Develop Reference

How to extract words from repeating strings

Here I have a string in a list:
['aaaaaaappppppprrrrrriiiiiilll']
I want to get the word 'april' in the list, but not just one of them, instead how many times the word 'april' actually occurs the string.
The output should be something like:
['aprilaprilapril']
Because the word 'april' occurred three times in that string.
Well the word actually didn't occurred three times, all the characters did. So I want to order these characters to 'april' for how many times did they appeared in the string.
My idea is basically to extract words from some random strings, but not just extracting the word, instead to extract all of the word that appears in the string. Each word should be extracted and the word (characters) should be ordered the way I wanted to.
But here I have some annoying conditions; you can't delete all the elements in the list and then just replace them with the word 'april'(you can't replace the whole string with the word 'april'); you can only extract 'april' from the string, not replacing them. You can't also delete the list with the string. Just think of all the string there being very important data, we just want some data, but these data must be ordered, and we need to delete all other data that doesn't match our "data chain" (the word 'april'). But once you delete the whole string you will lose all the important data. You don't know how to make another one of these "data chains", so we can't just put the word 'april' back in the list.
If anyone know how to solve my weird problem, please help me out, I am a beginner python programmer. Thank you!

One way is to use itertools.groupby which will group the characters individually and unpack and iterate them using zip which will iterate n times given n is the number of characters in the smallest group (i.e. the group having lowest number of characters)
from itertools import groupby
'aaaaaaappppppprrrrrriiiiiilll'
result = ''
for each in zip(*[list(g) for k, g in groupby('aaaaaaappppppprrrrrriiiiiilll')]):
result += ''.join(each)
# result = 'aprilaprilapril'
Another possible solution is to create a custom counter that will count each unique sequence of characters (Please be noted that this method will work only for Python 3.6+, for lower version of Python, order of dictionaries is not guaranteed):
def getCounts(strng):
if not strng:
return [], 0
counts = {}
current = strng[0]
for c in strng:
if c in counts.keys():
if current==c:
counts[c] += 1
else:
current = c
counts[c] = 1
return counts.keys(), min(counts.values())
result = ''
counts=getCounts('aaaaaaappppppprrrrrriiiiiilll')
for i in range(counts[1]):
result += ''.join(counts[0])
# result = 'aprilaprilapril'

How about using regex?
import re
word = 'april'
text = 'aaaaaaappppppprrrrrriiiiiilll'
regex = "".join(f"({c}+)" for c in word)
match = re.match(regex, text)
if match:
# Find the lowest amount of character repeats
lowest_amount = min(len(g) for g in match.groups())
print(word * lowest_amount)
else:
print("no match")
Outputs:
aprilaprilapril
Works like a charm

Here is a more native approach, with plain iteration.
It has a time complexity of O(n).
It uses an outer loop to iterate over the character in the search key, then an inner while loop that consumes all occurrences of that character in the search string while maintaining a counter. Once all consecutive occurrences of the current letter have been consumes, it updates a the minLetterCount to be the minimum of its previous value or this new count. Once we have iterated over all letters in the key, we return this accumulated minimum.
def countCompleteSequenceOccurences(searchString, key):
left = 0
minLetterCount = 0
letterCount = 0
for i, searchChar in enumerate(key):
while left < len(searchString) and searchString[left] == searchChar:
letterCount += 1
left += 1
minLetterCount = letterCount if i == 0 else min(minLetterCount, letterCount)
letterCount = 0
return minLetterCount
Testing:
testCasesToOracles = {
"aaaaaaappppppprrrrrriiiiiilll": 3,
"ppppppprrrrrriiiiiilll": 0,
"aaaaaaappppppprrrrrriiiiii": 0,
"aaaaaaapppppppzzzrrrrrriiiiiilll": 0,
"pppppppaaaaaaarrrrrriiiiiilll": 0,
"zaaaaaaappppppprrrrrriiiiiilll": 3,
"zzzaaaaaaappppppprrrrrriiiiiilll": 3,
"aaaaaaappppppprrrrrriiiiiilllzzz": 3,
"zzzaaaaaaappppppprrrrrriiiiiilllzzz": 3,
}
key = "april"
for case, oracle in testCasesToOracles.items():
result = countCompleteSequenceOccurences(case, key)
assert result == oracle
Usage:
key = "april"
result = countCompleteSequenceOccurences("aaaaaaappppppprrrrrriiiiiilll", key)
print(result * key)
Output:
aprilaprilapril

