeb5bb4ced40684942e59c93a0a0e010b52991db4e9b39fb",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_... | {
"raw_source_hash": "6f10fe3937e35951eeb5bb4ced40684942e59c93a0a0e010b52991db4e9b39fb",
"normalized_source_hash": "407e7f9d1bb635e49146c17ff9c2114196a9bfb41a2fe601cfbdbd4131314577",
"source_ast_hash": "32c8e1b70d7d473326d699b762e40b32ffe93d89c34e56815e4ee970f4ab80e0",
"artifact_hash": "4c1c12475fd6922727adab14... | true | true | null |
python_to_en_plaincode | from data_collection.management.commands import BaseXpressDemocracyClubCsvImporter
class Command(BaseXpressDemocracyClubCsvImporter):
council_id = 'E06000027'
addresses_name = 'parl.2017-06-08/Version 1/Torbay Democracy_Club__08June2017.tsv'
stations_name = 'parl.2017-06-08/Version 1/Torbay Democracy_Club_... | Load BaseXpressDemocracyClubCsvImporter from data_collection.management.commands.
Define class Command inheriting from BaseXpressDemocracyClubCsvImporter:
Set council_id to "E06000027".
Set addresses_name to "parl.2017-06-08/Version 1/Torbay Democracy_Club__08June2017.tsv".
Set stations_name to "parl.2017-0... | python | en | run_002_20260417_060406 | 14 | {
"max_stars_repo_path": "polling_stations/apps/data_collection/management/commands/import_torbay.py",
"max_stars_repo_name": "chris48s/UK-Polling-Stations",
"max_stars_count": 0,
"id": "24",
"raw_source_hash": "48635c377f6ab9534cee049f3e98044d65deae3fe190824d51208337b58fd5ba",
"sanitize_meta": {
"tripl... | {
"raw_source_hash": "48635c377f6ab9534cee049f3e98044d65deae3fe190824d51208337b58fd5ba",
"normalized_source_hash": "1cc5d98b43271ebc6510e715769baf9f3133fe6b939db294fede245703bd59a2",
"source_ast_hash": "620edbabd69b18ad63ba770dbb2aa7978941a84033cabe04b235f8d65de45256",
"artifact_hash": "1b1d90692bf3fa144c711351... | true | true | null |
python_to_es_plaincode | from data_collection.management.commands import BaseXpressDemocracyClubCsvImporter
class Command(BaseXpressDemocracyClubCsvImporter):
council_id = 'E06000027'
addresses_name = 'parl.2017-06-08/Version 1/Torbay Democracy_Club__08June2017.tsv'
stations_name = 'parl.2017-06-08/Version 1/Torbay Democracy_Club_... | Importar BaseXpressDemocracyClubCsvImporter desde data_collection.management.commands.
Definir clase Command heredando de BaseXpressDemocracyClubCsvImporter:
Establecer council_id como "E06000027".
Establecer addresses_name como "parl.2017-06-08/Version 1/Torbay Democracy_Club__08June2017.tsv".
Establecer s... | python | es | run_002_20260417_060406 | 14 | {
"max_stars_repo_path": "polling_stations/apps/data_collection/management/commands/import_torbay.py",
"max_stars_repo_name": "chris48s/UK-Polling-Stations",
"max_stars_count": 0,
"id": "24",
"raw_source_hash": "48635c377f6ab9534cee049f3e98044d65deae3fe190824d51208337b58fd5ba",
"sanitize_meta": {
"tripl... | {
"raw_source_hash": "48635c377f6ab9534cee049f3e98044d65deae3fe190824d51208337b58fd5ba",
"normalized_source_hash": "1cc5d98b43271ebc6510e715769baf9f3133fe6b939db294fede245703bd59a2",
"source_ast_hash": "620edbabd69b18ad63ba770dbb2aa7978941a84033cabe04b235f8d65de45256",
"artifact_hash": "1b1d90692bf3fa144c711351... | true | true | null |
python_to_fr_plaincode | from data_collection.management.commands import BaseXpressDemocracyClubCsvImporter
class Command(BaseXpressDemocracyClubCsvImporter):
council_id = 'E06000027'
addresses_name = 'parl.2017-06-08/Version 1/Torbay Democracy_Club__08June2017.tsv'
stations_name = 'parl.2017-06-08/Version 1/Torbay Democracy_Club_... | Charger BaseXpressDemocracyClubCsvImporter depuis data_collection.management.commands.
Définir classe Command héritant de BaseXpressDemocracyClubCsvImporter:
Affecter council_id à "E06000027".
Affecter addresses_name à "parl.2017-06-08/Version 1/Torbay Democracy_Club__08June2017.tsv".
Affecter stations_name... | python | fr | run_002_20260417_060406 | 14 | {
"max_stars_repo_path": "polling_stations/apps/data_collection/management/commands/import_torbay.py",
"max_stars_repo_name": "chris48s/UK-Polling-Stations",
"max_stars_count": 0,
"id": "24",
"raw_source_hash": "48635c377f6ab9534cee049f3e98044d65deae3fe190824d51208337b58fd5ba",
"sanitize_meta": {
"tripl... | {
"raw_source_hash": "48635c377f6ab9534cee049f3e98044d65deae3fe190824d51208337b58fd5ba",
"normalized_source_hash": "1cc5d98b43271ebc6510e715769baf9f3133fe6b939db294fede245703bd59a2",
"source_ast_hash": "620edbabd69b18ad63ba770dbb2aa7978941a84033cabe04b235f8d65de45256",
"artifact_hash": "1b1d90692bf3fa144c711351... | true | true | null |
en_plaincode_to_python | Load BaseXpressDemocracyClubCsvImporter from data_collection.management.commands.
Define class Command inheriting from BaseXpressDemocracyClubCsvImporter:
Set council_id to "E06000027".
Set addresses_name to "parl.2017-06-08/Version 1/Torbay Democracy_Club__08June2017.tsv".
Set stations_name to "parl.2017-0... | from data_collection.management.commands import BaseXpressDemocracyClubCsvImporter
class Command(BaseXpressDemocracyClubCsvImporter):
council_id = 'E06000027'
addresses_name = 'parl.2017-06-08/Version 1/Torbay Democracy_Club__08June2017.tsv'
stations_name = 'parl.2017-06-08/Version 1/Torbay Democracy_Club_... | en | python | run_002_20260417_060406 | 14 | {
"max_stars_repo_path": "polling_stations/apps/data_collection/management/commands/import_torbay.py",
"max_stars_repo_name": "chris48s/UK-Polling-Stations",
"max_stars_count": 0,
"id": "24",
"raw_source_hash": "48635c377f6ab9534cee049f3e98044d65deae3fe190824d51208337b58fd5ba",
"sanitize_meta": {
"tripl... | {
"raw_source_hash": "48635c377f6ab9534cee049f3e98044d65deae3fe190824d51208337b58fd5ba",
"normalized_source_hash": "1cc5d98b43271ebc6510e715769baf9f3133fe6b939db294fede245703bd59a2",
"source_ast_hash": "620edbabd69b18ad63ba770dbb2aa7978941a84033cabe04b235f8d65de45256",
"artifact_hash": "1b1d90692bf3fa144c711351... | true | true | null |
python_to_en_plaincode | from django.db.models import Q
from django.shortcuts import render
from django.http import Http404
# Create your views here.
from rest_framework.views import APIView
from rest_framework.response import Response
from rest_framework.decorators import api_view
from .models import Product, Category
from .serializers imp... | Load Q from django.db.models.
Load render from django.shortcuts.
Load Http404 from django.http.
# Create your views here.
Load APIView from rest_framework.views.
Load Response from rest_framework.response.
Load api_view from rest_framework.decorators.
Load Product, Category from the current package.models.
Load Product... | python | en | run_002_20260417_060406 | 15 | {
"max_stars_repo_path": "Backend/product/views.py",
"max_stars_repo_name": "Bhavya0020/Readopolis",
"max_stars_count": 0,
"id": "25",
"raw_source_hash": "371e23c5cb59408b66ff53795e32d56b67cca34d4bb8eb6abf142a8a695ed799",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"larg... | {
"raw_source_hash": "371e23c5cb59408b66ff53795e32d56b67cca34d4bb8eb6abf142a8a695ed799",
"normalized_source_hash": "fd34ad4436e9e8bc4ca46d0d75b284324f24c8d45b98e83b803908dd33fcc098",
"source_ast_hash": "174ebbb46424f5ec8d17df0f1022bfbb34bbfc29ccc8d089bbeb00dc5d36e99c",
"artifact_hash": "1ff9d35a7303d11a505a791a... | true | true | null |
python_to_es_plaincode | from django.db.models import Q
from django.shortcuts import render
from django.http import Http404
# Create your views here.
from rest_framework.views import APIView
from rest_framework.response import Response
from rest_framework.decorators import api_view
from .models import Product, Category
from .serializers imp... | Importar Q desde django.db.models.
