added stringdate 2024-11-18 17:59:49 2024-11-19 03:44:43 | created int64 0 2,086B | id stringlengths 40 40 | int_score int64 2 5 | metadata dict | score float64 2.31 5.5 | source stringclasses 1
value | text stringlengths 258 23.4k | num_lines int64 16 649 | avg_line_length float64 15 61 | max_line_length int64 31 179 | ast_depth int64 8 40 | length int64 101 3.8k | lang stringclasses 1
value | sast_codeql_findings stringlengths 2 265k | sast_codeql_findings_count int64 0 45 | sast_codeql_success bool 1
class | sast_codeql_error stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2024-11-18T21:14:44.964547+00:00 | 1,634,768,532,000 | 4c9d7ce37f6c45166b59931d62dbd7194b7cafe4 | 3 | {
"blob_id": "4c9d7ce37f6c45166b59931d62dbd7194b7cafe4",
"branch_name": "refs/heads/main",
"committer_date": 1634768532000,
"content_id": "ec6908c0f60dd345553d081b6f536094718ef9b0",
"detected_licenses": [
"MIT"
],
"directory_id": "f725c1b0c63f9eb9bbd9307ecb2a55f148b0b136",
"extension": "py",
"file... | 2.796875 | stackv2 | # -*- coding: utf-8 -*-
"""
Created on Wed Jul 28 13:55:56 2021
@author: alex
"""
import numpy as np
import matplotlib.pyplot as plt
import imageio
from skimage.util import montage
from scipy.optimize import nnls
def calc_t2_signal(TE,T2,S0):
'''
Parameters
----------
TE : (float) Single echo time
... | 147 | 32.2 | 101 | 18 | 1,411 | python | [] | 0 | true | |
2024-11-18T21:14:45.075939+00:00 | 1,615,900,282,000 | 4bcfa2e1a6eeffc2e1f471d66a2573d2e8cdf85d | 2 | {
"blob_id": "4bcfa2e1a6eeffc2e1f471d66a2573d2e8cdf85d",
"branch_name": "refs/heads/master",
"committer_date": 1615900282000,
"content_id": "1817ec61cb5aa18cd602575ded6d46e26a328bee",
"detected_licenses": [
"MIT"
],
"directory_id": "70450f0c551adf47b450468e424f4f90bebfb58d",
"extension": "py",
"fi... | 2.4375 | stackv2 | import os, numpy
from icecube import icetray, dataclasses, dataio
from I3Tray import *
from copy import deepcopy
def convert_omkey(key):
try:
string = int(key.split(',')[0])
om = int(key.split(',')[1])
omkey = icetray.OMKey(string, om)
return omkey
except ValueError:
ice... | 165 | 44.24 | 138 | 21 | 1,732 | python | [] | 0 | true | |
2024-11-18T21:14:45.593453+00:00 | 1,604,099,980,000 | f11e86d33a8602dc0386dedde4904ab8d419ce1b | 2 | {
"blob_id": "f11e86d33a8602dc0386dedde4904ab8d419ce1b",
"branch_name": "refs/heads/master",
"committer_date": 1604099980000,
"content_id": "0ae5327fd1d0e411b29ab998a2527cd911d56377",
"detected_licenses": [
"MIT"
],
"directory_id": "9706a96ef8727d0923bf63dff3458999b7b30671",
"extension": "py",
"fi... | 2.375 | stackv2 | import os
from typing import List, Tuple
import ants_ai.training.neural_network.encoders.encoders as enc
from ants_ai.training.neural_network.sequences.data_structs import GameIndex, LoadedIndex, DatasetType
from ants_ai.training.neural_network.sequences.file_system_sequence import FileSystemSequence
import numpy as n... | 86 | 52.98 | 107 | 18 | 993 | python | [] | 0 | true | |
2024-11-18T21:14:45.819749+00:00 | 1,379,965,504,000 | 2fea6382a59fc2b742bc4b691f790d1a3e50ff15 | 3 | {
"blob_id": "2fea6382a59fc2b742bc4b691f790d1a3e50ff15",
"branch_name": "refs/heads/master",
"committer_date": 1379965504000,
"content_id": "3b7f6672f27fde347982348a420baee38e3dcd29",
"detected_licenses": [
"MIT"
],
"directory_id": "7035396d70a68faed5631bee025008fa9098ce41",
"extension": "py",
"fi... | 2.84375 | stackv2 | """
REMINDERS:
- When manipulating a page, if you are wiping it,
remember to clear your views registered live_regions with erase_regions
- When using dialogs, remember to reset the LiveView's last_click_time
so it doesn't think the focusing back on the view after you click ok is another click.
"""
import uui... | 484 | 36.58 | 110 | 23 | 3,749 | python | [] | 0 | true | |
2024-11-18T21:14:45.943928+00:00 | 1,514,957,845,000 | 90500b37e46f59408f15e6af7f9ab6ac8be699ea | 3 | {
"blob_id": "90500b37e46f59408f15e6af7f9ab6ac8be699ea",
"branch_name": "refs/heads/master",
"committer_date": 1514957845000,
"content_id": "e025875e78e2daabe1b9ea6979f1566642df30d8",
"detected_licenses": [
"MIT"
],
"directory_id": "0e3a65003d90f2d34cd7caf650c8ab39c8e6f440",
"extension": "py",
"fi... | 2.671875 | stackv2 | import sys,os
import requests
from bs4 import BeautifulSoup
import re
import json
import copy
import random
def store(filename,data):
with open(filename, 'w') as json_file:
json_file.write(json.dumps(data))
def fetch(baseUrl,id_list,data):
template=copy.deepcopy(data["configs"][0])
data['config... | 83 | 24.48 | 120 | 16 | 587 | python | [] | 0 | true | |
2024-11-18T21:14:46.005842+00:00 | 1,372,136,256,000 | 7bda73872a160cae8e408f9501afedfec4107d37 | 4 | {
"blob_id": "7bda73872a160cae8e408f9501afedfec4107d37",
"branch_name": "refs/heads/master",
"committer_date": 1372136256000,
"content_id": "4d9e5d777eb0054fd1720b244b22b0bc8bf26a49",
"detected_licenses": [
"MIT"
],
"directory_id": "7900cab0c058905120a41bfec8e897691029944e",
"extension": "py",
"fi... | 3.734375 | stackv2 | import sys
def find_intersection(list1, list2):
"""Returns the intersection of the two given lists.
Lists are comma separated strings.
"""
list1 = list1.split(',')
list2 = list2.split(',')
output = []
for elem in list1:
if elem in list2:
output.append(elem)
return ... | 24 | 20.04 | 55 | 11 | 122 | python | [] | 0 | true | |
2024-11-18T21:14:46.079747+00:00 | 1,563,459,494,000 | d1df8d40660287e24c03a57cb1c3346ff0338ae2 | 2 | {
"blob_id": "d1df8d40660287e24c03a57cb1c3346ff0338ae2",
"branch_name": "refs/heads/master",
"committer_date": 1563459494000,
"content_id": "d2edfb47a930ff8487b192bc7e1373abf8a54a72",
"detected_licenses": [
"MIT"
],
"directory_id": "cb6b04b64fc977195831d6910d0af07053b3e30a",
"extension": "py",
"fi... | 2.328125 | stackv2 | # -*- coding: utf-8 -*-
from typing import List, Union
import pandas as pd
from zvt.domain import SimAccount, TradingLevel, Order
from zvt.reader.reader import DataReader
class AccountReader(DataReader):
def __init__(self,
the_timestamp: Union[str, pd.Timestamp] = None,
start_t... | 65 | 37.26 | 105 | 14 | 510 | python | [] | 0 | true | |
2024-11-18T21:14:46.131569+00:00 | 1,692,773,342,000 | 65cfc45682c3045ba388e0f00e1fea93bf68db6a | 2 | {
"blob_id": "65cfc45682c3045ba388e0f00e1fea93bf68db6a",
"branch_name": "refs/heads/main",
"committer_date": 1692773342000,
"content_id": "951372b56a6e78b540bf7ad3c948f4a46bd0e499",
"detected_licenses": [
"MIT"
],
"directory_id": "3edb8e25f34b67361bc1010cedff3d79e34e5be0",
"extension": "py",
"file... | 2.4375 | stackv2 | import torch
import torch.nn.functional as F
def cxywh2xy(bboxes):
cxy = bboxes[...,:2]
hwh = bboxes[...,2:]/2
minxy = cxy-hwh
maxxy = cxy+hwh
return torch.cat([minxy,maxxy],dim=-1)
def xy2cxywh(bboxes):
wh = bboxes[...,2:]-bboxes[...,:2]
cxy = (bboxes[...,2:]+bboxes[...,:2])/2
return ... | 104 | 28.72 | 90 | 13 | 1,117 | python | [] | 0 | true | |
2024-11-18T21:14:46.178377+00:00 | 1,684,482,176,000 | e1326e824e360e5ec81befcb78afa507fc24b750 | 3 | {
"blob_id": "e1326e824e360e5ec81befcb78afa507fc24b750",
"branch_name": "refs/heads/master",
"committer_date": 1684482176000,
"content_id": "3694480a5198361dc7dd476d317888960c285242",
"detected_licenses": [
"MIT"
],
"directory_id": "ad0857eaba945c75e705594a53c40dbdd40467fe",
"extension": "py",
"fi... | 3.25 | stackv2 | # Title: 절대값 힙
# Link: https://www.acmicpc.net/problem/11286
import sys
from heapq import heappop, heappush
sys.setrecursionlimit(10 ** 6)
read_single_int = lambda: int(sys.stdin.readline().strip())
def solution(ops: list):
q = []
for op in ops:
if op == 0:
print(heappop(q)[1] if q el... | 32 | 16.22 | 59 | 15 | 167 | python | [] | 0 | true | |
2024-11-18T20:10:31.283760+00:00 | 1,585,633,111,000 | 7ba1b16af7f79282b58951ca16e64e8b56e81cc9 | 3 | {
"blob_id": "7ba1b16af7f79282b58951ca16e64e8b56e81cc9",
"branch_name": "refs/heads/master",
"committer_date": 1585633111000,
"content_id": "4c12d48bed69320257d5a41e9471bc4649fda8db",
"detected_licenses": [
"MIT"
],
"directory_id": "9200fee8f6f78700f4e75e4d43e60a6733f7f6ec",
"extension": "py",
"fi... | 2.984375 | stackv2 | # -*- coding: utf-8 -*-
"""
File check_label_file.py
@author:ZhengYuwei
"""
import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.metrics import confusion_matrix
def plot_confusion_matrix(y_true, y_pred, labels, title='Confusion matrix', is_save=False):
... | 73 | 32.59 | 91 | 16 | 762 | python | [] | 0 | true | |
2024-11-18T20:10:31.399875+00:00 | 1,391,061,805,000 | a2283a2ac2e1978da9ad4a9a399c15d55624375d | 3 | {
"blob_id": "a2283a2ac2e1978da9ad4a9a399c15d55624375d",
"branch_name": "refs/heads/master",
"committer_date": 1391061805000,
"content_id": "1825618c8c4dfc6ef80dfe197b209936c937b80a",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "818a1909e6664e5dfa67f67c8a6f9de83fe54833",
"extension": "p... | 3.34375 | stackv2 | '''
Classifier for the Variant filter script.
Authors: Bernie Pope, Danny Park, Fabrice Odefrey, Tu Nguyen-Dumont.
