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1,468 | def BeginThreadsSimpleMarshal(numThreads, cookie):
ret = []
for i in range(numThreads):
hEvent = win32event.CreateEvent(None, 0, 0, None)
thread.start_new(TestInterpInThread, (hEvent, cookie))
ret.append(hEvent)
return ret
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1,470 | @set_database
def get_download_youtube_ids(paths=None, downloaded=False, **kwargs):
if paths:
youtube_ids = dict()
for path in paths:
selector = (((Item.kind != 'Topic') & Item.path.contains(path)) & Item.youtube_id.is_null(False))
if downloaded:
selector &= (Item.files_complete > 0)
else:
selector &= (Item.files_complete == 0)
youtube_ids.update(dict([item for item in Item.select(Item.youtube_id, Item.title).where(selector).tuples() if item[0]]))
return youtube_ids
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1,471 | def precision_recall_curve(y_true, probas_pred, pos_label=None, sample_weight=None):
(fps, tps, thresholds) = _binary_clf_curve(y_true, probas_pred, pos_label=pos_label, sample_weight=sample_weight)
precision = (tps / (tps + fps))
recall = (tps / tps[(-1)])
last_ind = tps.searchsorted(tps[(-1)])
sl = slice(last_ind, None, (-1))
return (np.r_[(precision[sl], 1)], np.r_[(recall[sl], 0)], thresholds[sl])
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1,472 | def find_value(stdout, key):
match = _HORCM_PATTERNS[key]['pattern'].search(stdout)
if match:
if (_HORCM_PATTERNS[key]['type'] is list):
return [value.strip() for value in LDEV_SEP_PATTERN.split(match.group(key))]
return _HORCM_PATTERNS[key]['type'](match.group(key))
return None
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1,474 | @treeio_login_required
@handle_response_format
def currency_delete(request, currency_id, response_format='html'):
currency = get_object_or_404(Currency, pk=currency_id)
if (not request.user.profile.has_permission(currency, mode='w')):
return user_denied(request, "You don't have access to this Currency", response_format)
if currency.is_default:
return user_denied(request, 'You cannot delete the Base Currency', response_format)
if request.POST:
if ('delete' in request.POST):
if ('trash' in request.POST):
currency.trash = True
currency.save()
else:
currency.delete()
return HttpResponseRedirect(reverse('finance_settings_view'))
elif ('cancel' in request.POST):
return HttpResponseRedirect(reverse('finance_currency_view', args=[currency.id]))
return render_to_response('finance/currency_delete', {'currency': currency}, context_instance=RequestContext(request), response_format=response_format)
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1,475 | def MakeUniformPmf(low, high, n):
pmf = Pmf()
for x in np.linspace(low, high, n):
pmf.Set(x, 1)
pmf.Normalize()
return pmf
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1,476 | def change_process_owner(uid, gid):
try:
os.setgid(gid)
os.setuid(uid)
except Exception as exc:
error = DaemonOSEnvironmentError(('Unable to change file creation mask (%(exc)s)' % vars()))
raise error
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1,479 | def list_bucket_files(bucket_name, prefix, max_keys=1000):
scope = 'https://www.googleapis.com/auth/devstorage.read_only'
url = ('https://%s.commondatastorage.googleapis.com/?' % bucket_name)
query = [('max-keys', max_keys)]
if prefix:
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url += urllib.urlencode(query)
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result = urlfetch.fetch(url, method=urlfetch.GET, headers={'Authorization': ('OAuth %s' % auth_token), 'x-goog-api-version': '2'})
if (result and (result.status_code == 200)):
doc = xml.dom.minidom.parseString(result.content)
return [node.childNodes[0].data for node in doc.getElementsByTagName('Key')]
raise BackupValidationException('Request to Google Cloud Storage failed')
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1,480 | def runmodule(name='__main__', **kw):
main(defaultTest=name, **kw)
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1,481 | def plot_histograms(ax, prng, nb_samples=10000):
params = ((10, 10), (4, 12), (50, 12), (6, 55))
for (a, b) in params:
values = prng.beta(a, b, size=nb_samples)
ax.hist(values, histtype='stepfilled', bins=30, alpha=0.8, normed=True)
ax.annotate('Annotation', xy=(0.25, 4.25), xycoords='data', xytext=(0.9, 0.9), textcoords='axes fraction', va='top', ha='right', bbox=dict(boxstyle='round', alpha=0.2), arrowprops=dict(arrowstyle='->', connectionstyle='angle,angleA=-95,angleB=35,rad=10'))
return ax
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1,482 | def is_centos_or_rhel(distribution):
return distribution.startswith(('centos-', 'rhel-'))
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1,483 | def nested_view(request):
c = Client()
c.get('/no_template_view/')
return render(request, 'base.html', {'nested': 'yes'})
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1,485 | def id_(reset=False):
if reset:
id_pattern = re.compile('Monit id (?P<id>[^ ]+)')
cmd = 'echo y|monit -r'
out = __salt__['cmd.run_all'](cmd, python_shell=True)
ret = id_pattern.search(out['stdout']).group('id')