A word will only occur as many times as the minimum letter recurrence. To account for the possibility of having repeated letters in the word (for example, appril, you need to factor this count out. Here is one way of doing this using collections.Counter:
from collections import Counter
def count_recurrence(kernel, string):
# we need to count both strings
kernel_counter = Counter(kernel)
string_counter = Counter(string)
# now get effective count by dividing the occurence in string by occurrence
# in kernel
effective_counter = {
k: int(string_counter.get(k, 0)/v)
for k, v in kernel_counter.items()
}
# min occurence of kernel is min of effective counter
min_recurring_count = min(effective_counter.values())
return kernel * min_recurring_count

Looking for matching strings of length > 4 between two text files

I'm trying to read in two text files, and then search each for strings that are common between the two, of minimum length 5.
The code I've written:
db = open("list_of_2","r").read()
lp = open("lastpass","r").read()
word = ''
length = 0
for dbchar in db:
for lpchar in lp:
if dbchar == lpchar:
word += str(dbchar)
length += 1
else:
length = 0
word = ''
if length > 4:
print(word)
The code currently prints strings like '-----' and '55555', over and over and doesn't seem to break the loop (these particular strings only appear in lp once). I also don't believe it's finding strings that aren't just the same character repeated.
How do I alter the code to:
Only make it run through and print each occurrence once, and
Not just find strings of the same character repeated?
Edit: Here are some mock text files. In these, the string 'ghtyty' appears in file1 three times, and in file2 4 times. The code should print 'ghtyty' to console once.
file1
file2

I would suggest a different approach. Split the files into words and keep only words 5 characters or greater. Use sets to find the intersection--this will be faster.
db_words = set([x for x in db.split() if len(x) > 4])
lp_words = set([x for x in lp.split() if len(x) > 4])
matches = db_words & lp_words
If you want to exclude words of all same character, you can define the list comprehension like this:
[x for x in db.split() if len(x) > 4 and x != x[0]*len(x)]
If you are looking for any consecutive sequence of characters that match, this might work better:
i_skip = set() # characters to skip if they are already in a printed word
j_skip = set()
for i in range(len(db)-4):
if i in i_skip: continue
for j in range(len(lp)-4):
if j in j_skip: continue
if db[i] == lp[j]:
word_len = 5
while db[i:i+word_len] == lp[j:j+word_len]:
if db[i:i+word_len+1] == lp[j:j+word_len+1]:
word_len += 1
else:
print(db[i:i+word_len])
i_skip.update(range(i, i+word_len))
j_skip.update(range(j, j+word_len))
break

compare specific string to a word python

say I have a certain string and a list of strings.
I would like to append to a new list all the words from the list (of strings)
that are exactly like the pattern
for example:
list of strings = ['string1','string2'...]
pattern =__letter__letter_ ('_c__ye_' for instance)
I need to add all strings that are made up of the same letters in the same places as the pattern, and has the same length.
so for instance:
new_list = ['aczxyep','zcisyef'...]
I have tried this:
def pattern_word_equality(words,pattern):
list1 = []
for word in words:
for letter in word:
if letter in pattern:
list1.append(word)
return list1
help will be much appreciated :)

If your pattern is as simple as _c__ye_, then you can look for the characters in the specific positions:
words = ['aczxyep', 'cxxye', 'zcisyef', 'abcdefg']
result1 = list(filter(lambda w: w[1] == 'c' and w[4:6] == 'ye', words))
If your pattern is getting more complex, then you can start using regular expressions:
pat = re.compile("^.c..ye.$")
result2 = list(filter(lambda w: pat.match(w), words))
Output:
print(result1) # ['aczxyep', 'zcisyef']
print(result2) # ['aczxyep', 'zcisyef']

This works:
words = ['aczxyep', 'cxxye', 'zcisyef', 'abcdefg']
pattern = []
for i in range(len(words)):
if (words[i])[1].lower() == 'c' and (words[i])[4:6].lower() == 'ye':
pattern.append(words[i])
print(pattern)
You start by defining the words and pattern lists. Then you loop around for the amount of items in words by using len(words). You then find whether the i item number is follows the pattern by seeing if the second letter is c and the 5th and 6th letters are y and e. If this is true then it appends that word onto pattern and it prints them all out at the end.

