From 340ee5cbcf6c7944f0d74f58af243114e82a779a Mon Sep 17 00:00:00 2001 From: bytebutcher Date: Fri, 7 Jul 2023 11:33:32 +0200 Subject: [PATCH] #8 Adds documentation regarding usage of ListDisplayFilter, ObjectDisplayFilter, SQLDisplayFilter --- README.md | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index 7df0a77..b29d7a9 100644 --- a/README.md +++ b/README.md @@ -23,8 +23,9 @@ A Wireshark-like display filter various data formats, including Python dictionar 1.3 [Filtering Data](#filtering-data) -2. [Examples](#examples) -3. [Acknowledgements](#acknowledgements) +2. [Features](#features) +3. [Examples](#examples) +4. [Acknowledgements](#acknowledgements) ## Quick Start @@ -87,13 +88,12 @@ For example, let's filter male actors born between 1960 and 1964 whose names end filter_query = "gender == male and (age.born > 1960 and age.born < 1965) and name matches .*e$" filtered_data = df.filter(filter_query) print(list(filtered_data)) +[ + Actor(name=['Laurence', 'Fishburne'], age={'born': '1961'}, gender='male') +] ``` -This will output the filtered data: -```python -[Actor(name=['Laurence', 'Fishburne'], age={'born': '1961'}, gender='male')] -``` - +## Features Overall, PyDFQL supports a wide range of features, including: * **Data Sources**: ```Dictionaries```, ```Lists```, ```Objects```, ```SQL Databases``` * **Comparison Operators:** ```==```, ```!=```, ```<=```, ```<```, ```>=```, ```>```, ```~=```, ```~```, ```&```