I am trying to read an Excel file in which I have written my expenses, and to plot the evolution of these expenses by smooth curves in a Matplotlib plot. I tried with different headers parameters but I don't think that's the problem! Response = requests.request("POST", url, headers=headers, data=body)īut the request is blocking at the requests.request command and doing nothing. Order, created = _or_create(customer=customer, complete=False) (it is being imported to views.py and then rendered to the store.html template): def cartData(request): ![]() Zipcode = models.CharField(max_length=200, null=False)ĭate_added = models.DateTimeField(auto_now_add=True) State = models.CharField(max_length=200, null=False) Total = * self.quantityĬustomer = models.ForeignKey(Customer, on_delete=models.SET_NULL, null=True)Īddress = models.CharField(max_length=200, null=False)Ĭity = models.CharField(max_length=200, null=False) Quantity = models.IntegerField(default=0, null=True, blank=True) Order = models.ForeignKey(Order, on_delete=models.SET_NULL, null=True) Product = models.ForeignKey(Product, on_delete=models.SET_NULL, null=True) Transaction_id = models.CharField(max_length=100, null=True) Image = models.ImageField(null=True, blank=True)Ĭustomer = models.ForeignKey(Customer, on_delete=models.SET_NULL, null=True, blank=True)ĭate_ordered = models.DateTimeField(auto_now_add=True)Ĭomplete = models.BooleanField(default=False, null=True, blank=True) Price = models.DecimalField(max_digits=7, decimal_places=2)ĭigital = models.BooleanField(default=False,null=True, blank=True) """String for representing a model object""" Name = models.CharField(max_length=200, null=True) User = models.OneToOneField(User, null=True, blank=True, on_delete=models.CASCADE) How can I integrate this new registered users to have this customer instance so they can be redirected to the store page? or give a condition where not all users must have a customer instance. The new registered users does not have this customer instance I guess, reason I'm getting the User has no customer RelatedObjectDoesNotExist. In the users app, new users are to register, logged in and be redirected to the store page(store.html). Non logged in users can as well add to cart. Ecommerce app has situation where logged in users are expected to be customers and they can add to cart. In a Django project, i have two apps ecommerce and users. ![]() I am using sympy and numpy to solve the following the problem:Given a point (x0, y0) and a curve yax2 bx c, compute the minimal distances of (x0, y0) to (x,y). The dataset is about 50,000 article in blog. /private/tmp/statsmodels/statsmodels/stats/outliersinfluence.py:309: RuntimeWarning: invalid value encountered in sqrt return / sigma. python - sympy lambdify RuntimeWarning: invalid value encountered in doublescalars - Stack Overflow. This is the code: ldaseq = LdaSeqModel(corpus=corpus_comments, id2word=dictionary_comments,time_slice=time_docs, num_topics=5, chunksize=10,lda_model=model) \.conda\envs\pennylane\lib\site-packages\autograd\numpy\numpy_vjps.py:85: RuntimeWarning: invalid value encountered in double_scalarsĭefvjp(anp.arcsin, lambda ans, x : lambda g: g / anp.When using the ldaseqmodel in gensim, I got the running time warning:ĭ:\Anaconda3\lib\site-packages\gensim\models\ldaseqmodel.py:1474: RuntimeWarning: invalid value encountered in double_scalarsĬonverged = np.fabs((lhood_old - lhood) / (lhood_old * total))ĭ:\Anaconda3\lib\site-packages\gensim\models\ldaseqmodel.py:293: RuntimeWarning: divide by zero encountered in double_scalarsĬonvergence = np.fabs((bound - old_bound) / old_bound) Print("cost_fn(params):", cost_fn(params))Ĭonsole output: > python vqe_200_template.py \.conda\envs\pennylane\lib\site-packages\autograd\numpy\numpy_vjps.py:85: RuntimeWarning: divide by zero encountered in double_scalarsĭefvjp(anp.arcsin, lambda ans, x : lambda g: g / anp.sqrt(1 - x**2)) encountered in doublescalars /home/adam/anaconda/lib/python2.7/site-packages/IPython/kernel/main.py:6: RuntimeWarning: invalid value encountered in. Params = np.random.uniform(low=-100, high=100, size=(num_qubits)) The cost function and parameters are valid, but the optimiser output is not? I’m trying my hand at the QHack VQE problems, specifically vqe_200.īut the optimisers I’ve tried all keeps returning NaN, due to some division by zero.
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