return (ret if ret else False)
else:
cmd = 'monit -i'
out = __salt__['cmd.run'](cmd)
ret = out.split(':')[(-1)].strip()
return ret
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1,486 | @pytest.fixture
def small_push_dir(tmpdir):
contents = ('abcdefghijlmnopqrstuvwxyz\n' * 10000)
push_dir = tmpdir.join('push-from').ensure(dir=True)
push_dir.join('arbitrary-file').write(contents)
push_dir.join('pg_xlog').mksymlinkto('/tmp/wal-e-test-must-not-exist')
push_dir.join('holy-smokes').ensure()
return push_dir
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1,488 | def test_found():
with pytest.raises(falcon.http_status.HTTPStatus) as redirect:
hug.redirect.found('/')
assert ('302' in redirect.value.status)
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] | test to ensure function causes a redirect with http 302 status code . | train | false |
1,490 | def rgb_to_ints(rgb):
if (len(rgb) == 6):
return tuple([int(h, 16) for h in RE_RGB6.split(rgb)[1:4]])
else:
return tuple([int((h * 2), 16) for h in RE_RGB3.split(rgb)[1:4]])
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1,491 | def _process_quantiles(x, dim):
x = np.asarray(x, dtype=float)
if (x.ndim == 0):
x = x[np.newaxis]
elif (x.ndim == 1):
if (dim == 1):
x = x[:, np.newaxis]
else:
x = x[np.newaxis, :]
return x
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1,492 | def deserialize(collection, topological=True):
datastruct = deserialize_raw(collection.collection_type())
if (topological and (type(datastruct) == list)):
datastruct.sort(__depth_cmp)
if (type(datastruct) == dict):
collection.from_dict(datastruct)
elif (type(datastruct) == list):
collection.from_list(datastruct)
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1,494 | def test_ada_sk_estimator():
check_estimator(ADASYN)
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] | test the sklearn estimator compatibility . | train | false |
1,495 | def gcg(seq):
try:
seq = str(seq)
except AttributeError:
pass
index = checksum = 0
for char in seq:
index += 1
checksum += (index * ord(char.upper()))
if (index == 57):
index = 0
return (checksum % 10000)
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1,496 | def ramp(x=None, v_min=0, v_max=1, name=None):
return tf.clip_by_value(x, clip_value_min=v_min, clip_value_max=v_max, name=name)
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1,497 | def extract_line(text, index):
p = (text.rfind('\n', 0, index) + 1)
q = text.find('\n', index)
if (q < 0):
q = len(text)
return text[p:q]
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1,498 | def parse_ref(container, refspec):
refspec = to_bytes(refspec)
possible_refs = [refspec, ('refs/' + refspec), ('refs/tags/' + refspec), ('refs/heads/' + refspec), ('refs/remotes/' + refspec), (('refs/remotes/' + refspec) + '/HEAD')]
for ref in possible_refs:
if (ref in container):
return ref
else:
raise KeyError(refspec)
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1,499 | @newrelic.agent.function_trace()
@allow_CORS_GET
@prevent_indexing
def _document_deleted(request, deletion_logs):
if (request.user and request.user.has_perm('wiki.restore_document')):
deletion_log = deletion_logs.order_by('-pk')[0]
context = {'deletion_log': deletion_log}
return render(request, 'wiki/deletion_log.html', context, status=404)
raise Http404
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] | when a document has been deleted return a 404 . | train | false |
1,500 | def check_arg_errcode(result, func, cargs):
check_err(arg_byref(cargs))
return result
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1,501 | def ascent():
import pickle
import os
fname = os.path.join(os.path.dirname(__file__), 'ascent.dat')
with open(fname, 'rb') as f:
ascent = array(pickle.load(f))
return ascent
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1,502 | def addToNamePathDictionary(directoryPath, namePathDictionary):
pluginFileNames = getPluginFileNamesFromDirectoryPath(directoryPath)
for pluginFileName in pluginFileNames:
namePathDictionary[pluginFileName.replace('_', '')] = os.path.join(directoryPath, pluginFileName)
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1,503 | def _module(language):
return _modules.setdefault(language, __import__(language, globals(), {}, [], (-1)))
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1,505 | def reset_ignored():
cmd = ['softwareupdate', '--reset-ignored']
salt.utils.mac_utils.execute_return_success(cmd)
return (list_ignored() == [])
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1,506 | def percentiles(a, pcts, axis=None):
scores = []
try:
n = len(pcts)
except TypeError:
pcts = [pcts]
n = 0
for (i, p) in enumerate(pcts):
if (axis is None):
score = stats.scoreatpercentile(a.ravel(), p)
else:
score = np.apply_along_axis(stats.scoreatpercentile, axis, a, p)
scores.append(score)
scores = np.asarray(scores)
if (not n):
scores = scores.squeeze()
return scores
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1,507 | def p_field_id(p):
p[0] = p[1]
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] | field_id : intconstant : . | train | false |
