Methods to extract email signature - python

I would like to extract email signatures from a single-column Pandas data frame where each row contains a discrete email message as a string. Some emails are HTML encoded and some are not. They can be of any email provider (e.g.: Gmail, Microsoft, Yahoo, etc.).
I know that Gmail signatures are contained in a div where class="email_signature" which simplifies parsing those. My dilemma is: what is the best way to extract non-gmail email signatures? Is there a regex that captures the content of an email? How can I apply this regex over the Pandas data frame in Python?
I'd provide an example but the data is private and frankly I don't think it's necessary for this question.

Checkout SigParser.com. It is an API for doing this pretty much. It uses email signatures to extract contact data. Is this what you're looking for?

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Send rich text format email using python

I need to create emails with rich text format. Inside the email, it has a table, and under one column of the table, for each row, i need to attach different emails
Would above be achievable using python
Any help will be appreciated!

Parse email and send reply using googleapiclient in Python

I'm currently working on a project and I have chosen to use Gmail for sending and receiving emails. I want to be able to send an email, have a user reply to it, and parse their response. The response can be any number of lines (so something like response.split('\n')[0] won't work). It should then be able to reply directly to that email thread.
I've been following the googleapiclient tutorials, but they leave a lot to be desired. However, I've managed to read email threads using:
service.users.threads().get(userId='me', id=thread_id).execute()
where thread_id is (predictably) the ID of the email thread (which I find elsewhere). In the large dict returned by this, there is a section of base64 data which contains the content of the email. This was the only place I could find the actual data for the response. Unfortunately, I get this when it is decoded:
b'This is my response from my phone\r\n\r\nOn Sat, 28 Nov 2020, 8:40 PM , <myemail#gmail.com>\r\nwrote:\r\n\r\n> This is sent from the python script\r\n>\r\n'
This is all the data in the thread, however, I only want the response as there is clearly no way to split this to get only the data I need. The best I can think of is to parse out anything of the form On <date>, <time>, but that could lead to problems. There must be another way to extract only This is my response from my phone and no other data.
Once I get the response, I want to parse it and reply with an appropriate response based on the contents of the message. I would prefer to reply directly to the thread, rather than starting a new one. Unfortunately, all the Google documentation says is:
If you're trying to send a reply and want the email to thread, make sure that:
The Subject headers match
The References and In-Reply-To headers follow the RFC 2822 standard.
The documentation provides this code (with some minor modifications by me) for sending an email:
def create_message(sender, to, subject, message_text):
message = MIMEText(message_text)
message['to'] = to
message['from'] = sender
message['subject'] = subject
return {'raw': base64.urlsafe_b64encode(message.as_bytes()).decode()}
Sending a reply with the same subject line is pretty straight forward (message['subject'] = same_subject_as_before), but I don't even know where to start with the References and In-Reply-To headers. How do I set these?
Why is this hard?
You are trying to use e-mail for something it simply wasn't originally designed for. My impression is you want the e-mail response to contain structured data, but e-mail text lacks any well-defined structure. It also depends on which e-mail client the other user has, and whether they send HTML e-mail or not.
This is usually easy for a human to see, but difficult for a computer. Which suggests that Machine Learning might be the best strategy if you want higher reliability. Whatever solution you choose, it's not going to be 100% reliable.
E-mail can be plain text or HTML, or both.
There is no well-defined structure to separate replies from the original text. Wikipedia lists a few different "posting styles".
In the old days when "Netiquette" was still cool, putting your reply on top ("top-posting") was considered bad practice, and new Internet users were told by old folks to avoid top-posting. Some users still reply below or interleaved with the original text.
The reply line (e.g. "On DATE, EMAIL wrote:" or "-------- Original Message --------") will be different, depending on which e-mail client is used, what language that client is set to, and the user's own preferences.
Using a text delimiter
A class of software which faces a similar problem as the one you describe is customer service applications, which allow operators to use e-mail for communication. A common strategy is to inject some unique text in your templates for outgoing e-mail. For example, Zendesk uses a text "delimiter" such as:
##- Please type your reply above this line -##
This serves two purposes; it tells users to top-post, and it provides a separator to cut out most of the irrelevant text.
If you first handle any HTML encoding, you should be able to split the message by such a text delimiter. It's not perfect, but it usually works.
Use products made by others
There are some open source options, such as:
https://github.com/zapier/email-reply-parser
And I found a commercial product, SigParser, which seems to use a machine learning model that they've trained very carefully:
https://sigparser.com/developers/extract-reply-chains-from-emails/
They also explain some of the challenges of parsing e-mail text into structured data.

