├── .gitignore ├── requirements.txt ├── environment.yml ├── README.md ├── whatsapp_scraper.py └── LICENSE /.gitignore: -------------------------------------------------------------------------------- 1 | .vscode 2 | whatsapp-venv 3 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | numpy==1.16.4 2 | pandas==0.24.2 3 | python-dateutil==2.8.0 4 | pytz==2019.1 5 | six==1.12.0 6 | -------------------------------------------------------------------------------- /environment.yml: -------------------------------------------------------------------------------- 1 | name: whatsapp-conda-env 2 | channels: 3 | - anaconda-fusion 4 | - defaults 5 | dependencies: 6 | - blas=1.0=mkl 7 | - ca-certificates=2019.5.15=1 8 | - certifi=2019.6.16=py37_1 9 | - icc_rt=2019.0.0=h0cc432a_1 10 | - intel-openmp=2019.4=245 11 | - mkl=2019.4=245 12 | - mkl-service=2.0.2=py37he774522_0 13 | - mkl_fft=1.0.14=py37h14836fe_0 14 | - mkl_random=1.0.2=py37h343c172_0 15 | - numpy=1.16.4=py37h19fb1c0_0 16 | - numpy-base=1.16.4=py37hc3f5095_0 17 | - openssl=1.1.1c=he774522_1 18 | - pandas=0.25.1=py37ha925a31_0 19 | - pip=19.2.2=py37_0 20 | - python=3.7.4=h5263a28_0 21 | - python-dateutil=2.8.0=py37_0 22 | - pytz=2019.2=py_0 23 | - setuptools=41.0.1=py37_0 24 | - six=1.12.0=py37_0 25 | - sqlite=3.29.0=he774522_0 26 | - vc=14.1=h0510ff6_4 27 | - vs2015_runtime=14.15.26706=h3a45250_4 28 | - wheel=0.33.4=py37_0 29 | - wincertstore=0.2=py37_0 30 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # WhatsApp Scraper 2 | 3 | A script that takes WhatsApp messages in .txt format, pareses the DateTime, Sender and Message and outputs them as a CSV file for furtur analysis/visualisation. 4 | 5 | > Set-up instructions have been divided into 'New User Set-up', directly below, and 'Experienced User Set-up', furthur down the page. 6 | 7 | ## New User Set-up 8 | 9 | ### **1. Downloading the Files** 10 | 11 | 1. Head to - https://github.com/UoMResearchIT/whatsapp-scraper 12 | 13 | 2. Click 'Clone or Download', select 'Download as .ZIP' 14 | 15 | 3. Unzip the file, put the 'whatsapp-scraper-master' into your 'Documents' directory. 16 | 17 | ### **2. Python Set-up** 18 | 19 | 1. Download Anaconda, a Python distribution, here - https://www.anaconda.com/distribution/ 20 | 21 | 2. Choose your OS, and download the the 'Python 3.7 version'. 22 | 23 | 3. Once it has finished downloading, install it, choosing the default options. 24 | 25 | ### **3. Virtual Environment Set-up** 26 | 27 | 1. Open the 'Anaconda Navigator" application. 28 | 29 | 2. Click the 'Environments' tab on the left. 30 | 31 | 3. Click the 'Import' button at the bottom. 32 | 33 | 4. Click the folder button next to "Specification File'. Choose the 'environment.yml' file that's in the whatsapp_scraper_master directory. 34 | 35 | 5. Click 'Import' 36 | 37 | 6. Once the environment is imported it will appear in the list of environments. It will be called 'whatsapp-conda-env' 38 | 39 | ### **4. Running the Script.** 40 | 41 | 1. Click the play button next to the 'whatsapp-conda-env' environment, and choose 'Open Terminal'. 42 | 43 | 2. In the terminal type - 44 | 45 | `cd Documents` 46 | 47 | then 48 | 49 | `cd whatsapp-scraper-master` 50 | 51 | then 52 | 53 | `python whatsapp_scraper.py` 54 | 55 | The script will run, creating a new directory for each chat txt file, inside it is the original .txt file along with a sorted .csv file. 56 | 57 | ### **5. Importing into Excel** 58 | 59 | To import the data in to Excel 365 - 60 | 61 | 1. Open Excel, 62 | 2. Click the 'Data' panel. 63 | 3. Click 'From Text/CSV' 64 | 4. Choose the .csv you want to import, 65 | 5. Set 'File Origin" to '--None--' (at the top of the list), 'Delimiter' to 'Comma', Data Type Detection to 'Based on entire dataset' 66 | 6. Click 'Load'. The data will now be imported to the open worksheet. 