question stringlengths 11 198 ⌀ | code stringlengths 0 12.1k |
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null | db.rollback() |
null | a = ['cat', 'dog', 'mouse'] |
null | myinst.__dict__['attr'] |
null | numpy.outer(numpy.array([1, 2]), numpy.array([3, 4])) |
null | b = numpy.append(a, numpy.zeros([len(a), 1]), 1) |
null | [[], [], []] |
null | dtype([('x', '<i8'), ('y', 'S')]) |
null | window.after(1, lambda : window.focus_force()) |
null | my_function = __import__('my_apps.views').my_function |
null | print(df.loc['one']) |
null | zip(big_list[:], big_list[1:], big_list[2:]) |
null | """""".join(sorted(x)) |
null | parser.parse_args() |
null | xl.Workbooks.Open('C:\\Foo\\Bar.xlsx') |
null | urllib.parse.urlencode({'data': {'wifi': {'ssid': 'guest', 'rssi': '80'}}}) |
null | bin(0) |
null | tom_index = next(index for index, d in enumerate(lst) if d['name'] == 'Tom') |
null | ax.get_xticklines()[i].set_visible(False) |
null | y = x.astype(int) |
null | """""".join(random.choices(string.ascii_uppercase + string.digits, k=N)) |
null | f.write('foo\nbar\nbaz\n') |
null | [len(x) for x in s.split()] |
null | parser.add_option('-f', '--file', dest='filename', help='foo help') |
null | hdl = logging.FileHandler('hits.log') |
null | result = (list_[0][0] + list_[1][0]) * (list_[0][1] + list_[1][1]) |
null | dict((k, mydict[k]) for k in keys_to_select if k in mydict) |
null | {k: sum(v) for k, v in list(trimmed.items())} |
null | cv2.rectangle(image, (x, y), (x + w, y + h), (255, 255, 0), 5) |
null | df[0].apply(lambda x: (0, 0) if x is np.nan else x) |
null | myDict.pop(key, None) |
null | connection = cql.connect('localhost:9160', cql_version='3.0.0') |
null | [('1', 6), ('2', 4), ('7', 3), ('10', 2)] |
null | print(', '.join(data[:-2] + [' and '.join(data[-2:])])) |
null | zip(string, string[1:], string[2:]) |
null | pd.read_csv('whitespace.csv', header=None, delimiter='\\s+') |
null | int(x) / int(y) == math.floor(float(x) / float(y)) |
null | lines.sort(key=itemgetter(2), reverse=True) |
null | df.filter(regex='^foo\\.', axis=1) |
null | return date.today() > self.date |
null | text = text.replace('?"', '? "').replace('!"', '! "').replace('."', '. "') |
null | return func(*args, **kwargs) |
null | session.query(func.myThingFunction('bar')).all() |
null | """^\\s*[\\w_][\\w\\d_]*\\s*.*\\s*[\\w_][\\w\\d_]*\\s*\\(.*\\)\\s*$""" |
null | {key: val for key, val in parent_dict.items() if 2 < key < 4} |
null | random.sample(list(range(1, 10)), 5) |
null | print(mydate.strftime('%Y-%m-%d')) |
null | re.compile('[') |
null | bbox_data = ax.transData.inverted().transform(bbox) |
null | map(int, bin(6)[2:]) |
null | print("All normal prints after 'RESET' above.") |
null | pdb.set_trace() |
null | print(etree.tostring(root, pretty_print=True)) |
null | df.convert_objects(convert_numeric=True) |
null | """\\xc3\\x85あ""".encode('utf-8').decode('unicode_escape').encode('latin-1') |
null | word = '*' * len(name) |
null | u = User.objects.filter(userjob__job=a).filter(userjob__job=c) |
null | return render_to_response('foo.html', {'results': decoded_json['Result']}) |
null | {v: (v ** 2) for v in l} |
null | df.stack().between(2, 10, inclusive=False).unstack() |
null | self.setWindowFlags(PyQt4.QtCore.Qt.WindowStaysOnTopHint) |
null | pygame.init() |
null | df.select(lambda x: re.search('prefix$', str(x)) is None, axis=1) |
null | br.select_form(nr=1) |
null | [(mylist[i:] + [newelement] + mylist[:i]) for i in range(len(mylist), -1, -1)] |
null | print(lxml.etree.tostring(order, pretty_print=True)) |
null | print(r.dtype) |
null | print(A.reshape(-1, k)[np.arange(n * m), B.ravel()]) |
null | soup = BeautifulSoup.BeautifulSoup(urllib.request.urlopen(url).read()) |
null | json1_data = json.loads(json1_str)[0] |
null | Group.objects.get(id=1).members.filter(is_main_user=True)[0] |
null | sys.stdout.write('\rComplete! \n') |
null | numpy.set_printoptions(formatter={'float': lambda x: 'float: ' + str(x)}) |
null | print(map(lambda key_value: int(key_value[1]), list(ss.items()))) |
null | new = text[:1] + 'Z' + text[2:] |
null | len(['DATE', 'TIME', 'DLAT', 'DLON', 'SLAT', 'SLON', 'SHGT', 'HGT', 'N', 'E']) |
null | [[1, 1, 2, 2], [1, 1, 2, 2], [3, 3, 4, 4], [3, 3, 4, 4]] |
null | a_lower = dict((k.lower(), v) for k, v in list(a.items())) |
null | dfrm.drop(dfrm.index[len(dfrm) - 1]) |
null | 'This is a string: %s' % 'abc' |
null | [[1, -2], [3, -2]] |
null | isinstance(variable, States) |
null | del myList[i] |
null | [x for y in l for x in y] |
null | base = df.index.get_loc(18) |
null | good_data = [data[(n), :][flag == 1].tolist() for n in range(data.shape[0])] |
null | db_table = 'schema"."tablename' |
null | ax.set_xlabel('Distance from heated face($10^{-2}$ m)') |
null | print(len(str(decimal.Decimal('0.1')))) |
null | img.save('/tmp/image.bmp') |
null | print(maximize_nonoverlapping_count([[3, 4], [5, 8], [0, 6], [1, 2]])) |
null | df.plot(kind='bar', stacked=True, color=my_colors) |
null | output = subprocess.check_output(['ping', '-c', '2', '-W', '2', '1.1.1.1']) |
null | output = ''.join(item[0].upper() for item in re.findall('\\w+', input)) |
null | [line for line in file if not line.startswith('#')] |
null | return HttpResponse(json.dumps(locs), mimetype='application/json') |
null | stopword_pattern.match('1999') |
null | print('{:.6f}'.format(i)) |
null | winsound.PlaySound('alert.wav') |
null | new_data = np.vectorize(boolstr_to_floatstr)(data).astype(float) |
null | plt.rcParams['patch.edgecolor'] = 'white' |
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