Spam filtering made easy for you

Overview

spammy

PyPI version Build Status Python Versions percentagecov Requirements Status License

Author: Tasdik Rahman
Latest version: 1.0.3

1   Overview

spammy : Spam filtering at your service

spammy powers the web app https://plino.herokuapp.com

2   Features

  • train the classifier on your own dataset to classify your emails into spam or ham
  • Dead simple to use. See usage
  • Blazingly fast once the classifier is trained. (See benchmarks)
  • Custom exceptions raised so that when you miss something, spammy tells you where did you go wrong in a graceful way
  • Written in uncomplicated python
  • Built on top of the giant shoulders of nltk

3   Example

[back to top]

  • Your data directory structure should be something similar to
$ tree /home/tasdik/Dropbox/projects/spammy/examples/test_dataset
/home/tasdik/Dropbox/projects/spammy/examples/test_dataset
├── ham
│   ├── 5458.2001-04-25.kaminski.ham.txt
│   ├── 5459.2001-04-25.kaminski.ham.txt
│   ...
│   ...
│   └── 5851.2001-05-22.kaminski.ham.txt
└── spam
    ├── 4136.2005-07-05.SA_and_HP.spam.txt
    ├── 4137.2005-07-05.SA_and_HP.spam.txt
    ...
    ...
    └── 5269.2005-07-19.SA_and_HP.spam.txt

Example

>>> import os
>>> from spammy import Spammy
>>>
>>> directory = '/home/tasdik/Dropbox/projects/spamfilter/data/corpus3'
>>>
>>> # directory structure
>>> os.listdir(directory)
['spam', 'Summary.txt', 'ham']
>>> os.listdir(os.path.join(directory, 'spam'))[:3]
['4257.2005-04-06.BG.spam.txt', '0724.2004-09-21.BG.spam.txt', '2835.2005-01-19.BG.spam.txt']
>>>
>>> # Spammy object created
>>> cl = Spammy(directory, limit=100)
>>> cl.train()
>>>
>>> SPAM_TEXT = \
... """
... My Dear Friend,
...
... How are you and your family? I hope you all are fine.
...
... My dear I know that this mail will come to you as a surprise, but it's for my
... urgent need for a foreign partner that made me to contact you for your sincere
... genuine assistance My name is Mr.Herman Hirdiramani, I am a banker by
... profession currently holding the post of Director Auditing Department in
... the Islamic Development Bank(IsDB)here in Ouagadougou, Burkina Faso.
...
... I got your email information through the Burkina's Chamber of Commerce
... and industry on foreign business relations here in Ouagadougou Burkina Faso
... I haven'disclose this deal to any body I hope that you will not expose or
... betray this trust and confident that I am about to repose on you for the
... mutual benefit of our both families.
...
... I need your urgent assistance in transferring the sum of Eight Million,
... Four Hundred and Fifty Thousand United States Dollars ($8,450,000:00) into
... your account within 14 working banking days This money has been dormant for
... years in our bank without claim due to the owner of this fund died along with
... his entire family and his supposed next of kin in an underground train crash
... since years ago. For your further informations please visit
... (http://news.bbc.co.uk/2/hi/5141542.stm)
... """
>>> cl.classify(SPAM_TEXT)
'spam'
>>>

3.1   Accuracy of the classifier

>>> from spammy import Spammy
>>> directory = '/home/tasdik/Dropbox/projects/spammy/examples/training_dataset'
>>> cl = Spammy(directory, limit=300)  # training on only 300 spam and ham files
>>> cl.train()
>>> data_dir = '/home/tasdik/Dropbox/projects/spammy/examples/test_dataset'
>>>
>>> cl.accuracy(directory=data_dir, label='spam', limit=300)
0.9554794520547946
>>> cl.accuracy(directory=data_dir, label='ham', limit=300)
0.9033333333333333
>>>

NOTE:

4   Installation

[back to top]

NOTE: spammy currently supports only python2

Install the dependencies first

$ pip install nltk==3.2.1, beautifulsoup4==4.4.1

To install use pip:

$ pip install spammy

or if you don't have pip``use ``easy_install

$ easy_install spammy

Or build it yourself (only if you must):

$ git clone https://github.com/tasdikrahman/spammy.git
$ python setup.py install

4.1   Upgrading

To upgrade the package,

$ pip install -U spammy

4.2   Installation behind a proxy

If you are behind a proxy, then this should work

$ pip --proxy [username:password@]domain_name:port install spammy

5   Benchmarks

[back to top]

Spammy is blazingly fast once trained

Don't believe me? Have a look

>>> import timeit
>>> from spammy import Spammy
>>>
>>> directory = '/home/tasdik/Dropbox/projects/spamfilter/data/corpus3'
>>> cl = Spammy(directory, limit=100)
>>> cl.train()
>>> SPAM_TEXT_2 = \
... """
... INTERNATIONAL MONETARY FUND (IMF)
... DEPT: WORLD DEBT RECONCILIATION AGENCIES.
... ADVISE: YOUR OUTSTANDING PAYMENT NOTIFICATION
...
... Attention
... A power of attorney was forwarded to our office this morning by two gentle men,
... one of them is an American national and he is MR DAVID DEANE by name while the
... other person is MR... JACK MORGAN by name a CANADIAN national.
... This gentleman claimed to be your representative, and this power of attorney
... stated that you are dead; they brought an account to replace your information
... in other to claim your fund of (US$9.7M) which is now lying DORMANT and UNCLAIMED,
...  below is the new account they have submitted:
...                     BANK.-HSBC CANADA
...                     Vancouver, CANADA
...                     ACCOUNT NO. 2984-0008-66
...
... Be further informed that this power of attorney also stated that you suffered.
... """
>>>
>>> def classify_timeit():
...    result = cl.classify(SPAM_TEXT_2)
...
>>> timeit.repeat(classify_timeit, number=5)
[0.1810469627380371, 0.16121697425842285, 0.16121196746826172]
>>>

6   Contributing

[back to top]

Refer CONTRIBUTING page for details

6.1   Roadmap

  • Include more algorithms for increased accuracy
  • python3 support

7   Licensing

[back to top]

Spammy is built by Tasdik Rahman and licensed under GPLv3.

spammy Copyright (C) 2016 Tasdik Rahman([email protected])

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see <http://www.gnu.org/licenses/>.

You can find a full copy of the LICENSE file here

8   Credits

[back to top]

If you'd like give me credit somewhere on your blog or tweet a shout out to @tasdikrahman, well hey, I'll take it.

9   Donation

If you have found my little bits of software of any use to you, you can help me pay my internet bills :)

Paypal badge

Instamojo

gratipay

patreon

Owner
Tasdik Rahman
Engineering Platform @gojek, former SRE @razorpay. Weekend chef, Backpacker, past contributor to @oVirt (Redhat).
Tasdik Rahman
StarGAN - Official PyTorch Implementation

StarGAN - Official PyTorch Implementation ***** New: StarGAN v2 is available at https://github.com/clovaai/stargan-v2 ***** This repository provides t

Yunjey Choi 5.1k Dec 30, 2022
Basic Utilities for PyTorch Natural Language Processing (NLP)

Basic Utilities for PyTorch Natural Language Processing (NLP) PyTorch-NLP, or torchnlp for short, is a library of basic utilities for PyTorch NLP. tor

Michael Petrochuk 2.1k Jan 01, 2023
pysentimiento: A Python toolkit for Sentiment Analysis and Social NLP tasks

A Python multilingual toolkit for Sentiment Analysis and Social NLP tasks

297 Dec 29, 2022
Transformer Based Korean Sentence Spacing Corrector

TKOrrector Transformer Based Korean Sentence Spacing Corrector License Summary This solution is made available under Apache 2 license. See the LICENSE

Paul Hyung Yuel Kim 3 Apr 18, 2022
Official PyTorch code for ClipBERT, an efficient framework for end-to-end learning on image-text and video-text tasks