Importar render desde django.shortcuts.
Importar Http404 desde django.http.
# Create your views here.
Importar APIView desde rest_framework.views.
Importar Response desde rest_framework.response.
Importar api_view desde rest_framework.decorators.
Importar Product, Category desde el pa... | python | es | run_002_20260417_060406 | 15 | {
"max_stars_repo_path": "Backend/product/views.py",
"max_stars_repo_name": "Bhavya0020/Readopolis",
"max_stars_count": 0,
"id": "25",
"raw_source_hash": "371e23c5cb59408b66ff53795e32d56b67cca34d4bb8eb6abf142a8a695ed799",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"larg... | {
"raw_source_hash": "371e23c5cb59408b66ff53795e32d56b67cca34d4bb8eb6abf142a8a695ed799",
"normalized_source_hash": "fd34ad4436e9e8bc4ca46d0d75b284324f24c8d45b98e83b803908dd33fcc098",
"source_ast_hash": "174ebbb46424f5ec8d17df0f1022bfbb34bbfc29ccc8d089bbeb00dc5d36e99c",
"artifact_hash": "1ff9d35a7303d11a505a791a... | true | true | null |
python_to_fr_plaincode | from django.db.models import Q
from django.shortcuts import render
from django.http import Http404
# Create your views here.
from rest_framework.views import APIView
from rest_framework.response import Response
from rest_framework.decorators import api_view
from .models import Product, Category
from .serializers imp... | Charger Q depuis django.db.models.
Charger render depuis django.shortcuts.
Charger Http404 depuis django.http.
# Create your views here.
Charger APIView depuis rest_framework.views.
Charger Response depuis rest_framework.response.
Charger api_view depuis rest_framework.decorators.
Charger Product, Category depuis le pa... | python | fr | run_002_20260417_060406 | 15 | {
"max_stars_repo_path": "Backend/product/views.py",
"max_stars_repo_name": "Bhavya0020/Readopolis",
"max_stars_count": 0,
"id": "25",
"raw_source_hash": "371e23c5cb59408b66ff53795e32d56b67cca34d4bb8eb6abf142a8a695ed799",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"larg... | {
"raw_source_hash": "371e23c5cb59408b66ff53795e32d56b67cca34d4bb8eb6abf142a8a695ed799",
"normalized_source_hash": "fd34ad4436e9e8bc4ca46d0d75b284324f24c8d45b98e83b803908dd33fcc098",
"source_ast_hash": "174ebbb46424f5ec8d17df0f1022bfbb34bbfc29ccc8d089bbeb00dc5d36e99c",
"artifact_hash": "1ff9d35a7303d11a505a791a... | true | true | null |
en_plaincode_to_python | Load Q from django.db.models.
Load render from django.shortcuts.
Load Http404 from django.http.
# Create your views here.
Load APIView from rest_framework.views.
Load Response from rest_framework.response.
Load api_view from rest_framework.decorators.
Load Product, Category from the current package.models.
Load Product... | from django.db.models import Q
from django.shortcuts import render
from django.http import Http404
# Create your views here.
from rest_framework.views import APIView
from rest_framework.response import Response
from rest_framework.decorators import api_view
from .models import Product, Category
from .serializers imp... | en | python | run_002_20260417_060406 | 15 | {
"max_stars_repo_path": "Backend/product/views.py",
"max_stars_repo_name": "Bhavya0020/Readopolis",
"max_stars_count": 0,
"id": "25",
"raw_source_hash": "371e23c5cb59408b66ff53795e32d56b67cca34d4bb8eb6abf142a8a695ed799",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"larg... | {
"raw_source_hash": "371e23c5cb59408b66ff53795e32d56b67cca34d4bb8eb6abf142a8a695ed799",
"normalized_source_hash": "fd34ad4436e9e8bc4ca46d0d75b284324f24c8d45b98e83b803908dd33fcc098",
"source_ast_hash": "174ebbb46424f5ec8d17df0f1022bfbb34bbfc29ccc8d089bbeb00dc5d36e99c",
"artifact_hash": "1ff9d35a7303d11a505a791a... | true | true | null |
python_to_en_plaincode | from sys import maxsize
class Contact:
def __init__(self, fname=None, mname=None, lname=None, nick=None, title=None, comp=None, addr=None,
home=None, mobile=None, work=None, fax=None, email1=None, email2=None, email3=None,
homepage=None, bday=None, bmonth=None, byear=None, aday=... | Load maxsize from sys.
Define class Contact:
Define method __init__ with parameters self, fname (default: None), mname (default: None), lname (default: None), nick (default: None), title (default: None), comp (default: None), addr (default: None), home (default: None), mobile (default: None), work (default: None), ... | python | en | run_002_20260417_060406 | 16 | {
"max_stars_repo_path": "model/contact.py",
"max_stars_repo_name": "hubogeri/python_training",
"max_stars_count": 0,
"id": "26",
"raw_source_hash": "0cde2967b1feb08a16836293cbedac48942ca7b246b3bc4e40a0237b8ddc0a83",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_t... | {
"raw_source_hash": "0cde2967b1feb08a16836293cbedac48942ca7b246b3bc4e40a0237b8ddc0a83",
"normalized_source_hash": "34b39cd1944f9fd988a0d41a2b939af23582790b1c774c817aa3788536fd470a",
"source_ast_hash": "774a86b020617074bdb2e148ba47d8a7287cffefd982ba6080fcdd77a492d6d7",
"artifact_hash": "50d606b3c3d2058b17c264ee... | true | true | null |
python_to_es_plaincode | from sys import maxsize
class Contact:
def __init__(self, fname=None, mname=None, lname=None, nick=None, title=None, comp=None, addr=None,
home=None, mobile=None, work=None, fax=None, email1=None, email2=None, email3=None,
homepage=None, bday=None, bmonth=None, byear=None, aday=... | Importar maxsize desde sys.
Definir clase Contact:
Definir método __init__ con parámetros self, fname (predeterminado: None), mname (predeterminado: None), lname (predeterminado: None), nick (predeterminado: None), title (predeterminado: None), comp (predeterminado: None), addr (predeterminado: None), home (predete... | python | es | run_002_20260417_060406 | 16 | {
"max_stars_repo_path": "model/contact.py",
"max_stars_repo_name": "hubogeri/python_training",
"max_stars_count": 0,
"id": "26",
"raw_source_hash": "0cde2967b1feb08a16836293cbedac48942ca7b246b3bc4e40a0237b8ddc0a83",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_t... | {
"raw_source_hash": "0cde2967b1feb08a16836293cbedac48942ca7b246b3bc4e40a0237b8ddc0a83",
"normalized_source_hash": "34b39cd1944f9fd988a0d41a2b939af23582790b1c774c817aa3788536fd470a",
"source_ast_hash": "774a86b020617074bdb2e148ba47d8a7287cffefd982ba6080fcdd77a492d6d7",
"artifact_hash": "50d606b3c3d2058b17c264ee... | true | true | null |
python_to_fr_plaincode | from sys import maxsize
class Contact:
def __init__(self, fname=None, mname=None, lname=None, nick=None, title=None, comp=None, addr=None,
home=None, mobile=None, work=None, fax=None, email1=None, email2=None, email3=None,
homepage=None, bday=None, bmonth=None, byear=None, aday=... | Charger maxsize depuis sys.
Définir classe Contact:
Définir méthode __init__ avec paramètres self, fname (par défaut: None), mname (par défaut: None), lname (par défaut: None), nick (par défaut: None), title (par défaut: None), comp (par défaut: None), addr (par défaut: None), home (par défaut: None), mobile (par d... | python | fr | run_002_20260417_060406 | 16 | {
"max_stars_repo_path": "model/contact.py",
"max_stars_repo_name": "hubogeri/python_training",
"max_stars_count": 0,
"id": "26",
"raw_source_hash": "0cde2967b1feb08a16836293cbedac48942ca7b246b3bc4e40a0237b8ddc0a83",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_t... | {
"raw_source_hash": "0cde2967b1feb08a16836293cbedac48942ca7b246b3bc4e40a0237b8ddc0a83",
"normalized_source_hash": "34b39cd1944f9fd988a0d41a2b939af23582790b1c774c817aa3788536fd470a",
"source_ast_hash": "774a86b020617074bdb2e148ba47d8a7287cffefd982ba6080fcdd77a492d6d7",
"artifact_hash": "50d606b3c3d2058b17c264ee... | true | true | null |
en_plaincode_to_python | Load maxsize from sys.