How to parse email body in Python? [duplicate]

I want to retrieve body (only text) of emails using python imap and email package.
As per this SO thread, I'm using the following code:
mail = email.message_from_string(email_body)
bodytext = mail.get_payload()[ 0 ].get_payload()
Though it's working fine for some instances, but sometime I get similar to following response
[<email.message.Message instance at 0x0206DCD8>, <email.message.Message instance at 0x0206D508>]
You are assuming that messages have a uniform structure, with one well-defined "main part". That is not the case; there can be messages with a single part which is not a text part (just an "attachment" of a binary file, and nothing else) or it can be a multipart with multiple textual parts (or, again, none at all) and even if there is only one, it need not be the first part. Furthermore, there are nested multiparts (one or more parts is another MIME message, recursively).
In so many words, you must inspect the MIME structure, then decide which part(s) are relevant for your application. If you only receive messages from a fairly static, small set of clients, you may be able to cut some corners (at least until the next upgrade of Microsoft Plague hits) but in general, there simply isn't a hierarchy of any kind, just a collection of (not necessarily always directly related) equally important parts.
The main problem in my case is that replied or forwarded message shown as message instance in the bodytext.
Solved my problem using the following code:
bodytext=mail.get_payload()[0].get_payload();
if type(bodytext) is list:
bodytext=','.join(str(v) for v in bodytext)
My external lib: https://github.com/ikvk/imap_tools
from imap_tools import MailBox
# get list of email bodies from INBOX folder
with MailBox('imap.mail.com').login('test#mail.com', 'pwd', 'INBOX') as mailbox:
bodies = [msg.text or msg.html for msg in mailbox.fetch()]
Maybe this post (of mine) can be of help. I receive a Newsletter with prices of different kind of oil in the US. I fetch email in gmail with a given pattern for the title, then I extract the prices in the mail body using regex. So i have to access the mail body for the last n emails which title observe given pattern.
I am using email.message_from_string() also: msg = email.message_from_string(response_part[1])
so maybe it gives you concrete example of how to use methods in this python lib.

Parsing Gmail Labels into tree structure

For those who don't know. If you have a gmail account, you can make various "folders" in your gmail account called labels. Now all these really are - are just a list of values with a name (its not actually a tree structure)
family
family/finance
However, Gmail will under the hood parse this into a tree structure.
The online gmail API will only return a list similar to what we have on the left
['family','family/eat/me','family/finance']
I want to parse this into a structure like
[{'name':'family','parent':None,'children':['family/eat/me','family/finance']},
{'name':'family/eat/me','parent':'family','children':[]},
{'name':'family/finance','parent':'family','children':[]}]
However, I am really stumped, anyone have any ideas on how to do this?

Information Extraction from Text into Structured Data with Python

I'm near a total outsider of programming, just interested in it.
I work in a Shipbrokering company and need to match between positions (which ship will be open at where, when) and orders (what kind of ships will be needed at where, when for what kind of employment).
And we send and receive such info (positions and orders) by emails to and from our principals and co-brokers.
There are thousands of such emails each day.
We do the matching by reading the emails manually.
I want to build an app to do the matching for us.
One important part of this app will do the information extraction from email text.
==> My question is how do I use Python to extract unstructured info into structured data.
Sample email of an order [annotation in the brackets, but is not included in the email]:
Email Subject: 20k dwt requirement, 20-30/mar, Santos-Conti
Content:
Acct ABC [Account Name]
Abt 20,000 MT Deadweight [Size of Ship Needed]
Delivery to make Santos [Delivery Point/Range, Owners will deliver the ship to Charterers here]
Laycan 20-30/Mar [Laycan (the time spread in which delivery can be accepted]
1 time charter with grains [What kind of Empolyment/Trade, Cargo]
Duration about 35 days [Duration]
Redelivery 1 safe port Continent [Redelivery Point/Range, Charterers will redeliver the ship back to Owners here.]
Broker name/email/phone...
End Email
Same email above can be written in many different ways - some writes in one line, some use l/c instead of laycan...
And there are emails for positions with ship's name, open port, date range, ship's deadweight and other specs.
How can I extract the info and put it into structured data, with Python?
Let's say I have put all email contents into text files.
Thanks.
Below is a possible approach:
Step 1: Classify the mails in categories using the subject and/or message in the mail.
As you stated one category is of mails requesting position and the other is of mails of order.
Machine Learning can be used to classify. You can use set of previous mails as training corpus. You might consider using NLTK(Natural Langauage Toolkit) for Python. Here is the link on text classification using NLTK.
Step 2: Once an email is identified as an order mail, process it to fetch the details(account name, size, time spread etc.) As you mentioned the challenge here is that there is no fixed format for these data. To solve this problem, you might consider preparing an exhaustive list of synonyms for each label(like for account the list could be like ['acct', 'a/c', 'account', 'acnt']). This should be done once, by going through a fixed volume of previous mails.
To make the solution more effective, you could consider implementing option for active learning
(i.e., prompt the user if in a mail a lable is found which is not found in any list. E.g. in a mail, if "accnt" is used, it wont be resolved, hence user should be prompted to ask in which category it falls.)
Once a lable is identifies, you can use basic string operations, to parse the email in a fetch relevant data in structured format.
You can refer to this discussion for a better understanding.

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