'''
# The classify function decides if a particular variant from the
# variant list should be kept or binned (discarded). It returns
# a classification of the variant which can be used to
# determine if ... | 55 | 44.04 | 116 | 14 | 604 | python | [] | 0 | true | |
2024-11-18T20:10:31.452567+00:00 | 1,464,083,404,000 | 81371fe2c0c1f41cd28c51ca7e9501b2a9f73f7d | 3 | {
"blob_id": "81371fe2c0c1f41cd28c51ca7e9501b2a9f73f7d",
"branch_name": "refs/heads/master",
"committer_date": 1464083404000,
"content_id": "290591280368068bd5fe1b16228749e350678580",
"detected_licenses": [
"MIT"
],
"directory_id": "d976c1b1a51cec898e6265378bb7f4a647ff75a3",
"extension": "py",
"fi... | 2.859375 | stackv2 | from scrapy.contrib.spiders import CrawlSpider, Rule
from scrapy.contrib.linkextractors import LinkExtractor
from hackernews_scrapy.items import HackerNewsItem
class HackerNewsSpider(CrawlSpider):
name = "hackernews"
allowed_domains = ["ycombinator.com"]
start_urls = [
"https://news.ycombinator.co... | 27 | 31 | 101 | 16 | 206 | python | [] | 0 | true | |
2024-11-18T20:10:31.555956+00:00 | 1,562,953,857,000 | 737410aac86fc975150aac9560912a2e9defccb0 | 3 | {
"blob_id": "737410aac86fc975150aac9560912a2e9defccb0",
"branch_name": "refs/heads/master",
"committer_date": 1562953857000,
"content_id": "7a37d911ec33d5d464eafe5ba201c33d47f117d5",
"detected_licenses": [
"MIT"
],
"directory_id": "cda629e9ba9d5fca7fc208060368d61543c44a84",
"extension": "py",
"fi... | 2.8125 | stackv2 | """ For a given GOI, returns the specific AA level mutations found
On a per-cell basis. """
import numpy as np
from . import VCF # comes from Kamil Slowikowski
import os
import csv
import pandas as pd
import sys
import itertools
import warnings
import click
warnings.simplefilter(action='ignore', category=FutureWarni... | 321 | 27.62 | 120 | 20 | 2,744 | python | [] | 0 | true | |
2024-11-18T20:10:31.609073+00:00 | 1,618,063,903,000 | a3e82586d61b62b97d1cc42073322dbd89334765 | 3 | {
"blob_id": "a3e82586d61b62b97d1cc42073322dbd89334765",
"branch_name": "refs/heads/main",
"committer_date": 1618063903000,
"content_id": "29be464c1c1674439aec011c349512b69f9e56b9",
"detected_licenses": [
"MIT"
],
"directory_id": "b1322c8e3db134d9ae4e44be7597c30d5a67c084",
"extension": "py",
"file... | 3.234375 | stackv2 | import numpy as np
import pandas as pd
from matplotlib.figure import Figure
from datetime import datetime
# How much x label to appear in the x axis(tick + 1)
tick = 5
def custplot(ax, df, chartType="", timeline=""):
# Plot vertical lines and boxes
xticklabelList = np.array([])
if timeline == "week" or ti... | 117 | 30.94 | 83 | 14 | 1,094 | python | [] | 0 | true | |
2024-11-18T20:10:31.772255+00:00 | 1,596,569,061,000 | 1cb3c6c1f5024706793e25ab87f5915dae4746fe | 2 | {
"blob_id": "1cb3c6c1f5024706793e25ab87f5915dae4746fe",
"branch_name": "refs/heads/master",
"committer_date": 1596569061000,
"content_id": "e37db56470d2f8b7a4a6f36cda349b330efe3174",
"detected_licenses": [
"MIT"
],
"directory_id": "f207586e34b37b13ee6012ea08f174e302fa0078",
"extension": "py",
"fi... | 2.359375 | stackv2 | import copy
import numpy as np
from scipy import special as special
from scipy.special import logsumexp
from mimo.abstraction import Distribution
from mimo.mixtures.full import MixtureOfGaussians
from mimo.distributions.bayesian import CategoricalWithDirichlet
from mimo.distributions.bayesian import CategoricalWithS... | 416 | 32.06 | 106 | 23 | 3,220 | python | [] | 0 | true | |
2024-11-18T20:10:31.835003+00:00 | 1,552,448,327,000 | e91a95375d9665f503a7bbf8e7d041049afa25e1 | 2 | {
"blob_id": "e91a95375d9665f503a7bbf8e7d041049afa25e1",
"branch_name": "refs/heads/master",
"committer_date": 1552448327000,
"content_id": "f3704263938f34cc400d3dc4ddf84d131ffbc8c3",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "3093dcbcb998bd2caa1cbda28a25d30bc5a26af3",
"extension": "p... | 2.453125 | stackv2 | import copy
import json
from functools import reduce
import yaml
from foxylib.tools.log.logger_tools import LoggerToolkit, FoxylibLogger
class JToolkit:
@classmethod
def jkey_v2json(cls, l, v_IN):
j_OUT = reduce(lambda j, k: {k: j}, reversed(l), v_IN)
return j_OUT
@classmethod
def d... | 105 | 24.2 | 90 | 15 | 689 | python | [] | 0 | true | |
2024-11-18T20:10:31.941124+00:00 | 1,527,086,987,000 | c1c746a2d586159cc6fcbcea2dfe42b32a425018 | 2 | {
"blob_id": "c1c746a2d586159cc6fcbcea2dfe42b32a425018",
"branch_name": "refs/heads/master",
"committer_date": 1527086987000,
"content_id": "cfda6da9c64d165f282d14c4177a1bf86302cb59",
"detected_licenses": [
"MIT"
],
"directory_id": "ff6b45c290db6adeda94e4be839cf6f5a4d2f8bb",
"extension": "py",
"fi... | 2.4375 | stackv2 | import logging
from six.moves.queue import Empty, Queue
from flask import current_app, request
from fluent import sender
class Fluentd(object):
def __init__(self, app=None):
self.app = app
if app is not None:
self.init_app(app)
# Send events after every request finishes
... | 53 | 30.17 | 74 | 15 | 337 | python | [] | 0 | true | |
2024-11-18T20:10:32.064595+00:00 | 1,681,125,874,000 | 6df72d0496166e8d933e6eae3bca4785e193af8f | 4 | {
"blob_id": "6df72d0496166e8d933e6eae3bca4785e193af8f",
"branch_name": "refs/heads/master",
"committer_date": 1681125874000,
"content_id": "f808237669d2259c22fda08fc91a1d9e81cc7c0e",
"detected_licenses": [
"BSD-2-Clause"
],
"directory_id": "9c2c3d918043b3bc9fcefffc9d2fe5fc0ca82bb4",
"extension": "p... | 3.5 | stackv2 | import os
import os.path
import copy
NOT_APPLICABLE = 'n/a'
def expandFileName(filename):
"""Expand environment variable in a file name.
If the input file name begins with either a Unix-style or IRAF-style
environment variable (e.g. $lref/name_dqi.fits or lref$name_dqi.fits
respectively), this routi... | 86 | 28.13 | 78 | 22 | 583 | python | [] | 0 | true | |
2024-11-18T20:10:32.116721+00:00 | 1,571,581,840,000 | 845bece664337d93a59c042ffc13843adf14f8e9 | 3 | {
"blob_id": "845bece664337d93a59c042ffc13843adf14f8e9",
"branch_name": "refs/heads/master",
"committer_date": 1571581840000,
"content_id": "b9171382179c7e91c95397c7745e95425f3ca179",
"detected_licenses": [
"MIT"
],
"directory_id": "8d445c91a2d8893374d6c943f34b00309d728122",
"extension": "py",
"fi... | 3.359375 | stackv2 | # AES 256 encryption/decryption using pycrypto library
import base64
import hashlib
from Crypto.Cipher import AES
from Crypto import Random
class aes(object):
"""docstring for aes"""
def __init__(self, key):
self.key = hashlib.sha256(key.encode("utf-8")).digest()
self.BLOCK_SIZE = 16
s... | 41 | 30.66 | 127 | 19 | 342 | python | [{"finding_id": "codeql_py/weak-sensitive-data-hashing_6ddb959e3516cd96_93a20d67", "tool_name": "codeql", "rule_id": "py/weak-sensitive-data-hashing", "finding_type": "path-problem", "severity": "medium", "confidence": "high", "message": "[Sensitive data (password)](1) is used in a hashing algorithm (SHA256) that is in... | 1 | true | |
2024-11-18T20:10:32.266708+00:00 | 1,418,413,799,000 | 27568a5722da2b559a162cd7819c556b4eb45248 | 4 | {
"blob_id": "27568a5722da2b559a162cd7819c556b4eb45248",
"branch_name": "refs/heads/master",
"committer_date": 1418413799000,
"content_id": "40a9efadaaebe4baadce4b15c9354962351c646f",
"detected_licenses": [
"MIT"
],
"directory_id": "7ba61d52f235e9089a64d2462ca3dcc2f284fb5b",
"extension": "py",
"fi... | 3.734375 | stackv2 | from fractions import gcd
class Fraction:
def __init__(self, nominator, denominator):
self.nominator = nominator
self.denominator = denominator
# least common multiple
@staticmethod
def lcm(a, b):
absolute_value = abs(a * b)
greatest_common_divisor = gcd(a, b)
... | 63 | 28.13 | 71 | 13 | 473 | python | [] | 0 | true | |
2024-11-18T20:10:32.403216+00:00 | 1,622,408,002,000 | dcca292432bd92d9003ba3de7bde2acf32ce2cb9 | 3 | {
"blob_id": "dcca292432bd92d9003ba3de7bde2acf32ce2cb9",
"branch_name": "refs/heads/main",
"committer_date": 1622408002000,
"content_id": "cf59f199b08ca5b585201bf0c78fe78ebf06c0b2",
"detected_licenses": [
"MIT"
],
"directory_id": "c5d78eb310ccc5e4eb397132bd2105ec0c077b1d",
"extension": "py",
"file... | 3.015625 | stackv2 | """Model testing and validation"""
import matplotlib.pyplot as plt
import numpy as np
import time
def validate_model(model_generator, datasets_generator, epochs=50, loss_name="mean_squared_error", measure_name="val_mean_squared_error", \
print_summary=True):
"""K-fold validation of model"""
... | 210 | 37.64 | 139 | 14 | 1,817 | python | [] | 0 | true | |
2024-11-18T20:10:32.523656+00:00 | 1,622,688,625,000 | 3449f1d5ea193bc76991f8760c550c3f65162bfd | 2 | {
"blob_id": "3449f1d5ea193bc76991f8760c550c3f65162bfd",
"branch_name": "refs/heads/main",
"committer_date": 1622688625000,
"content_id": "b5cb25a353f72e9b6184711355017927be38cc83",
"detected_licenses": [
"MIT"
],
"directory_id": "cc880a44a227b8be20991b654990640c7c5b5fc4",
"extension": "py",
"file... | 2.40625 | stackv2 | import matplotlib.pyplot as plt
import numpy as np
import torch
import pandas as pd
import torch.nn as nn
import torch.optim as optim
from torch.autograd import Variable
from copy import deepcopy
from sklearn.metrics import roc_auc_score
import pickle
import sklearn.preprocessing as preprocessing
import numpy as np
fro... | 326 | 35.98 | 152 | 17 | 3,284 | python | [] | 0 | true | |
2024-11-18T20:10:32.579435+00:00 | 1,399,581,832,000 | de4385d88c01e8876a9414ef7d62d377fa6b4955 | 3 | {
"blob_id": "de4385d88c01e8876a9414ef7d62d377fa6b4955",
"branch_name": "refs/heads/master",
"committer_date": 1399581832000,
"content_id": "4714b7c79ae570759cf02dc4c2fbf72b0f07fb28",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "ed4bb60ad6c0a6e78f7a5bf368e1be8a1edab993",
"extension": "p... | 2.828125 | stackv2 | """
Form span utility.
(C) Copyright 2014 Stuart McMillan, Useful Automation
"""
import re
import six
from django.core import validators
DEFAULT_CHARS_PER_SPAN = 5
DEFAULT_MAX_SPAN = 12
class FormSpanMixin(object):
"""Bootstrap form utility which adds file class spanN (indicating field length)"""
LENGTH_RE =... | 103 | 43.36 | 97 | 25 | 939 | python | [] | 0 | true | |
2024-11-18T20:10:32.639877+00:00 | 1,512,126,329,000 | 84404a99897d925d4fd4b80125bfcb68b100cc45 | 2 | {
"blob_id": "84404a99897d925d4fd4b80125bfcb68b100cc45",
"branch_name": "refs/heads/master",
"committer_date": 1512126329000,
"content_id": "19f8b81cffc42c60c559069d09b80ce75de1f6dc",
"detected_licenses": [
"MIT"
],
"directory_id": "f1027de90ca3b07dee4c8729e00e59f225f1baff",
"extension": "py",
"fi... | 2.421875 | stackv2 | from robot import RobotArm
import numpy as np
import time
import vrep
import decimal
import utility
import decimal
def status(title, ra):
print("")
print(title)
print("Is object held> ", ra.is_object_held())
print("Is object in bin> ", ra.is_object_in_bin())
print("------------------------>")
ra... | 75 | 19.48 | 85 | 9 | 492 | python | [] | 0 | true | |
2024-11-18T20:10:32.738191+00:00 | 1,643,343,399,000 | cbc4effb0c0f71875349a3af82627b374a8e36df | 4 | {
"blob_id": "cbc4effb0c0f71875349a3af82627b374a8e36df",
"branch_name": "refs/heads/master",
"committer_date": 1643343399000,
"content_id": "48ef123738adb9347b635bcfc23829bcc45be74a",
"detected_licenses": [
"MIT"
],
"directory_id": "151df28f762e690aa1b437f3d123d54eca99b379",
"extension": "py",
"fi... | 4.15625 | stackv2 | """
An image is represented by an m x n integer grid image where image[i][j] represents the pixel value of the image.
