code stringlengths 3 6.57k |
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test_update_bots_endpoint(setup_scopez_server_action) |
os.path.dirname(os.path.abspath(__file__) |
os.path.exists(l_test_file) |
open(l_test_file) |
l_tf.read() |
json.loads(l_test_payload) |
requests.get(l_uri, headers=l_headers) |
load_bots (compare time) |
datetime.datetime.now() |
strftime('%Y-%m-%dT%H:%M:%SZ') |
requests.post(l_url, timeout=3, json=l_json_payload) |
l_result.json() |
requests.get(l_uri, headers=l_headers) |
format(resp_code=l_r.status_code) |
requests.get(l_uri, headers=l_headers) |
format(resp_code=l_r.status_code) |
l_json_payload.pop('customer_id') |
requests.post(l_url, json=l_json_payload) |
format(l_cust_id) |
find_packages(exclude=["tests", "*.tests", "*.tests.*"]) |
ElanaspantryfeedSpider(BaseSpider, ElanaspantryMixin) |
parse(self, response) |
XmlXPathSelector(response) |
xxs.select("//item/*[local-name() |
text() |
extract() |
Request(x, callback=self.parse_item) |
Turno(models.Model) |
models.DateTimeField() |
models.DateTimeField(null=True, blank=True) |
models.IntegerField(default=1, blank=True) |
models.ForeignKey(Trabajador, blank=True) |
models.IntegerField(default=0) |
models.IntegerField(default=0, blank=True) |
models.IntegerField(default=0, blank=True) |
models.IntegerField(default=0, blank=True) |
monto_cierre_informado(self) |
estado_turno(self) |
save(self, force_insert=False, force_update=False) |
len(Turno.objects.exclude(id=self.id) |
filter(trabajador__id=self.trabajador.id) |
filter(estado=1) |
Exception(u"Usted ya cuenta con un turno abierto.") |
super(Turno, self) |
save(force_insert, force_update) |
BoletaDeposito(models.Model) |
models.OneToOneField(Turno, blank=True) |
models.PositiveIntegerField(default=0, blank=True) |
models.PositiveIntegerField(default=0, blank=True) |
models.PositiveIntegerField(default=0, blank=True) |
models.PositiveIntegerField(default=0, blank=True) |
models.PositiveIntegerField(default=0, blank=True) |
models.PositiveIntegerField(default=0, blank=True) |
models.PositiveIntegerField(default=0, blank=True) |
models.PositiveIntegerField(default=0, blank=True) |
models.PositiveIntegerField(default=0, blank=True) |
models.PositiveIntegerField(default=0, blank=True) |
models.PositiveIntegerField(default=0, blank=True) |
models.PositiveIntegerField(default=0, blank=True) |
Venta(models.Model) |
models.DateTimeField() |
models.PositiveIntegerField(null=True, blank=True) |
models.PositiveIntegerField() |
models.PositiveIntegerField() |
models.PositiveIntegerField() |
models.PositiveIntegerField() |
models.PositiveIntegerField() |
models.PositiveIntegerField(null=True) |
models.ForeignKey('Turno') |
__unicode__(self) |
LineaDetalle(models.Model) |
models.IntegerField() |
models.IntegerField() |
models.IntegerField() |
models.ForeignKey(Producto, null=True, blank=True) |
models.ForeignKey(Promocion, null=True, blank=True) |
models.ForeignKey('Venta') |
Train (basic) |
time.strftime("%Y-%b-%d-%H:%M:%S", time.gmtime() |
torch.device("cuda" if torch.cuda.is_available() |
torch.cuda.is_available() |
view(-1) |
torch.where(_labels > _labels.mean() |
Subset(dataset, sorted(high_idx) |
weights (each sample should get its own weight) |
torch.LongTensor(discretize(labels.tolist() |
sum() |
torch.arange(nbins) |
class_sample_count.float() |
torch.zeros_like(labels) |
torch.unique(bin_labels) |
WeightedRandomSampler(sample_weights, len(sample_weights) |
sampler(_labels, nbins=10, stratify=False) |
weights.type(torch.float) |
TensorDataset(*dataset[:].values() |
_labels.tolist() |
Subset(dataset, sorted(idx) |
zip(splits, subset_idx) |
sampler (only needed for training) |
sampler(stratified["train"][:][1].view(-1) |
Subsets and Splits
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