Define class Contact:
Define method __init__ with parameters self, fname (default: None), mname (default: None), lname (default: None), nick (default: None), title (default: None), comp (default: None), addr (default: None), home (default: None), mobile (default: None), work (default: None), ... | from sys import maxsize
class Contact:
def __init__(self, fname=None, mname=None, lname=None, nick=None, title=None, comp=None, addr=None,
home=None, mobile=None, work=None, fax=None, email1=None, email2=None, email3=None,
homepage=None, bday=None, bmonth=None, byear=None, aday=... | en | python | run_002_20260417_060406 | 16 | {
"max_stars_repo_path": "model/contact.py",
"max_stars_repo_name": "hubogeri/python_training",
"max_stars_count": 0,
"id": "26",
"raw_source_hash": "0cde2967b1feb08a16836293cbedac48942ca7b246b3bc4e40a0237b8ddc0a83",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_t... | {
"raw_source_hash": "0cde2967b1feb08a16836293cbedac48942ca7b246b3bc4e40a0237b8ddc0a83",
"normalized_source_hash": "34b39cd1944f9fd988a0d41a2b939af23582790b1c774c817aa3788536fd470a",
"source_ast_hash": "774a86b020617074bdb2e148ba47d8a7287cffefd982ba6080fcdd77a492d6d7",
"artifact_hash": "50d606b3c3d2058b17c264ee... | true | true | null |
python_to_en_plaincode | ##########################################################################
#
# Copyright (c) 2010-2012, Image Engine Design Inc. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redis... | # #########################################################################
#
# Copyright (c) 2010-2012, Image Engine Design Inc. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redi... | python | en | run_002_20260417_060406 | 17 | {
"max_stars_repo_path": "test/IECore/BasicPreset.py",
"max_stars_repo_name": "ericmehl/cortex",
"max_stars_count": 386,
"id": "27",
"raw_source_hash": "74b990b374d9cc4341a13766f582dd42085c421704886f9da7903fb8ca73a4ac",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"larges... | {
"raw_source_hash": "74b990b374d9cc4341a13766f582dd42085c421704886f9da7903fb8ca73a4ac",
"normalized_source_hash": "833086e3dab9940d42c46ae425f997c34b3991776f3154e096a3f1d7c5b8d809",
"source_ast_hash": "636945b3bb27818fcfd739ddeec071bdde49472e883135822307cc977be27cb6",
"artifact_hash": "75653a904d94281e00d85b72... | true | true | null |
python_to_es_plaincode | ##########################################################################
#
# Copyright (c) 2010-2012, Image Engine Design Inc. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redis... | # #########################################################################
#
# Copyright (c) 2010-2012, Image Engine Design Inc. All rights reserved.
#
# Redistribution y también use en source y también binary forms, con o without
# modification, are permitted provided that the following conditions are
# met:
#
# ... | python | es | run_002_20260417_060406 | 17 | {
"max_stars_repo_path": "test/IECore/BasicPreset.py",
"max_stars_repo_name": "ericmehl/cortex",
"max_stars_count": 386,
"id": "27",
"raw_source_hash": "74b990b374d9cc4341a13766f582dd42085c421704886f9da7903fb8ca73a4ac",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"larges... | {
"raw_source_hash": "74b990b374d9cc4341a13766f582dd42085c421704886f9da7903fb8ca73a4ac",
"normalized_source_hash": "833086e3dab9940d42c46ae425f997c34b3991776f3154e096a3f1d7c5b8d809",
"source_ast_hash": "636945b3bb27818fcfd739ddeec071bdde49472e883135822307cc977be27cb6",
"artifact_hash": "75653a904d94281e00d85b72... | true | true | null |
python_to_fr_plaincode | ##########################################################################
#
# Copyright (c) 2010-2012, Image Engine Design Inc. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redis... | # #########################################################################
#
# Copyright (c) 2010-2012, Image Engine Design Inc. All rights reserved.
#
# Redistribution et use dans source et binary forms, avec ou without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redi... | python | fr | run_002_20260417_060406 | 17 | {
"max_stars_repo_path": "test/IECore/BasicPreset.py",
"max_stars_repo_name": "ericmehl/cortex",
"max_stars_count": 386,
"id": "27",
"raw_source_hash": "74b990b374d9cc4341a13766f582dd42085c421704886f9da7903fb8ca73a4ac",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"larges... | {
"raw_source_hash": "74b990b374d9cc4341a13766f582dd42085c421704886f9da7903fb8ca73a4ac",
"normalized_source_hash": "833086e3dab9940d42c46ae425f997c34b3991776f3154e096a3f1d7c5b8d809",
"source_ast_hash": "636945b3bb27818fcfd739ddeec071bdde49472e883135822307cc977be27cb6",
"artifact_hash": "75653a904d94281e00d85b72... | true | true | null |
en_plaincode_to_python | # #########################################################################
#
# Copyright (c) 2010-2012, Image Engine Design Inc. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redi... | ##########################################################################
#
# Copyright (c) 2010-2012, Image Engine Design Inc. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redis... | en | python | run_002_20260417_060406 | 17 | {
"max_stars_repo_path": "test/IECore/BasicPreset.py",
"max_stars_repo_name": "ericmehl/cortex",
"max_stars_count": 386,
"id": "27",
"raw_source_hash": "74b990b374d9cc4341a13766f582dd42085c421704886f9da7903fb8ca73a4ac",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"larges... | {
"raw_source_hash": "74b990b374d9cc4341a13766f582dd42085c421704886f9da7903fb8ca73a4ac",
"normalized_source_hash": "833086e3dab9940d42c46ae425f997c34b3991776f3154e096a3f1d7c5b8d809",
"source_ast_hash": "636945b3bb27818fcfd739ddeec071bdde49472e883135822307cc977be27cb6",
"artifact_hash": "75653a904d94281e00d85b72... | true | true | null |
python_to_en_plaincode | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | # !/usr/bin/env python
# -*- coding: utf-8 -*-
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ... | python | en | run_002_20260417_060406 | 18 | {
"max_stars_repo_path": "setup.py",
"max_stars_repo_name": "giggslam/python-messengerbot-sdk",
"max_stars_count": 23,
"id": "31",
"raw_source_hash": "ce56d34e69da106b88244614c721079a9945a555c6a9ad8b182811ec6992247f",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_... | {
"raw_source_hash": "ce56d34e69da106b88244614c721079a9945a555c6a9ad8b182811ec6992247f",
"normalized_source_hash": "90c9d63015b116b0788cbd730c0ac73c157b8159f45f27bd873d125d01f385c2",
"source_ast_hash": "681debe965af8efcdecb42402fae0a645e4a922fa579cd0025f67e9caa60481a",
"artifact_hash": "833cdf7b2890f8041dcd5932... | true | true | null |
python_to_es_plaincode | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | # !/usr/bin/env python
# -*- coding: utf-8 -*-
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# no use this file except en compliance con the License. You may obtain
# a copy de the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required por applicable law o ag... | python | es | run_002_20260417_060406 | 18 | {
"max_stars_repo_path": "setup.py",
"max_stars_repo_name": "giggslam/python-messengerbot-sdk",
"max_stars_count": 23,
"id": "31",
"raw_source_hash": "ce56d34e69da106b88244614c721079a9945a555c6a9ad8b182811ec6992247f",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_... | {
"raw_source_hash": "ce56d34e69da106b88244614c721079a9945a555c6a9ad8b182811ec6992247f",
"normalized_source_hash": "90c9d63015b116b0788cbd730c0ac73c157b8159f45f27bd873d125d01f385c2",
"source_ast_hash": "681debe965af8efcdecb42402fae0a645e4a922fa579cd0025f67e9caa60481a",
"artifact_hash": "833cdf7b2890f8041dcd5932... | true | true | null |
python_to_fr_plaincode | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | # !/usr/bin/env python
# -*- coding: utf-8 -*-
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# non use this file except dans compliance avec the License. You may obtain
# a copy de the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required par applicable law ... | python | fr | run_002_20260417_060406 | 18 | {
"max_stars_repo_path": "setup.py",
"max_stars_repo_name": "giggslam/python-messengerbot-sdk",
"max_stars_count": 23,
"id": "31",
"raw_source_hash": "ce56d34e69da106b88244614c721079a9945a555c6a9ad8b182811ec6992247f",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_... | {
"raw_source_hash": "ce56d34e69da106b88244614c721079a9945a555c6a9ad8b182811ec6992247f",
"normalized_source_hash": "90c9d63015b116b0788cbd730c0ac73c157b8159f45f27bd873d125d01f385c2",
"source_ast_hash": "681debe965af8efcdecb42402fae0a645e4a922fa579cd0025f67e9caa60481a",
"artifact_hash": "833cdf7b2890f8041dcd5932... | true | true | null |
en_plaincode_to_python | # !/usr/bin/env python
# -*- coding: utf-8 -*-
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ... | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | en | python | run_002_20260417_060406 | 18 | {
"max_stars_repo_path": "setup.py",
"max_stars_repo_name": "giggslam/python-messengerbot-sdk",
"max_stars_count": 23,
"id": "31",
"raw_source_hash": "ce56d34e69da106b88244614c721079a9945a555c6a9ad8b182811ec6992247f",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_... | {
"raw_source_hash": "ce56d34e69da106b88244614c721079a9945a555c6a9ad8b182811ec6992247f",
"normalized_source_hash": "90c9d63015b116b0788cbd730c0ac73c157b8159f45f27bd873d125d01f385c2",
"source_ast_hash": "681debe965af8efcdecb42402fae0a645e4a922fa579cd0025f67e9caa60481a",
"artifact_hash": "833cdf7b2890f8041dcd5932... | true | true | null |
python_to_en_plaincode | from abc import (
ABC,
abstractmethod,
)
import logging
from typing import (
TYPE_CHECKING,
Tuple,
Type,
)
from eth._utils.datatypes import (
Configurable,
)
from eth.db.backends.base import (
BaseAtomicDB,
)
from eth.exceptions import (
BlockNotFound,
)
from eth.validation import (
... | Load ABC, abstractmethod from abc.