You are also given three integers sr, sc, and newColor. You should perform a flood fill on the image starting from the
pixel image[sr][sc].
To perform a flood fill, consider the starting pixel, plus a... | 72 | 35.67 | 120 | 14 | 712 | python | [] | 0 | true | |
2024-11-18T20:10:32.919302+00:00 | 1,536,914,244,000 | e4869dd67c0e3f338deba0ad4738bed7809b36f0 | 3 | {
"blob_id": "e4869dd67c0e3f338deba0ad4738bed7809b36f0",
"branch_name": "refs/heads/master",
"committer_date": 1536914244000,
"content_id": "19a585d2cddd12e8d760ede6c879a6afb676e568",
"detected_licenses": [
"MIT"
],
"directory_id": "2118bed8a4a11d6e093fccb5b619582fca263c1e",
"extension": "py",
"fi... | 3.34375 | stackv2 | months = [
'January',
'February',
'March',
'Aprill',
'May',
'June',
'July',
'August',
'September',
'October',
'November',
'December'
]
endings =['st','nd','rd']+17*['th']+['st','nd','rd']+7*['th']+['st']
year =raw_input('year:')
month =raw_input('month(1-12):')
day =raw... | 30 | 16.77 | 68 | 11 | 172 | python | [] | 0 | true | |
2024-11-18T20:10:33.040400+00:00 | 1,691,513,950,000 | acca5b2cdb28742dd629314d0c8f504e6f52d5c1 | 3 | {
"blob_id": "acca5b2cdb28742dd629314d0c8f504e6f52d5c1",
"branch_name": "refs/heads/main",
"committer_date": 1691513950000,
"content_id": "37c32e00d041f59a65fa7d43c273b590e448699d",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "1684e493bcdae4279c3ce0d0b34b02d58444d3f9",
"extension": "py",
... | 2.625 | stackv2 | #
# Copyright (c) 2022 Intel Corporation
#
# 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 agreed to i... | 43 | 29.56 | 83 | 13 | 296 | python | [] | 0 | true | |
2024-11-18T20:10:33.089596+00:00 | 1,462,214,820,000 | e5c9f43fa857e2bdc0b57b0630713b89c4b718e6 | 3 | {
"blob_id": "e5c9f43fa857e2bdc0b57b0630713b89c4b718e6",
"branch_name": "refs/heads/master",
"committer_date": 1462214820000,
"content_id": "5af241bcfcccd07ae87951054bd605f301a0e860",
"detected_licenses": [
"MIT"
],
"directory_id": "872d6a0658d56a7be280c9f2ca033a6217e25b7b",
"extension": "py",
"fi... | 3.03125 | stackv2 | # -*- coding: utf-8 -*-
import scrapy
from astronomy_scraper.items import DayConditions
import re
class WeatherSpider(scrapy.Spider):
name = "weather"
allowed_domains = ["http://www.timeanddate.com/"]
start_urls = (
'http://www.timeanddate.com/weather/usa/new-york',
)
def parse(self, respo... | 21 | 35.9 | 121 | 13 | 210 | python | [] | 0 | true | |
2024-11-18T20:10:33.205672+00:00 | 1,604,558,221,000 | 5bf30c82dedccf70399de0bdaf63a503ed02fe6f | 4 | {
"blob_id": "5bf30c82dedccf70399de0bdaf63a503ed02fe6f",
"branch_name": "refs/heads/master",
"committer_date": 1604558221000,
"content_id": "a34947e4608b0b2c6f7bb29525935b3173662879",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "d7b8e2af96c10ea6dc80ef69ca4e25c19e9ce310",
"extension": "py"... | 3.5625 | stackv2 | a_set = {2, 3, 4, 5, 6, 196}
print(a_set)
print(3 in a_set)
print(31 in a_set)
print()
b_set = {4, 5, 6, 900}
print(a_set.union(b_set))
print(a_set.intersection(b_set))
print(a_set.difference(b_set))
print(a_set.symmetric_difference(b_set))
print()
print(b_set.symmetric_difference(a_set))
print(b_set.symmetric_differ... | 49 | 17.02 | 77 | 8 | 350 | python | [] | 0 | true | |
2024-11-18T20:10:33.357621+00:00 | 1,588,601,869,000 | 202bfd65a96a65d2ce2fc966c5cbdedc8a429538 | 3 | {
"blob_id": "202bfd65a96a65d2ce2fc966c5cbdedc8a429538",
"branch_name": "refs/heads/master",
"committer_date": 1588601869000,
"content_id": "8a4836decd90e2309e5e6da43b74de57d229e885",
"detected_licenses": [
"MIT"
],
"directory_id": "45deb4da94224d749966e54461822928115c9dcf",
"extension": "py",
"fi... | 3.390625 | stackv2 | # Data Preprocessing Template
# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
'''# Importing the dataset
dataset = pd.read_csv('Data.csv')
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, 3].values
# Splitting the dataset into the Training set and Test set
from skl... | 63 | 26.43 | 95 | 8 | 432 | python | [] | 0 | true | |
2024-11-18T20:10:33.457176+00:00 | 1,687,184,603,000 | c6d0d79b2cf920f25b9bb639719b760dabab7ce6 | 3 | {
"blob_id": "c6d0d79b2cf920f25b9bb639719b760dabab7ce6",
"branch_name": "refs/heads/master",
"committer_date": 1687184603000,
"content_id": "0abbcfefab17bdfe77d1d3a7a8ecde0e5322525a",
"detected_licenses": [
"MIT"
],
"directory_id": "4372fd7fc45e7e28febc242566d8c650d271f7c8",
"extension": "py",
"fi... | 2.765625 | stackv2 | import pandas
import tables
import logging
try:
from tqdm import tqdm
except ImportError:
tqdm = lambda x, **kwargs: x
logger = logging.getLogger(__name__)
class SyntenyScorer(object):
def __init__(self, h5_handle, genome, windowsize=10):
self.h5_handle = h5_handle
self.genome = genome
... | 102 | 46.94 | 132 | 20 | 1,250 | python | [] | 0 | true | |
2024-11-18T20:10:33.569440+00:00 | 1,511,275,588,000 | 038035421f67d83d8501133e9d278109e01d9789 | 3 | {
"blob_id": "038035421f67d83d8501133e9d278109e01d9789",
"branch_name": "refs/heads/master",
"committer_date": 1511275588000,
"content_id": "8d0534fa2bf37b75f11e088cc85bbb506afc0132",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "ffa0f47b7115812fc21ebbc2d03126ef806de82d",
"extension": "py"... | 2.546875 | stackv2 | from copy import deepcopy
from typing import Any, Dict
from keras import backend as K
from keras import initializers, activations
from overrides import overrides
from ...common.params import pop_choice
from ...tensors.backend import apply_feed_forward
from ...tensors.similarity_functions import similarity_functions
f... | 165 | 48.81 | 108 | 17 | 1,737 | python | [] | 0 | true | |
2024-11-18T20:10:33.628612+00:00 | 1,452,090,387,000 | 4cd405be708b40b21a2bc494c4d7177aa52dd536 | 2 | {
"blob_id": "4cd405be708b40b21a2bc494c4d7177aa52dd536",
"branch_name": "refs/heads/master",
"committer_date": 1452090387000,
"content_id": "265770cf5efe31a0bccdec5234abd548c6e37a0d",
"detected_licenses": [
"MIT"
],
"directory_id": "47c9490dd95a0c06b601dd34365cd7e198c4c288",
"extension": "py",
"fi... | 2.34375 | stackv2 | from time import time
from errbot import BotPlugin, botcmd, webhook
import pytumblr
class MarxBot(BotPlugin):
"""Your daily dose of Marx"""
min_err_version = '1.6.0'
tumblr_client = None
poll_interval = 60 * 15
class NotConfiguredError(Exception):
pass
def activate(self):
su... | 64 | 33.72 | 79 | 13 | 473 | python | [] | 0 | true | |
2024-11-18T20:10:33.742269+00:00 | 1,528,154,375,000 | 87a9170df1e0a7c9a4634cd6d19d26150934df8f | 2 | {
"blob_id": "87a9170df1e0a7c9a4634cd6d19d26150934df8f",
"branch_name": "refs/heads/master",
"committer_date": 1528154375000,
"content_id": "831e59ea76532fa15d8cfcb0878f7aa89f75bd26",
"detected_licenses": [
"MIT"
],
"directory_id": "5ba1feb2a5b1476ee7c893300445693c30cd9998",
"extension": "py",
"fi... | 2.40625 | stackv2 | import praw
import datetime
import tweepy
#Check apps.twitter.com for consumer key, consumer secret,
#access token, and acess token secret
#check http://dev.twitter.com/apps for more info on these keys
consumer_key = ""
consumer_secret = ""
access_token = ""
access_token_secret = ""
twitterAuth = tweepy.OAuthHandler(... | 29 | 29.28 | 112 | 13 | 211 | python | [] | 0 | true | |
2024-11-18T20:10:33.809140+00:00 | 1,638,449,008,000 | b54bd77edcfa12b60f126e9560a4e4d9459a07b0 | 3 | {
"blob_id": "b54bd77edcfa12b60f126e9560a4e4d9459a07b0",
"branch_name": "refs/heads/master",
"committer_date": 1638449008000,
"content_id": "74e1aea3dd610ff29db6f480a67711ad1daff9a6",
"detected_licenses": [
"MIT"
],
"directory_id": "19d93813cff4c210ceb77128516d4b8bc8c81b76",
"extension": "py",
"fi... | 3.375 | stackv2 | import os
class inputLine:
def __init__(self, min, max, criteria, password):
self.min = min
self.max = max
self.criteria = criteria
self.password = password
def IsCountBetweenCriteria(self):
cnt = self.password.count(self.criteria)
if cnt >= self.min and cnt <= self.max:
return True
... | 43 | 27.58 | 133 | 17 | 328 | python | [] | 0 | true | |
2024-11-18T20:10:33.870985+00:00 | 1,583,514,141,000 | 5b83246a2543f20eb4aef35573e19f558df4a8ed | 3 | {
"blob_id": "5b83246a2543f20eb4aef35573e19f558df4a8ed",
"branch_name": "refs/heads/master",
"committer_date": 1583514141000,
"content_id": "e96c7a33d1994ee302917ecef498974066023fd6",
"detected_licenses": [
"MIT"
],
"directory_id": "ce340425d9fe5a2ba6a533629f607dbb7ad479a1",
"extension": "py",
"fi... | 3.15625 | stackv2 | '''
Created on 26 nov. 2018
@author: david
'''
import logging
import time
from sensor.attitude import AttitudeSensor
logging.basicConfig(level=logging.DEBUG)
print("Press CTRL+C to finish")
sensor = AttitudeSensor(channel=1)
sensor.start()
try:
calibTime = 30
logging.info("Starting magnetometer calibra... | 37 | 18.62 | 93 | 12 | 178 | python | [] | 0 | true | |
2024-11-18T20:10:34.104862+00:00 | 1,600,518,080,000 | 9636c9fb46c06d3ea15c081e86ba2868f4cd7ca9 | 3 | {
"blob_id": "9636c9fb46c06d3ea15c081e86ba2868f4cd7ca9",
"branch_name": "refs/heads/master",
"committer_date": 1600518080000,
"content_id": "e3393809592189235b7b900d7d5d0b1f752cdb46",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "8954a550561a008a07f3b1c2617685db9b303841",
"extension": "py"... | 3.1875 | stackv2 | import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
"""This module demonstrates keras api and shows that the saved model should reproduce the same results as the
presaved model.