Official PyTorch code for ClipBERT, an efficient framework for end-to-end learning on image-text and video-text tasks. It takes raw videos/images + text as inputs, and outputs task predictions. ClipB

Jie Lei 雷杰 612 Jan 04, 2023
A collection of scripts to preprocess ASR datasets and finetune language-specific Wav2Vec2 XLSR models

wav2vec-toolkit A collection of scripts to preprocess ASR datasets and finetune language-specific Wav2Vec2 XLSR models This repository accompanies the

Anton Lozhkov 29 Oct 23, 2022
A sentence aligner for comparable corpora

About Yalign is a tool for extracting parallel sentences from comparable corpora. Statistical Machine Translation relies on parallel corpora (eg.. eur

Machinalis 128 Aug 24, 2022
Research code for "What to Pre-Train on? Efficient Intermediate Task Selection", EMNLP 2021

efficient-task-transfer This repository contains code for the experiments in our paper "What to Pre-Train on? Efficient Intermediate Task Selection".

AdapterHub 26 Dec 24, 2022
The (extremely) naive sentiment classification function based on NBSVM trained on wisesight_sentiment

thai_sentiment The naive sentiment classification function based on NBSVM trained on wisesight_sentiment วิธีติดตั้ง pip install thai_sentiment==0.1.3

Charin 7 Dec 08, 2022
AI Assistant for Building Reliable, High-performing and Fair Multilingual NLP Systems

AI Assistant for Building Reliable, High-performing and Fair Multilingual NLP Systems

Microsoft 37 Nov 29, 2022
Smart discord chatbot integrated with Dialogflow to manage different classrooms and assist in teaching!

smart-school-chatbot Smart discord chatbot integrated with Dialogflow to interact with students naturally and manage different classes in a school. De

Tom Huynh 5 Oct 24, 2022
Journey is a NLP-Powered Developer assistant

Journey Journey is a NLP-Powered Developer assistant Using on the powerful Natural Language Processing library Mindmeld, this projects aims to assist

Christian Eilers 21 Dec 11, 2022
Code for the paper "A Simple but Tough-to-Beat Baseline for Sentence Embeddings".

Code for the paper "A Simple but Tough-to-Beat Baseline for Sentence Embeddings".

1.1k Dec 27, 2022
Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering

Disfl-QA is a targeted dataset for contextual disfluencies in an information seeking setting, namely question answering over Wikipedia passages. Disfl-QA builds upon the SQuAD-v2 (Rajpurkar et al., 2

Google Research Datasets 52 Jun 21, 2022
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis (SV2TTS)

This repository is an implementation of Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis (SV2TTS) with a vocoder that works in real-time. Feel free to check my the

Corentin Jemine 38.5k Jan 03, 2023
Japanese synonym library

chikkarpy chikkarpyはchikkarのPython版です。 chikkarpy is a Python version of chikkar. chikkarpy は Sudachi 同義語辞書を利用し、SudachiPyの出力に同義語展開を追加するために開発されたライブラリです。

Works Applications 48 Dec 14, 2022
[WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs

New Benchmarks for Learning on Non-Homophilous Graphs Here are the codes and datasets accompanying the paper: New Benchmarks for Learning on Non-Homop

94 Dec 21, 2022
Shared code for training sentence embeddings with Flax / JAX

flax-sentence-embeddings This repository will be used to share code for the Flax / JAX community event to train sentence embeddings on 1B+ training pa

Nils Reimers 23 Dec 30, 2022
Unsupervised text tokenizer focused on computational efficiency

YouTokenToMe YouTokenToMe is an unsupervised text tokenizer focused on computational efficiency. It currently implements fast Byte Pair Encoding (BPE)

VK.com 847 Dec 19, 2022
Grading tools for Advanced NLP (11-711)Grading tools for Advanced NLP (11-711)

Grading tools for Advanced NLP (11-711) Installation You'll need docker and unzip to use this repo. For docker, visit the official guide to get starte

Hao Zhu 2 Sep 27, 2022