How to check if letters of one string are in another

I have a list L of words in alphabetical order, e.g hello = ehllo
how do I check for this words "blanagrams", which are words with mostly all similar letters except 1. For example, orchestra turns into orchestre. I've only been able to think to this part. I have an idea in which you have to test every letter of the current word and see whether this corresponds, to the other and if it does, it is a blanagram and create a dictionary, but i'm struggling to put it into code
L = [list of alphabetically ordered strings]
for word in L:
for letter in word:
#confused at this part

from collections import Counter
def same_except1(s1, s2):
ct1, ct2 = Counter(s1), Counter(s2)
return sum((ct1 - ct2).values()) == 1 and sum((ct2 - ct1).values()) == 1
Examples:
>>> same_except1('hello', 'hella')
True
>>> same_except1('hello', 'heela')
False
>>> same_except1('hello', 'hello')
False
>>> same_except1('hello', 'helloa')
False

Steven Rumbalski's answer got me thinking and there's also another way you can do this with a Counter (+1 for use of collections and thank you for sparking my interest)
from collections import Counter
def diff_one(w,z):
c=Counter(sorted(w+z)).values()
c=filter(lambda x:x%2!=0,c)
return len(c)==2
Basically all matched letters will have a counter value that will be even. So you filter those out and get left with the unmatched ones. If you have more than 2 unmatched then you have a problem.

Assuming this is similar to the part of the ladders game commonly used in AI, and you are trying to create a graph with adjacent nodes as possible words and not a dictionary.
d = {}
# create buckets of words that differ by one letter
for word in L:
for i in range(len(word)):
bucket = word[:i] + '_' + word[i+1:]
if bucket in d:
d[bucket].append(word)
else:
d[bucket] = [word]

10 ,most frequent words in a string Python

I need to display the 10 most frequent words in a text file, from the most frequent to the least as well as the number of times it has been used. I can't use the dictionary or counter function. So far I have this:
import urllib
cnt = 0
i=0
txtFile = urllib.urlopen("http://textfiles.com/etext/FICTION/alice30.txt")
uniques = []
for line in txtFile:
words = line.split()
for word in words:
if word not in uniques:
uniques.append(word)
for word in words:
while i<len(uniques):
i+=1
if word in uniques:
cnt += 1
print cnt
Now I think I should look for every word in the array 'uniques' and see how many times it is repeated in this file and then add that to another array that counts the instance of each word. But this is where I am stuck. I don't know how to proceed.
Any help would be appreciated. Thank you

The above problem can be easily done by using python collections
below is the Solution.
from collections import Counter
data_set = "Welcome to the world of Geeks " \
"This portal has been created to provide well written well" \
"thought and well explained solutions for selected questions " \
"If you like Geeks for Geeks and would like to contribute " \
"here is your chance You can write article and mail your article " \
" to contribute at geeksforgeeks org See your article appearing on " \
"the Geeks for Geeks main page and help thousands of other Geeks. " \
# split() returns list of all the words in the string
split_it = data_set.split()
# Pass the split_it list to instance of Counter class.
Counters_found = Counter(split_it)
#print(Counters)
# most_common() produces k frequently encountered
# input values and their respective counts.
most_occur = Counters_found.most_common(4)
print(most_occur)

You're on the right track. Note that this algorithm is quite slow because for each unique word, it iterates over all of the words. A much faster approach without hashing would involve building a trie.
# The following assumes that we already have alice30.txt on disk.
# Start by splitting the file into lowercase words.
words = open('alice30.txt').read().lower().split()
# Get the set of unique words.
uniques = []
for word in words:
if word not in uniques:
uniques.append(word)
# Make a list of (count, unique) tuples.
counts = []
for unique in uniques:
count = 0 # Initialize the count to zero.
for word in words: # Iterate over the words.
if word == unique: # Is this word equal to the current unique?
count += 1 # If so, increment the count
counts.append((count, unique))
counts.sort() # Sorting the list puts the lowest counts first.
counts.reverse() # Reverse it, putting the highest counts first.
# Print the ten words with the highest counts.
for i in range(min(10, len(counts))):
count, word = counts[i]
print('%s %d' % (word, count))

