Tweet Anagram Finder

---

A program to mimic the behavior of https://twitter.com/anagramatron

anagrams/ contains:

• a file which parses input tweet data -- anagrams.py
• a file to make dummy tweet data given a dictionary -- make_tweet.json

dictionaries/ contains:

• a small dictionary of the 1,000 most common words common_word_dictionary.txt
• a large dictionary of ~ 170,000 words -- dictionary.txt
• these are for passing to make_tweet_json.py to construct tweet data

tweet_data/ contains:

• a small .json file of sample tweet data -- tweets.json

bin/

• the binaries to execute; added to path with pip install

To execute

1. Clone repository: git clone https://github.com/killakam3084/anagrams.git

2. Install anagrams package cd anagrams/ && pip install .

3. To make sample JSON make-tweet-data -l 3 -n 100000 tweets.json dictionary.txt

    usage: make-tweet-data [-h] [-l, word-length WORD_LENGTH]
            	       [-n, number-of-tweets NUM_TWEETS]
                   	output_file dictionary_file
   
    		A program to make dummy tweet json for anagrams
   
    positional arguments:
    output_file           A output file to write tweet data to.
    dictionary_file       The dictionary to construct anagrams.
   
    optional arguments:
    -h, --help            show this help message and exit
    -l, word-length WORD_LENGTH
                    The max character count for a word.
    -n, number-of-tweets NUM_TWEETS
                    The number of tweets to constructs.
   

4. Run script

   usage: find-anagrams [-h] input_file
   		A vanilla program to detect anagrams in tweet json
   
   positional arguments:
   input_file  The input file of tweets.
   
   optional arguments:
   -h, --help  show this help message and exit
   
   Certainly this isn't how Anagramatron does it	
   

Notes on ijjson iterative parser**

• ijson is an iterative JSON parser with a standard Python iterator interface
• Ijson provides several implementations of the actual parsing in the form of backends located in ijson/backends:
• The script should output memory_profiler data showing the effectiveness of ijson's lazy loading
• Processed 50,000,000 two word tweets with words of length 4 in about ~ 2 hours, around ~3.5G file size.