1,508 | def from_xml(xml):
if (xml is None):
return None
deserializer = XmlDeserializer()
return deserializer(xml)
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] | deserialize xml to a dictionary . | train | false |
1,510 | def gamma_correct(cs, c):
gamma = cs.gamma
if (gamma == GAMMA_REC709):
cc = 0.018
if (c < cc):
c = (((1.099 * math.pow(cc, 0.45)) - 0.099) / cc)
else:
c = ((1.099 * math.pow(c, 0.45)) - 0.099)
else:
c = math.pow(c, (1.0 / gamma))
return c
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1,512 | def JoinLists(**args):
out = {}
for (key, val) in args.items():
if val:
out[key] = StrJoin(JOIN_DELIMS[key], val)
else:
out[key] = ''
return out
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1,513 | def safe_dump_all(documents, stream=None, **kwds):
return dump_all(documents, stream, Dumper=SafeDumper, **kwds)
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1,514 | def find_bucket_key(s3_path):
s3_components = s3_path.split('/')
bucket = s3_components[0]
s3_key = ''
if (len(s3_components) > 1):
s3_key = '/'.join(s3_components[1:])
return (bucket, s3_key)
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1,515 | def _textlist(self, _addtail=False):
result = []
if ((not _addtail) and (self.text is not None)):
result.append(self.text)
for elem in self:
result.extend(elem.textlist(True))
if (_addtail and (self.tail is not None)):
result.append(self.tail)
return result
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] | returns a list of text strings contained within an element and its sub-elements . | train | true |
1,516 | def columnate(l, prefix):
if (not l):
return ''
l = l[:]
clen = max((len(s) for s in l))
ncols = ((tty_width() - len(prefix)) / (clen + 2))
if (ncols <= 1):
ncols = 1
clen = 0
cols = []
while (len(l) % ncols):
l.append('')
rows = (len(l) / ncols)
for s in range(0, len(l), rows):
cols.append(l[s:(s + rows)])
out = ''
for row in zip(*cols):
out += ((prefix + ''.join((('%-*s' % ((clen + 2), s)) for s in row))) + '\n')
return out
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"+",
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] | format elements of l in columns with prefix leading each line . | train | false |
1,517 | def _pb_timestamp_to_datetime(timestamp_pb):
return (_EPOCH + datetime.timedelta(seconds=timestamp_pb.seconds, microseconds=(timestamp_pb.nanos / 1000.0)))
| [
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1,518 | def get_effective_domain_id(request):
default_domain = get_default_domain(request)
domain_id = default_domain.get('id')
domain_name = default_domain.get('name')
return (None if (domain_name == DEFAULT_DOMAIN) else domain_id)
| [
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] | gets the id of the default domain to use when creating identity objects . | train | true |
1,519 | def mulmatmat(matlist1, matlist2, K):
matcol = [list(i) for i in zip(*matlist2)]
result = []
for row in matlist1:
result.append([mulrowcol(row, col, K) for col in matcol])
return result
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1,520 | def total_result_to_dict(total):
return {'meta': extract_meta(total), 'duration': _get_duration(world), 'features': [extract_feature_data(feature_result) for feature_result in total.feature_results]}
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] | transform a totalresult to a json-serializable python dictionary . | train | false |
1,521 | def test_determinism_even_sequences():
rng = np.random.RandomState(123)
lengths = rng.randint(1, 10, 100)
data = [(['w'] * l) for l in lengths]
batch_size = 5
my_iter = EvenSequencesSubsetIterator(data, batch_size)
visited1 = ([0] * len(data))
for (b_ind, ind_list) in enumerate(my_iter):
assert [(len(data[i]) == len(data[ind_list[0]])) for i in ind_list]
for i in ind_list:
visited1[i] = b_ind
my_iter = EvenSequencesSubsetIterator(data, batch_size)
visited2 = ([0] * len(data))
for (b_ind, ind_list) in enumerate(my_iter):
assert [(len(data[i]) == len(data[ind_list[0]])) for i in ind_list]
for i in ind_list:
visited2[i] = b_ind
assert np.all((np.asarray(visited1) == np.asarray(visited2)))
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] | check that evensequencessubsetiterator deterministically visits entries of a dataset of sequence data . | train | false |
1,523 | def visit_binary_product(fn, expr):
stack = []
def visit(element):
if isinstance(element, ScalarSelect):
(yield element)
elif ((element.__visit_name__ == 'binary') and operators.is_comparison(element.operator)):
stack.insert(0, element)
for l in visit(element.left):
for r in visit(element.right):
fn(stack[0], l, r)
stack.pop(0)
for elem in element.get_children():
visit(elem)
else:
if isinstance(element, ColumnClause):
(yield element)
for elem in element.get_children():
for e in visit(elem):
(yield e)
list(visit(expr))
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1,525 | @pytest.fixture(autouse=True)
def init_fake_clipboard(quteproc):
quteproc.send_cmd(':debug-set-fake-clipboard')
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1,527 | def mock_responses(resps):
def wrapper(func):