Load logging.
Load TYPE_CHECKING, Tuple, Type from typing.
Load Configurable from eth._utils.datatypes.
Load BaseAtomicDB from eth.db.backends.base.
Load BlockNotFound from eth.exceptions.
Load validate_word from eth.validation.
Load Hash32 from eth_typing.
Load ValidationError, encod... | python | en | run_002_20260417_060406 | 19 | {
"max_stars_repo_path": "eth2/beacon/chains/base.py",
"max_stars_repo_name": "mhchia/trinity",
"max_stars_count": 0,
"id": "33",
"raw_source_hash": "0fdf55898a047dcb568336091976a73f11ffb352a11657711ba48b761be983ad",
"sanitize_meta": {
"triple_block_count": 16,
"total_triple_chars": 2220,
"large... | {
"raw_source_hash": "0fdf55898a047dcb568336091976a73f11ffb352a11657711ba48b761be983ad",
"normalized_source_hash": "0b254fb2098f3ce7a400cd1a8e040f2e62948e90e35f057798f144bb62b529ad",
"source_ast_hash": "06aeecb0dc7bcb91be79969928df449443f32d0c6a383404072f59bdac3c3c58",
"artifact_hash": "27cf31f6509331774fddc803... | true | true | null |
python_to_es_plaincode | from abc import (
ABC,
abstractmethod,
)
import logging
from typing import (
TYPE_CHECKING,
Tuple,
Type,
)
from eth._utils.datatypes import (
Configurable,
)
from eth.db.backends.base import (
BaseAtomicDB,
)
from eth.exceptions import (
BlockNotFound,
)
from eth.validation import (
... | Importar ABC, abstractmethod desde abc.
Importar logging.
Importar TYPE_CHECKING, Tuple, Type desde typing.
Importar Configurable desde eth._utils.datatypes.
Importar BaseAtomicDB desde eth.db.backends.base.
Importar BlockNotFound desde eth.exceptions.
Importar validate_word desde eth.validation.
Importar Hash32 desde ... | python | es | run_002_20260417_060406 | 19 | {
"max_stars_repo_path": "eth2/beacon/chains/base.py",
"max_stars_repo_name": "mhchia/trinity",
"max_stars_count": 0,
"id": "33",
"raw_source_hash": "0fdf55898a047dcb568336091976a73f11ffb352a11657711ba48b761be983ad",
"sanitize_meta": {
"triple_block_count": 16,
"total_triple_chars": 2220,
"large... | {
"raw_source_hash": "0fdf55898a047dcb568336091976a73f11ffb352a11657711ba48b761be983ad",
"normalized_source_hash": "0b254fb2098f3ce7a400cd1a8e040f2e62948e90e35f057798f144bb62b529ad",
"source_ast_hash": "06aeecb0dc7bcb91be79969928df449443f32d0c6a383404072f59bdac3c3c58",
"artifact_hash": "27cf31f6509331774fddc803... | true | true | null |
python_to_fr_plaincode | from abc import (
ABC,
abstractmethod,
)
import logging
from typing import (
TYPE_CHECKING,
Tuple,
Type,
)
from eth._utils.datatypes import (
Configurable,
)
from eth.db.backends.base import (
BaseAtomicDB,
)
from eth.exceptions import (
BlockNotFound,
)
from eth.validation import (
... | Charger ABC, abstractmethod depuis abc.
Charger logging.
Charger TYPE_CHECKING, Tuple, Type depuis typing.
Charger Configurable depuis eth._utils.datatypes.
Charger BaseAtomicDB depuis eth.db.backends.base.
Charger BlockNotFound depuis eth.exceptions.
Charger validate_word depuis eth.validation.
Charger Hash32 depuis e... | python | fr | run_002_20260417_060406 | 19 | {
"max_stars_repo_path": "eth2/beacon/chains/base.py",
"max_stars_repo_name": "mhchia/trinity",
"max_stars_count": 0,
"id": "33",
"raw_source_hash": "0fdf55898a047dcb568336091976a73f11ffb352a11657711ba48b761be983ad",
"sanitize_meta": {
"triple_block_count": 16,
"total_triple_chars": 2220,
"large... | {
"raw_source_hash": "0fdf55898a047dcb568336091976a73f11ffb352a11657711ba48b761be983ad",
"normalized_source_hash": "0b254fb2098f3ce7a400cd1a8e040f2e62948e90e35f057798f144bb62b529ad",
"source_ast_hash": "06aeecb0dc7bcb91be79969928df449443f32d0c6a383404072f59bdac3c3c58",
"artifact_hash": "27cf31f6509331774fddc803... | true | true | null |
en_plaincode_to_python | Load ABC, abstractmethod from abc.
Load logging.
Load TYPE_CHECKING, Tuple, Type from typing.
Load Configurable from eth._utils.datatypes.
Load BaseAtomicDB from eth.db.backends.base.
Load BlockNotFound from eth.exceptions.
Load validate_word from eth.validation.
Load Hash32 from eth_typing.
Load ValidationError, encod... | from abc import (
ABC,
abstractmethod,
)
import logging
from typing import (
TYPE_CHECKING,
Tuple,
Type,
)
from eth._utils.datatypes import (
Configurable,
)
from eth.db.backends.base import (
BaseAtomicDB,
)
from eth.exceptions import (
BlockNotFound,
)
from eth.validation import (
... | en | python | run_002_20260417_060406 | 19 | {
"max_stars_repo_path": "eth2/beacon/chains/base.py",
"max_stars_repo_name": "mhchia/trinity",
"max_stars_count": 0,
"id": "33",
"raw_source_hash": "0fdf55898a047dcb568336091976a73f11ffb352a11657711ba48b761be983ad",
"sanitize_meta": {
"triple_block_count": 16,
"total_triple_chars": 2220,
"large... | {
"raw_source_hash": "0fdf55898a047dcb568336091976a73f11ffb352a11657711ba48b761be983ad",
"normalized_source_hash": "0b254fb2098f3ce7a400cd1a8e040f2e62948e90e35f057798f144bb62b529ad",
"source_ast_hash": "06aeecb0dc7bcb91be79969928df449443f32d0c6a383404072f59bdac3c3c58",
"artifact_hash": "27cf31f6509331774fddc803... | true | true | null |
python_to_en_plaincode | # for n in range(400,500):
# i = n // 100
# j = n // 10 % 10
# k = n % 10
# if n == i ** 3 + j ** 3 + k ** 3:
# print(n)
# 第一道题(16)
# input("请输入(第一次):")
# s1 = input("请输入(第二次):")
# l1 = s1.split(' ')
# l2 = []
# for i in l1:
# if i.isdigit():
# l2.append(int(i))
# for i in l2:
# ... | # for n in range(400,500):
# i = n // 100
# j = n // 10 % 10
# k = n % 10
# if n == i ** 3 + j ** 3 + k ** 3:
# print(n)
# 第一道题(16)
# input("请输入(第一次):")
# s1 = input("请输入(第二次):")
# l1 = s1.split(' ')
# l2 = []
# for i in l1:
# if i.isdigit():
# l2.append(int(i))
# for i in l2:
# ... | python | en | run_002_20260417_060406 | 20 | {
"max_stars_repo_path": "old/.history/a_20201125192943.py",
"max_stars_repo_name": "pscly/bisai1",
"max_stars_count": 0,
"id": "35",
"raw_source_hash": "40daad66139ecb5c081448dec2e82a1402aaf650ef4327c07595648dbd37c0c3",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"large... | {
"raw_source_hash": "40daad66139ecb5c081448dec2e82a1402aaf650ef4327c07595648dbd37c0c3",
"normalized_source_hash": "2150577fafbd605e57ccd30fcd406290d00474642223ceefe4834a23c774bc09",
"source_ast_hash": "ca9dfab1f9b072c2dc0c48de8f2c4cddd12c66b53cd44753fd3c7676deb06eaf",
"artifact_hash": "9d19cedca847e963793932a2... | true | true | null |
python_to_es_plaincode | # for n in range(400,500):
# i = n // 100
# j = n // 10 % 10
# k = n % 10
# if n == i ** 3 + j ** 3 + k ** 3:
# print(n)
# 第一道题(16)
# input("请输入(第一次):")
# s1 = input("请输入(第二次):")
# l1 = s1.split(' ')
# l2 = []
# for i in l1:
# if i.isdigit():
# l2.append(int(i))
# for i in l2:
# ... | # for n en range(400,500):
# i = n // 100
# j = n // 10 % 10
# k = n % 10
# si n == i ** 3 + j ** 3 + k ** 3:
# print(n)
# 第一道题(16)
# input("请输入(第一次):")
# s1 = input("请输入(第二次):")
# l1 = s1.split(' ')
# l2 = []
# for i en l1:
# si i.isdigit():
# l2.append(int(i))
# for i en l2:
# ... | python | es | run_002_20260417_060406 | 20 | {
"max_stars_repo_path": "old/.history/a_20201125192943.py",
