Skip to main content

python re extract smallest substring between two strings [duplicate]

Sorry in advance for a potentially duplicate question, I'm somewhat new to re and can't find an answer

I have a string something like this:

<foo><bar><biz><Baz><buz>Extract Me!</span><foo><bar>

I want to extract Extract Me!, which is between a > and the only </span> that appears in the string. I tried >(.*)</span>, but that extracts ><bar><biz><Baz><buz>Extract Me!</span>.

Edit:

1:

This question got closed, linking to this as a duplicate, but making the regular expression >(.*)</span> "non greedy" by turning it into >(.*?)</span> yields the same result. I had already attempted this before posting.

2:

After some discussions, I was recommended to just use BeautifulSoup, which makes sense. I've solved the issue with re.search(r'(?:>)(\b.*)(<\/span>)', but I'll provide a bit more code so further exploration can be done.

So:

Unveiling the curtain a bit, this is the pseudo code of what I'm working with:

src = selenium_driver.page_source
soup = BeautifulSoup(src) 
list_of_things = soup.findAll(True, {'class':['list of classes']})
for thing in list_of_things:
  print(type(thing))
  print(thing)
  extract_extractMe() # <- do stuff

The result of print(type(thing)) and print(thing) would be something like this:

#type
<class 'bs4.element.Tag'>

#thing
<li class="property-item"><div class="property-text"><span data-spm-anchor-id="a2g0o.detail.1000016.i2.11ab42d1npvRCb">14CM</span></div></li>

I'm trying to extract 14CM from each "thing"



source https://stackoverflow.com/questions/74892989/python-re-extract-smallest-substring-between-two-strings

Labels

Labels:

Comments

Post a Comment

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...
Post a Comment
Read more

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
Post a Comment
Read more

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...
Post a Comment
Read more