1629017388
Python Library For Using SWI Prolog
swiplserver
A library that integrates SWI Prolog with Python.
swiplserver is a Python module designed for developers that want to use SWI Prolog in the implementation of a Python application. It allows running any query you could run from the SWI Prolog console (i.e. the "top level") from within your Python code. Answers to Prolog queries are returned as JSON.
The library integrates SWI Prolog by launching it and connecting to a special server running inside Prolog called the Prolog Language Server. Queries are run using the Python library. The library manages launching and shutting down the server automatically, making the process management invisible to the developer. The whole process should feel just like using any other library.
from swiplserver import PrologServer, PrologThread
with PrologServer() as server:
with server.create_thread() as prolog_thread:
result = prolog_thread.query("member(X, [color(blue), color(red)])")
print(result)
[{'X': {'functor': 'color', 'args': ['blue']}},
{'X': {'functor': 'color', 'args': ['red']}}]
To install and learn how to use the swiplserver Python library, see the docs.
While swiplserver automatically manages dealing with the Language Server in SWI Prolog, documentation for it is provided since it is intended to be used for integrating other programming languages with SWI Prolog as well. The code is available in this repository at: swiplserver/language_server.pl Read more in:
Supported Configurations
Should work on:
- SWI Prolog 8.2.2 or greater (may work on older builds, untested)
- Any Mac, Linux Variants or Windows that are supported by SWI Prolog
- Python 3.7 or later (may work on older builds, untested)
Has been tested with:
- Ubuntu 20.04.2 + SWI Prolog 8.3.22 + Python 3.7.8
- Windows 8.1 Pro 64 bit + SWI Prolog 8.2.4 + Python 3.8.1
- MacOS Catalina/Big Sur + SWI Prolog 8.3.24 + Python 3.7.4
Performance
If you're interested in rough performance overhead of the approach this library takes. On a late 2013 macbook pro the per call overhead of the library for running a Prolog query is about:
- 170 uSec per call using TCP/IP localhost
- 145 uSec per call using Unix Domain Sockets
Download Details:
Author: EricZinda
Source Code: https://github.com/EricZinda/swiplserver
What is GEEK
Buddha Community
1619518440
top 30 Python Tips and Tricks for Beginners
Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.
1) swap two numbers.
2) Reversing a string in Python.
3) Create a single string from all the elements in list.
4) Chaining Of Comparison Operators.
5) Print The File Path Of Imported Modules.
6) Return Multiple Values From Functions.
7) Find The Most Frequent Value In A List.
8) Check The Memory Usage Of An Object.
…
#python #python hacks tricks #python learning tips #python programming tricks #python tips #python tips and tricks #python tips and tricks advanced #python tips and tricks for beginners #python tips tricks and techniques #python tutorial #tips and tricks in python #tips to learn python #top 30 python tips and tricks for beginners
1619510796
Lambda, Map, Filter functions in python
Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.
Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is
Syntax: x = lambda arguments : expression
Now i will show you some python lambda function examples:
#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map
1598811780
Top 7 Python Libraries Used For Hacking
python is one of the most go-for languages among the developers due to the availability of open-source libraries and frameworks. According to a survey report, Python is the top language preferred for Statistical Modelling, and an overwhelming majority of practitioners prefer Python as the language for statistical works.
Python has become a favourite language for hackers these days. The reason is the presence of pre-built tools and libraries, which makes hacking easy. In fact, the language is adequate for ethical hacking as ethical hackers need to develop smaller scripts, and Python fulfils this criterion.
Below here, we listed down the top 7 Python libraries used in hacking.
1| Requests
Stars: 43.3k
**About: **Requests is a simple HTTP library for Python that allows a user to send HTTP/1.1 requests extremely easily. This library helps in building robust HTTP applications and includes intuitive features such as automatic content decompression and decoding, connection timeouts, basic & digits authentication, among others.
Know more here.
2| Scapy
Stars: 5.5k
About: Scapy is a powerful Python-based interactive packet manipulation program and library. This library is able to forge or decode packets of a wide number of protocols, send them on the wire, capture them, store or read them using pcap files, match requests, and more. It allows the construction of tools that can easily scan or attack networks. It is designed to allow fast packet prototyping by using default values that work. It can also perform tasks such as sending invalid frames, injecting your own 802.11 frames, combining techniques, such as VLAN hopping with ARP cache poisoning, VOIP decoding on WEP encrypted channel, etc., which most other tools cannot.
Know more here.
3| IMpacket
**Stars: **5.3k
**About: **IMpacket is a library that includes a collection of Python classes for working with network protocols. It is focused on providing low-level programmatic access to network packets. It allows Python developers to craft and decode network packets in a simple and consistent manner. The library provides a set of tools as examples of what can be done within the context of this library.
Know more here.
4| Cryptography
**Stars: **3.5k
**About: **Cryptography is a package which provides cryptographic recipes and primitives to Python developers. It includes both high-level recipes and low-level interfaces to common cryptographic algorithms such as symmetric ciphers, message digests and key derivation functions. This library is broadly divided into two levels. One is with safe cryptographic recipes that require little to no configuration choices. The other level is low-level cryptographic primitives, which are often dangerous and can be used incorrectly.
Know more here.
#developers corner #hacking tools #libraries for hacking #python #python libraries #python libraries used for hacking #python tools
1619571780
Top 20 Most Useful Python Modules or Packages
March 25, 2021 Deepak@321 0 Comments
Welcome to my blog, In this article, we will learn the top 20 most useful python modules or packages and these modules every Python developer should know.
Hello everybody and welcome back so in this article I’m going to be sharing with you 20 Python modules you need to know. Now I’ve split these python modules into four different categories to make little bit easier for us and the categories are:
- Web Development
- Data Science
- Machine Learning
- AI and graphical user interfaces.
Near the end of the article, I also share my personal favorite Python module so make sure you stay tuned to see what that is also make sure to share with me in the comments down below your favorite Python module.
#python #packages or libraries #python 20 modules #python 20 most usefull modules #python intersting modules #top 20 python libraries #top 20 python modules #top 20 python packages
1597751700
How To Compare Tesla and Ford Company By Using Magic Methods in Python
Magic Methods are the special methods which gives us the ability to access built in syntactical features such as ‘<’, ‘>’, ‘==’, ‘+’ etc…
You must have worked with such methods without knowing them to be as magic methods. Magic methods can be identified with their names which start with __ and ends with __ like init, call, str etc. These methods are also called Dunder Methods, because of their name starting and ending with Double Underscore (Dunder).
Now there are a number of such special methods, which you might have come across too, in Python. We will just be taking an example of a few of them to understand how they work and how we can use them.
1. init
class AnyClass:
def __init__():
print("Init called on its own")
obj = AnyClass()
The first example is _init, _and as the name suggests, it is used for initializing objects. Init method is called on its own, ie. whenever an object is created for the class, the init method is called on its own.
The output of the above code will be given below. Note how we did not call the init method and it got invoked as we created an object for class AnyClass.
Init called on its own
2. add
Let’s move to some other example, add gives us the ability to access the built in syntax feature of the character +. Let’s see how,
class AnyClass:
def __init__(self, var):
self.some_var = var
def __add__(self, other_obj):
print("Calling the add method")
return self.some_var + other_obj.some_var
obj1 = AnyClass(5)
obj2 = AnyClass(6)
obj1 + obj2
#python3 #python #python-programming #python-web-development #python-tutorials #python-top-story #python-tips #learn-python