[ENH] Heuristic extraction of forwarded mails
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enhancement
- Dominant language
- Python
- Stars
- 377
- Forks
- 280
- Avg merge
- 2d 2h
- Merged PRs (30d)
- 10
Description
As there are often mails being forwarded to security departments, i.e.
The mail followed by the forwarded mail.
Greetings
Jens
________________________________
From: Name <mail@gmail.com>
Sent: Friday, 20 February 2026 11:43
To: Other Name
Subject: Are you in the office?
or
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=us-ascii">
<style type="text/css" style="display:none;"><!-- P {margin-top:0;margin-bottom:0;} --></style>
</head>
<body dir="ltr">
<div id="divtagdefaultwrapper" style="font-size:12pt;color:#000000;font-family:Calibri,Helvetica,sans-serif;" dir="ltr">
<p>Hello,</p>
<p><br>
</p>
<br>
<br>
<div style="color: rgb(0, 0, 0);">
<hr tabindex="-1" style="display:inline-block; width:98%">
<div id="divRplyFwdMsg" dir="ltr"><font face="Calibri, sans-serif" color="#000000" style="font-size:11pt"><b>From:</b> Name <mail@gmail.com><br>
<b>Sent:</b> Friday, 20 February 2026 11:43<br>
<b>To:</b> Other Name <br>
<b>Subject:</b> Are you in the office?</font>
<div> </div>
</div>
<div>
<div dir="ltr">
<div dir="ltr"><br>
</div>
</div>
</div>
</div>
</div>
</body>
</html>
so extracting the partial inline mails as dependent mail objects seems to be a useful feature
[I would be willing to try to implement this, if it is wanted]
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the Python entry point that processes forwarded mail content, then compare it with the plain-text and HTML examples in the issue. Done means partial inline forwarded mails are extracted and represented as dependent mail objects, with behavior covering both shown formats.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- backend
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100