"max_stars_repo_name": "pscly/bisai1",
"max_stars_count": 0,
"id": "35",
"raw_source_hash": "40daad66139ecb5c081448dec2e82a1402aaf650ef4327c07595648dbd37c0c3",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"large... | {
"raw_source_hash": "40daad66139ecb5c081448dec2e82a1402aaf650ef4327c07595648dbd37c0c3",
"normalized_source_hash": "2150577fafbd605e57ccd30fcd406290d00474642223ceefe4834a23c774bc09",
"source_ast_hash": "ca9dfab1f9b072c2dc0c48de8f2c4cddd12c66b53cd44753fd3c7676deb06eaf",
"artifact_hash": "9d19cedca847e963793932a2... | true | true | null |
python_to_fr_plaincode | # for n in range(400,500):
# i = n // 100
# j = n // 10 % 10
# k = n % 10
# if n == i ** 3 + j ** 3 + k ** 3:
# print(n)
# 第一道题(16)
# input("请输入(第一次):")
# s1 = input("请输入(第二次):")
# l1 = s1.split(' ')
# l2 = []
# for i in l1:
# if i.isdigit():
# l2.append(int(i))
# for i in l2:
# ... | # for n dans range(400,500):
# i = n // 100
# j = n // 10 % 10
# k = n % 10
# si n == i ** 3 + j ** 3 + k ** 3:
# print(n)
# 第一道题(16)
# input("请输入(第一次):")
# s1 = input("请输入(第二次):")
# l1 = s1.split(' ')
# l2 = []
# for i dans l1:
# si i.isdigit():
# l2.append(int(i))
# for i dans l2:
... | python | fr | run_002_20260417_060406 | 20 | {
"max_stars_repo_path": "old/.history/a_20201125192943.py",
"max_stars_repo_name": "pscly/bisai1",
"max_stars_count": 0,
"id": "35",
"raw_source_hash": "40daad66139ecb5c081448dec2e82a1402aaf650ef4327c07595648dbd37c0c3",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"large... | {
"raw_source_hash": "40daad66139ecb5c081448dec2e82a1402aaf650ef4327c07595648dbd37c0c3",
"normalized_source_hash": "2150577fafbd605e57ccd30fcd406290d00474642223ceefe4834a23c774bc09",
"source_ast_hash": "ca9dfab1f9b072c2dc0c48de8f2c4cddd12c66b53cd44753fd3c7676deb06eaf",
"artifact_hash": "9d19cedca847e963793932a2... | true | true | null |
en_plaincode_to_python | # for n in range(400,500):
# i = n // 100
# j = n // 10 % 10
# k = n % 10
# if n == i ** 3 + j ** 3 + k ** 3:
# print(n)
# 第一道题(16)
# input("请输入(第一次):")
# s1 = input("请输入(第二次):")
# l1 = s1.split(' ')
# l2 = []
# for i in l1:
# if i.isdigit():
# l2.append(int(i))
# for i in l2:
# ... | # for n in range(400,500):
# i = n // 100
# j = n // 10 % 10
# k = n % 10
# if n == i ** 3 + j ** 3 + k ** 3:
# print(n)
# 第一道题(16)
# input("请输入(第一次):")
# s1 = input("请输入(第二次):")
# l1 = s1.split(' ')
# l2 = []
# for i in l1:
# if i.isdigit():
# l2.append(int(i))
# for i in l2:
# ... | en | python | run_002_20260417_060406 | 20 | {
"max_stars_repo_path": "old/.history/a_20201125192943.py",
"max_stars_repo_name": "pscly/bisai1",
"max_stars_count": 0,
"id": "35",
"raw_source_hash": "40daad66139ecb5c081448dec2e82a1402aaf650ef4327c07595648dbd37c0c3",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"large... | {
"raw_source_hash": "40daad66139ecb5c081448dec2e82a1402aaf650ef4327c07595648dbd37c0c3",
"normalized_source_hash": "2150577fafbd605e57ccd30fcd406290d00474642223ceefe4834a23c774bc09",
"source_ast_hash": "ca9dfab1f9b072c2dc0c48de8f2c4cddd12c66b53cd44753fd3c7676deb06eaf",
"artifact_hash": "9d19cedca847e963793932a2... | true | true | null |
python_to_en_plaincode | """
A query transformer is a function that accepts a program and returns a program, plus a priority level.
Higher priority transformers are placed closer to the front of the list. We’re ensuring is a function,
because we’re going to evaluate it later 31 .
We’ll assume there won’t be an enormous number of transformer ad... | Text block:
""
"A query transformer is a function that accepts a program and returns a program, plus a priority level."
"Higher priority transformers are placed closer to the front of the list. We\u2019re ensuring is a function,"
"because we\u2019re going to evaluate it later 31 ."
"We\u2019ll assume there won\u2019t b... | python | en | run_002_20260417_060406 | 21 | {
"max_stars_repo_path": "graphdb/transformer.py",
"max_stars_repo_name": "muggat0n/graphdb",
"max_stars_count": 2,
"id": "36",
"raw_source_hash": "b3c876767fc289cce0b62ec9582025d24fb101ffce0942a3476775cffa8b4a59",
"sanitize_meta": {
"triple_block_count": 6,
"total_triple_chars": 1975,
"largest_... | {
"raw_source_hash": "b3c876767fc289cce0b62ec9582025d24fb101ffce0942a3476775cffa8b4a59",
"normalized_source_hash": "6e6bab9e63a65cbdd34ba35a2ecf3174137ca0b47fd297eed7fcd7b51c767230",
"source_ast_hash": "f1fc02e907b5320947db4235666957a6826eb492fa2add702d17bf0f1d6a3d2f",
"artifact_hash": "06b24e0a05f2c7cffa90a4d2... | true | true | null |
python_to_es_plaincode | """
A query transformer is a function that accepts a program and returns a program, plus a priority level.
Higher priority transformers are placed closer to the front of the list. We’re ensuring is a function,
because we’re going to evaluate it later 31 .
We’ll assume there won’t be an enormous number of transformer ad... | Texto literal:
""
"A query transformer is a function that accepts a program and returns a program, plus a priority level."
"Higher priority transformers are placed closer to the front of the list. We\u2019re ensuring is a function,"
"because we\u2019re going to evaluate it later 31 ."
"We\u2019ll assume there won\u2019... | python | es | run_002_20260417_060406 | 21 | {
"max_stars_repo_path": "graphdb/transformer.py",
"max_stars_repo_name": "muggat0n/graphdb",
"max_stars_count": 2,
"id": "36",
"raw_source_hash": "b3c876767fc289cce0b62ec9582025d24fb101ffce0942a3476775cffa8b4a59",
"sanitize_meta": {
"triple_block_count": 6,
"total_triple_chars": 1975,
"largest_... | {
"raw_source_hash": "b3c876767fc289cce0b62ec9582025d24fb101ffce0942a3476775cffa8b4a59",
"normalized_source_hash": "6e6bab9e63a65cbdd34ba35a2ecf3174137ca0b47fd297eed7fcd7b51c767230",
"source_ast_hash": "f1fc02e907b5320947db4235666957a6826eb492fa2add702d17bf0f1d6a3d2f",
"artifact_hash": "06b24e0a05f2c7cffa90a4d2... | true | true | null |
python_to_fr_plaincode | """
A query transformer is a function that accepts a program and returns a program, plus a priority level.
Higher priority transformers are placed closer to the front of the list. We’re ensuring is a function,
because we’re going to evaluate it later 31 .
We’ll assume there won’t be an enormous number of transformer ad... | Texte littéral:
""
"A query transformer is a function that accepts a program and returns a program, plus a priority level."
"Higher priority transformers are placed closer to the front of the list. We\u2019re ensuring is a function,"
"because we\u2019re going to evaluate it later 31 ."
