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Merge pull request #14 from sodascience/v4
Whatsapp script-New format
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[16/03/2022, 15:20:25] user1: Hi shiva! | ||
[16/03/2022, 15:25:38] user2: Hi 👋 | ||
[16/03/2022, 15:26:48] user3: Hoi! | ||
[16/03/2022, 18:39:29] user2: https://youtu.be/KBmUTY6mK_E | ||
[16/03/2022, 18:35:51] user1: Location: https://maps.google.com/?q=52.089451,5.108469 | ||
[20/03/2022, 20:08:51] user4: I’m about to generate some very random messages so that I can make some screenshots for the explanation to participants | ||
[24/03/2022, 20:19:38] user1: @user3 if you remove your Profile picture for a moment I will redo the screenshots 😁 | ||
[26/03/2022, 18:52:15] user2: Well done Utrecht 😁 | ||
Opkomst provinciesteden rond 20 procent, Utrecht hoogste opkomst van G4 | ||
https://nos.nl/l/2421368#UPDATE-container-60145354 | ||
[14/07/2020, 22:05:54] user4: 👍Bedankt | ||
[16/03/2022, 15:10:17] Messages and calls are end-to-end encrypted. No one outside of this chat, not even WhatsApp, can read or listen to them. Tap to learn more. | ||
[16/03/2022, 15:20:25] person1: Hi shiva! | ||
[16/03/2022, 15:25:38] person2: Hi 👋 | ||
[16/03/2022, 15:26:48] person3: Hoi! | ||
[16/03/2022, 18:39:29] person2: https://youtu.be/KBmUTY6mK_E | ||
[16/03/2022, 18:35:51] person1: Location: https://maps.google.com/?q=52.089451,5.108469 | ||
[20/03/2022, 20:08:51] person4: I’m about to generate some very random messages so that I can make some screenshots for the explanation to participants | ||
[24/03/2022, 20:19:38] person1: @user3 if you remove your Profile picture for a moment I will redo the screenshots 😁 | ||
[26/03/2022, 18:52:15] person2: Well done Utrecht 😁 | ||
[14/07/2020, 22:05:54] person4: 👍Bedankt |
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from whatsapp_chat import process | ||
from whatsapp_chat import anonymize_participants | ||
from pathlib import Path | ||
import pandas as pd | ||
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from whatsapp_chat import process | ||
from whatsapp_chat import anonymize_participants | ||
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from pandas.testing import assert_frame_equal | ||
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DATA_PATH = Path(__file__).parent / "data" | ||
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EXPECTED = [ | ||
{'username': 'user1', 'total_words_no': 20, 'url_no': 1, 'location_no': 1, 'file_no': 0, 'message_no': 3, | ||
'out_degree': 2, 'in_degree': 3, 'user_reply2': 'user2', 'reply_2_user': 'user2'}, | ||
{'username': 'person1', 'Total number of words': 20, 'Number of URLs': 1, | ||
'Number of shared locations': 1, 'file_no': 0, 'Number of messages': 3, | ||
'Date first message': pd.to_datetime('2022-03-16 15:20:25'), | ||
'Date last message': pd.to_datetime('2022-03-24 20:19:38'), | ||
'user_reply2': 'person2', 'reply_2_user': 'person2'}, | ||
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{'username': 'user2', 'total_words_no': 18, 'url_no': 2, 'location_no': 0, 'file_no': 0, 'message_no': 3, | ||
'out_degree': 3, 'in_degree': 3, 'user_reply2': 'user1', 'reply_2_user': 'user1'}, | ||
{'username': 'person2', 'Total number of words': 7, 'Number of URLs': 1, | ||
'Number of shared locations': 0, 'file_no': 0, 'Number of messages': 3, | ||
'Date first message': pd.to_datetime('2022-03-16 15:25:38'), | ||
'Date last message': pd.to_datetime('2022-03-26 18:52:15'), | ||
'user_reply2': 'person1', 'reply_2_user': 'person1'}, | ||
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{'username': 'user3', 'total_words_no': 1, 'url_no': 0, 'location_no': 0, 'file_no': 0, 'message_no': 1, | ||
'out_degree': 1, 'in_degree': 1, 'user_reply2': 'user2', 'reply_2_user': 'user2'}, | ||
{'username': 'person3', 'Total number of words': 1, 'Number of URLs': 0, | ||
'Number of shared locations': 0, 'file_no': 0, 'Number of messages': 1, | ||
