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EnglishPal/app/pickle_idea.py

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###########################################################################
# 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.
import pickle
from datetime import datetime
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def lst_to_dict(lst, d):
"""
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Store the information in list lst to dictionary d.
Note: nothing is returned.
"""
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for x in lst:
word = x[0]
freq = x[1]
if word not in d:
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d[word] = freq
else:
d[word] += freq
def dict_to_lst(d):
return list(d.items()) # a list of (key, value) pairs
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def merge_frequency(list1, list2):
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d = {}
lst_to_dict(list1, d)
lst_to_dict(list2, d)
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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']
exclusion_lst = []
d2 = {}
for k in d:
if not k in exclusion_lst and not k.isnumeric() and len(k) > 1:
d2[k] = d[k]
pickle.dump(d2, f)
f.close()
def unfamiliar(path, word):
f = open(path, "rb")
dic = pickle.load(f)
dic[word] += [datetime.now().strftime('%Y%m%d%H%M')]
fp = open(path, "wb")
pickle.dump(dic, fp)
def familiar(path, word):
f = open(path, "rb")
dic = pickle.load(f)
if len(dic[word]) > 1:
del dic[word][0]
else:
dic.pop(word)
fp = open(path, "wb")
pickle.dump(dic, fp)
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if __name__ == '__main__':
lst1 = [('apple', 2), ('banana', 1)]
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d = {}
lst_to_dict(lst1, d) # d will change
save_frequency_to_pickle(d, 'frequency.p') # frequency.p is our database
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lst2 = [('banana', 2), ('orange', 4)]
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d = load_record('frequency.p')
lst1 = dict_to_lst(d)
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d = merge_frequency(lst2, lst1)
print(d)