Is there a way to make my code more effiecient Question: Hey so I’m a beginner and was just trying out projects to get better so I made a password checker. Just want to see if there is anyway I can make my code neater or more efficient to tips are nice. import re regex …
Pydantic root_validator – ok to use once for entire model, instead of individual validators? Question: I am using Pydantic to create a Timeseries model based on pandas Timestamp (start, end) and Timedelta (period) objects. The model will be used by a small data analysis program with a number of configurations/scenarios. I need to instantiate and …
Extracting contents from an XML file with BeautifulSoup on Python Question: I have an XML structure like this: <Trainers> <Trainer name="VisitorID" value=" NPRoiuKL213kiolkm2231"/> <Trainer name="VisitorNumber" value="BR-76594823-009922"/> <Trainer name="ServerIndex" value="213122"/> <Trainer name="VisitorPolicyID" value="ETR1234123"/> </Trainers> I want to extract the values based on the Trainer names. So basically something like this: NPRoiuKL213kiolkm2231 from the VisitorID , BR-76594823-009922 …
WARNING:tensorflow:Early stopping conditioned on metric `val_loss` which is not available. Available metrics are: loss,recall Question: I have the error in the title when running the code below: def create_model(learning_rate, dropout, l2_lambda): model = Sequential() model.add(Dense(128,input_dim=X_train.shape[1], activation=’relu’, kernel_regularizer=regularizers.l2(l2_lambda))) model.add(BatchNormalization()) model.add(Dropout(dropout)) model.add(Dense(64, activation=’relu’, kernel_regularizer=regularizers.l2(l2_lambda))) model.add(Dropout(dropout)) model.add(Dense(1, activation=’sigmoid’)) optimizer = Adam(learning_rate=learning_rate) model.compile(loss=’binary_crossentropy’, optimizer=optimizer, metrics=[‘Recall’]) return model early_stopping = …
Can not validate the AuthForm Question: I’m developing the Login view of my app, in order to do that I used the Django’s built-in authentication form, but when I try to validate the form it returns False and I don’t know why. I let here my code… models.py class User(AbstractUser): ”’ Model that represents a …
Split DBP15K from pytorch geometric in train test and validation Question: I have a code in which I use the DBP15K dataset via from torch_geometric.datasets import DBP15K data = DBP15K(path, args.category, transform=SumEmbedding())[0].to(device) But according to the documentation of pytorch geometric this one is divided only in train and in test. I tried to divide it …
Validate if a list has only None elements, strings that only have whitespaces or is empty Question: #examples: lista = [" ", None, None, "", " "] #print ‘yes!’ lista = [] #print ‘yes!’ lista = [" ", None, None, "", " s"] #print ‘no!’ lista = ["sun is bright", "aa", "Hello!"] #print ‘no!’ if …
How to limit the character in Entry Question: I need to limit the entry to a maximum of 5 digits. def validate(S): try: float(S) return True except ValueError: messagebox.showerror(message="Datos erroneos, únicamente números.", title="ERROR") return False e1 = tk.Entry(master, validate="key", validatecommand=(master.register(validate), ‘%S’)) I have this method to receive and validate that it’s just numbers at the …
output python dataframe to excel and create a new data_validation column in the exported excel sheet Question: context: i have a dataframe that i want to export into an excel workbook. i want the excel to have an additional column (that is not in the dataframe) that is a data validated column in the workbook …
How to display something after an Entry widget is filled in another area of the GUI? Question: I’m building a GUI to write to an excel spreadsheet. However, before I do the writing to spreadsheet, the user will input data in the GUI. What I want to do is when the user puts in a …
