EnglishPal/app/pickle_idea2.py

###########################################################################
# Copyright 2019 (C) Hui Lan <hui.lan@cantab.net>
# Written permission must be obtained from the author for commercial uses.
###########################################################################


# Purpose: dictionary & pickle as a simple means of database.
# Task: incorporate the functions into wordfreqCMD.py such that it will also show cumulative frequency.
# Note: unlike pick_idea.py, now the second item is not frequency, but a list of dates.

import pickle
from datetime import datetime

def lst2dict(lst, d):
    ''' 
    Store the information in list lst to dictionary d. 
    Note: nothing is returned.

    '''
    for x in lst:
        word = x[0]
        dates = x[1]
        if not word in d:
            d[word] = dates
        else:
            d[word] += dates

def deleteRecord(path,word):
    with open(path, 'rb') as f:
        db = pickle.load(f)
    try:
        db.pop(word)
    except KeyError:
        print("sorry")
    with open(path, 'wb') as ff:
            pickle.dump(db, ff)

def dict2lst(d):
    if len(d) > 0:
        keys = list(d.keys())
        if isinstance(d[keys[0]], int):
            lst = []
            for k in d:
                lst.append((k, [datetime.now().strftime('%Y%m%d%H%M')]))
            return lst
        elif isinstance(d[keys[0]], list):
            return list(d.items()) # a list of (key, value) pairs

    return []

def merge_frequency(lst1, lst2):
    d = {}
    lst2dict(lst1, d)
    lst2dict(lst2, d)
    return d


def load_record(pickle_fname):
    f = open(pickle_fname, 'rb')
    d = pickle.load(f)
    f.close()
    return d


def save_frequency_to_pickle(d, pickle_fname):
    f = open(pickle_fname, 'wb')
    exclusion_lst = ['one', 'no', 'has', 'had', 'do', 'that', 'have', 'by', 'not', 'but', 'we', 'this', 'my', 'him', 'so', 'or', 'as', 'are', 'it', 'from', 'with', 'be', 'can', 'for', 'an', 'if', 'who', 'whom', 'whose', 'which', 'the', 'to', 'a', 'of', 'and', 'you', 'i', 'he', 'she', 'they', 'me', 'was', 'were', 'is', 'in', 'at', 'on', 'their', 'his', 'her', 's', 'said', 'all', 'did', 'been', 'w']
    d2 = {}
    for k in d:
        if not k in exclusion_lst and not k.isnumeric() and not len(k) < 2:
            d2[k] = list(sorted(d[k])) # This code sorts the values of the dictionary 'd' associated with the key 'k' and assigns the resulting sorted list to the key 'k' in the dictionary 'd2'. However, it does not remove duplicates from the original list, which means that it keeps track of all counts even when the same value is clicked multiple times in a row.
    pickle.dump(d2, f)
    f.close()



if __name__ == '__main__':

    lst1 = [('apple',['201910251437', '201910251438']),  ('banana',['201910251439'])]
    d = {}
    lst2dict(lst1, d) # d will change
    save_frequency_to_pickle(d, 'frequency.p') # frequency.p is our database


    lst2 = [('banana',['201910251439']), ('orange', ['201910251440', '201910251439'])]
    d = load_record('frequency.p')
    lst1 = dict2lst(d)
    d = merge_frequency(lst2, lst1)
    print(d)