Automation

Automatically Send Custom Named Certificates via Mail

Certificate-Launchpad After any event, sending certificates to attendees or participants is very frustrating & difficult task. So, this is where Certificate Launchpad comes in! Certificate Launchpad simplifies the process of sending Bulk Custom Certificates to Bulk Emails of Participants. Demo Getting Started Clone this repo git clone https://github.com/dhanrajdc7/Certificate-Launchpad Suggested IDE: JetBrains PyCharm IDE Install all dependencies from requirements.txt by using pip install -r requirements.txt Copy .env.sample and rename it .env using copy .env.sample .env on Windows cp env.sample .env on […]

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Simulation

A PowSyBl and Python integration based on GraalVM native image

PyPowSyBl The PyPowSyBl project gives access PowSyBl Java framework to Python developers. This Python integration relies on GraalVM to compile Java code to a native library. Installation PyPowSyBl is released on PyPi. First, make sure you have an up-to-date version of pip and setuptools: pip3 install –upgrade setuptools pip –user Then you can install PyPowSyBl using pip: pip3 install pypowsybl –user Build from sources Requirements: To build from sources and install PyPowSyBl package: git clone –recursive https://github.com/powsybl/pypowsybl.git export JAVA_HOME= pip3 […]

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Tool

Python microframework for building nature-inspired algorithms

NiaPy Nature-inspired algorithms are a very popular tool for solving optimization problems. Numerous variants of nature-inspired algorithms have been developed (paper 1, paper 2) since the beginning of their era. To prove their versatility, those were tested in various domains on various applications, especially when they are hybridized, modified or adapted. However, implementation of nature-inspired algorithms is sometimes a difficult, complex and tedious task. In order to break this wall, NiaPy is intended for simple and quick use, without spending […]

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Command-line Tools

A python based command line tool to compare Github Users or Repositories

gitcomp A simple python package with a CLI to compare GitHub users and repositories by associating a git_score to each entry which is a weighted sum of features mapped to a score. git_score for a user is calculated on the basis of followers, followers to following ratio, number of public gists and number of organisations a user is part of. For a public repository, the determining factors are number of forks, if the repository itself is forked or not, number […]

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Machine Learning

A super lightweight Lagrangian model for calculating millions of trajectories using ERA5 data

Easy-ERA5-Trck Easy-ERA5-Trck is a super lightweight Lagrangian model for calculating thousands (even millions) of trajectories simultaneously and efficiently using ERA5 data sets. It can implement super simplified equations of 3-D motion to accelerate integration, and use python multiprocessing to parallelize the integration tasks. Due to its simplification and parallelization, Easy-ERA5-Trck performs great speed in tracing massive air parcels, which makes areawide tracing possible. Another version using WRF output to drive the model can be found here. Caution: Trajectory calculation is […]

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Security

Remote control your Greenbone Vulnerability Manager

The Greenbone Vulnerability Management Tools gvm-tools are a collection of tools that help with remote controlling a Greenbone Security Manager (GSM) appliance and its underlying Greenbone Vulnerability Management (GVM) framework. The tools aid in accessing the communication protocols GMP (Greenbone Management Protocol) and OSP (Open Scanner Protocol). This module is comprised of interactive and non-interactive clients. The programming language Python is supported directly for interactive scripting. But it is also possible to issue remote GMP/OSP commands without programming in Python. […]

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Neural Machine Translation (NMT), NMT Leave a comment

Machine Translation Weekly 81: Unsupervsied MT and Parallel Sentence Mining

This week I am going to briefly comment on a paper that uses unsupervised machine translation to improve unsupervised scoring for parallel data mining. The title of the paper is Unsupervised Multilingual Sentence Embeddings for Parallel Corpus Mining, it has authors from Charles University and the University of the Basque Country and will appear at this year’s ACL student research workshop. The idea of the paper is quite simple. They took XLM, a BERT-like model that was trained for 100 […]

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Python

Python News: What’s New From May 2021?

If you want to get up to speed on what happened in the world of Python in May 2021, then you’ve come to the right place to get your news! May was a month of big events. The Pallets Projects, home to popular frameworks like Flask and Click, released new major versions of all six of its core projects. The Python Software Foundation (PSF) hosted PyCon US 2021, a virtual conference that delivered an authentic in-person experience. Let’s dive into […]

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Network

Convenient script for trading with python

quick_trade convenient script for trading with python. used: ├──ta by Darío López Padial (Bukosabino https://github.com/bukosabino/ta) ├──tensorflow (https://github.com/tensorflow/tensorflow) ├──pykalman (https://github.com/pykalman/pykalman) ├──plotly (https://github.com/plotly/plotly.py) ├──scipy (https://github.com/scipy/scipy) ├──pandas (https://github.com/pandas-dev/pandas) ├──numpy (https://github.com/numpy/numpy) └──iexfinance (https://github.com/addisonlynch/iexfinance) Algo-trading system with python. customize your strategy! import quick_trade.trading_sys as qtr from quick_trade import brokers import yfinance as yf import ccxt class My_trader(qtr.Trader): def strategy_sell_and_hold(self): ret = [] for i in self.df[‘Close’].values: ret.append(qtr.utils.SELL) self.returns = ret self.set_credit_leverages(1.0) self.set_open_stop_and_take() return ret a = My_trader(‘MSFT’, df=yf.download(‘MSFT’, start=’2019-01-01′)) a.set_pyplot() a.set_client(brokers.TradingClient(ccxt.binance())) a.strategy_sell_and_hold() a.backtest() find the […]

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Machine Learning

Custom integration to use Lobe with cameras in Home Assistant

Lobe This is a Home Assistant custom component for Lobe. Lobe is an AI tool that can classify images. This component lets you easily use an exported model along with another server to classify a camera entity’s feed with it. Installation Use HACS for the integration. You’ll also need a seperate server. Steps to install on another server: Install the Lobe library. Install Flask. Export a Tensorflow Lite model into a folder on the server. Copy over app.py and change […]

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