https://www.tensorflow.org/guide/keras/train_and_evaluate#training_evaluation_from_tfdata_datasets
""... | 124 | 32.31 | 114 | 12 | 1,029 | python | [] | 0 | true | |
2024-11-18T20:10:34.338440+00:00 | 1,442,933,892,000 | 1345d9c1511c10ba6561f716dc78290aca5dc640 | 2 | {
"blob_id": "1345d9c1511c10ba6561f716dc78290aca5dc640",
"branch_name": "refs/heads/master",
"committer_date": 1442933892000,
"content_id": "841e9874a15db5aca644d9193f8d6ee5ec9e14b0",
"detected_licenses": [
"MIT"
],
"directory_id": "7925bff6582db37fbd4c52300736dcb1ebdcff00",
"extension": "py",
"fi... | 2.390625 | stackv2 | ##input: /Users/metagenomics/Documents/Databases/uniprot_tremble.dat or uniprot_sprot.dat
import sys
import os
from Bio import SeqIO
uniprot = open(sys.argv[1], "rU")
for record in SeqIO.parse(uniprot, "swiss"):
id = record.id
taxa = record.annotations['taxonomy']
#if record.annotations['taxonomy'] >1:
# domain ... | 18 | 25.94 | 89 | 8 | 154 | python | [] | 0 | true | |
2024-11-18T20:10:34.390443+00:00 | 1,677,201,496,000 | 45d48a62c7fcb6451f60d47802503aed0d7337cb | 2 | {
"blob_id": "45d48a62c7fcb6451f60d47802503aed0d7337cb",
"branch_name": "refs/heads/master",
"committer_date": 1677201496000,
"content_id": "4c157b21b790ace88e04fd7e9900cb5d3f845d6f",
"detected_licenses": [
"BSD-3-Clause",
"BSD-2-Clause"
],
"directory_id": "245c57a44cf7239595b4883567a264bf60713049... | 2.3125 | stackv2 | '''class Tool, class InstallMethod, and related subclasses and methods'''
__author__ = "dpark@broadinstitute.org,irwin@broadinstitute.org"
import collections
import json
import operator
import os
import re
import logging
import tempfile
import shutil
import shlex
import subprocess
import util.file
import util.misc
f... | 185 | 27.72 | 106 | 17 | 1,128 | python | [] | 0 | true | |
2024-11-18T20:10:34.559836+00:00 | 1,561,801,764,000 | abaeae7b2e2889b15eef4799291db9beaf07806e | 3 | {
"blob_id": "abaeae7b2e2889b15eef4799291db9beaf07806e",
"branch_name": "refs/heads/master",
"committer_date": 1561801764000,
"content_id": "00022335f4e998c475cffcf7a99c83cef5b7b71c",
"detected_licenses": [
"MIT"
],
"directory_id": "97d123306ed743f131263bda49f309fabcf33e78",
"extension": "py",
"fi... | 2.8125 | stackv2 | from node import Node
from ops import Relu
from ops import VariableOp
from ops import Mult
from ops import Add
from ops import Sub
from ops import PlaceholderOp
import numpy as np
np.random.seed(42)
class Sequential:
def __init__(self):
pass
def __add_node(op, name, parents=[], variable_type='none', is_trainable... | 159 | 28.89 | 114 | 16 | 1,299 | python | [] | 0 | true | |
2024-11-18T20:10:34.804495+00:00 | 1,506,457,164,000 | 841f42450ca97762577f8e3b284ec1c5576e742c | 3 | {
"blob_id": "841f42450ca97762577f8e3b284ec1c5576e742c",
"branch_name": "refs/heads/master",
"committer_date": 1506457164000,
"content_id": "ace48edc34812d81b11826082f0a934af0300caf",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "4e66c94b362a39e93483025e4e9098f7d8a40d71",
"extension": "py"... | 3.25 | stackv2 | # -*- coding: utf-8 -*-
__author__ = 'Dmitriy.Dakhnovskiy'
import ast
from .abstract_source_parser import AbstractSourceParser
class PythonSourceParser(AbstractSourceParser):
def __init__(self, source):
"""
:param source: исходный код
"""
super().__init__(source)
@staticmeth... | 76 | 26.89 | 88 | 16 | 473 | python | [] | 0 | true | |
2024-11-18T20:10:34.997727+00:00 | 1,688,968,658,000 | 787a41a449879797f928e3c6c11e0e171d399e6b | 2 | {
"blob_id": "787a41a449879797f928e3c6c11e0e171d399e6b",
"branch_name": "refs/heads/master",
"committer_date": 1688968658000,
"content_id": "39c7ee9bdc3ea411c4c124348f7b37c84994f9a6",
"detected_licenses": [
"MIT"
],
"directory_id": "bc2ccaed5cf0367d196cedeef51d4b89db310db0",
"extension": "py",
"fi... | 2.390625 | stackv2 | import pylab as plt
def pylab_style(paper=False):
# list of avaliable parameters
# https://matplotlib.org/stable/tutorials/introductory/customizing.html#the-default-matplotlibrc-file
params = {
"boxplot.boxprops.linewidth": 10.0,
"figure.figsize": [8, 5],
"figure.titlesize": 20,
... | 48 | 33.44 | 105 | 10 | 487 | python | [] | 0 | true | |
2024-11-18T20:10:35.115444+00:00 | 1,409,777,933,000 | aca419578d38775a2b3f8e6b7e37bfe8ca9d7afd | 3 | {
"blob_id": "aca419578d38775a2b3f8e6b7e37bfe8ca9d7afd",
"branch_name": "refs/heads/master",
"committer_date": 1409777933000,
"content_id": "1b2cbe96f65cf43e5ca8c4901388e8b5fad9e1ff",
"detected_licenses": [
"MIT",
"BSD-3-Clause",
"Python-2.0",
"BSD-2-Clause"
],
"directory_id": "3569dffb117... | 2.546875 | stackv2 | # /usr/bin/env python2.7
# -*- coding: utf-8 -*-
"""
myip
created by hgschmidt on 03.12.12, 21:53 CET
Copyright (c) 2012 otype
"""
import logging
import tornado.ioloop
import tornado.web
import tornado.options
import tornado.httpserver
from tornado import web
# LOGGING PARAMETERS
#
#
LOG_FORMAT =... | 103 | 23.25 | 99 | 19 | 615 | python | [{"finding_id": "codeql_py/log-injection_e642b2dfa415fd2e_3ee3460b", "tool_name": "codeql", "rule_id": "py/log-injection", "finding_type": "path-problem", "severity": "medium", "confidence": "medium", "message": "This log entry depends on a [user-provided value](1).", "remediation": "", "location": {"file_path": "unkno... | 1 | true | |
2024-11-18T20:10:35.910047+00:00 | 1,402,806,219,000 | a7e4f4cc3696067a2aaaafba17bc61572e2c76d5 | 3 | {
"blob_id": "a7e4f4cc3696067a2aaaafba17bc61572e2c76d5",
"branch_name": "refs/heads/master",
"committer_date": 1402806219000,
"content_id": "f8416bc652154d2b3ee846e0ee51d3e73f738c5a",
"detected_licenses": [
"MIT"
],
"directory_id": "4d8e2dbc570415059c271556415c22789094b5af",
"extension": "py",
"fi... | 2.53125 | stackv2 | # coding: utf-8
from os.path import join as path_join, getmtime
from sh import rsync
import os
import subprocess as sp
def isfile(filename, mode='rb'):
try:
with open(filename, mode):
return True
except IOError:
pass
return False
def rm_files(files_list, raise_on_error=Fals... | 38 | 18.55 | 48 | 12 | 172 | python | [] | 0 | true | |
2024-11-18T20:10:35.981096+00:00 | 1,496,023,692,000 | 49a4f658ae2a92740e13217d333eabbbaab38f84 | 3 | {
"blob_id": "49a4f658ae2a92740e13217d333eabbbaab38f84",
"branch_name": "refs/heads/master",
"committer_date": 1496023692000,
"content_id": "4244d412ec118e8d5d661ffb2c98f4ba986f2e98",
"detected_licenses": [
"MIT"
],
"directory_id": "31cc1eb7fe334b963a9a56fd63c79cf6382778da",
"extension": "py",
"fi... | 3.1875 | stackv2 | # interrupt-based distance measurement with median filtering
# remember to use GPIO.cleanup()
import RPi.GPIO as GPIO
import time
class ultrasonic():
def __init__(self, echoPin, trigPin):
# Pin definitions
self.GND = 6 # only for reference
self.ECHO = echoPin
self.TRIG = trigPin
... | 41 | 26.34 | 60 | 12 | 269 | python | [] | 0 | true | |
2024-11-18T20:10:36.407663+00:00 | 1,613,405,869,000 | ea6252293c8a248f23b98fc56ce8737fbdc7c7ee | 3 | {
"blob_id": "ea6252293c8a248f23b98fc56ce8737fbdc7c7ee",
"branch_name": "refs/heads/main",
"committer_date": 1613405869000,
"content_id": "9428ae1af31ce683a78d674559d1c9a7a5ed92b6",
"detected_licenses": [
"MIT"
],
"directory_id": "404573518af29790b3c9c1884f5ae64aa5062070",
"extension": "py",
"file... | 3.03125 | stackv2 | import random
import requests
import BitVector as bit
API_URL = 'http://cryptlygos.pythonanywhere.com' #DON'T CHANGE THIS
my_id = 24775 #ATTN: Change this into your id number
endpoint = '{}/{}/{}'.format(API_URL, "poly", my_id )
response = requests.get(endpoint)
a = 0
b = 0
if response.ok:
res = respo... | 62 | 20.34 | 67 | 10 | 403 | python | [] | 0 | true | |
2024-11-18T20:10:36.517628+00:00 | 1,681,799,580,000 | 1d1e31a39a8ee82729c114bb7e1b1eeef70b92a6 | 3 | {
"blob_id": "1d1e31a39a8ee82729c114bb7e1b1eeef70b92a6",
"branch_name": "refs/heads/main",
"committer_date": 1681799580000,
"content_id": "097863e805be0405eb8a8d7a80af658973b11475",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "f7a64dbde3be55048389e6b161d0515bf4ddc77f",
"extension": "py"... | 2.65625 | stackv2 | # https://arxiv.org/pdf/1301.1071.pdf "Direct TSQR"
import sys
import numpy as np
import cupy as cp
import time
from parla import Parla
from parla.cpu import cpu
from parla.cuda import gpu
from parla.array import clone_here
from parla.function_decorators import specialized
from parla.tasks import *
ROWS = 500000 # M... | 174 | 29.09 | 119 | 15 | 1,524 | python | [] | 0 | true | |
2024-11-18T20:10:36.570821+00:00 | 1,633,779,306,000 | 3fb1b84636b1141248db33635cb400c895ea5da0 | 3 | {
"blob_id": "3fb1b84636b1141248db33635cb400c895ea5da0",
"branch_name": "refs/heads/master",
"committer_date": 1633779306000,
"content_id": "f63aed950a4a76789ebc9561f275760e8f7df198",
"detected_licenses": [
"MIT"
],
"directory_id": "f0f687dd2d6789b860afc2ce972564d68fe6601c",
"extension": "py",
"fi... | 3.296875 | stackv2 | from tkinter import *
import math
from PIL import Image, ImageTk
FIELDS = ('insert radiation of sphere','mark distance between spheres centre')
def calculate(entries):
r = float(entries['insert radiation of sphere'].get())
d = float(entries['mark distance between spheres centre'].get())
new_r = math.sqrt... | 54 | 26.24 | 78 | 13 | 403 | python | [] | 0 | true | |
2024-11-18T20:10:36.800831+00:00 | 1,544,330,106,000 | 38d03c6ac1985bda489196d021a4f7c8693110ba | 3 | {
"blob_id": "38d03c6ac1985bda489196d021a4f7c8693110ba",
"branch_name": "refs/heads/master",
"committer_date": 1544330106000,
"content_id": "40a52bc0019e38f6f2ace00c875b2c4e2c13ac8d",
"detected_licenses": [
"MIT"
],
"directory_id": "3182430b1610b619cf2a3779718abe481cf99950",
"extension": "py",
"fi... | 2.84375 | stackv2 | import mysql.connector
from mysql.connector import Error
class DatabaseHandler:
def __init__(self):
try:
self.conn = mysql.connector.connect(host='localhost', database='annotation', user='root', password='')
if self.conn.is_connected():
print("database is connected")
... | 20 | 33.3 | 114 | 14 | 131 | python | [] | 0 | true | |
2024-11-18T20:10:36.955142+00:00 | 1,561,161,782,000 | 66142ee5a1c283227b7f8b7d5dcd630d82a599ec | 3 | {
"blob_id": "66142ee5a1c283227b7f8b7d5dcd630d82a599ec",
"branch_name": "refs/heads/master",
"committer_date": 1561161782000,
"content_id": "1066ca214eca6b1fb3aeee84769a93b77d43b107",
"detected_licenses": [
"MIT"
],
"directory_id": "96afcfa239ef923358d1fe7c96ccaaf40dcefdf5",
"extension": "py",
"fi... | 2.953125 | stackv2 | """Implementation of neural style transfer.
