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TempCatcher, identify spam emails on clean domains.

What is TempCatcher?

TempCatcher is a service which provides intelligence on temporary email addresses.

Why use TempCatcher?

Our service is the logical next step If you have exhausted all other solutions in your battle against spam (domain white-listing / blacklisting).

How do i use TempCatcher?

Please refer to quick start guide

Where do you get your data?

We aggregate our data from a variety of known spam providers.

Do you offer any paid services?

Yes, we offer a more simple "checks" api which allows you to send an email via http(s) and check if that is in our database.

For enterprise customers also provide intelligence on phone numbers as well.

if you are interested in these services please email contact@tempcatcher.com


Quick Start guide

1) Install TempCatcher api.

pip install tempcatcher

2) Example code:

from tempcatcher import *
t = TempCatcher()

email, status = t.check(input("Input email you would like to check: "), dns = True)

match status:
    case 0:
        print(f"Email: `{email}` was found in the tempcatcher data. (spam)")
    case 1:
        print(f"Email: `{email}` was not found in the tempcatcher data. (not spam)")
    case 2:
        print(f"Email was formatted incorrectly.")
    case 3:
        print(f"Email: `{email}` Could not find DNS MX record assocciated with domain")
    case _:
        print(f"How did we get here?")
del t # join update thread

3) Known Issues.

On windows / NT you may get a UnicodeDecodeError when trying to import tempcatcher,

the quickest solution is to add -X utf8 to your command arguments,

but here is a link to more in-depth analysis / help.

Metadata

Release files for TempCatcher 1.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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Source distribution for TempCatcher 1.0.0
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Table of built distributions (wheels) for TempCatcher 1.0.0
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tempcatcher-1.0.0-py3-none-any.whl Python 3 none any Details

Total release size: 34.7 kB

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