Quickly find tokens (words, phrases, etc) within your data.

Data Filter is a lightweight data cleansing framework that can be easily extended to support different data types, structures or processing requirements. It natively supports the following data types:

• CSV files
• Text files
• Text strings

• Requirements
• Installation
• Basic Usage
• Features
  • Base
  • Filters
    • CSV
    • Text
    • TextFile

• Python 3.6+

To install, simply use pipenv (or pip):

>>> pipenv install datafilter

from datafilter import CSV

tokens = ["Lorem", "ipsum", "Volutpat est", "mi sit amet"]
data = CSV("test.csv", tokens=tokens)
data.save("filtered.csv")

In this example, we open a CSV file, search all rows for normalized tokens and flag them. The save method creates a new CSV file with all rows that weren't flagged.

from datafilter import Text

text = "Lorem ipsum dolor sit amet, consectetur adipiscing elit"
data = Text(text, tokens=["Lorem"])
print(next(data.results()))

In this example, we search a text string for normalized tokens. We can then iterator over the results using the .results() method, which returns a generator that yields formatted results.

from datafilter import TextFile

data = TextFile("test.txt", tokens=["Lorem", "ipsum"], re_split=r"(?<=\.)")
print(next(data.results()))

In this example, we open a text file and split the data based on a regular expression defined by re_split.

Data Filter was designed to be highly extensible. Common or useful filters can be easily reused and shared. A few example use cases include:

• Filters that can handle different data types such as Microsoft Word, Google Docs, etc.
• Filters that can handle incoming data from external APIs.

Abstract base class that's subclassed by every filter.

Base includes several methods to ensure data is properly normalized, formatted and returned. The .results() method is an @abstractmethod to enforce its use in subclasses.

type <list>

A list of strings that will be searched for within a set of data.

type <list>

A list of strings that will be removed during normalization.

Default

['0123456789', '(){}[]<>!?.:;,`\'"@#$%^&*+-|=~–—/\\_', '\t\n\r\x0c\x0b']

type <bool>

When True, token matching will be bidirectional.

Default

True

Note:

A common obfuscation method is to reverse the offending string or phrase. This helps detect those instances.

type <bool>

When True, tokens and data are converted to lowercase during normalization.

Default

True

Abstract method used to return results within a filter. This is defined by a Base subclass

Returns a translation table used during normalization.

Returns

type <dict>

Returns normalized data. Normalization includes converting data to lowercase and removing strings.

Accepts parameter data.

Returns

type <tuple>

Note:

Normalized data is returned as a tuple. The first element is the original data. The second element is the normalized data.

Returns parsed and formatted data.

Accepts parameter data.

Returns

type <dict>

Example

Assume we're searching for the token "Lorem" in a very short text string.

data = Text("Lorem ipsum dolor sit amet", tokens=["Lorem"])
print(next(data.results()))

The returned result would be formatted as:

{
    "data": "Lorem ipsum dolor sit amet",
    "flagged": True,
    "describe": {
        "tokens": {
            "detected": ["Lorem"],
            "count": 1,
            "frequency": {
                "Lorem": 1,
            },
        }
    },
}

Note:

.parse() should never be called directly. Use .results() instead.

Filters subclass and extend the Base class to support various data types and structure. This extensibility allows for the creation of powerful custom filters specifically tailored to a given task, data type or structure.

CSV is a subclass of Base and inherits all parameters.

type <str>

Path to a CSV file.

CSV is a subclass of Base and inherits all methods.

Saves results to a file.

Accepts parameter path. path is the absolute path and filename of the new file.

Text is a subclass of Base and inherits all parameters.

type <str>

A text string.

type <str>

A regular expression pattern or string that will be applied to text with re.split before normalization.

Text is a subclass of Base and inherits all methods.

Saves results to a file.

Accepts parameter path and endofline. path is the absolute path and filename of the new file. endofline is a line delimiter that will be added to the end of every row.

TextFile is a subclass of Base and inherits all parameters.

type <str>

Path to a text file.

type <str>

A regular expression pattern or string that will be applied to text with re.split before normalization.

TextFile is a subclass of Base and inherits all methods.

Saves results to a file.

Accepts parameter path and endofline. path is the absolute path and filename of the new file. endofline is a line delimiter that will be added to the end of every row.