The style of the reference image is imposed onto the target image.
This is the original implementation of neural style transfer proposed by
Leon Gatys et al. 2015. It is preferable to run this script on GPU, for speed.
Parts of this implementation are adapted from Google's ... | 405 | 34.46 | 143 | 15 | 3,321 | python | [] | 0 | true | |
2024-11-18T20:10:37.555002+00:00 | 1,648,939,287,000 | 8a581c15935c71fb9aa8086c788b55a09a7f760c | 3 | {
"blob_id": "8a581c15935c71fb9aa8086c788b55a09a7f760c",
"branch_name": "refs/heads/master",
"committer_date": 1648939287000,
"content_id": "0a2486eb5e17fe1e3751e4d7fe9ff7332ae19fb0",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "d1173b24964d25106e013eb5b4578fef85c3a0e9",
"extension": "py"... | 2.625 | stackv2 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import json
import deepnlpf.log as log
class Util(object):
def __init__(self):
pass
def openfile_json(self, path_file):
try:
with open(path_file, "r") as data:
return json.load(data)
except Exception as err:
... | 65 | 26.63 | 62 | 17 | 378 | python | [] | 0 | true | |
2024-11-18T20:10:37.714914+00:00 | 1,651,665,706,000 | 5e8109ee51a02cc64458c0dfcd57379b76dd5f98 | 3 | {
"blob_id": "5e8109ee51a02cc64458c0dfcd57379b76dd5f98",
"branch_name": "refs/heads/master",
"committer_date": 1651665706000,
"content_id": "6453e7b236a87f1be2ce6004e4bedc9bf656cdf1",
"detected_licenses": [
"MIT"
],
"directory_id": "25c95966eed54fe9a7399aef1f2bee95eca4e7cb",
"extension": "py",
"fi... | 3.40625 | stackv2 | from enum import Enum, auto
# Standard enum
class MyEnum(Enum):
A = 'a'
B = 'b'
# Enum with custom objects as values
class Value:
def __init__(self, value):
self.value = value
def __str__(self):
return self.value
class CustomObjectEnum(Enum):
A = Value(1)
B = Value('B')
... | 40 | 16.18 | 63 | 11 | 184 | python | [] | 0 | true | |
2024-11-18T20:10:37.886969+00:00 | 1,629,255,275,000 | 09d60b0cb898f0d930f70c8e4ab6f154a24f64f3 | 3 | {
"blob_id": "09d60b0cb898f0d930f70c8e4ab6f154a24f64f3",
"branch_name": "refs/heads/main",
"committer_date": 1629255275000,
"content_id": "42d610d0c60b3dce7248e0baa7d4252c9e2e750b",
"detected_licenses": [
"MIT"
],
"directory_id": "35f534d95b04700b11ff96536257c3de6504b655",
"extension": "py",
"file... | 2.65625 | stackv2 | import fnmatch
from datetime import *
import itertools
from math import sqrt
import numpy as np
from sklearn.cluster import KMeans
from sklearn.metrics import confusion_matrix, balanced_accuracy_score, precision_score
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassif... | 57 | 30.56 | 101 | 16 | 410 | python | [] | 0 | true | |
2024-11-18T20:10:38.073411+00:00 | 1,692,024,876,000 | dceacc88b1348338106d04a5be748cb25e90f929 | 2 | {
"blob_id": "dceacc88b1348338106d04a5be748cb25e90f929",
"branch_name": "refs/heads/main",
"committer_date": 1692024876000,
"content_id": "9af77bc367e30e548282561662531a52b65c7756",
"detected_licenses": [
"MIT"
],
"directory_id": "a70ad4b89501c39d6a9e20355bb50d8e12e53773",
"extension": "py",
"file... | 2.40625 | stackv2 | from importlib import import_module
from celery import shared_task
import asyncio
from django.conf import settings
from feedreader.functions.feedupdate import FeedsUpdater
from feedreader.models import Feed
from feedreader.functions import find_favicon
import logging
logger = logging.getLogger(__name__)
@shared_... | 61 | 26.61 | 82 | 13 | 370 | python | [] | 0 | true | |
2024-11-18T20:10:38.207915+00:00 | 1,589,065,875,000 | eea44f23ffd53bdaff542b0acec4740bb2605915 | 3 | {
"blob_id": "eea44f23ffd53bdaff542b0acec4740bb2605915",
"branch_name": "refs/heads/master",
"committer_date": 1589065875000,
"content_id": "16159703ddc3ce542ffc8dde18acec432b7caafb",
"detected_licenses": [
"MIT"
],
"directory_id": "2dd90463a4a3e16788c2139696add927fb6fc376",
"extension": "py",
"fi... | 3.03125 | stackv2 | from pyautogui import alert, password
from src.util import lock_user_account
import requests
import time
class Locker(object):
def __init__(self, host, token):
self.__host = host
self.__token = token
def get_offline_message(self):
# Informa que o servidor não está funcionando.
... | 93 | 29.71 | 107 | 18 | 593 | python | [] | 0 | true | |
2024-11-18T20:10:38.261416+00:00 | 1,478,512,582,000 | 92c94e8346731c564706419b3d572f8995baea55 | 3 | {
"blob_id": "92c94e8346731c564706419b3d572f8995baea55",
"branch_name": "refs/heads/master",
"committer_date": 1478512582000,
"content_id": "1f009a5d18bdc147071b2b83f75f0e96106a6cbb",
"detected_licenses": [
"MIT"
],
"directory_id": "5583ac672d249a827e0d3ae162d220114e100f80",
"extension": "py",
"fi... | 2.859375 | stackv2 | # -*- coding: utf-8 -*-
import hashlib
import requests
from xml.etree import ElementTree
from aws_requests_auth.aws_auth import AWSRequestsAuth
def create_bucket(host, bucketName, accessKey, secretKey):
"""
Create a bucket.
@param host: S3/Cleversafe host
@param bucketName: Bucket name
@param acc... | 203 | 35.82 | 125 | 14 | 1,676 | python | [] | 0 | true | |
2024-11-18T20:10:38.436775+00:00 | 1,690,675,108,000 | a837382e57717bfefdce14c314fd0a8a1ec2d2bd | 2 | {
"blob_id": "a837382e57717bfefdce14c314fd0a8a1ec2d2bd",
"branch_name": "refs/heads/master",
"committer_date": 1690675108000,
"content_id": "9e396d24faa02192bd27275e03d627afa03b2bff",
"detected_licenses": [
"MIT"
],
"directory_id": "84d8b10d5f8be3b84d0629d45fce4f75e7b45082",
"extension": "py",
"fi... | 2.5 | stackv2 | from glob import glob
import os
from pprint import pprint
names = []
for svg_fp in glob("/Users/mlevental/dev_projects/makslevental.github.io/images/memory_planning/*.svg"):
# if "small_bert" in svg_fp:
# svg_fp = svg_fp.replace("small_bert", "smallbert")
# model_name, strat = os.path.split(svg_fp)[-... | 62 | 38.08 | 135 | 15 | 710 | python | [] | 0 | true | |
2024-11-18T20:10:38.667019+00:00 | 1,675,463,248,000 | 1140a08b54057318516441917dea42d0f56ecb0e | 2 | {
"blob_id": "1140a08b54057318516441917dea42d0f56ecb0e",
"branch_name": "refs/heads/master",
"committer_date": 1675463248000,
"content_id": "adc7be5e35077416bb72c4ab74c8db5d903bdf84",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "01a4e25806f12087c1cae5db25696cad997e17a9",
"extension": "py"... | 2.375 | stackv2 | #
# Description: This example brings up a previously built EnXR router,
# executes some show commands and parses via cAAs/TCL and
# parsergen/Python, with differences in the parse results
# shown.
import os
from pyats.easypy import run
def main():
# Find the examples/tests d... | 35 | 35.63 | 70 | 12 | 316 | python | [] | 0 | true | |
2024-11-18T20:10:38.836282+00:00 | 1,687,154,248,000 | 0c49ff8881bf35b6384a76cf9c2472fc1d366de3 | 2 | {
"blob_id": "0c49ff8881bf35b6384a76cf9c2472fc1d366de3",
"branch_name": "refs/heads/master",
"committer_date": 1687154248000,
"content_id": "c0dd6ec5b0744d5bdb34b1407da6a054f4229145",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "6d09e43b6a32a75548562e6aba9848469f0f236c",
"extension": "py"... | 2.359375 | stackv2 | from typing import Dict, Type
from HABApp.core.const.json import load_json
from .events import OpenhabEvent, \
ItemStateEvent, ItemStateUpdatedEvent, ItemStateChangedEvent, ItemCommandEvent, ItemAddedEvent, \
ItemUpdatedEvent, ItemRemovedEvent, ItemStatePredictedEvent, \
GroupStateUpdatedEvent, GroupStateC... | 46 | 40.43 | 111 | 13 | 438 | python | [] | 0 | true | |
2024-11-18T20:10:39.017419+00:00 | 1,537,345,724,000 | 30ed7163583c7e656db739c856a4e0027e406957 | 3 | {
"blob_id": "30ed7163583c7e656db739c856a4e0027e406957",
"branch_name": "refs/heads/master",
"committer_date": 1537345724000,
"content_id": "e19b568924338de1effe863750c666635e68362a",
"detected_licenses": [
"Unlicense"
],
"directory_id": "bc9096935c61b10c8c156406e4649fd4a7d46028",
"extension": "py",... | 2.515625 | stackv2 | from django.db import models
class Person(models.Model):
first_name = models.CharField(max_length=40, null=False)
last_name = models.CharField(max_length=40, null=False)
description = models.TextField()
avatar = models.ImageField(upload_to="media/", null=True)
class Address(models.Model):
"""
... | 49 | 36.63 | 79 | 10 | 392 | python | [] | 0 | true | |
2024-11-18T20:10:39.077629+00:00 | 1,616,134,621,000 | a87ec33eaa8c715d3700e5ae5833ca6edf0f231a | 2 | {
"blob_id": "a87ec33eaa8c715d3700e5ae5833ca6edf0f231a",
"branch_name": "refs/heads/master",
"committer_date": 1616134621000,
"content_id": "b25824b670d8751c054295d36e6c5f0a9b1f04fa",
"detected_licenses": [
"MIT"
],
"directory_id": "062069a8f1f13a49439bc25a3abafa011a7fcdea",
"extension": "py",
"fi... | 2.375 | stackv2 | class BdApiError(IOError):
pass
def mute_error(func):
def wrapper(*args, **kwargs):
try:
return func(*args, **kwargs)
except Exception:
pass
return wrapper
def log_error(func):
import logging
logger = logging.getLogger('BdPan')
def wrapper(*args, **k... | 28 | 19.14 | 43 | 14 | 123 | python | [] | 0 | true | |
2024-11-18T20:10:39.139437+00:00 | 1,429,789,540,000 | ee3a3603b6235c633589246703132a4cc17222f6 | 3 | {
"blob_id": "ee3a3603b6235c633589246703132a4cc17222f6",
"branch_name": "refs/heads/master",
"committer_date": 1429789540000,
"content_id": "66d80eb95091b10203e891308047953f8a833f93",
"detected_licenses": [
"MIT"
],
"directory_id": "19c40c08e6908054b73355bba69794e7083c206a",
"extension": "py",
"fi... | 2.78125 | stackv2 | from decimal import Decimal, ROUND_HALF_DOWN
import requests
import json
from qsforex.event.event import TickEvent
from qsforex.data.price import PriceHandler
class StreamingForexPrices(PriceHandler):
def __init__(
self, domain, access_token,
account_id, pairs, events_queue
):
self.d... | 80 | 39.9 | 89 | 23 | 742 | python | [] | 0 | true | |
2024-11-18T20:10:39.310617+00:00 | 1,448,866,520,000 | 4d1228288fa14136b704827a6b76873671b985ff | 2 | {
"blob_id": "4d1228288fa14136b704827a6b76873671b985ff",
"branch_name": "refs/heads/master",
"committer_date": 1448871740000,
"content_id": "824400b3992ed4f21540d35f2a31befa9d7b7d1f",
"detected_licenses": [
"MIT"
],
"directory_id": "218623be0476d2eda498b9e979478eb9865eb221",
"extension": "py",
"fi... | 2.359375 | stackv2 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Usage: python apk_launcher.py <apk file>
#
import sys
import os
import subprocess
import re
import command_util
from optparse import OptionParser
from sys import stderr
from sys import stdout
# -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- #
# command line arg... | 55 | 25.87 | 79 | 13 | 426 | python | [] | 0 | true | |
2024-11-18T20:10:39.366390+00:00 | 1,623,246,379,000 | d08d9f89745109526be1b519f4d65c438124fdb0 | 3 | {
"blob_id": "d08d9f89745109526be1b519f4d65c438124fdb0",
"branch_name": "refs/heads/main",
"committer_date": 1623246379000,
"content_id": "e181764d41711789e85c7c89c7d18ad3d10fc22f",
