Python interface to filter emails on Google Mail.
Project description
Manage your emails in Gmail with Python
The pydatamail_google
is a python module to automate the filtering of emails on Gmail using the Gmail API. You can either
write your own python script to combine the different functions or use the JSON
based input or the command line input,
all three provide acccess to the same functionality and are explained in more detail below.
Configuration
The pydatamail_google
stores the configuration files in the users home directory ~/.pydatamail
. This folder contains:
config.json
theJSON
configuration file forJSON
based input, which is explained in more detial below.credentials.json
the authentication credentials for the Google API, which at least requires access to Gmail and additional access to Google Drive in case you want to store your attachments on Google drive.token_files
the token directory is used to store the active token for accessing the APIs, these are created automatically, there should be no need for the user to modify these.
Installation
Install the package from github using pip
:
pip install git+https://github.com/pyscioffice/pydatamail_google.git
Finally setup the credentials.json
in your Google Apps and store it in ~/.pydatamail/credentials.json
.
Python interface
Import the pydatamail_google
module
from pydatamail_google import Gmail
Initialize pydatamail_google
Create a gmail
object from the Gmail()
class
gmail = Gmail()
For testing purposes you can use the optimal client_service_file
parameter to specify the location of the
authentication credentials in case they are not stored in ~/.pydatamail/credentials.json
.
List Labels
List the available labels in your Gmail account:
gmail.labels
Returns a list of email labels as you defined them in your email client. This is in contrast to the Gmail API which typically returns the label IDs rather than the user defined label names.
Filter Emails
Filter a set of emails in a specific label using a predefined list of dictionaries:
gmail.filter_label_by_sender(label, filter_dict_lst)
The label can be any email label and the filter_dict_lst is a list of email filters defined as dictionary. A typical email filter list might look like this:
[{"from": "my_email@provider.com", "label": "my_special_label"},
{"to": "spam@google.com", "label": "another_email_label"},
{"subject": "you won", "label": "success_story"}]
At the current stage only one of the three fields from
, to
or subject
can be validated per filter and all
filters are applied as "is in" rather than an exact match.
Search for Emails
Search emails either by a specific query or optionally limit your search to a list of labels.
gmail.search_email(query_string="", label_lst=[], only_message_ids=False)
The query_string
supports all the functionality the gmail search has to offer, for example you can search for emails
with attachments using the query "has:attachment"
. In addition with the option only_message_ids
the return values
can be reduced to just a list of email ids, otherwise both the email ids and the thread ids are returned.
Remove Labels
As Gmail provides a set of smart labels which are accessible on the web interface but typically hidden in the mobile application many people want to remove these labels. Still this functionality is more general and can be applied to any list of labels, so be warned when using it.
gmail.remove_labels_from_emails(label_lst)
To remove the Gmail smart labels just set the label_lst
to ["CATEGORY_FORUMS", "CATEGORY_UPDATES", "CATEGORY_PROMOTIONS", "CATEGORY_SOCIAL"]
.
Load Tasks from JSON file
This is the function for the file based interface, which is explained below in a separate section.
gmail.load_json_tasks(config_json=None)
By default the json config file is expected to be located in ~/.pydatamail/config.json
.
Save attachments for a specific label
Save all attachments of emails marked with a selected label to a specific folder on Google drive. This requires Google drive authorisation to be included in the authentication credentials.
gmail.save_attachments_of_label(label, path)
The label is given by its label name rather than the google internal label ID and the path has to be a relative path
starting at the root of your google drive, for example backup/emails
. In this path a new subfolder is created with the
name of the label.
Download messages to pandas Dataframe
For offline processing it is helpful to download messages in bulk to pandas dataframes:
gmail.download_messages_to_dataframe(message_id_lst)
The message_id_lst
is a list of message ids, this can be obtained from gmail.search_email()
.
Get email content as dictionary
The content of the email rendered as python dictionary for further postprocessing:
gmail.get_email_dict(message_id)
The message_id
can be derived from a function like gmail.search_email()
.
Update database
Update local database stored in ~/.pydatamail/email.db
:
gmail.update_database()
Command Line interface
The command line interface is currently rather limited, it supports the following options:
pydatamail_google
run the tasks defined in~/.pydatamail/config.json
.pydatamail_google --file ~/.pydatamail/config.json
run the tasks defined in a user specific task file.pydatamail_google --labels
list all labels of your Gmail account.pydatamail_google --database
update local database.
File based interface
Currently the file based interface only supports two functions:
remove_labels_from_emails
to remove specific labels from all emails on your account.filter_label_by_sender
to filter emails using the filter dictionary list
Both functions are explained in more detail above in the python interface section. Below is an example configuration file
which would be located at ~/.pydatamail/config.json
:
{
"database": "sqlite:////~/.pydatamail/email.db",
"remove_labels_from_emails":
["CATEGORY_FORUMS", "CATEGORY_UPDATES", "CATEGORY_PROMOTIONS", "CATEGORY_SOCIAL"],
"filter_label_by_sender": {
"label": "my_other_email_provider",
"filter_dict_lst": [
{"from": "my_email@provider.com", "label": "my_special_label"},
{"to": "spam@google.com", "label": "another_email_label"},
{"subject": "you won", "label": "success_story"}
]
}
}
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