"""Library WhatsApp objects."""
from whatstk._chat import BaseChat
from whatstk.utils.chat_merge import merge_chats
from whatstk.whatsapp.parser import df_from_txt_whatsapp
[docs]class WhatsAppChat(BaseChat):
"""Load and process a WhatsApp chat file.
Args:
df (pandas.DataFrame): Chat.
Example:
This simple example loads a chat using :func:`WhatsAppChat <WhatsAppChat>`. Once loaded, we can access its
attribute :func:`df <WhatsAppChat.df>`, which contains the loaded chat as a DataFrame.
.. code-block:: python
>>> from whatstk.whatsapp.objects import WhatsAppChat
>>> from whatstk.data import whatsapp_urls
>>> chat = WhatsAppChat.from_source(filepath=whatsapp_urls.POKEMON)
>>> chat.df.head(5)
username message
date
2016-08-06 13:23:00 Ash Ketchum Hey guys!
2016-08-06 13:25:00 Brock Hey Ash, good to have a common group!
2016-08-06 13:30:00 Misty Hey guys! Long time haven't heard anything fro...
2016-08-06 13:45:00 Ash Ketchum Indeed. I think having a whatsapp group nowada...
2016-08-06 14:30:00 Misty Definetly
"""
def __init__(self, df):
"""Constructor.
Args:
df (pandas.DataFrame): Chat.
"""
super().__init__(df, platform='whatsapp')
[docs] @classmethod
def from_source(cls, filepath, **kwargs):
"""Create an instance from a chat text file.
Args:
filepath (str): Path to the file. It can be a local file (e.g. 'path/to/file.txt') or an URL to a hosted
file (e.g. 'http://www.url.to/file.txt')
**kwargs: Refer to the docs from
:func:`df_from_txt_whatsapp <whatstk.whatsapp.parser.df_from_txt_whatsapp>` for details on
additional arguments.
Returns:
WhatsAppChat: Class instance with loaded and parsed chat.
.. seealso::
* :func:`df_from_txt_whatsapp <whatstk.whatsapp.parser.df_from_txt_whatsapp>`
* :func:`WhatsAppChat.from_sources <whatstk.WhatsAppChat.from_sources>`
"""
# Prepare DataFrame
df = df_from_txt_whatsapp(filepath=filepath, **kwargs)
return cls(df)
[docs] @classmethod
def from_sources(cls, filepaths, auto_header=None, hformat=None, encoding='utf-8'):
"""Load a WhatsAppChat instance from multiple sources.
Args:
filepaths (list): List with filepaths.
auto_header (bool, optional): Detect header automatically (applies to all files). If None, attempts to
perform automatic header detection for all files. If False, ``hformat`` is
required.
hformat (list, optional): List with the :ref:`header format <The header format>` to be used for each file.
The list must be of length equal to ``len(filenames)``. A valid header format
might be '[%y-%m-%d %H:%M:%S] - %name:'.
encoding (str): Encoding to use for UTF when reading/writing (ex. ‘utf-8’).
`List of Python standard encodings
<https://docs.python.org/3/library/codecs.html#standard-encodings>`_.
Returns:
WhatsAppChat: Class instance with loaded and parsed chat.
.. seealso::
* :func:`WhatsAppChat.from_source <WhatsAppChat.from_source>`
* :func:`merge_chats <whatstk.utils.chat_merge.merge_chats>`
Example:
Load a chat using two text files. In this example, we use sample chats (available online, see urls in
source code :mod:`whatstk.data <whatstk.data>`).
.. code-block:: python
>>> from whatstk.whatsapp.objects import WhatsAppChat
>>> from whatstk.data import whatsapp_urls
>>> filepath_1 = whatsapp_urls.LOREM1
>>> filepath_2 = whatsapp_urls.LOREM2
>>> chat = WhatsAppChat.from_sources(filepaths=[filepath_1, filepath_2])
>>> chat.df.head(5)
username message
date
2019-10-20 10:16:00 John Laborum sed excepteur id eu cillum sunt ut.
2019-10-20 11:15:00 Mary Ad aliquip reprehenderit proident est irure mo...
2019-10-20 12:16:00 +1 123 456 789 Nostrud adipiscing ex enim reprehenderit minim...
2019-10-20 12:57:00 +1 123 456 789 Deserunt proident laborum exercitation ex temp...
2019-10-20 17:28:00 John Do ex dolor consequat tempor et ex.
"""
dfs = []
if auto_header is None or auto_header:
auto_header = [True]*len(filepaths)
else:
auto_header = [False]*len(filepaths)
if hformat is None:
hformat = [None]*len(filepaths)
for filepath, ah, hf in zip(filepaths, auto_header, hformat):
chat = WhatsAppChat.from_source(filepath, auto_header=ah, hformat=hf, encoding=encoding)
dfs.append(chat.df)
df = merge_chats(dfs)
return cls(df)
[docs] def to_txt(self, filepath, hformat=None):
"""Export chat to a text file.
Usefull to export the chat to different formats (i.e. using different hformats).
Args:
filepath (str): Name of the file to export (must be a local path).
hformat (str, optional): Header format. Defaults to '%y-%m-%d, %H:%M - %name:'.
"""
if not filepath.endswith('.txt'):
raise ValueError("filepath must end with .txt")
if not hformat:
hformat = "%y-%m-%d, %H:%M - %name:"
lines = []
raw_lines = self.df.reset_index().values.tolist()
for line in raw_lines:
date, user, text = line
hformat = hformat.replace('%name', '{name}')
header = date.strftime(hformat).format(name=user)
formatted_line = '{} {}'.format(header, text)
lines.append(formatted_line)
text = '\n'.join(lines)
with open(filepath, 'w') as f:
f.write(text)