67 | 68 | To import the data in to Excel 2016 - 69 | 70 | 1. Open Excel, 71 | 2. Click the 'Data' panel. 72 | 3. Click 'New Query' 73 | 4. Click 'From File', then 'From CSV' 74 | 5. Choose the .csv you want to import, 75 | 6. Set 'File Origin" to '--None--' (at the top of the list), 'Delimiter' to 'Comma', Data Type Detection to 'Based on entire dataset' 76 | 7. Click 'Load'. The data will now be imported to the open worksheet. 77 | 78 | ### **Re-running the script in the future.** 79 | 80 | 1. Open 'Anaconda Navigator' 81 | 82 | 2. Click the 'Environments' tab on the left. 83 | 84 | 3. Repeat the steps in **4. Running the Script.** 85 | 86 | ## Experienced User Set-up 87 | 88 | ### Requirements 89 | 90 | #### Windows 91 | 92 | Python 3.7+ 93 | virtualenv 94 | Git Bash 95 | Command Line Interface 96 | 97 | NOTE: All commands that use "git" are done in Git Bash. It lets you use MinGW/Linux tools with Git at the command line. 98 | 99 | #### Linux/macOS 100 | 101 | Python 3.7+ 102 | virtualenv 103 | Git 104 | Command Line Interface 105 | 106 | ### 1. Set-up 107 | 108 | git clone git@github.com:UoMResearchIT/whatsapp-scraper.git 109 | 110 | cd whatsapp-scraper 111 | 112 | #### 2. Virtual Environment 113 | 114 | ##### Windows 115 | 116 | $ virtualenv 117 | 118 | $ \Scripts\activate 119 | 120 | $ pip install -r requirements.txt 121 | 122 | ##### Linux 123 | 124 | $ virtualenv 125 | 126 | $ source /bin/activate 127 | 128 | $ pip install -r requirements.txt 129 | 130 | ### 3. Running Scripts 131 | 132 | 1. Place the .txt files you want to process into the `whatsapp-scraper` directory. 133 | 2. In the command line run `whatsapp_scraper.py` 134 | 3. The scripts will process all the .txt files in `whatsapp-scraper` and create new folders for each file, conataining the original .txt file and the new .csv file. 135 | 136 | #### 4. Importing into Excel 137 | 138 | To import the data in to Excel - 139 | 140 | 1. Open Excel, 141 | 2. Click the 'Data' panel. 142 | 3. Click 'From Text/CSV' 143 | 4. Choose the .csv you want to import, 144 | 5. Set 'File Origin" to '--None--' (at the top of the list), 'Delimiter' to 'Comma', Data Type Detection to 'Based on entire dataset' 145 | 6. Click 'Load'. The data will now be imported to the open worksheet. 146 | -------------------------------------------------------------------------------- /whatsapp_scraper.py: -------------------------------------------------------------------------------- 1 | import pandas as pd 2 | import re 3 | import sys 4 | import os 5 | import shutil 6 | import csv 7 | import datetime 8 | 9 | 10 | # Get current working directory 11 | cwd = os.getcwd() 12 | checklist = os.listdir(cwd) 13 | 14 | # Checks to see how many text files there are. If there's only one 15 | # the script is stopped 16 | text_list = [] 17 | for filename in checklist: 18 | if filename.endswith(".txt") == 1: 19 | text_list.append(filename) 20 | if len(text_list) == 1: 21 | print('No are no WhatsApp .txt files') 22 | sys.exit() 23 | 24 | # loop over all files in CWD 25 | for filename in checklist: 26 | 27 | # search for all text files that aren't the requirements file 28 | if filename != ("requirements.txt") and filename.endswith(".txt"): 29 | 30 | # open the text file 31 | with open(filename, "r", encoding='utf-8') as f: 32 | 33 | # Checks the first line to see if its an old WhatsAPP message or new one. 34 | first_line = f.readline() 35 | 36 | test = f.readlines() 37 | start = 1 38 | num_items = len(test) 39 | want = range(start, num_items) 40 | 41 | # List where the datetime, sender, message and message number go 42 | msg_date_time = [] 43 | msg_sender = [] 44 | msg = [] 45 | msg_number_list = [] 46 | 47 | # checks first charcater of firstline, if its a opening of square brackets, 48 | # it will run new whatsApp loop, otherwise it will run the old one. 49 | if first_line[0] == '[': 50 | 51 | for row in want: 52 | try: 53 | date = re.search(r'(.