Skip to main content

How do I turn an unformatted text file list into a python list in another file?

I've created a text file that just has an unformatted list of emails, all on a new line. Ex:

This is the unformatted list called emailListTest.txt

a@a.org
b@b.org
c@c.org
d@d.org
e@e.org
f@f.org
g@g.org
h@h.org

I have another app that opens and reads the unformatted email list file. Then it creates a new python file and tries to put the unformatted list of emails all in a python list.

This all started because I wanted to learn how to send emails with code. I've made another app that does this, but I wanted one that sends emails to multiple people at the same time.

This is my writer app

emailListFile = open("emailListTest.txt", "r")
emailListFileList = open("emailListTestList.py","w")


print(emailListFileList.write("emailAsList = "))
print(emailListFileList.write("["))

def emailAddressList():
    #try:
    for i in emailListFile:
        print(emailListFileList.write( "\n'" + i + "'" + ", "))


emailAddressList()

print(emailListFileList.write("]"))



emailListFile.close()
emailListFileList.close()

I must be missing something because the output is

emailAsList = [
'a@a.org
', 
'b@b.org
', 
'c@c.org
', 
'd@d.org
', 
'e@e.org
', 
'f@f.org
', 
'g@g.org
', 
'h@h.org', ]

I feel like it's so close to being right, if only there weren't these new lines from the unformatted list file splitting the ', onto a new line.

If anyone knows how to solve my issue, I'd greatly appreciate it! (Also, if anyone has any other tips to simplify other parts in my code, I'd love to know. I'm still learning!)

Thank you!



source https://stackoverflow.com/questions/75584456/how-do-i-turn-an-unformatted-text-file-list-into-a-python-list-in-another-file

Comments

Popular posts from this blog

ValueError: X has 10 features, but LinearRegression is expecting 1 features as input

So, I am trying to predict the model but its throwing error like it has 10 features but it expacts only 1. So I am confused can anyone help me with it? more importantly its not working for me when my friend runs it. It works perfectly fine dose anyone know the reason about it? cv = KFold(n_splits = 10) all_loss = [] for i in range(9): # 1st for loop over polynomial orders poly_order = i X_train = make_polynomial(x, poly_order) loss_at_order = [] # initiate a set to collect loss for CV for train_index, test_index in cv.split(X_train): print('TRAIN:', train_index, 'TEST:', test_index) X_train_cv, X_test_cv = X_train[train_index], X_test[test_index] t_train_cv, t_test_cv = t[train_index], t[test_index] reg.fit(X_train_cv, t_train_cv) loss_at_order.append(np.mean((t_test_cv - reg.predict(X_test_cv))**2)) # collect loss at fold all_loss.append(np.mean(loss_at_order)) # collect loss at order plt.plot(np.log(al...

Sorting large arrays of big numeric stings

I was solving bigSorting() problem from hackerrank: Consider an array of numeric strings where each string is a positive number with anywhere from to digits. Sort the array's elements in non-decreasing, or ascending order of their integer values and return the sorted array. I know it works as follows: def bigSorting(unsorted): return sorted(unsorted, key=int) But I didnt guess this approach earlier. Initially I tried below: def bigSorting(unsorted): int_unsorted = [int(i) for i in unsorted] int_sorted = sorted(int_unsorted) return [str(i) for i in int_sorted] However, for some of the test cases, it was showing time limit exceeded. Why is it so? PS: I dont know exactly what those test cases were as hacker rank does not reveal all test cases. source https://stackoverflow.com/questions/73007397/sorting-large-arrays-of-big-numeric-stings

How to load Javascript with imported modules?

I am trying to import modules from tensorflowjs, and below is my code. test.html <!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <title>Document</title </head> <body> <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@2.0.0/dist/tf.min.js"></script> <script type="module" src="./test.js"></script> </body> </html> test.js import * as tf from "./node_modules/@tensorflow/tfjs"; import {loadGraphModel} from "./node_modules/@tensorflow/tfjs-converter"; const MODEL_URL = './model.json'; const model = await loadGraphModel(MODEL_URL); const cat = document.getElementById('cat'); model.execute(tf.browser.fromPixels(cat)); Besides, I run the server using python -m http.server in my command prompt(Windows 10), and this is the error prompt in the console log of my browser: Failed to loa...