"detected_licenses": [
"MIT"
],
"directory_id": "d3aaed8298a6c9a0564ee53e1401f8e118d9662c",
"extension": "py",
"file... | 3.359375 | stackv2 | from timeit import default_timer as timer
from functools import wraps
from inspect import getframeinfo, stack, getargspec
def ctimeit(function):
"""
A custom decorator for timing a function
Usage:
Simply add: @ctimeit before a function definition
Example:
@ctimeit
... | 49 | 27.59 | 92 | 18 | 328 | python | [] | 0 | true | |
2024-11-18T20:10:39.430393+00:00 | 1,580,287,626,000 | 3e92ac93c33a5c99b3ef7efb55df5ecce20e2807 | 3 | {
"blob_id": "3e92ac93c33a5c99b3ef7efb55df5ecce20e2807",
"branch_name": "refs/heads/master",
"committer_date": 1580287626000,
"content_id": "376463088522468ff532607d242a8e1d66a87b1d",
"detected_licenses": [
"MIT"
],
"directory_id": "1d44e2d1eceb3800276d38f38cbda613b50fc4ca",
"extension": "py",
"fi... | 3.09375 | stackv2 | from ycyc.ycollections.heap import Heap
class SerialListItem(object):
def __init__(self, sn, value):
self.sn = sn
self.value = value
class SerialList(object):
def __init__(self, sn=0, reverse=False):
self.next_sn = sn
self.heap = Heap(cmp_attrs=["sn"], reverse=False)
def... | 40 | 24.62 | 57 | 16 | 228 | python | [] | 0 | true | |
2024-11-18T20:10:39.641056+00:00 | 1,625,160,965,000 | 6b51f71551f397e55a35e6fcc7ea8c37419789fa | 3 | {
"blob_id": "6b51f71551f397e55a35e6fcc7ea8c37419789fa",
"branch_name": "refs/heads/master",
"committer_date": 1625160965000,
"content_id": "fd9f501b976ccc065617179dd3fa4be9e73db76d",
"detected_licenses": [
"MIT"
],
"directory_id": "2a7edf6063fd5c4f1372ffaf2bffc5339ccab74e",
"extension": "py",
"fi... | 2.546875 | stackv2 | from __future__ import print_function
import os.path
import pickle
import pyttsx3
from googleapiclient.discovery import build
from google_auth_oauthlib.flow import InstalledAppFlow
from google.auth.transport.requests import Request
import os
import playsound
from gtts import gTTS
import datetime
import pytz
import spac... | 297 | 33.29 | 122 | 23 | 2,442 | python | [{"finding_id": "codeql_py/clear-text-logging-sensitive-data_673d79ec966abf0f_5cd72e75", "tool_name": "codeql", "rule_id": "py/clear-text-logging-sensitive-data", "finding_type": "path-problem", "severity": "medium", "confidence": "high", "message": "This expression logs [sensitive data (password)](1) as clear text.", ... | 1 | true | |
2024-11-18T20:10:39.771618+00:00 | 1,688,462,636,000 | 2c97dcd37324354e1efa8ee2110e4663e3603fd4 | 3 | {
"blob_id": "2c97dcd37324354e1efa8ee2110e4663e3603fd4",
"branch_name": "refs/heads/master",
"committer_date": 1688462636000,
"content_id": "8f27ff0dca5b8e956d14f7b0043cc34ae498431e",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "a7cfc888250e38b5fbde527d6ec714140548d129",
"extension": "p... | 2.546875 | stackv2 | """PASPAL implementation (in Python, based on the original MATLAB).
Copyright 2009-2010 Sofia Mosci and Lorenzo Rosasco (Matlab implementation)
Copyright 2018 Federico Tomasi (Python implementation)
"""
from __future__ import print_function, division
from itertools import combinations
import numpy as np
from scipy ... | 251 | 31.46 | 118 | 18 | 2,346 | python | [] | 0 | true | |
2024-11-18T20:10:40.005048+00:00 | 1,632,422,493,000 | 0fcad28464e4b41b453a98038cd268c6406b88ec | 3 | {
"blob_id": "0fcad28464e4b41b453a98038cd268c6406b88ec",
"branch_name": "refs/heads/main",
"committer_date": 1632422493000,
"content_id": "7df882d0879ec9dcb170e1006718f9971eb341c6",
"detected_licenses": [
"MIT"
],
"directory_id": "96e8b6024075e425254d324b6eb20e11b4b87a70",
"extension": "py",
"file... | 3.28125 | stackv2 | # -*- coding: utf-8 -*-
"""TextAnaly1.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1zen1h2ly517z9HEwTFdksGymM_CPfYEC
"""
import nltk
from nltk import sent_tokenize,word_tokenize
nltk.download('punkt')
text= "Hello iam doing text analytics her... | 68 | 17.47 | 77 | 9 | 359 | python | [] | 0 | true | |
2024-11-18T20:10:40.106724+00:00 | 1,667,240,910,000 | 98d64befaf7044edf6502110639a28c0b1061f98 | 4 | {
"blob_id": "98d64befaf7044edf6502110639a28c0b1061f98",
"branch_name": "refs/heads/master",
"committer_date": 1667240910000,
"content_id": "98b00153efc9e074ef09b72722b6f7fc870fdc65",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "9d5ffeb26d7ff6305c85c35057a074e55a7296d7",
"extension": "py"... | 3.9375 | stackv2 | # Given an array nums of integers, return how many of them contain an even number of digits.
# Example 1:
# Input: nums = [12,345,2,6,7896]
# Output: 2
# Explanation:
# 12 contains 2 digits (even number of digits).
# 345 contains 3 digits (odd number of digits).
# 2 contains 1 digit (odd number of digits).
# 6... | 43 | 21.58 | 92 | 11 | 327 | python | [] | 0 | true | |
2024-11-18T20:10:40.259567+00:00 | 1,519,164,056,000 | 2310513ea34ee18675a9e0138f458cbe5884acc4 | 3 | {
"blob_id": "2310513ea34ee18675a9e0138f458cbe5884acc4",
"branch_name": "refs/heads/master",
"committer_date": 1519164056000,
"content_id": "6258ba5f0c3b1614e7b5b2490765fb29c0cd6e34",
"detected_licenses": [
"MIT"
],
"directory_id": "e169fd5ea9e79bb3be21e7148900eae700778a50",
"extension": "py",
"fi... | 2.6875 | stackv2 | import os
import sys
import subprocess as sp
from pathlib import PurePath
PARSER_PATH = sys.modules[__name__].__file__
def geojson_to_topojson(infile,outfile):
"""
geojson_to_topojson converts a geojson file into a topojson file.
This function uses [https://github.com/topojson/topojson-server](https://git... | 23 | 33.43 | 113 | 13 | 207 | python | [] | 0 | true | |
2024-11-18T20:10:40.363420+00:00 | 1,513,239,259,000 | a52f4e390950d4c557e3c0103017a965cf61d3b6 | 3 | {
"blob_id": "a52f4e390950d4c557e3c0103017a965cf61d3b6",
"branch_name": "refs/heads/master",
"committer_date": 1513239259000,
"content_id": "10022bfb2dcb46d091f88fffba6fd5bb5b0df26a",
"detected_licenses": [
"MIT"
],
"directory_id": "110bff45691ab83612b5573a49b445abe6db87e9",
"extension": "py",
"fi... | 3.125 | stackv2 | import sys
'''
The below is only needed for Bayesian Optimization on Luis' Machine.
Ignore and comment out if it causes problems.
'''
path = "/home/luis/Documents/Harvard_School_Work/Spring_2015/cs181/assignments/practicals/prac4/practical4-code/"
if path not in sys.path:
sys.path.append(path)
'''
End Bayesian
'''... | 72 | 30.62 | 113 | 12 | 489 | python | [] | 0 | true | |
2024-11-18T20:10:40.420529+00:00 | 1,630,321,760,000 | 9447dd0fce3f6668ebbaa40d820123eb55560395 | 2 | {
"blob_id": "9447dd0fce3f6668ebbaa40d820123eb55560395",
"branch_name": "refs/heads/main",
"committer_date": 1630321760000,
"content_id": "105d30199e1df06fcd5ab3185dbaf77aab59716c",
"detected_licenses": [
"MIT"
],
"directory_id": "a4d90752c3af106270f63a277f380115acd55164",
"extension": "py",
"file... | 2.375 | stackv2 | import torchvision.datasets as dset
import torchvision.transforms as transforms
from torch.utils.data import DataLoader
import matplotlib.pyplot as plt
import torchvision.utils
from torch import optim
from Config import *
from ContrastiveLoss import *
from SiameseNetwork import *
from SiameseNetworkDataset import *
imp... | 75 | 40.67 | 148 | 18 | 729 | python | [] | 0 | true | |
2024-11-18T20:10:40.995046+00:00 | 1,491,415,110,000 | c251ab0391c5d0bcad009c89ef049c9ff0432782 | 3 | {
"blob_id": "c251ab0391c5d0bcad009c89ef049c9ff0432782",
"branch_name": "refs/heads/master",
"committer_date": 1491415110000,
"content_id": "430a23fd10c18592aea0f46c2df1f1e73fec3911",
"detected_licenses": [
"MIT"
],
"directory_id": "cbe03fadf9998859b928c61d8e4502b45873623f",
"extension": "py",
"fi... | 2.65625 | stackv2 | # coding=utf-8
"""Wait for all subtasks have done.
"""
import tornado
import tornado.locks
from tornado.concurrent import Future
class ProcessWaiter(tornado.locks._TimeoutGarbageCollector):
def __init__(self):
super(ProcessWaiter, self).__init__()
self._value = 0
def __repr__(self):
... | 62 | 31.74 | 103 | 19 | 452 | python | [] | 0 | true | |
2024-11-18T20:10:41.098571+00:00 | 1,510,247,223,000 | cfdcc73d7fa05bbeba9af3eb69b32d7f5b430614 | 4 | {
"blob_id": "cfdcc73d7fa05bbeba9af3eb69b32d7f5b430614",
"branch_name": "refs/heads/master",
"committer_date": 1510247223000,
"content_id": "9216037582c5203d89a5f4be500cb8a569752261",
"detected_licenses": [
"MIT"
],
"directory_id": "74988651d8e70163c3c834599fcd631972f73c02",
"extension": "py",
"fi... | 3.5 | stackv2 | #!/usr/bin/env python 3
# -*- coding: utf-8 -*-
###
# Name: Andrew_Papilion
# Student ID: 2265916
# Email: papil103@mail.chapman.edu
# Course: PHYS220/MATH220/CPSC220 Fall 2017
# Assignment: Classwork_04
###
import math
import numpy as np
import math
import numpy as np
def gen_gaussian_list(a, b, n=1000):
dx ... | 67 | 26.72 | 76 | 14 | 547 | python | [] | 0 | true | |
2024-11-18T20:10:42.063362+00:00 | 1,622,364,750,000 | 50114972a046b5ff2e4543b1ff655441d44b78bc | 3 | {
"blob_id": "50114972a046b5ff2e4543b1ff655441d44b78bc",
"branch_name": "refs/heads/main",
"committer_date": 1622364750000,
"content_id": "e5d979fb3fa8e379cd23b394e73d717e06b3e2a8",
"detected_licenses": [
"MIT"
],
"directory_id": "2b059e66517881a619ceae9cff7400e14cb25411",
"extension": "py",
"file... | 3.25 | stackv2 | from typing import List
class Solution:
def searchRange(self, nums: List[int], target: int) -> List[int]:
def findIndex(isLeft):
left = 0
right = len(nums)
while left < right:
mid = left + (right - left)//2
if nums[mid... | 32 | 26.12 | 74 | 16 | 214 | python | [] | 0 | true | |
2024-11-18T20:10:42.128594+00:00 | 1,608,741,560,000 | 771ca5460d426ee6849dfaaa80cc629ed5999fcc | 3 | {
"blob_id": "771ca5460d426ee6849dfaaa80cc629ed5999fcc",
"branch_name": "refs/heads/master",
"committer_date": 1608741560000,
"content_id": "5a1642b83a8fc3054c9b4093dc4512c956547f52",
"detected_licenses": [
"CC0-1.0"
],
"directory_id": "58cc38c8e3c8c9006692667ab5ef3ab86bd90ed5",
"extension": "py",
... | 3.015625 | stackv2 | """
authors: Adam Villarreal
depending on your environment you may need to install:
pandas>=1.0.3
numpy>=1.18
sqlalchemy>=1.3
tqdm>=4.44
psycopg2>=2.8
matplotlib>=3.1
seaborn==0.9
"""
import sqlalchemy
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
#Connecting to the Database Server
username... | 104 | 35.31 | 151 | 13 | 1,065 | python | [] | 0 | true | |
2024-11-18T20:10:42.386996+00:00 | 1,490,659,469,000 | 5b6dd20d7dc0601b67fe4932a9293665ec02d869 | 2 | {
"blob_id": "5b6dd20d7dc0601b67fe4932a9293665ec02d869",
"branch_name": "refs/heads/master",
"committer_date": 1490659469000,
"content_id": "30dc6ab055f72016e83cbda25eb782ec2391a1af",
"detected_licenses": [
"MIT"
],
"directory_id": "f0db275fb5a4f4c1600cf884be6fb9edddf594f5",
"extension": "py",
"fi... | 2.328125 | stackv2 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
'''
transit.py
----------
The TRAPPIST-1 transit model class.