\d+/\d+/\d+), (\d+:\d+:\d\d.)', test[row]).group(0) 54 | 55 | #gets rid of brackets for nicer CSV formatting 56 | date = re.sub(r'\[', '', date) 57 | date = re.sub(r'\]', '', date) 58 | except AttributeError: 59 | new_message = msg[-1] + " " + test[row] 60 | del msg[-1] 61 | msg.append(new_message) 62 | continue 63 | 64 | # Looks for message and creates a "No Message" this helps filter out the admin messages, eg. this person changed group icon etc 65 | try: 66 | message = re.search(r"(:\s).*[\d+/\d+/\d+]*", test[row]).group(0).replace(": ", "") 67 | except: 68 | message = "No Message" 69 | 70 | try: 71 | # Finds the sender by deleting the message and date/time from the row. 72 | row = test[row] 73 | sender = re.sub(r"(.\d+/\d+/\d+), (\d+:\d+:\d\d.)", "", row) 74 | sender = re.sub(r":.*", "", sender) 75 | 76 | except: 77 | sender = " " 78 | 79 | 80 | msg_date_time.append(str(date)) 81 | 82 | msg_sender.append(sender) 83 | 84 | msg.append(message) 85 | 86 | else: 87 | 88 | for row in want: 89 | 90 | # try to find the date, if can't then a message has continued from previous line. 91 | # this is then appended to previous message by finding it in the msg list and concantonbating it 92 | try: 93 | date = re.search(r'(\d+/\d+/\d+), (\d+:\d+)', test[row]).group(0) 94 | except AttributeError: 95 | new_message = msg[-1] + " " + test[row] 96 | del msg[-1] 97 | msg.append(new_message) 98 | continue 99 | 100 | # Tries sender and creates a blank 101 | try: 102 | sender = re.search(r'(?s)(?<=-\s).*?(?=:)',test[row]).group(0).replace("- ", "") 103 | except: 104 | sender = " " 105 | 106 | # Looks for message and creates a "No Message" this helps filter out the admin messages, eg. this person changed group icon etc 107 | try: 108 | message = re.search(r"(:\s).*[\d+/\d+/\d+]*", test[row]).group(0).replace(": ", "") 109 | except: 110 | message = "No Message" 111 | 112 | msg_date_time.append(date) 113 | 114 | msg_sender.append(sender) 115 | 116 | msg.append(message) 117 | 118 | # Creates a pandas dataframe 119 | df = pd.DataFrame(list(zip(msg_date_time, msg_sender, msg)), 120 | columns=['Date Time','Sender', 'Message']) 121 | 122 | # Drops all rows where the message is "No Message" 123 | df = df[~df.Message.str.contains("No Message")] 124 | 125 | # Create a message number column 126 | msg_number_list 127 | loop_num = len(df.index) 128 | msg_number = 1 129 | for number in range(loop_num) : 130 | msg_number_list.append(str(msg_number)) 131 | msg_number += 1 132 | 133 | # Creates new df with message number column 134 | df = df.assign(message_number = msg_number_list) 135 | 136 | # Reanmes column 137 | df = df.rename({'message_number': 'Message Number'}, axis=1) 138 | 139 | # Reorders columns 140 | df = df[['Message Number', 'Date Time', 'Sender', 'Message']] 141 | 142 | # get filename minus extension 143 | split_filename = os.path.splitext(filename)[0] 144 | 145 | # use the split filename with new extensions 146 | csv_filename = split_filename + '.csv' 147 | 148 | # dataframe saved to CSV 149 | df.to_csv(csv_filename, index=False) 150 | 151 | # makes a new directory and puts the source and outputs file in it 152 | os.makedirs(split_filename) 153 | shutil.move(filename, split_filename) 154 | shutil.move(csv_filename, split_filename) 155 | 156 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. 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