### Set Up Development Environment

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/contributing.md

Clone the repository, create and activate a virtual environment, and install development dependencies. This is the initial setup for contributing code.

```bash
git clone https://github.com/mags0ft/spamfilter.git
cd spamfilter
python3 -m venv .venv
source .venv/bin/activate  # On Windows use .venv\Scripts\activate
pip install -e .[dev]
```

--------------------------------

### Install Spamfilter using Pip

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/installation.md

Use this command to install the spamfilter library via pip, the standard Python package installer. This is the recommended and easiest method.

```bash
pip install spamfilter
```

--------------------------------

### Install Spamfilter with Transformers Support

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/installation.md

Install spamfilter with the '[transformers]' extra dependency to leverage machine learning text classification using 🤗 Transformers.

```bash
pip install spamfilter[transformers]
```

--------------------------------

### Install Spamfilter using Python -m pip

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/installation.md

If the standard 'pip install' command fails, likely due to PATH issues, use this alternative command to install spamfilter via the Python interpreter.

```bash
python3 -m pip install spamfilter
```

--------------------------------

### Install Spamfilter with API Support

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/installation.md

Install spamfilter with the '[api]' extra dependency to enable support for third-party API calling features.

```bash
pip install spamfilter[api]
```

--------------------------------

### Install Spamfilter with OpenAI Integration

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/installation.md

Install spamfilter with the '[openai]' extra dependency to enable integration with OpenAI services.

```bash
pip install spamfilter[openai]
```

--------------------------------

### Verify Spamfilter Installation

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/get_started.md

Run this Python code in the console to verify that the spamfilter library has been installed successfully by checking its version.

```python
>>> import spamfilter
>>> spamfilter.__version__
'v3.0.0'
>>> 
```

--------------------------------

### Install Spamfilter with Development Dependencies

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/installation.md

Install spamfilter with the '[dev]' extra dependency to include all necessary packages for development purposes.

```bash
pip install spamfilter[dev]
```

--------------------------------

### Create and Use Chat Pipeline

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/premade.md

Demonstrates creating a chat pipeline with `create_pipeline` and accessing the default `chatPipeline` object.

```python
from spamfilter.premade import chat

c1 = chat.create_pipeline(...args)
c2 = chat.chatPipeline
```

--------------------------------

### Fine-tune Article Pipeline with create_pipeline

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/premade.md

Illustrates creating an article pipeline with `create_pipeline`, allowing adjustments to parameters for high-quality writing environments.

```python
from spamfilter.premade import article

c = article.create_pipeline(
    bypass_protection: bool = True,
    length_filter: bool = True,
    min_: int = 400,
    max_: int = 300_000,
    wordlength_filter: bool = True,
    max_word_length: int = 50,
    max_num_too_long_words: int = 3,
    capitals_filter: bool = True,
    capitals_percentage: float = 0.4,
    capitals_mode: str = "normal",
    specialchars_filter: bool = True,
    profanity_filter: bool = False,
    profanity_blocklist_filepath: str = ""
)
```

--------------------------------

### Create and Use a Pipeline with Multiple Filters

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/pipelines.md

Demonstrates creating a pipeline with Capitals, SpecialChars, and Length filters. The pipeline checks if a string passes all filter conditions, including length constraints.

```python
from spamfilter.pipelines import Pipeline
from spamfilter.filters import (
    Capitals,
    SpecialChars,
    Length
)

m = Pipeline([
    Capitals(),
    SpecialChars(mode = "crop"),
    Length(min_ = 20, max_ = 60)
])

print(
    m.check("Test string!").passed
)
```

--------------------------------

### Fine-tune Chat Pipeline with create_pipeline

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/premade.md

Shows how to customize a chat pipeline using `create_pipeline` with various arguments for fine-grained control.

```python
from spamfilter.premade import chat

c = chat.create_pipeline(
    bypass_protection: bool = True,
    length_filter: bool = True,
    min_: int = 1,
    max_: int = 200,
    wordlength_filter: bool = True,
    max_word_length: int = 20,
    max_num_too_long_words: int = 1,
    capitals_filter: bool = True,
    capitals_percentage: float = 0.3,
    capitals_mode: str = "crop",
    specialchars_filter: bool = True,
    profanity_filter: bool = False,
    profanity_blocklist_filepath: str = ""
)
```

