Gefilte Fish automates the creation of GMail filters

Gefilte Fish: GMail filter maker

Gefilte Fish automates the creation of GMail filters. You write a Python program using gefilte's domain-specific language (DSL), run the program, and import the XML it creates.

Sample Python

Here's an example of creating filters:

from gefilte import GefilteFish, GFilter

# Specialize GFilter for repo-specific GitHub notifications.
class GitHubFilter(GFilter):
    def repo(self, repo_name):
        org, repo = repo_name.split("/")
        return self.list_(f"{repo}.{org}.github.com")

# Make the filter-maker and use its DSL. All of the methods of GitHubFilter
# are now usable as global functions.
fish = GefilteFish(GitHubFilter)
with fish.dsl():

    # Google's spam moderation messages should never get sent to spam.
    with replyto("[email protected]"):
        never_spam()
        mark_important()

    # If the subject and body have these, label it "liked".
    with subject(exact("[Confluence]")).has(exact("liked this page")):
        label("liked")

    # We get a lot of notifications from GitHub,
    # we'll make a number of filters that apply.
    with from_("[email protected]"):

        # Skip the inbox (archive them).
        skip_inbox()

        # Notifications from some repos are special.
        with repo("myproject/tasks") as f:
            label("todo")
            with f.elif_(repo("otherproject/something")) as f:
                label("otherproject")
                with f.else_():
                    # But everything else goes into "Code reviews".
                    label("Code reviews")

        # Delete annoying bot messages.
        with from_("renovate[bot]"):
            delete()

        # GitHub sends to synthetic addresses to provide information.
        with to("[email protected]"):
            label("mine").star()

        with has('Merged, "into master"'):
            label("merged")

        # Data-driven filters. I'm mentoring these people
        # on these projects so make sure they get my attention.
        for who, where in [
            ("Joe Junior", "myproject/component1"),
            ("Francine Firstyear", "myproject/thing2"),
        ]:
            with from_(exact(who)).repo(where):
                label("mentee").star().mark_important()

    # Some inbound addresses come to me. Mark them so
    # I understand what I'm looking at in my inbox.
    for toaddr, the_label in [
        ("[email protected]", "info@"),
        ("[email protected]", "security@"),
        ("[email protected]", "con20"),
        ("[email protected]", "con21"),
    ]:
        with to(toaddr):
            label(the_label)

print(fish.xml())

The with clauses create nested contexts in which all of the enclosing filters apply. The elif_ and else_ structures are a little awkward, but easier than manually making filters with the same effect.

Installing filters

When you run your program, it will create XML output. Save that output in a file. In your browser, go to GMail - Settings - Filters and Blocked Addresses. Then "Import Filters", "Choose File", "Open File", then "Create Filters".

Note

Be careful with the "Apply new filters to existing email" choice. "Delete" actions that run on incoming email will delete individual messages, but when run during import, they delete the entire conversation the message is in.

For more information about filtering in GMail, see Search operators you can use with Gmail.

GitHub

https://github.com/nedbat/gefilte