'''
from __future__ import division, print_function, absolute_import #, unicode_literals
import numpy as np
import pysyzygy as ps
import everest
import os
TRAPPIST_DAT = os.path.join(os.path.dirname(os.path.ab... | 187 | 32.53 | 153 | 20 | 2,280 | python | [] | 0 | true | |
2024-11-18T20:10:42.453428+00:00 | 1,624,220,533,000 | 7412d7da38d7429f47a6a7abf491f158e6055c17 | 3 | {
"blob_id": "7412d7da38d7429f47a6a7abf491f158e6055c17",
"branch_name": "refs/heads/master",
"committer_date": 1624220533000,
"content_id": "26cd38cbc0f605bf777acb321e24d60d99116bfe",
"detected_licenses": [
"MIT"
],
"directory_id": "f28c2e25a2b101c339aa752014287a1f9e3b5545",
"extension": "py",
"fi... | 2.71875 | stackv2 | from bin.classes.class_system import *
from bin.input import input_vars
from bin.revised_simplex_with_ETA import revised_simplex_with_ETA
from bin.canonical_form import canonical_form
from bin.make_standardized_form import make_standardized_form
from bin.print_ import *
from bin.dual_simplex import dual_simplex
from bi... | 36 | 26.83 | 110 | 14 | 247 | python | [] | 0 | true | |
2024-11-18T20:10:42.748509+00:00 | 1,608,007,305,000 | b4f26187f17256e8b640b68427e2c37f3360ead2 | 3 | {
"blob_id": "b4f26187f17256e8b640b68427e2c37f3360ead2",
"branch_name": "refs/heads/main",
"committer_date": 1608007305000,
"content_id": "9277b4b0341188f38d2e8aa557377a51be71200c",
"detected_licenses": [
"MIT"
],
"directory_id": "9974e520c1135f362d707f87a009431fd74717a5",
"extension": "py",
"file... | 3.0625 | stackv2 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Dec 7 00:45:09 2020
@author: yanglingqin
Description: o Read from the listings csv file of rating, subway and tourist attractions data.
o Plot box plot of rating~subway and rating~tourist attraction.
"""
import pandas as pd
import seabor... | 42 | 21.52 | 94 | 11 | 266 | python | [] | 0 | true | |
2024-11-18T20:10:42.804070+00:00 | 1,600,648,639,000 | 239ddecdc2c228db3ce8e3e8270eb1e7ce63551e | 2 | {
"blob_id": "239ddecdc2c228db3ce8e3e8270eb1e7ce63551e",
"branch_name": "refs/heads/master",
"committer_date": 1600648639000,
"content_id": "16e3db5b92c417980e2703a71ec81f2e2a77f573",
"detected_licenses": [
"MIT"
],
"directory_id": "dae95c2ea64fa10e5495b6abb981e204bfe8b4af",
"extension": "py",
"fi... | 2.5 | stackv2 | import pandas as pd
import torch
import numpy as np
import transformers
from transformers import AutoModel, BertTokenizerFast, AdamW, BertModel
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
import torch.nn as nn
import tensorflow
from keras import Input, Model
from keras.layers im... | 95 | 34.28 | 160 | 10 | 851 | python | [] | 0 | true | |
2024-11-18T20:10:42.991627+00:00 | 1,618,940,886,000 | f5ccb8dbec71e451b6cf546d47e2b32afa0778da | 3 | {
"blob_id": "f5ccb8dbec71e451b6cf546d47e2b32afa0778da",
"branch_name": "refs/heads/main",
"committer_date": 1618940886000,
"content_id": "162d0cbed223548108f4a97cee6a5f1fdfa5a96c",
"detected_licenses": [
"MIT"
],
"directory_id": "4f9f608670adfe2a8b7b87afd1c35f6f24514652",
"extension": "py",
"file... | 2.546875 | stackv2 | import csv
import os
from datetime import datetime
from typing import List
from data_set_dimension_reductioner.classes.data_class.dimension_reduction_result import DimensionReductionResult
from data_set_dimension_reductioner.classes.dimension_reduction_statistics_reporter.statistic_reporter import \
DimensionReduc... | 29 | 44.14 | 113 | 14 | 249 | python | [] | 0 | true | |
2024-11-18T20:10:43.073861+00:00 | 1,590,715,742,000 | 9bcff7658c32a5b0a104658c70b71c0e924207a6 | 3 | {
"blob_id": "9bcff7658c32a5b0a104658c70b71c0e924207a6",
"branch_name": "refs/heads/master",
"committer_date": 1590715742000,
"content_id": "6965f6f8b64307244027676510911f91b7a17824",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "8a6104c025242590ac659ae9dd7488bc9faac053",
"extension": "p... | 2.75 | stackv2 | '''Plot Stimuli from NWB files'''
from pathlib import Path
import os
import sys
from pynwb import NWBHDF5IO
import cv2
import numpy as np
import re
def plotStimuli(nwbFilePath):
# Input Path Here
#nwbFilePath = ('V:/LabUsers/chandravadian/NWB Data/p/P9HMH_NOID5.nwb')
#session = 'P9HMH_NOID5.nwb' # 'P42H... | 80 | 26.27 | 106 | 13 | 575 | python | [] | 0 | true | |
2024-11-18T20:10:43.124500+00:00 | 1,611,094,657,000 | 80b9588daf1de48689cc9cbd663637e3d0b2e2d5 | 3 | {
"blob_id": "80b9588daf1de48689cc9cbd663637e3d0b2e2d5",
"branch_name": "refs/heads/master",
"committer_date": 1611094657000,
"content_id": "83ea445475cdbaad735fe700378c25d2dd705549",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "b660237a088048f879ca3fb76a98b6a562abe062",
"extension": "py"... | 2.59375 | stackv2 | from .base_patterns import Pattern
from .pattern_containers import register_pattern_json
import autograd.numpy as np
import copy
import itertools
import json
import scipy as osp
from scipy import sparse
def _unconstrain_array(array, lb, ub):
# Assume that the inputs obey the constraints, lb < ub and
# lb <= a... | 367 | 33.45 | 79 | 18 | 2,924 | python | [] | 0 | true | |
2024-11-18T20:10:43.301682+00:00 | 1,688,416,464,000 | 3539d7927b65d1f1a42159da7db2f9719b713256 | 2 | {
"blob_id": "3539d7927b65d1f1a42159da7db2f9719b713256",
"branch_name": "refs/heads/master",
"committer_date": 1688416464000,
"content_id": "14442a84c66debbede0c72bc7e6b4a4e1c5c1ccc",
"detected_licenses": [],
"directory_id": "5231c6307a055e21c31d4366c5a2af8dba487caa",
"extension": "py",
"filename": "mpi... | 2.359375 | stackv2 | #!/usr/bin/env python3
import numpy as np
import pandas as pd
import re
import gzip
import argparse
from collections import defaultdict
import subprocess
import os
import tempfile
def samtools_mpileup(bam_file, fasta, region=None, regions_bed=None, variant_ids=None,
output_extra=None, prefix=None... | 336 | 36.93 | 110 | 24 | 3,217 | python | [] | 0 | true | |
2024-11-18T20:10:46.731769+00:00 | 1,512,626,647,000 | 08586fa305334b8f4a7e38e1655a5bf61dd40024 | 3 | {
"blob_id": "08586fa305334b8f4a7e38e1655a5bf61dd40024",
"branch_name": "refs/heads/master",
"committer_date": 1512626647000,
"content_id": "5948b1fa2ed28bbc5cfe9265562a60f1524d243e",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "0ba6abd94c6000566ee0751ca6557c006355578d",
"extension": "py"... | 2.78125 | stackv2 | # -*- coding:utf-8 -*-
import unittest
import multiprocessing
import time
from a_1 import *
from b_1 import *
from parametic import *
class TestOne(ParametrizedTestCase):
def test_a(self):
i = 1
print("proc1 send***: %s" % (i))
self.param.send(i)
time.sleep(5)
print("do so... | 56 | 25.32 | 84 | 13 | 383 | python | [] | 0 | true | |
2024-11-18T20:10:46.856494+00:00 | 1,690,979,144,000 | a1dd330729af0e10e28000c4071d1f3756fea6fa | 3 | {
"blob_id": "a1dd330729af0e10e28000c4071d1f3756fea6fa",
"branch_name": "refs/heads/master",
"committer_date": 1690979144000,
"content_id": "018539abc235a6d8c2f2ef2825e71174d443638d",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "3d063af394b4b55ea49ded7915d0793602015859",
"extension": "py"... | 2.6875 | stackv2 | """
Load data from Companies House from a dump file or an id file.