from string import punctuation #you will need it to strip the punctuation
import urllib
txtFile = urllib.urlopen("http://textfiles.com/etext/FICTION/alice30.txt")
counter = {}
for line in txtFile:
words = line.split()
for word in words:
k = word.strip(punctuation).lower() #the The or you You counted only once
# you still have words like I've, you're, Alice's
# you could change re to are, ve to have, etc...
if "'" in k:
ks = k.split("'")
else:
ks = [k,]
#now the tally
for k in ks:
counter[k] = counter.get(k, 0) + 1
#and sorting the counter by the value which holds the tally
for word in sorted(counter, key=lambda k: counter[k], reverse=True)[:10]:
print word, "\t", counter[word]

import urllib
import operator
txtFile = urllib.urlopen("http://textfiles.com/etext/FICTION/alice30.txt").readlines()
txtFile = " ".join(txtFile) # this with .readlines() replaces new lines with spaces
txtFile = "".join(char for char in txtFile if char.isalnum() or char.isspace()) # removes everything that's not alphanumeric or spaces.
word_counter = {}
for word in txtFile.split(" "): # split in every space.
if len(word) > 0 and word != '\r\n':
if word not in word_counter: # if 'word' not in word_counter, add it, and set value to 1
word_counter[word] = 1
else:
word_counter[word] += 1 # if 'word' already in word_counter, increment it by 1
for i,word in enumerate(sorted(word_counter,key=word_counter.get,reverse=True)[:10]):
# sorts the dict by the values, from top to botton, takes the 10 top items,
print "%s: %s - %s"%(i+1,word,word_counter[word])
output:
1: the - 1432
2: and - 734
3: to - 703
4: a - 579
5: of - 501
6: she - 466
7: it - 440
8: said - 434
9: I - 371
10: in - 338
This methods ensures that only alphanumeric and spaces are in the counter. Doesn't matter that much tho.

Personally I'd make my own implementation of collections.Counter. I assume you know how that object works, but if not I'll summarize:
text = "some words that are mostly different but are not all different not at all"
words = text.split()
resulting_count = collections.Counter(words)
# {'all': 2,
# 'are': 2,
# 'at': 1,
# 'but': 1,
# 'different': 2,
# 'mostly': 1,
# 'not': 2,
# 'some': 1,
# 'that': 1,
# 'words': 1}
We can certainly sort that based on frequency by using the key keyword argument of sorted, and return the first 10 items in that list. However that doesn't much help you because you don't have Counter implemented. I'll leave THAT part as an exercise for you, and show you how you might implement Counter as a function rather than an object.
def counter(iterable):
d = {}
for element in iterable:
if element in d:
d[element] += 1
else:
d[element] = 1
return d
Not difficult, actually. Go through each element of an iterable. If that element is NOT in d, add it to d with a value of 1. If it IS in d, increment that value. It's more easily expressed by:
def counter(iterable):
d = {}
for element in iterable:
d.setdefault(element, 0) += 1
Note that in your use case, you probably want to strip out the punctuation and possibly casefold the whole thing (so that someword gets counted the same as Someword rather than as two separate words). I'll leave that to you as well, but I will point out str.strip takes an argument as to what to strip out, and string.punctuation contains all the punctuation you're likely to need.

You can also do it through pandas dataframes and get result in convinient form as a table: "word-its freq." ordered.
def count_words(words_list):
words_df = pn.DataFrame(words_list)
words_df.columns = ["word"]
words_df_unique = pn.DataFrame(pn.unique(words_list))
words_df_unique.columns = ["unique"]
words_df_unique["count"] = 0
i = 0
for word in pn.Series.tolist(words_df_unique.unique):
words_df_unique.iloc[i, 1] = len(words_df.word[words_df.word == word])
i+=1
res = words_df_unique.sort_values('count', ascending = False)
return(res)

To do the same operation on a pandas data frame, you may use the following through Counter function from Collections:
from collections import Counter
cnt = Counter()
for text in df['text']:
for word in text.split():
cnt[word] += 1
# Find most common 10 words from the Pandas dataframe
cnt.most_common(10)