@responses.activate
@functools.wraps(func)
def wrapped(*args, **kwargs):
for resp in resps:
responses.add(*resp.args, **resp.kwargs)
return func(*args, **kwargs)
return wrapped
return wrapper
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1,528 | def _restore_int(name, value):
if ((name == 'http01_port') and (value == 'None')):
logger.info('updating legacy http01_port value')
return cli.flag_default('http01_port')
try:
return int(value)
except ValueError:
raise errors.Error('Expected a numeric value for {0}'.format(name))
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1,529 | def context_get(stack, name):
return stack.get(name)
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] | find and return a name from a contextstack instance . | train | false |
1,532 | def _get_cols_m2m(cls, k, child, fk_left_col_name, fk_right_col_name, fk_left_deferrable, fk_left_initially, fk_right_deferrable, fk_right_initially, fk_left_ondelete, fk_left_onupdate, fk_right_ondelete, fk_right_onupdate):
(col_info, left_col) = _get_col_o2m(cls, fk_left_col_name, ondelete=fk_left_ondelete, onupdate=fk_left_onupdate, deferrable=fk_left_deferrable, initially=fk_left_initially)
right_col = _get_col_o2o(cls, k, child, fk_right_col_name, ondelete=fk_right_ondelete, onupdate=fk_right_onupdate, deferrable=fk_right_deferrable, initially=fk_right_initially)
left_col.primary_key = right_col.primary_key = True
return (left_col, right_col)
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1,533 | def _valid_code(seed, drift=0):
return totp(key=seed, t=(int(time.time()) + (drift * 30)))
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1,534 | def assert_equal_steps(test_case, expected, actual):
expected_steps = getattr(expected, 'steps')
actual_steps = getattr(actual, 'steps')
if (None in (expected_steps, actual_steps)):
test_case.assertEqual(expected, actual)
else:
mismatch_steps = []
missing_steps = []
index = 0
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try:
actual_step = actual_steps[index]
except IndexError:
missing_steps = expected_steps[index:]
break
if (expected_step != actual_step):
mismatch_steps.append('* expected: {} !=\n actual: {}'.format(expected_step, actual_step))
extra_steps = actual_steps[(index + 1):]
if (mismatch_steps or missing_steps or extra_steps):
test_case.fail('Step Mismatch\nMismatch:\n{}\nMissing:\n{}\nExtra:\n{}'.format('\n'.join(mismatch_steps), missing_steps, extra_steps))
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1,535 | def set_global_options(options):
global _global_options
_global_options = dict(options)
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] | sets the global options used as defaults for web server execution . | train | false |
1,536 | def get_pairs(all_files, read1_indicator, read2_indicator, match_barcodes=False, barcode_indicator='_I1_'):
pairs = {}
bc_pairs = {}
read1_files = []
read2_files = []
bc_files = []
for curr_file in all_files:
curr_file_string_r1 = curr_file.split(read1_indicator)
curr_file_string_r2 = curr_file.split(read2_indicator)
if match_barcodes:
curr_file_string_bc = curr_file.split(barcode_indicator)
if (len(curr_file_string_r1) == 2):
read1_files.append(curr_file_string_r1)
elif (len(curr_file_string_r2) == 2):
read2_files.append(curr_file_string_r2)
elif (match_barcodes and (len(curr_file_string_bc) == 2)):
bc_files.append(curr_file_string_bc)
else:
raise ValueError, ((('Invalid filename found for splitting on input ' + ('for file %s, ' % curr_file)) + 'check input read1_indicator ') + 'and read2_indicator parameters as well.')
for curr_read1 in read1_files:
for curr_read2 in read2_files:
if (curr_read1 == curr_read2):
pairs[read1_indicator.join(curr_read1)] = read2_indicator.join(curr_read2)
if match_barcodes:
for curr_read1 in read1_files:
for curr_bc in bc_files:
if (curr_read1 == curr_bc):
bc_pairs[read1_indicator.join(curr_read1)] = barcode_indicator.join(curr_bc)
forward_reads = set(pairs.keys())
bc_reads = set(bc_pairs.keys())
non_matching_f_reads = (forward_reads - bc_reads)
if non_matching_f_reads:
raise ValueError, ('Found forward reads without matching barcodes file: %s' % non_matching_f_reads)
return (pairs, bc_pairs)
| [
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"%",
"non_matching_f_reads",
")",
"return",
"(",
"pairs",
",",
"bc_pairs",
")"
] | get the list of callback/errback pairs from the user . | train | false |
1,537 | def _json_decode_datetime(d):
return datetime.datetime.strptime(d['isostr'], _DATETIME_FORMAT)
| [
"def",
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"(",
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"strptime",
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"d",
"[",
"'isostr'",
"]",
",",
"_DATETIME_FORMAT",
")"
] | converts a dict of json primitives to a datetime object . | train | false |
1,538 | def solow_jacobian(t, k, g, n, s, alpha, delta):
jac = (((s * alpha) * (k ** (alpha - 1))) - ((g + n) + delta))
return jac
| [
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] | jacobian matrix for the solow model . | train | false |
1,540 | def _get_all_permissions(opts):