'Date first message': pd.to_datetime('2022-03-16 15:26:48'), | ||
'Date last message': pd.to_datetime('2022-03-16 15:26:48'), | ||
'user_reply2': 'person2', 'reply_2_user': 'person2'}, | ||
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{'username': 'user4', 'total_words_no': 21, 'url_no': 0, 'location_no': 0, 'file_no': 0, 'message_no': 2, | ||
'out_degree': 2, 'in_degree': 1, 'user_reply2': 'user1', 'reply_2_user': 'user1'} | ||
{'username': 'person4', 'Total number of words': 21, 'Number of URLs': 0, | ||
'Number of shared locations': 0, 'file_no': 0, 'Number of messages': 2, | ||
'Date first message': pd.to_datetime('2020-07-14 22:05:54'), | ||
'Date last message': pd.to_datetime('2022-03-20 20:08:51'), | ||
'user_reply2': 'person1', 'reply_2_user': 'person1'} | ||
] | ||
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def test_process(): | ||
""" Test process function. | ||
compares the expected dataframe with the output of the process function to check if all the columns are match. | ||
compares the expected dataframe with the output of the process function | ||
to check if all the columns are match. | ||
Raises | ||
------- | ||
AssertionError: When provided expected dataframe could not match the participants dataframe | ||
AssertionError: When provided expected dataframe could not match the | ||
participants dataframe | ||
""" | ||
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df_expected = pd.DataFrame(EXPECTED) | ||
df_expected = anonymize_participants(df_expected) | ||
df_expected['message_no'] = df_expected['message_no'].astype('int64') | ||
df_expected['url_no'] = df_expected['url_no'].astype('int32') | ||
df_expected['location_no'] = df_expected['location_no'].astype('int32') | ||
df_expected['Number of messages'] = df_expected['Number of messages'].astype('int64') | ||
df_expected['Number of URLs'] = df_expected['Number of URLs'].astype('int32') | ||
df_expected['Number of shared locations'] = \ | ||
df_expected['Number of shared locations'].astype('int32') | ||
df_expected['file_no'] = df_expected['file_no'].astype('int32') | ||
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# result = process(DATA_PATH.joinpath("whatsapp_chat.zip")) | ||
result = process(DATA_PATH.joinpath("_chat.txt")) | ||
assert len(result) == 1 | ||
df_result = result[0]["data_frame"] | ||
assert_frame_equal(df_result, df_expected) | ||
results = [] | ||
df_melt = pd.melt(df_expected, id_vars=["username"], | ||
value_vars=["Total number of words", | ||
"Number of messages", | ||
"Date first message", | ||
"Date last message", | ||
"Number of URLs", | ||
"file_no", | ||
"Number of shared locations", | ||
"reply_2_user", | ||
"user_reply2"], | ||
var_name='Description', value_name='Value') | ||
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usernames = df_melt["username"].unique() | ||
for user in usernames: | ||
df_user = df_melt[(df_melt["username"] == user) & df_melt["Value"] != 0] | ||
results.append(df_user) | ||
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expected_results = [] | ||
for df in results: | ||
user_name = pd.unique(df["username"])[0] | ||
expected_results.append( | ||
{ | ||
"id": user_name, # "overview", | ||
"title": user_name, # "The following data is extracted from the file:", | ||
"data_frame": df[["Description", "Value"]].reset_index(drop=True) | ||
} | ||
) | ||
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df_result = process(DATA_PATH.joinpath("_chat.txt")) | ||
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assert_frame_equal(df_result[0]["data_frame"], expected_results[0]["data_frame"]) | ||
assert_frame_equal(df_result[1]["data_frame"], expected_results[1]["data_frame"]) | ||
assert_frame_equal(df_result[2]["data_frame"], expected_results[2]["data_frame"]) | ||
assert_frame_equal(df_result[3]["data_frame"], expected_results[3]["data_frame"]) |
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