[Sync Iteration] python/little-sisters-vocab/1

solutions/python/little-sisters-vocab/1/strings.py

@@ -0,0 +1,61 @@
+"""Functions for creating, transforming, and adding prefixes to strings."""
+
+
+def add_prefix_un(word):
+    """Take the given word and add the 'un' prefix.
+
+    :param word: str - containing the root word.
+    :return: str - of root word prepended with 'un'.
+    """
+
+    return "un" + word
+
+
+def make_word_groups(vocab_words):
+    """Transform a list containing a prefix and words into a string with the prefix followed by the words with prefix prepended.
+
+    :param vocab_words: list - of vocabulary words with prefix in first index.
+    :return: str - of prefix followed by vocabulary words with
+            prefix applied.
+
+    This function takes a `vocab_words` list and returns a string
+    with the prefix and the words with prefix applied, separated
+     by ' :: '.
+
+    For example: list('en', 'close', 'joy', 'lighten'),
+    produces the following string: 'en :: enclose :: enjoy :: enlighten'.
+    """
+
+    prefix = vocab_words[0]
+    prefixed_words = [prefix + word for word in vocab_words[1:]]
+    return " :: ".join([prefix] + prefixed_words)
+
+def remove_suffix_ness(word):
+    """Remove the suffix from the word while keeping spelling in mind.
+
+    :param word: str - of word to remove suffix from.
+    :return: str - of word with suffix removed & spelling adjusted.
+
+    For example: "heaviness" becomes "heavy", but "sadness" becomes "sad".
+    """
+
+    new_word = word.replace("ness", "")
+    if new_word[-1] == "i": return new_word.replace("i", "y")
+    return new_word
+
+
+def adjective_to_verb(sentence, index):
+    """Change the adjective within the sentence to a verb.
+
+    :param sentence: str - that uses the word in sentence.
+    :param index: int - index of the word to remove and transform.
+    :return: str - word that changes the extracted adjective to a verb.
+
+    For example, ("It got dark as the sun set.", 2) becomes "darken".
+    """
+
+    no_punctuation = sentence.strip(".,!?")
+    words = no_punctuation.split()
+
+
+    return words[index] + "en"