builtin = _get_builtin_permissions(opts)
custom = list(opts.permissions)
return (builtin + custom)
| [
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] | returns for all permissions in the given opts . | train | false |
1,541 | def no_setting_conf_directly_in_tests(logical_line, filename):
if ('nova/tests/' in filename):
res = conf_attribute_set_re.match(logical_line)
if res:
(yield (0, 'N320: Setting CONF.* attributes directly in tests is forbidden. Use self.flags(option=value) instead'))
| [
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")",
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] | check for setting conf . | train | false |
1,542 | def prespi_AccountBroker_initialize(self, conn, put_timestamp, **kwargs):
if (not self.account):
raise ValueError('Attempting to create a new database with no account set')
self.create_container_table(conn)
self.create_account_stat_table(conn, put_timestamp)
| [
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] | the accountbroker initialze() function before we added the policy stat table . | train | false |
1,543 | def stats_aggregate():
return s3_rest_controller()
| [
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"stats_aggregate",
"(",
")",
":",
"return",
"s3_rest_controller",
"(",
")"
] | restful crud controller . | train | false |
1,544 | def numeric_mixing_matrix(G, attribute, nodes=None, normalized=True):
d = attribute_mixing_dict(G, attribute, nodes)
s = set(d.keys())
for (k, v) in d.items():
s.update(v.keys())
m = max(s)
mapping = dict(zip(range((m + 1)), range((m + 1))))
a = dict_to_numpy_array(d, mapping=mapping)
if normalized:
a = (a / a.sum())
return a
| [
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] | return numeric mixing matrix for attribute . | train | false |
1,545 | def _write_proxy_conf(proxyfile):
msg = 'Invalid value for proxy file provided!, Supplied value = {0}'.format(proxyfile)
log.trace('Salt Proxy Module: write proxy conf')
if proxyfile:
log.debug('Writing proxy conf file')
with salt.utils.fopen(proxyfile, 'w') as proxy_conf:
proxy_conf.write('master = {0}'.format(__grains__['master']))
msg = 'Wrote proxy file {0}'.format(proxyfile)
log.debug(msg)
return msg
| [
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"(",
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] | write to file . | train | true |
1,547 | def _get_config_errors(request, cache=True):
global _CONFIG_ERROR_LIST
if ((not cache) or (_CONFIG_ERROR_LIST is None)):
error_list = []
for module in appmanager.DESKTOP_MODULES:
try:
validator = getattr(module.conf, CONFIG_VALIDATOR)
except AttributeError:
continue
if (not callable(validator)):
LOG.warn(('Auto config validation: %s.%s is not a function' % (module.conf.__name__, CONFIG_VALIDATOR)))
continue
try:
for (confvar, error) in validator(request.user):
error = {'name': (confvar if isinstance(confvar, str) else confvar.get_fully_qualifying_key()), 'message': error}
if isinstance(confvar, BoundConfig):
error['value'] = confvar.get()
error_list.append(error)
except Exception as ex:
LOG.exception(('Error in config validation by %s: %s' % (module.nice_name, ex)))
_CONFIG_ERROR_LIST = error_list
return _CONFIG_ERROR_LIST
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"_CONFIG_ERROR_LIST"
] | returns a list of tuples . | train | false |
1,548 | def find_room(name, api_url=None, api_key=None, api_version=None):
rooms = list_rooms(api_url=api_url, api_key=api_key, api_version=api_version)
if rooms:
for x in range(0, len(rooms)):
if (rooms[x]['name'] == name):
return rooms[x]
return False
| [
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] | find a room by name and return it . | train | false |
1,549 | def _get_object(obj_ref):
return _db_content[obj_ref.type][obj_ref]
| [
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"]"
] | helper function to retrieve objtype from pillars if objname is string_types . | train | false |
1,551 | def country_codes():
create_country_codes()
try:
country_codes = tk.get_action('tag_list')(data_dict={'vocabulary_id': 'country_codes'})
return country_codes
except tk.ObjectNotFound:
return None
| [
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] | return the list of country codes from the country codes vocabulary . | train | false |
1,552 | def reset_orig():
mpl.rcParams.update(_orig_rc_params)
| [
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":",
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".",
"rcParams",
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")"
] | restore all rc params to original settings . | train | false |
1,554 | def run_network(filename, n, eta):
random.seed(12345678)
np.random.seed(12345678)
(training_data, validation_data, test_data) = mnist_loader.load_data_wrapper()
net = network2.Network([784, n, 10], cost=network2.CrossEntropyCost)
print 'Train the network using the default starting weights.'
(default_vc, default_va, default_tc, default_ta) = net.SGD(training_data, 30, 10, eta, lmbda=5.0, evaluation_data=validation_data, monitor_evaluation_accuracy=True)
print 'Train the network using the large starting weights.'