"We\u2019ll assume there won\u201... | python | fr | run_002_20260417_060406 | 21 | {
"max_stars_repo_path": "graphdb/transformer.py",
"max_stars_repo_name": "muggat0n/graphdb",
"max_stars_count": 2,
"id": "36",
"raw_source_hash": "b3c876767fc289cce0b62ec9582025d24fb101ffce0942a3476775cffa8b4a59",
"sanitize_meta": {
"triple_block_count": 6,
"total_triple_chars": 1975,
"largest_... | {
"raw_source_hash": "b3c876767fc289cce0b62ec9582025d24fb101ffce0942a3476775cffa8b4a59",
"normalized_source_hash": "6e6bab9e63a65cbdd34ba35a2ecf3174137ca0b47fd297eed7fcd7b51c767230",
"source_ast_hash": "f1fc02e907b5320947db4235666957a6826eb492fa2add702d17bf0f1d6a3d2f",
"artifact_hash": "06b24e0a05f2c7cffa90a4d2... | true | true | null |
en_plaincode_to_python | Text block:
""
"A query transformer is a function that accepts a program and returns a program, plus a priority level."
"Higher priority transformers are placed closer to the front of the list. We\u2019re ensuring is a function,"
"because we\u2019re going to evaluate it later 31 ."
"We\u2019ll assume there won\u2019t b... | """
A query transformer is a function that accepts a program and returns a program, plus a priority level.
Higher priority transformers are placed closer to the front of the list. We’re ensuring is a function,
because we’re going to evaluate it later 31 .
We’ll assume there won’t be an enormous number of transformer ad... | en | python | run_002_20260417_060406 | 21 | {
"max_stars_repo_path": "graphdb/transformer.py",
"max_stars_repo_name": "muggat0n/graphdb",
"max_stars_count": 2,
"id": "36",
"raw_source_hash": "b3c876767fc289cce0b62ec9582025d24fb101ffce0942a3476775cffa8b4a59",
"sanitize_meta": {
"triple_block_count": 6,
"total_triple_chars": 1975,
"largest_... | {
"raw_source_hash": "b3c876767fc289cce0b62ec9582025d24fb101ffce0942a3476775cffa8b4a59",
"normalized_source_hash": "6e6bab9e63a65cbdd34ba35a2ecf3174137ca0b47fd297eed7fcd7b51c767230",
"source_ast_hash": "f1fc02e907b5320947db4235666957a6826eb492fa2add702d17bf0f1d6a3d2f",
"artifact_hash": "06b24e0a05f2c7cffa90a4d2... | true | true | null |
python_to_en_plaincode | #!/usr/bin/python3.6.8+
# -*- coding:utf-8 -*-
"""
@auth: cml
@date: 2020-12-2
@desc: ...
"""
class JobStatus(object):
PENDING = 0 # 任务等待执行
STARTED = 100 # 任务执行开始
PROCESS = 110
POLLING = 120
CALLBACK = 130
SUCCESS = 200 # 任务执行成功
RETRY = 300 # 任务重试
FAILURE = 400 # 任务执行失败
... | # !/usr/bin/python3.6.8+
# -*- coding:utf-8 -*-
Text block:
""
"@auth: cml"
"@date: 2020-12-2"
"@desc: ..."
ending with a newline.
Define class JobStatus inheriting from object:
Set PENDING to 0. # 任务等待执行
Set STARTED to 100. # 任务执行开始
Set PROCESS to 110.
Set POLLING to 120.
Set CALLBACK to 130.
S... | python | en | run_002_20260417_060406 | 22 | {
"max_stars_repo_path": "yzcore/templates/project_template/src/const/_job.py",
"max_stars_repo_name": "lixuemin13/yz-core",
"max_stars_count": 6,
"id": "37",
"raw_source_hash": "e557a00feaaa84c1dac22980c90d6a62a9f62eafdaae9e91599c07cfa7f6b1fb",
"sanitize_meta": {
"triple_block_count": 1,
"total_tri... | {
"raw_source_hash": "e557a00feaaa84c1dac22980c90d6a62a9f62eafdaae9e91599c07cfa7f6b1fb",
"normalized_source_hash": "6ceddd598876b5ddb564488757d140ed3b76b468264a419216e087f17494d5b4",
"source_ast_hash": "1489318c1bc3bfa3bba840c41775012b73652ba7f5d629b96b6f60e04fae9cfc",
"artifact_hash": "d94ff9ce961183b0f94b3e3c... | true | true | null |
python_to_es_plaincode | #!/usr/bin/python3.6.8+
# -*- coding:utf-8 -*-
"""
@auth: cml
@date: 2020-12-2
@desc: ...
"""
class JobStatus(object):
PENDING = 0 # 任务等待执行
STARTED = 100 # 任务执行开始
PROCESS = 110
POLLING = 120
CALLBACK = 130
SUCCESS = 200 # 任务执行成功
RETRY = 300 # 任务重试
FAILURE = 400 # 任务执行失败
... | # !/usr/bin/python3.6.8+
# -*- coding:utf-8 -*-
Texto literal:
""
"@auth: cml"
"@date: 2020-12-2"
"@desc: ..."
terminando con una nueva línea.
Definir clase JobStatus heredando de object:
Establecer PENDING como 0. # 任务等待执行
Establecer STARTED como 100. # 任务执行开始
Establecer PROCESS como 110.
Establecer PO... | python | es | run_002_20260417_060406 | 22 | {
"max_stars_repo_path": "yzcore/templates/project_template/src/const/_job.py",
"max_stars_repo_name": "lixuemin13/yz-core",
"max_stars_count": 6,
"id": "37",
"raw_source_hash": "e557a00feaaa84c1dac22980c90d6a62a9f62eafdaae9e91599c07cfa7f6b1fb",
"sanitize_meta": {
"triple_block_count": 1,
"total_tri... | {
"raw_source_hash": "e557a00feaaa84c1dac22980c90d6a62a9f62eafdaae9e91599c07cfa7f6b1fb",
"normalized_source_hash": "6ceddd598876b5ddb564488757d140ed3b76b468264a419216e087f17494d5b4",
"source_ast_hash": "1489318c1bc3bfa3bba840c41775012b73652ba7f5d629b96b6f60e04fae9cfc",
"artifact_hash": "d94ff9ce961183b0f94b3e3c... | true | true | null |
python_to_fr_plaincode | #!/usr/bin/python3.6.8+
# -*- coding:utf-8 -*-
"""
@auth: cml
@date: 2020-12-2
@desc: ...
"""
class JobStatus(object):
PENDING = 0 # 任务等待执行
STARTED = 100 # 任务执行开始
PROCESS = 110
POLLING = 120
CALLBACK = 130
SUCCESS = 200 # 任务执行成功
RETRY = 300 # 任务重试
FAILURE = 400 # 任务执行失败
... | # !/usr/bin/python3.6.8+
# -*- coding:utf-8 -*-
Texte littéral:
""
"@auth: cml"
"@date: 2020-12-2"
"@desc: ..."
se terminant par une nouvelle ligne.
Définir classe JobStatus héritant de object:
Affecter PENDING à 0. # 任务等待执行
Affecter STARTED à 100. # 任务执行开始
Affecter PROCESS à 110.
Affecter POLLING à 120... | python | fr | run_002_20260417_060406 | 22 | {
"max_stars_repo_path": "yzcore/templates/project_template/src/const/_job.py",
"max_stars_repo_name": "lixuemin13/yz-core",
"max_stars_count": 6,
"id": "37",
"raw_source_hash": "e557a00feaaa84c1dac22980c90d6a62a9f62eafdaae9e91599c07cfa7f6b1fb",
"sanitize_meta": {
"triple_block_count": 1,
"total_tri... | {
"raw_source_hash": "e557a00feaaa84c1dac22980c90d6a62a9f62eafdaae9e91599c07cfa7f6b1fb",
"normalized_source_hash": "6ceddd598876b5ddb564488757d140ed3b76b468264a419216e087f17494d5b4",
"source_ast_hash": "1489318c1bc3bfa3bba840c41775012b73652ba7f5d629b96b6f60e04fae9cfc",
"artifact_hash": "d94ff9ce961183b0f94b3e3c... | true | true | null |
en_plaincode_to_python | # !/usr/bin/python3.6.8+
# -*- coding:utf-8 -*-
Text block:
""
"@auth: cml"
"@date: 2020-12-2"
"@desc: ..."
ending with a newline.
Define class JobStatus inheriting from object:
Set PENDING to 0. # 任务等待执行
Set STARTED to 100. # 任务执行开始
Set PROCESS to 110.
Set POLLING to 120.
Set CALLBACK to 130.
S... | #!/usr/bin/python3.6.8+
# -*- coding:utf-8 -*-
"""
@auth: cml
@date: 2020-12-2
@desc: ...
