chat-miner provides lean parsers for every major platform transforming chats into pandas dataframes. Artistic visualizations allow you to explore your data differently and create artwork from your chats.
Latest release including dependencies can be installed via PyPI:
pip install chat-minerIf you're interested in contributing, running the latest source code, or just like to build everything yourself:
git clone https://github.com/joweich/chat-miner.git
cd chat-miner
pip install -r requirements.txtHave a look at the official tutorials for WhatsApp, Signal, Telegram, or Facebook Messenger to learn how to export chat logs for your platform.
Following code showcases the WhatsAppParser module.
The usage of SignalParser, TelegramJsonParser, and FacebookMessengerParser follows the same pattern.
from chatminer.chatparsers import WhatsAppParser
parser = WhatsAppParser(FILEPATH)
parser.parse_file_into_df()import chatminer.visualizations as vis
import matplotlib.pyplot as pltfig, ax = plt.subplots(2, 1, figsize=(9, 3))
ax[0] = vis.calendar_heatmap(parser.df, year=2020, cmap='Oranges', ax=ax[0])
ax[1] = vis.calendar_heatmap(parser.df, year=2021, linewidth=0, monthly_border=True, ax=ax[1])
fig, ax = plt.subplots(1, 2, figsize=(7, 3), subplot_kw={'projection': 'polar'})
ax[0] = vis.sunburst(parser.df, highlight_max=True, isolines=[2500, 5000], isolines_relative=False, ax=ax[0])
ax[1] = vis.sunburst(parser.df, highlight_max=False, isolines=[0.5, 1], color='C1', ax=ax[1])
fig, ax = plt.subplots(figsize=(8, 3))
stopwords = ['these', 'are', 'stopwords']
kwargs={"background_color": "white", "width": 800, "height": 300, "max_words": 500}
ax = vis.wordcloud(parser.df, ax=ax, stopwords=stopwords, **kwargs)
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