net.large_weight_initializer()
(large_vc, large_va, large_tc, large_ta) = net.SGD(training_data, 30, 10, eta, lmbda=5.0, evaluation_data=validation_data, monitor_evaluation_accuracy=True)
f = open(filename, 'w')
json.dump({'default_weight_initialization': [default_vc, default_va, default_tc, default_ta], 'large_weight_initialization': [large_vc, large_va, large_tc, large_ta]}, f)
f.close()
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] | train the network for num_epochs on training_set_size images . | train | false |
1,556 | def barycenter_kneighbors_graph(X, n_neighbors, reg=0.001, n_jobs=1):
knn = NearestNeighbors((n_neighbors + 1), n_jobs=n_jobs).fit(X)
X = knn._fit_X
n_samples = X.shape[0]
ind = knn.kneighbors(X, return_distance=False)[:, 1:]
data = barycenter_weights(X, X[ind], reg=reg)
indptr = np.arange(0, ((n_samples * n_neighbors) + 1), n_neighbors)
return csr_matrix((data.ravel(), ind.ravel(), indptr), shape=(n_samples, n_samples))
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1,557 | def staticfile(filename, root=None, match='', content_types=None, debug=False):
request = cherrypy.serving.request
if (request.method not in ('GET', 'HEAD')):
if debug:
cherrypy.log('request.method not GET or HEAD', 'TOOLS.STATICFILE')
return False
if (match and (not re.search(match, request.path_info))):
if debug:
cherrypy.log(('request.path_info %r does not match pattern %r' % (request.path_info, match)), 'TOOLS.STATICFILE')
return False
if (not os.path.isabs(filename)):
if (not root):
msg = ("Static tool requires an absolute filename (got '%s')." % filename)
if debug:
cherrypy.log(msg, 'TOOLS.STATICFILE')
raise ValueError(msg)
filename = os.path.join(root, filename)
return _attempt(filename, content_types, debug=debug)
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1,558 | @with_setup(prepare_stdout, registry.clear)
def test_xunit_xml_output_with_no_errors():
called = []
def assert_correct_xml_output(filename, doc):
called.append(True)
expect(doc.toxml).when.called.doesnt.throw(UnicodeDecodeError)
old = xunit_output.write_xml_doc
xunit_output.write_xml_doc = assert_correct_xml_output
runner = Runner(feature_name('xunit_unicode_and_bytestring_mixing'), enable_xunit=True)
try:
runner.run()
finally:
xunit_output.write_xml_doc = old
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] | test xunit doc xml output . | train | false |
1,559 | def showHttpErrorCodes():
if kb.httpErrorCodes:
warnMsg = 'HTTP error codes detected during run:\n'
warnMsg += ', '.join((('%d (%s) - %d times' % (code, (httplib.responses[code] if (code in httplib.responses) else '?'), count)) for (code, count) in kb.httpErrorCodes.items()))
logger.warn(warnMsg)
if any((((str(_).startswith('4') or str(_).startswith('5')) and (_ != httplib.INTERNAL_SERVER_ERROR) and (_ != kb.originalCode)) for _ in kb.httpErrorCodes.keys())):
msg = 'too many 4xx and/or 5xx HTTP error codes '
msg += 'could mean that some kind of protection is involved (e.g. WAF)'
logger.debug(msg)
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] | shows all http error codes raised till now . | train | false |
1,560 | def _imgLink(col, latex, model):
txt = _latexFromHtml(col, latex)
fname = ('latex-%s.png' % checksum(txt.encode('utf8')))
link = ('<img class=latex src="%s">' % fname)
if os.path.exists(fname):
return link
elif (not build):
return ('[latex]%s[/latex]' % latex)
else:
err = _buildImg(col, txt, fname, model)
if err:
return err
else:
return link
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] | return an img link for latex . | train | false |
1,561 | def get_concept_classified():
ct._write_head()
df = _get_type_data((ct.SINA_CONCEPTS_INDEX_URL % (ct.P_TYPE['http'], ct.DOMAINS['sf'], ct.PAGES['cpt'])))
data = []
for row in df.values:
rowDf = _get_detail(row[0])
rowDf['c_name'] = row[1]
data.append(rowDf)
data = pd.concat(data, ignore_index=True)
return data
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] | return dataframe code :股票代码 name :股票名称 c_name :概念名称 . | train | false |
1,562 | def assert_equal_in(logical_line):
res = (asse_equal_in_start_with_true_or_false_re.search(logical_line) or asse_equal_in_end_with_true_or_false_re.search(logical_line))
if res:
(yield (0, 'N338: Use assertIn/NotIn(A, B) rather than assertEqual(A in B, True/False) when checking collection contents.'))