"""
import requests
import time
import json
import sys
import sling.flags as flags
import sling.crawl.chs as chs
flags.define("--ids",
help="File with list of company numbers to load",
default=None,
metavar="FILE... | 111 | 24.48 | 65 | 13 | 659 | python | [] | 0 | true | |
2024-11-18T20:10:47.698796+00:00 | 1,683,902,021,000 | 42b9a030fa984d70ed1a8212e942e15553cee8e9 | 4 | {
"blob_id": "42b9a030fa984d70ed1a8212e942e15553cee8e9",
"branch_name": "refs/heads/master",
"committer_date": 1683902021000,
"content_id": "d5bbb268b2d3bf8e05503a7c543ec079b81cfd9a",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "19da55d3d1d822ec4c991ebc26e14203ef6fd035",
"extension": "py"... | 3.75 | stackv2 | """
一个有名的按摩师会收到源源不断的预约请求，每个预约都可以选择接或不接。在每次预约服务之间要有休息时间，因此她不能接受相邻的预约。
给定一个预约请求序列，替按摩师找到最优的预约集合（总预约时间最长），返回总的分钟数。
示例 1：
输入： [1,2,3,1]
输出： 4
解释： 选择 1 号预约和 3 号预约，总时长 = 1 + 3 = 4。
示例 2：
输入： [2,7,9,3,1]
输出： 12
解释： 选择 1 号预约、 3 号预约和 5 号预约，总时长 = 2 + 9 + 1 = 12。
示例 3：
输入： [2,1,4,5,3,1,1,3]
输出： 12
解释： 选择 1 号预约、 3 号预约、 5 号预约和 8 号... | 37 | 20.59 | 64 | 14 | 380 | python | [] | 0 | true | |
2024-11-18T20:10:47.745764+00:00 | 1,626,150,650,000 | 987f0384e927b5f1f7b311945b22d52d7d42dd77 | 2 | {
"blob_id": "987f0384e927b5f1f7b311945b22d52d7d42dd77",
"branch_name": "refs/heads/master",
"committer_date": 1626150650000,
"content_id": "f7dc6b899633dd0ae8e974776b1b3ea8d10a6248",
"detected_licenses": [
"BSD-3-Clause",
"BSD-2-Clause"
],
"directory_id": "20c2d07e67cf153a433d0b094c1706b8a5616521... | 2.359375 | stackv2 | # Copyright: (c) 2021, Edwin G. W. Peters
from demodulator.demodulator_base import Demodulator as Demodulator_base
class Demodulator(Demodulator_base):
def uploadAndFindCarrier(self,samples):
"""
Performs:
thresholding -- remove large spikes of interference
uploadToGPU --... | 20 | 29.2 | 72 | 9 | 144 | python | [] | 0 | true | |
2024-11-18T20:10:47.921346+00:00 | 1,522,710,638,000 | 6946a5fb8de4d0f03f032cff0e02874f21dd4470 | 3 | {
"blob_id": "6946a5fb8de4d0f03f032cff0e02874f21dd4470",
"branch_name": "refs/heads/master",
"committer_date": 1522710638000,
"content_id": "7a2809b5dd63e5516ed2f42db42d07f656cb3b44",
"detected_licenses": [
"MIT"
],
"directory_id": "4059f9624e23c5eb8db7f688317aa18a883a9087",
"extension": "py",
"fi... | 2.703125 | stackv2 |
import os
import numpy as np
def load_data(data_path, prefix = "_train"):
imgs_train = np.load(os.path.join(data_path, "imgs"+prefix+".npy"),
mmap_mode="r", allow_pickle=False)
msks_train = np.load(os.path.join(data_path, "msks"+prefix+".npy"),
mmap_mode="r", allow_pickle=False)
return imgs_train, m... | 45 | 26.24 | 78 | 14 | 412 | python | [] | 0 | true | |
2024-11-18T20:10:48.090055+00:00 | 1,596,397,594,000 | 0048b91b0d82e5155c88f09613a86e2125bc4668 | 2 | {
"blob_id": "0048b91b0d82e5155c88f09613a86e2125bc4668",
"branch_name": "refs/heads/master",
"committer_date": 1596397594000,
"content_id": "3674ecdf663c467ab9933a0b38fe5fe88a31d455",
"detected_licenses": [
"MIT"
],
"directory_id": "1e6dafa2fc46f8e6ddab04f671a5ce76d7a10033",
"extension": "py",
"fi... | 2.5 | stackv2 | import json as _json
import pathlib as _pathlib
import requests_oauthlib as _requests_oauthlib
def oauth(
consumer_key: str,
consumer_secret: str,
token_value: str,
token_secret: str,
) -> _requests_oauthlib.OAuth1:
return _requests_oauthlib.OAuth1(
client_key = consumer_key,
client_s... | 49 | 25 | 58 | 17 | 314 | python | [] | 0 | true | |
2024-11-18T20:10:48.291826+00:00 | 1,615,749,923,000 | e6030a6144c8a6968e4cfc717454f009b7c102f0 | 3 | {
"blob_id": "e6030a6144c8a6968e4cfc717454f009b7c102f0",
"branch_name": "refs/heads/master",
"committer_date": 1615749923000,
"content_id": "86f5230cb8739819da352461caeecea58fcc45b8",
"detected_licenses": [
"Zlib"
],
"directory_id": "d84bcc6b37482d078a738456756e948639cb5360",
"extension": "py",
"f... | 2.8125 | stackv2 | import math
import os
from matplotlib import pyplot as plt
distribution_names = {
"shuffled_16_values_int": "Shuffled (16 values)",
"shuffled_int": "Shuffled",
"all_equal_int": "All equal",
"ascending_int": "Ascending",
"descending_int": "Descending",
"pipe_organ_int": "Pipe organ",
"pus... | 84 | 35.14 | 139 | 18 | 884 | python | [] | 0 | true | |
2024-11-18T20:10:48.402812+00:00 | 1,590,548,166,000 | 22509bbe1ab91a1f7d895254d7372b206c8b0ec7 | 3 | {
"blob_id": "22509bbe1ab91a1f7d895254d7372b206c8b0ec7",
"branch_name": "refs/heads/master",
"committer_date": 1590548166000,
"content_id": "3ee20175cd15d485911c29056f886c3cdca5ad6b",
"detected_licenses": [
"MIT"
],
"directory_id": "3014d0408b05e2ebcbf7d9a08e5a1c7208a5110e",
"extension": "py",
"fi... | 2.59375 | stackv2 | # -*- coding: utf-8 -*-
import os
import datetime
import copy
import collections
from queue import Queue
from abc import ABC, abstractmethod
import numpy as np
import torch
from torch import nn
from tensorboardX import SummaryWriter
def train_local_mp(net, local_epochs, rnd, q, policy, w_d):
"""For multiprocessing... | 125 | 35.88 | 100 | 17 | 1,040 | python | [] | 0 | true | |
2024-11-18T20:10:48.503475+00:00 | 1,553,486,302,000 | 5a1caf77157834c7d810afdeeba389925ade2427 | 3 | {
"blob_id": "5a1caf77157834c7d810afdeeba389925ade2427",
"branch_name": "refs/heads/master",
"committer_date": 1553486302000,
"content_id": "2def10fc3e0d009739e51797b641b4c8bd14c00e",
"detected_licenses": [
"Apache-2.0"
],
"directory_id": "49aa27e9f1bf3efa1f6fdd54556124647fac972c",
"extension": "py"... | 3.21875 | stackv2 | from math import fabs
class Node:
def __init__(self, val):
self.val = val
self.next = None
carry, result, diffNode = 0, None, None
def getSizeOfList(head):
if not head:
return 0
count = 0
p = head
while p:
count += 1
p = p.next
return count
def pus... | 94 | 19.29 | 46 | 12 | 553 | python | [] | 0 | true | |
2024-11-18T20:10:48.619102+00:00 | 1,626,826,976,000 | ebde10ecd5cd7b861b32e403d4801143cadc94b4 | 4 | {
"blob_id": "ebde10ecd5cd7b861b32e403d4801143cadc94b4",
"branch_name": "refs/heads/main",
"committer_date": 1626826976000,
"content_id": "8b0b9c958dcc22258022ba91fcfb3ec882b6da11",
"detected_licenses": [
"MIT"
],
"directory_id": "ca3a49676cdf1016b2d729f0432b451d35b7a281",
"extension": "py",
"file... | 3.84375 | stackv2 | def fruit_distribution(s,n):
"""
In this task, you will be given a string that represents a number of apples and oranges
that are distributed in a basket of fruit this basket contains
apples, oranges, and mango fruits. Given the string that represents the total number of
the oranges and apples an... | 49 | 30.12 | 115 | 12 | 430 | python | [] | 0 | true | |
2024-11-18T20:10:48.681744+00:00 | 1,572,616,107,000 | 9b4a694de015639f344fd8803cc6717f621c309b | 2 | {
"blob_id": "9b4a694de015639f344fd8803cc6717f621c309b",
"branch_name": "refs/heads/master",
"committer_date": 1572616107000,
"content_id": "f199e6b25e73f6edcb784ea08ab25ce1bfacedcb",
"detected_licenses": [
"MIT"
],
"directory_id": "1da87e0507cf12804a58cc47232ed59c357d90f8",
"extension": "py",
"fi... | 2.328125 | stackv2 | import logging
import boto3
from botocore.exceptions import ClientError
import os,sys,threading,time
class CTRANSCRIBE():
def __init__(self):
pass
def initialize(self,server,access_key,access_secret):
ACCESS_KEY = access_key
SECRET_KEY = access_secret
try:
if 'aws' in server:
self.s3_client = boto3... | 148 | 30.34 | 146 | 16 | 1,195 | python | [] | 0 | true | |
2024-11-18T20:10:48.737287+00:00 | 1,543,418,786,000 | ecc604d0c0dedadddbdd80c7280dbd8cef6c300e | 2 | {
"blob_id": "ecc604d0c0dedadddbdd80c7280dbd8cef6c300e",
"branch_name": "refs/heads/master",
"committer_date": 1543418786000,
"content_id": "1bc916ac253b8fdfa4dfdb27370986e2da0dbd5f",
"detected_licenses": [
"CC0-1.0",
"MIT"
],
"directory_id": "79ab6eb5a37b345c3c377008001003f35abe5475",
"extensio... | 2.34375 | stackv2 | # -*- coding: utf-8 -*-
# Copyright (c) 2017 RS Components Ltd
# SPDX-License-Identifier: MIT License
"""
Interface for PmodGyro.
.. note::
"""
import RPi.GPIO as gpio
from time import sleep
import spidev
CAP = 'SPI'
PHY = '2x6'
READ = 0x80
CTRL_REG1 = 0x20
CTRL_REG2 = 0x21
CTRL_REG3 = 0x22
CTRL_REG4 = 0x23
CTRL_RE... | 141 | 24.07 | 83 | 15 | 1,180 | python | [] | 0 | true | |
2024-11-18T20:10:48.924934+00:00 | 1,493,353,966,000 | 7d50859c000358f91d2c72836c780932d524e68c | 2 | {
"blob_id": "7d50859c000358f91d2c72836c780932d524e68c",
"branch_name": "refs/heads/master",
"committer_date": 1493353966000,
"content_id": "8d86432c485b5b21fe79925406221dd36556d0d9",
"detected_licenses": [
"MIT"
],
"directory_id": "24866e043eb794df96a358bf6eedf353038c844c",
"extension": "py",
"fi... | 2.453125 | stackv2 | import handlers
routes = [
("/", "SimpleHandler"),
("/vote", "VoteHandler"),
("/result", "ResultHandler"),
]
class AppRoutes(object):
def __init__(self, app):
self.handlers = []
for route, handler_name in routes:
handler_class = getattr(handlers, handler_name)
... | 18 | 25.61 | 85 | 16 | 101 | python | [] | 0 | true | |
2024-11-18T20:10:48.993379+00:00 | 1,519,967,147,000 | 633c9230807f8a2fcb61f14db2ec0986fa8b8d99 | 3 | {
"blob_id": "633c9230807f8a2fcb61f14db2ec0986fa8b8d99",
"branch_name": "refs/heads/master",
"committer_date": 1519967147000,
"content_id": "25ad6df815164dbd5d90f45e89f82e13c8c7850d",
"detected_licenses": [
"MIT"
],
"directory_id": "900dac4c57f71f7ec9171178efa31bd95c29b002",
"extension": "py",
"fi... | 2.65625 | stackv2 | # -*- coding: utf-8 -*-
""" Learning rate assemble.
Author: Kai JIN
Updated: 2017-07-23
"""
import tensorflow as tf
def configure_lr(config, global_step):
"""Configures the learning rate.
Args:
config: config.train.lr
global_step: The global_step tensor.
Returns:
A `Tensor` representing the ... | 87 | 26.95 | 74 | 12 | 536 | python | [] | 0 | true | |
2024-11-18T20:10:49.079674+00:00 | 1,456,057,179,000 | 9af083ad1188082edb4c3ea2cfa4a2049e188178 | 3 | {
"blob_id": "9af083ad1188082edb4c3ea2cfa4a2049e188178",
"branch_name": "refs/heads/master",
"committer_date": 1456057179000,
"content_id": "512199f659433131dc3345c2461aa12b93d6efb8",
"detected_licenses": [
"BSD-3-Clause"
],
"directory_id": "d36f0d7e5fab499cb392f7efe1940761fc117ea2",
"extension": "p... | 2.546875 | stackv2 | from sqlalchemy import Column, String, DateTime, Integer, create_engine
from sqlalchemy.ext.declarative import declarative_base
engine = create_engine('sqlite:///slack-archives.db')
engine.echo = False
Base = declarative_base()
class Message(Base):
__tablename__ = 'messages'
id = Column(Integer(), primary_k... | 20 | 33.35 | 71 | 10 | 157 | python | [] | 0 | true | |
2024-11-18T20:10:49.208267+00:00 | 1,599,062,880,000 | f4c63e16ce559b2bd00a46946e1996268b0d57e0 | 3 | {
"blob_id": "f4c63e16ce559b2bd00a46946e1996268b0d57e0",
"branch_name": "refs/heads/master",
"committer_date": 1599062880000,
"content_id": "bedfe6d0bfeff798b43e57656c202941bc78e5fa",
"detected_licenses": [
"MIT"
],
"directory_id": "7c990fa2088c1f9afadf920eba1f6367ab14b8fa",
"extension": "py",
"fi... | 2.828125 | stackv2 | """
Author: Faidon Mitzalis
Edited from VL-BERT impelementation
Generates json file for training set with caption/images/frcnn for multi30k dataset
"""
import os
import json
import random
from tqdm import tqdm
captions_en = []
captions_de = []
# ****************
# Step 1: Read all files
filepath_en = '../train.en'
f... | 37 | 24.16 | 83 | 11 | 231 | python | [] | 0 | true |
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