--------------------------------

### Use Default Chat Pipeline

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/premade.md

Provides the code to instantiate the default, ready-to-use chat pipeline without any custom configuration.

```python
from spamfilter.premade import chat

c = chat.chatPipeline
```

--------------------------------

### Create and use a basic spamfilter pipeline

Source: https://github.com/mags0ft/spamfilter/blob/master/README.md

Demonstrates how to create a simple spam filtering pipeline using Length and SpecialChars filters and then test a string against it. The pipeline is configured to crop strings between 10 and 200 characters and limit the use of special characters.

```python
from spamfilter.filters import Length
from spamfilter.filters import SpecialChars
from spamfilter.pipelines import Pipeline

# create a new pipeline
m = Pipeline([
    # length of 10 to 200 chars, crop if needed
    Length(min_=10, max_=200, mode="crop"),
    # limit use of special characters
    SpecialChars(mode="normal")
])

# test a string against it
TEST_STRING = "This is a test string."
print(m.check(TEST_STRING).passed)
```

--------------------------------

### Use Default Article Pipeline

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/premade.md

Shows how to access the default article pipeline object for immediate use in demanding writing platforms.

```python
from spamfilter.premade import article

c = chat.articlePipeline
```

--------------------------------

### Import Pipeline Class

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/pipelines.md

Import the Pipeline class from the spamfilter.pipelines module.

```python
from spamfilter.pipelines import Pipeline
```

--------------------------------

### Create a Result Object

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/results.md

Instantiate a Result object when you need to create your own. Ensure the spamfilter.results module is imported.

```python
from spamfilter.results import Result

r = Result(...args)
```

--------------------------------

### Use Premade Chat Pipeline

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/get_started.md

This Python code demonstrates how to create and use a premade chat pipeline from the spamfilter library to check if a given string is considered spam. It prints 'True' if the string passes the filter and 'False' otherwise.

```python
from spamfilter.premade import chat

c = chat.create_pipeline()

INPUT_STRING = "This is a test string."
print(c.check(INPUT_STRING).passed)
```

--------------------------------

### Import Single Filter

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/filters.md

Import a single filter class from the spamfilter.filters module.

```python
from spamfilter.filters import Filter
```

--------------------------------

### Import All Filters

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/filters.md

Import all filter classes from the spamfilter.filters module. Wildcard imports are generally discouraged.

```python
from spamfilter.filters import *
```

--------------------------------

### Import Multiple Filters

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/filters.md

Import several filter classes simultaneously from the spamfilter.filters module.

```python
from spamfilter.filters import (
    Capitals,
    Length,
    SpecialChars
)
```

--------------------------------

### Filter Construction

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/filters.md

Construct a filter instance with specified options and mode. The 'normal' mode is commonly used.

```python
Filter(**options, mode = "normal")
```

--------------------------------

### Default OpenAI Response Parsing Function

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/filters.md

The standard function for parsing responses from the OpenAI filter. It determines if a response indicates spam and extracts corrected text.

```python
RespFuncType = Callable[[dict[str, Union[bool, str]]], Tuple[bool, str]]

STD_RESP_FUNC: RespFuncType = lambda resp: (
    not resp["is_spam"],
    (resp["corrected_text"] if "corrected_text" in resp else ""),
)
```

--------------------------------

### Filter Check Method

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/filters.md

Use the check method of a filter instance to assess a string. It returns a tuple indicating success and the processed string.

```python
(passed: int, output_string: str)
```

--------------------------------

### Default Email Filter Regex

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/filters.md

The default regular expression pattern used by the Email filter for email address validation.

```regex
([a-zA-Z0-9+._-]+@[a-zA-Z0-9._-]+\.[a-zA-Z0-9_-]+)
```

--------------------------------

### Default MLTextClassifier Response Parsing Function

Source: https://github.com/mags0ft/spamfilter/blob/master/docs/filters.md

The default function for parsing results from the MLTextClassifier filter. It identifies spam or toxic content based on score.

```python
def _default_response_parsing_function(
    result: list[dict[str, Union[str, float]]],
) -> bool:
    """
    Default response parsing function that checks if the label
    is 'spam' or 'toxic'.
    """

    sorted_result = sorted(result, key=lambda x: x["score"], reverse=True)
    top_label: str = str(sorted_result[0]["label"]).lower()

    return top_label not in ["spam", "toxic", "hate", "abusive"]
```

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