Yes, you can use a regular expression for this:

import re
output = re.sub(r'\d+', '', '123hello 456world')
print output  # 'hello world'

Try something like below:

import string
import re
import nltk
from nltk.tokenize import TweetTokenizer

tweet = "first think another Disney movie, might good, it's kids movie. watch it, can't help enjoy it. ages love movie. first saw movie 10 8 years later still love it! Danny Glover superb could play"

def clean_text(text):
    # remove numbers
    text_nonum = re.sub(r'\d+', '', text)
    # remove punctuations and convert characters to lower case
    text_nopunct = "".join([char.lower() for char in text_nonum if char not in string.punctuation]) 
    # substitute multiple whitespace with single whitespace
    # Also, removes leading and trailing whitespaces
    text_no_doublespace = re.sub('\s+', ' ', text_nopunct).strip()
    return text_no_doublespace

cleaned_tweet = clean_text(tweet)
tt = TweetTokenizer()
print(tt.tokenize(cleaned_tweet))

output:

['first', 'think', 'another', 'disney', 'movie', 'might', 'good', 'its', 'kids', 'movie', 'watch', 'it', 'cant', 'help', 'enjoy', 'it', 'ages', 'love', 'movie', 'first', 'saw', 'movie', 'years', 'later', 'still', 'love', 'it', 'danny', 'glover', 'superb', 'could', 'play']

Add a space before the \d+.

>>> s = "This must not b3 delet3d, but the number at the end yes 134411"
>>> s = re.sub(" \d+", " ", s)
>>> s
'This must not b3 delet3d, but the number at the end yes '

Edit: After looking at the comments, I decided to form a more complete answer. I think this accounts for all the cases.

s = re.sub("^\d+\s|\s\d+\s|\s\d+$", " ", s)

Would this work for your situation?

>>> s = '12abcd405'
>>> result = ''.join([i for i in s if not i.isdigit()])
>>> result
'abcd'

This makes use of a list comprehension, and what is happening here is similar to this structure:

no_digits = []
# Iterate through the string, adding non-numbers to the no_digits list
for i in s:
    if not i.isdigit():
        no_digits.append(i)

# Now join all elements of the list with '', 
# which puts all of the characters together.
result = ''.join(no_digits)

As @AshwiniChaudhary and @KirkStrauser point out, you actually do not need to use the brackets in the one-liner, making the piece inside the parentheses a generator expression (more efficient than a list comprehension). Even if this doesn't fit the requirements for your assignment, it is something you should read about eventually :) :

>>> s = '12abcd405'
>>> result = ''.join(i for i in s if not i.isdigit())
>>> result
'abcd'

Change

for word in word_list:
    word = punctuation.sub("", word)

to

word_list = [punctuation.sub("", word) for word in word_list]    

Assignment to word in the for-loop above, simply changes the value referenced by this temporary variable. It does not alter word_list.

>>> import re
>>> re.sub("[^0-9]", "", "sdkjh987978asd098as0980a98sd")
'987978098098098'
>>> # or
>>> re.sub(r"\D", "", "sdkjh987978asd098as0980a98sd")
'987978098098098'

Take a look at the other tokenizing options that nltk provides here. For example, you can define a tokenizer that picks out sequences of alphanumeric characters as tokens and drops everything else:

from nltk.tokenize import RegexpTokenizer

tokenizer = RegexpTokenizer(r'\w+')
tokenizer.tokenize('Eighty-seven miles to go, yet.  Onward!')

Output:

['Eighty', 'seven', 'miles', 'to', 'go', 'yet', 'Onward']

to do exactly what you ask, you can use a regular expression, eg:

import re

phrase="Boeing777 is very fast because it can goes to 950 kms/hours"

print re.sub(r'\s\d+\s', ' ', phrase)

which replaces any pattern of whitespace (\s) surrounding one or more (+) digits (\d) with the string ' '.

depending on how sophisticated you want this to be you can improve on that regex.

for example you might want to consider what you want to do about the phrase

phrase="Boeing777 is very fast. it's top speed is 950."

because 950 is followed there by a . you would need a different regex. this is what I thought of in a quick look:

re.sub(r'(?<=\s)(\d+)(?=\s|\.|,|$)', '', phrase)

this checks for whitespace before, and for whitespace, period or comma after, but obviously there is still room for improvement. Not knowing your actual requirements I am going to leave that with you.