"""
class JobStatus(object):
PENDING = 0 # 任务等待执行
STARTED = 100 # 任务执行开始
PROCESS = 110
POLLING = 120
CALLBACK = 130
SUCCESS = 200 # 任务执行成功
RETRY = 300 # 任务重试
FAILURE = 400 # 任务执行失败
... | en | python | run_002_20260417_060406 | 22 | {
"max_stars_repo_path": "yzcore/templates/project_template/src/const/_job.py",
"max_stars_repo_name": "lixuemin13/yz-core",
"max_stars_count": 6,
"id": "37",
"raw_source_hash": "e557a00feaaa84c1dac22980c90d6a62a9f62eafdaae9e91599c07cfa7f6b1fb",
"sanitize_meta": {
"triple_block_count": 1,
"total_tri... | {
"raw_source_hash": "e557a00feaaa84c1dac22980c90d6a62a9f62eafdaae9e91599c07cfa7f6b1fb",
"normalized_source_hash": "6ceddd598876b5ddb564488757d140ed3b76b468264a419216e087f17494d5b4",
"source_ast_hash": "1489318c1bc3bfa3bba840c41775012b73652ba7f5d629b96b6f60e04fae9cfc",
"artifact_hash": "d94ff9ce961183b0f94b3e3c... | true | true | null |
python_to_en_plaincode | # Copyright (c) 2016 <NAME>
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | # Copyright (c) 2016 <NAME>
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | python | en | run_002_20260417_060406 | 23 | {
"max_stars_repo_path": "nova/conf/hyperv.py",
"max_stars_repo_name": "raubvogel/nova",
"max_stars_count": 0,
"id": "41",
"raw_source_hash": "6a5a8b5a441ee76f3f2b831492172a3a5e69af861b02d6586b7f7f437081cfb2",
"sanitize_meta": {
"triple_block_count": 19,
"total_triple_chars": 7976,
"largest_trip... | {
"raw_source_hash": "6a5a8b5a441ee76f3f2b831492172a3a5e69af861b02d6586b7f7f437081cfb2",
"normalized_source_hash": "4bdefed70528ebc84fcb6a690fc3b1a770649b842fbb4cc93109b2c2e4f73812",
"source_ast_hash": "a1a9a9d76730331a1fd59944521b9b0a6a787e21ebb6c3231507dfdaf4882bd2",
"artifact_hash": "cf52dec0b424012fbca066d9... | true | true | null |
python_to_es_plaincode | # Copyright (c) 2016 <NAME>
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | # Copyright (c) 2016 <NAME>
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# no use this file except en compliance con the License. You may obtain
# a copy de the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required por app... | python | es | run_002_20260417_060406 | 23 | {
"max_stars_repo_path": "nova/conf/hyperv.py",
"max_stars_repo_name": "raubvogel/nova",
"max_stars_count": 0,
"id": "41",
"raw_source_hash": "6a5a8b5a441ee76f3f2b831492172a3a5e69af861b02d6586b7f7f437081cfb2",
"sanitize_meta": {
"triple_block_count": 19,
"total_triple_chars": 7976,
"largest_trip... | {
"raw_source_hash": "6a5a8b5a441ee76f3f2b831492172a3a5e69af861b02d6586b7f7f437081cfb2",
"normalized_source_hash": "4bdefed70528ebc84fcb6a690fc3b1a770649b842fbb4cc93109b2c2e4f73812",
"source_ast_hash": "a1a9a9d76730331a1fd59944521b9b0a6a787e21ebb6c3231507dfdaf4882bd2",
"artifact_hash": "cf52dec0b424012fbca066d9... | true | true | null |
python_to_fr_plaincode | # Copyright (c) 2016 <NAME>
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | # Copyright (c) 2016 <NAME>
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# non use this file except dans compliance avec the License. You may obtain
# a copy de the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required par... | python | fr | run_002_20260417_060406 | 23 | {
"max_stars_repo_path": "nova/conf/hyperv.py",
"max_stars_repo_name": "raubvogel/nova",
"max_stars_count": 0,
"id": "41",
"raw_source_hash": "6a5a8b5a441ee76f3f2b831492172a3a5e69af861b02d6586b7f7f437081cfb2",
"sanitize_meta": {
"triple_block_count": 19,
"total_triple_chars": 7976,
"largest_trip... | {
"raw_source_hash": "6a5a8b5a441ee76f3f2b831492172a3a5e69af861b02d6586b7f7f437081cfb2",
"normalized_source_hash": "4bdefed70528ebc84fcb6a690fc3b1a770649b842fbb4cc93109b2c2e4f73812",
"source_ast_hash": "a1a9a9d76730331a1fd59944521b9b0a6a787e21ebb6c3231507dfdaf4882bd2",
"artifact_hash": "cf52dec0b424012fbca066d9... | true | true | null |
en_plaincode_to_python | # Copyright (c) 2016 <NAME>
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | # Copyright (c) 2016 <NAME>
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | en | python | run_002_20260417_060406 | 23 | {
"max_stars_repo_path": "nova/conf/hyperv.py",
"max_stars_repo_name": "raubvogel/nova",
"max_stars_count": 0,
"id": "41",
"raw_source_hash": "6a5a8b5a441ee76f3f2b831492172a3a5e69af861b02d6586b7f7f437081cfb2",
"sanitize_meta": {
"triple_block_count": 19,
"total_triple_chars": 7976,
"largest_trip... | {
"raw_source_hash": "6a5a8b5a441ee76f3f2b831492172a3a5e69af861b02d6586b7f7f437081cfb2",
"normalized_source_hash": "4bdefed70528ebc84fcb6a690fc3b1a770649b842fbb4cc93109b2c2e4f73812",
"source_ast_hash": "a1a9a9d76730331a1fd59944521b9b0a6a787e21ebb6c3231507dfdaf4882bd2",
"artifact_hash": "cf52dec0b424012fbca066d9... | true | true | null |
python_to_en_plaincode | import requests
words_list = requests.get("https://raw.githubusercontent.com/atebits/Words/master/Words/fr.txt").text
words_list = filter(lambda x: len(x) > 4, words_list.split('\n'))
path = input("Chemin d'écriture ? (words.txt) ")
if path == "":
path = "./words.txt"
with open(path, "w", encoding="utf-8") as ... | Load requests.
Set words_list to (requests dot get with "https://raw.githubusercontent.com/atebits/Words/master/Words/fr.txt") dot text.
Set words_list to filter with (the lambda with parameter x returning len with x is greater than 4) and (words_list dot split with text block:
""
ending with a newline).
Set path to in... | python | en | run_002_20260417_060406 | 24 | {
"max_stars_repo_path": "src/fetchWords.py",
"max_stars_repo_name": "theyadev/thierry-bot",
"max_stars_count": 0,
"id": "42",
"raw_source_hash": "d7897bd64d9ac1658b1adfe7f08e6cb5ef97e8724604af106cd2f02cd9619eb6",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_trip... | {
"raw_source_hash": "d7897bd64d9ac1658b1adfe7f08e6cb5ef97e8724604af106cd2f02cd9619eb6",
"normalized_source_hash": "d7897bd64d9ac1658b1adfe7f08e6cb5ef97e8724604af106cd2f02cd9619eb6",
"source_ast_hash": "4a5ad916eef5ad7fa965a5d23510cf0c06c8e93065bd5b1c69c6c1691631b9b3",
"artifact_hash": "af670094121b8373146e647a... | true | true | null |
python_to_es_plaincode | import requests
words_list = requests.get("https://raw.githubusercontent.com/atebits/Words/master/Words/fr.txt").text
words_list = filter(lambda x: len(x) > 4, words_list.split('\n'))
path = input("Chemin d'écriture ? (words.txt) ")
if path == "":
path = "./words.txt"
with open(path, "w", encoding="utf-8") as ... | Importar requests.
Establecer words_list como (requests punto get con "https://raw.githubusercontent.com/atebits/Words/master/Words/fr.txt") punto text.
Establecer words_list como filter con (la lambda con parámetro x devolviendo len con x es mayor que 4) y también (words_list punto split con texto literal:
""
terminan... | python | es | run_002_20260417_060406 | 24 | {
"max_stars_repo_path": "src/fetchWords.py",
"max_stars_repo_name": "theyadev/thierry-bot",
"max_stars_count": 0,
"id": "42",
"raw_source_hash": "d7897bd64d9ac1658b1adfe7f08e6cb5ef97e8724604af106cd2f02cd9619eb6",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_trip... | {
"raw_source_hash": "d7897bd64d9ac1658b1adfe7f08e6cb5ef97e8724604af106cd2f02cd9619eb6",
"normalized_source_hash": "d7897bd64d9ac1658b1adfe7f08e6cb5ef97e8724604af106cd2f02cd9619eb6",
"source_ast_hash": "4a5ad916eef5ad7fa965a5d23510cf0c06c8e93065bd5b1c69c6c1691631b9b3",
"artifact_hash": "af670094121b8373146e647a... | true | true | null |
python_to_fr_plaincode | import requests
words_list = requests.get("https://raw.githubusercontent.com/atebits/Words/master/Words/fr.txt").text
words_list = filter(lambda x: len(x) > 4, words_list.split('\n'))
path = input("Chemin d'écriture ? (words.txt) ")
if path == "":
path = "./words.txt"
with open(path, "w", encoding="utf-8") as ... | Charger requests.