| [
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] | check for assertequal . | train | false |
1,565 | def getUnpackedLoops(loops):
if (len(loops) == 1):
firstLoop = loops[0]
if (firstLoop.__class__ == list):
return firstLoop
return loops
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1,566 | def p_assignment_operator(t):
pass
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] | assignment_operator : equals | timesequal | divequal | modequal | plusequal | minusequal | lshiftequal | rshiftequal | andequal | orequal | xorequal . | train | false |
1,569 | @verbose
def tfr_stockwell(inst, fmin=None, fmax=None, n_fft=None, width=1.0, decim=1, return_itc=False, n_jobs=1, verbose=None):
data = _get_data(inst, return_itc)
picks = pick_types(inst.info, meg=True, eeg=True)
info = pick_info(inst.info, picks)
data = data[:, picks, :]
n_jobs = check_n_jobs(n_jobs)
(power, itc, freqs) = _induced_power_stockwell(data, sfreq=info['sfreq'], fmin=fmin, fmax=fmax, n_fft=n_fft, width=width, decim=decim, return_itc=return_itc, n_jobs=n_jobs)
times = inst.times[::decim].copy()
nave = len(data)
out = AverageTFR(info, power, times, freqs, nave, method='stockwell-power')
if return_itc:
out = (out, AverageTFR(deepcopy(info), itc, times.copy(), freqs.copy(), nave, method='stockwell-itc'))
return out
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1,570 | def _prepare_report_dir(dir_name):
dir_name.rmtree_p()
dir_name.mkdir_p()
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] | sets a given directory to a created . | train | false |
1,572 | def build_user_vars(registry, xml_parent, data):
XML.SubElement(xml_parent, 'org.jenkinsci.plugins.builduser.BuildUser')
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] | yaml: build-user-vars set environment variables to the value of the user that started the build . | train | false |
1,573 | def sum_expr(operators):
return lo.LinOp(lo.SUM, operators[0].size, operators, None)
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1,574 | def _get_service_endpoint(context, svc, region=None, public=True):
region = _safe_region(region)
context = (context or identity)
url_type = {True: 'public', False: 'private'}[public]
svc_obj = context.services.get(svc)
if (not svc_obj):
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ep = svc_obj.endpoints.get(region, {}).get(url_type)
if (not ep):
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return ep
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"get",
"(",
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")",
"return",
"ep"
] | parses the services dict to get the proper endpoint for the given service . | train | true |
1,575 | def examplesfullTest(vm, prompt=Prompt):
installPexpect(vm, prompt)
vm.sendline('sudo -n python ~/mininet/examples/test/runner.py -v')
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] | full test of mininet examples . | train | false |
1,577 | @testing.requires_testing_data
def test_dipole_fitting_ctf():
raw_ctf = read_raw_ctf(fname_ctf).set_eeg_reference()
events = make_fixed_length_events(raw_ctf, 1)
evoked = Epochs(raw_ctf, events, 1, 0, 0, baseline=None).average()
cov = make_ad_hoc_cov(evoked.info)
sphere = make_sphere_model((0.0, 0.0, 0.0))
fit_dipole(evoked, cov, sphere)
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1,579 | def release():
return uname()[2]
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] | version should be a string like 0 . | train | false |
1,580 | def net_if_addrs():
has_enums = (sys.version_info >= (3, 4))
if has_enums:
import socket
rawlist = _psplatform.net_if_addrs()
rawlist.sort(key=(lambda x: x[1]))
ret = collections.defaultdict(list)
for (name, fam, addr, mask, broadcast, ptp) in rawlist:
if has_enums:
try:
fam = socket.AddressFamily(fam)
except ValueError:
if (WINDOWS and (fam == (-1))):
fam = _psplatform.AF_LINK
elif (hasattr(_psplatform, 'AF_LINK') and (_psplatform.AF_LINK == fam)):
fam = _psplatform.AF_LINK
if (fam == _psplatform.AF_LINK):
separator = (':' if POSIX else '-')
while (addr.count(separator) < 5):
addr += ('%s00' % separator)
ret[name].append(_common.snic(fam, addr, mask, broadcast, ptp))
return dict(ret)
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] | return the addresses associated to each nic installed on the system as a dictionary whose keys are the nic names and value is a list of namedtuples for each address assigned to the nic . | train | false |
1,582 | def testCount():
deleteMatches()
deletePlayers()
c = countPlayers()
if (c == '0'):
raise TypeError("countPlayers should return numeric zero, not string '0'.")
if (c != 0):
raise ValueError('After deletion, countPlayers should return zero.')
print '1. countPlayers() returns 0 after initial deletePlayers() execution.'
registerPlayer('Chandra Nalaar')
c = countPlayers()
if (c != 1):
raise ValueError('After one player registers, countPlayers() should be 1. Got {c}'.format(c=c))
print '2. countPlayers() returns 1 after one player is registered.'
registerPlayer('Jace Beleren')
c = countPlayers()
if (c != 2):
raise ValueError('After two players register, countPlayers() should be 2. Got {c}'.format(c=c))
print '3. countPlayers() returns 2 after two players are registered.'
deletePlayers()
c = countPlayers()
if (c != 0):
raise ValueError('After deletion, countPlayers should return zero.')
print '4. countPlayers() returns zero after registered players are deleted.\n5. Player records successfully deleted.'
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] | test for initial player count . | train | false |
1,583 | def get_collectors_from_module(mod):
for attrname in dir(mod):
attr = getattr(mod, attrname)
if (inspect.isclass(attr) and issubclass(attr, Collector) and (attr != Collector)):
if attrname.startswith('parent_'):
continue
fqcn = '.'.join([mod.__name__, attrname])
try:
cls = load_dynamic_class(fqcn, Collector)
(yield (cls.__name__, cls))
except Exception:
logger.error('Failed to load Collector: %s. %s', fqcn, traceback.format_exc())
continue
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] | locate all of the collector classes within a given module . | train | true |
1,584 | def Instance2Str(o, d):
if d.has_key(o.__class__):
return d[o.__class__](o, d)
cl = filter((lambda x, o=o: ((type(x) is types.ClassType) and isinstance(o, x))), d.keys())
if ((not cl) and hasattr(types, 'ObjectType')):
cl = filter((lambda x, o=o: ((type(x) is types.TypeType) and isinstance(o, x) and (d[x] is not Instance2Str))), d.keys())
if (not cl):
return d[types.StringType](o, d)
d[o.__class__] = d[cl[0]]
return d[cl[0]](o, d)
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"[",
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"]",
"]",
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1,586 | def search_by_build_id(hex_encoded_id):
cache = ((cache_dir + '-libc.so.') + hex_encoded_id)
if (os.path.exists(cache) and read(cache).startswith('\x7fELF')):
log.info_once(('Using cached data from %r' % cache))
return cache
log.info('Downloading data from GitHub')
url_base = 'https://gitlab.com/libcdb/libcdb/raw/master/hashes/build_id/'
url = urlparse.urljoin(url_base, hex_encoded_id)
data = ''
while (not data.startswith('\x7fELF')):
data = wget(url)
if (not data):
return None
if data.startswith('..'):
url = (os.path.dirname(url) + '/')
url = urlparse.urljoin(url, data)
write(cache, data)
return cache
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1,587 | def strtotuple(s):
if (not match('^[,.0-9 ()\\[\\]]*$', s)):
raise Exception('Invalid characters in string for tuple conversion')
if (s.count('(') != s.count(')')):
raise Exception('Invalid count of ( and )')
if (s.count('[') != s.count(']')):
raise Exception('Invalid count of [ and ]')
r = eval(s)
if (type(r) not in (list, tuple)):
raise Exception('Conversion failed')
return r
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] | convert a tuple string into a tuple with some security checks . | train | false |
1,588 | def decodeName(name):
decodedName = name
hexNumbers = re.findall('#([0-9a-f]{2})', name, (re.DOTALL | re.IGNORECASE))
for hexNumber in hexNumbers:
try:
decodedName = decodedName.replace(('#' + hexNumber), chr(int(hexNumber, 16)))
except:
return ((-1), 'Error decoding name')
return (0, decodedName)
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1,589 | def RtlGetVersion(os_version_info_struct):
rc = ctypes.windll.Ntdll.RtlGetVersion(ctypes.byref(os_version_info_struct))
if (rc != 0):
raise exceptions.WindowsError('Getting Windows version failed.')
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1,590 | def parameter_banks(device, device_dict=DEVICE_DICT):
if (device != None):
if (device.class_name in device_dict.keys()):
def names_to_params(bank):
return map(partial(get_parameter_by_name, device), bank)
return map(names_to_params, device_dict[device.class_name])
else:
if (device.class_name in MAX_DEVICES):
try:
banks = device.get_bank_count()
except:
banks = 0
if (banks != 0):
def _bank_parameters(bank_index):
try:
parameter_indices = device.get_bank_parameters(bank_index)
except:
parameter_indices = []
if (len(parameter_indices) != 8):
return [None for i in range(0, 8)]
else:
return [(device.parameters[i] if (i != (-1)) else None) for i in parameter_indices]
return map(_bank_parameters, range(0, banks))
return group(device_parameters_to_map(device), 8)
return []
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] | determine the parameters to use for a device . | train | false |
1,591 | def OpenQuickFixList(focus=False, autoclose=False):
vim.command(u'botright copen')
SetFittingHeightForCurrentWindow()
if autoclose:
vim.command(u'au WinLeave <buffer> q')
if VariableExists(u'#User#YcmQuickFixOpened'):
vim.command(u'doautocmd User YcmQuickFixOpened')
if (not focus):
JumpToPreviousWindow()
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1,592 | def _extract_nested_case(case_node, stmts_list):
if isinstance(case_node.stmts[0], (c_ast.Case, c_ast.Default)):
stmts_list.append(case_node.stmts.pop())
_extract_nested_case(stmts_list[(-1)], stmts_list)
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1,595 | def summarize_exit_codes(exit_codes):
for ec in exit_codes:
if (ec != 0):
return ec
return 0
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1,596 | def disable_key(key_id, region=None, key=None, keyid=None, profile=None):
conn = _get_conn(region=region, key=key, keyid=keyid, profile=profile)
r = {}
try:
key = conn.disable_key(key_id)
r['result'] = True
except boto.exception.BotoServerError as e:
r['result'] = False
r['error'] = __utils__['boto.get_error'](e)
return r
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] | mark key as disabled . | train | true |
1,597 | def get_drone(hostname):
if (hostname == 'localhost'):
return _LocalDrone()
try:
return _RemoteDrone(hostname)
except DroneUnreachable:
return None
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] | use this factory method to get drone objects . | train | false |
1,599 | def manage_accessed(wrapped):
def accessed(session, *arg, **kw):
session.accessed = now = int(time.time())
if (session._reissue_time is not None):
if ((now - session.renewed) > session._reissue_time):
session.changed()
return wrapped(session, *arg, **kw)
accessed.__doc__ = wrapped.__doc__
return accessed
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1,600 | def get_legal(state):
feature = np.zeros((1, state.size, state.size))
for (x, y) in state.get_legal_moves():
feature[(0, x, y)] = 1
return feature
| [
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] | zero at all illegal moves . | train | false |
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