Affecter words_list à (requests point de get avec "https://raw.githubusercontent.com/atebits/Words/master/Words/fr.txt") point de text.
Affecter words_list à filter avec (le lambda avec paramètre x retournant len avec x est supérieur à 4) et (words_list point de split avec texte littéral:
""
se termin... | python | fr | run_002_20260417_060406 | 24 | {
"max_stars_repo_path": "src/fetchWords.py",
"max_stars_repo_name": "theyadev/thierry-bot",
"max_stars_count": 0,
"id": "42",
"raw_source_hash": "d7897bd64d9ac1658b1adfe7f08e6cb5ef97e8724604af106cd2f02cd9619eb6",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_trip... | {
"raw_source_hash": "d7897bd64d9ac1658b1adfe7f08e6cb5ef97e8724604af106cd2f02cd9619eb6",
"normalized_source_hash": "d7897bd64d9ac1658b1adfe7f08e6cb5ef97e8724604af106cd2f02cd9619eb6",
"source_ast_hash": "4a5ad916eef5ad7fa965a5d23510cf0c06c8e93065bd5b1c69c6c1691631b9b3",
"artifact_hash": "af670094121b8373146e647a... | true | true | null |
en_plaincode_to_python | Load requests.
Set words_list to (requests dot get with "https://raw.githubusercontent.com/atebits/Words/master/Words/fr.txt") dot text.
Set words_list to filter with (the lambda with parameter x returning len with x is greater than 4) and (words_list dot split with text block:
""
ending with a newline).
Set path to in... | import requests
words_list = requests.get("https://raw.githubusercontent.com/atebits/Words/master/Words/fr.txt").text
words_list = filter(lambda x: len(x) > 4, words_list.split('\n'))
path = input("Chemin d'écriture ? (words.txt) ")
if path == "":
path = "./words.txt"
with open(path, "w", encoding="utf-8") as ... | en | python | run_002_20260417_060406 | 24 | {
"max_stars_repo_path": "src/fetchWords.py",
"max_stars_repo_name": "theyadev/thierry-bot",
"max_stars_count": 0,
"id": "42",
"raw_source_hash": "d7897bd64d9ac1658b1adfe7f08e6cb5ef97e8724604af106cd2f02cd9619eb6",
"sanitize_meta": {
"triple_block_count": 0,
"total_triple_chars": 0,
"largest_trip... | {
"raw_source_hash": "d7897bd64d9ac1658b1adfe7f08e6cb5ef97e8724604af106cd2f02cd9619eb6",
"normalized_source_hash": "d7897bd64d9ac1658b1adfe7f08e6cb5ef97e8724604af106cd2f02cd9619eb6",
"source_ast_hash": "4a5ad916eef5ad7fa965a5d23510cf0c06c8e93065bd5b1c69c6c1691631b9b3",
"artifact_hash": "af670094121b8373146e647a... | true | true | null |
python_to_en_plaincode | import unittest
from unittest import mock
import os
import subprocess
from testfixtures import TempDirectory
from simplegallery.upload.uploader_factory import get_uploader
class AWSUploaderTestCase(unittest.TestCase):
def test_no_location(self):
uploader = get_uploader('aws')
self.assertFalse(upl... | Load unittest.
Load mock from unittest.
Load os.
Load subprocess.
Load TempDirectory from testfixtures.
Load get_uploader from simplegallery.upload.uploader_factory.
Define class AWSUploaderTestCase inheriting from unittest.TestCase:
Define method test_no_location with parameter self:
Set uploader to get_up... | python | en | run_002_20260417_060406 | 25 | {
"max_stars_repo_path": "inspiration/simplegallery/test/upload/variants/test_aws_uploader.py",
"max_stars_repo_name": "Zenahr/simple-music-gallery",
"max_stars_count": 1,
"id": "43",
"raw_source_hash": "049b5ba60ecc6f6211db69e73b8950957b49346c1b3ab42c7dda3a057de03341",
"sanitize_meta": {
"triple_block_... | {
"raw_source_hash": "049b5ba60ecc6f6211db69e73b8950957b49346c1b3ab42c7dda3a057de03341",
"normalized_source_hash": "a40ee6ab86ba41019fe624ed4f55c4518a0344a4f9be513947e81825b46f0df9",
"source_ast_hash": "b9388165a5d277407e5a5c3b8366ada56c2d4aa9d8835a812fadc268f0223ff2",
"artifact_hash": "34e1a7b017024bbfbfd20291... | true | true | null |
python_to_es_plaincode | import unittest
from unittest import mock
import os
import subprocess
from testfixtures import TempDirectory
from simplegallery.upload.uploader_factory import get_uploader
class AWSUploaderTestCase(unittest.TestCase):
def test_no_location(self):
uploader = get_uploader('aws')
self.assertFalse(upl... | Importar unittest.
Importar mock desde unittest.
Importar os.
Importar subprocess.
Importar TempDirectory desde testfixtures.
Importar get_uploader desde simplegallery.upload.uploader_factory.
Definir clase AWSUploaderTestCase heredando de unittest.TestCase:
Definir método test_no_location con parámetro self:
... | python | es | run_002_20260417_060406 | 25 | {
"max_stars_repo_path": "inspiration/simplegallery/test/upload/variants/test_aws_uploader.py",
"max_stars_repo_name": "Zenahr/simple-music-gallery",
"max_stars_count": 1,
"id": "43",
"raw_source_hash": "049b5ba60ecc6f6211db69e73b8950957b49346c1b3ab42c7dda3a057de03341",
"sanitize_meta": {
"triple_block_... | {
"raw_source_hash": "049b5ba60ecc6f6211db69e73b8950957b49346c1b3ab42c7dda3a057de03341",
"normalized_source_hash": "a40ee6ab86ba41019fe624ed4f55c4518a0344a4f9be513947e81825b46f0df9",
"source_ast_hash": "b9388165a5d277407e5a5c3b8366ada56c2d4aa9d8835a812fadc268f0223ff2",
"artifact_hash": "34e1a7b017024bbfbfd20291... | true | true | null |
python_to_fr_plaincode | import unittest
from unittest import mock
import os
import subprocess
from testfixtures import TempDirectory
from simplegallery.upload.uploader_factory import get_uploader
class AWSUploaderTestCase(unittest.TestCase):
def test_no_location(self):
uploader = get_uploader('aws')
self.assertFalse(upl... | Charger unittest.
Charger mock depuis unittest.
Charger os.
Charger subprocess.
Charger TempDirectory depuis testfixtures.
Charger get_uploader depuis simplegallery.upload.uploader_factory.
Définir classe AWSUploaderTestCase héritant de unittest.TestCase:
Définir méthode test_no_location avec paramètre self:
... | python | fr | run_002_20260417_060406 | 25 | {
"max_stars_repo_path": "inspiration/simplegallery/test/upload/variants/test_aws_uploader.py",
"max_stars_repo_name": "Zenahr/simple-music-gallery",
"max_stars_count": 1,
"id": "43",
"raw_source_hash": "049b5ba60ecc6f6211db69e73b8950957b49346c1b3ab42c7dda3a057de03341",
"sanitize_meta": {
"triple_block_... | {
"raw_source_hash": "049b5ba60ecc6f6211db69e73b8950957b49346c1b3ab42c7dda3a057de03341",
"normalized_source_hash": "a40ee6ab86ba41019fe624ed4f55c4518a0344a4f9be513947e81825b46f0df9",
"source_ast_hash": "b9388165a5d277407e5a5c3b8366ada56c2d4aa9d8835a812fadc268f0223ff2",
"artifact_hash": "34e1a7b017024bbfbfd20291... | true | true | null |
en_plaincode_to_python | Load unittest.
Load mock from unittest.
Load os.
Load subprocess.
Load TempDirectory from testfixtures.
Load get_uploader from simplegallery.upload.uploader_factory.
Define class AWSUploaderTestCase inheriting from unittest.TestCase:
Define method test_no_location with parameter self:
Set uploader to get_up... | import unittest
from unittest import mock
import os
import subprocess
from testfixtures import TempDirectory
from simplegallery.upload.uploader_factory import get_uploader
class AWSUploaderTestCase(unittest.TestCase):
def test_no_location(self):
uploader = get_uploader('aws')
self.assertFalse(upl... | en | python | run_002_20260417_060406 | 25 | {
"max_stars_repo_path": "inspiration/simplegallery/test/upload/variants/test_aws_uploader.py",
"max_stars_repo_name": "Zenahr/simple-music-gallery",
"max_stars_count": 1,
"id": "43",
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"sanitize_meta": {
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"artifact_hash": "34e1a7b017024bbfbfd20291... | true | true | null |
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