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ONLYOFFICE is a powerful open-source service that can bring document, spreadsheet, and presentation editing to web apps written in any programming language. In this article, we will tell you how to integrate ONLYOFFICE into your Python app.
For this, we will create a simple document management system on Python and integrate ONLYOFFICE document editors into it. This is going to be easier than you think.
Blockchain is the way of the future. It is not farfetched to think that the future will be built around this emerging technology. Blockchain started off as a public, permissionless technology, and later, another type of blockchain was introduced, each for its own specific set of use cases. Public/permissionless blockchains are open, decentralized, and slow, whereas private/permissioned blockchains are closed and centralized, either partially or completely.
In this article, I am going to discuss what you need to learn in order to start building apps that use blockchain technology. When I first started learning blockchain, a lot of questions popped into my head. What are the different types of blockchains? Which programming languages should I use to program efficiently? And what are the platforms for blockchain development?
A lot of beginner tutorials start with “Hello World” examples. There are plenty of websites that use a calculator application as a kind of “Hello World” for GUI beginners. Calculators are a good way to learn because they have a set of widgets that you need to lay out in an orderly fashion. They also require a certain amount of logic to make them work correctly. For this calculator, let’s focus on being able to do the following:
I think that supporting these four functions is a great starting place and also give you plenty of room for enhancing the application on your own.
As I noted in this post, RSA encryption is often carried out reusing exponents. Sometimes, the exponent is exponent 3, which is subject to an attack we’ll describe below [1]. (The most common exponent is 65537.)
Suppose the same message m is sent to three recipients and all three use exponent e= 3. Each recipient has a different modulus Ni, and each will receive a different encrypted message
The most common way to test whether a large number is prime is the Miller-Rabin test. If the test says a number is composite, it's definitely composite. Otherwise, the number is very likely, but not certain, to be prime. A pseudoprime is a composite number that slips past the Miller-Rabin test. (Actually, a strong pseudoprime. More on that below.)
The Miller-Rabin test is actually a sequence of tests, one for each prime number. First, you run the test associated with 2, then the test associated with 3, then the one associated with 5, etc. If we knew the smallest numbers for which these tests fail, then for smaller numbers, we know for certain that they're prime if they pass. In other words, we can turn the Miller-Rabin test for probable primes into a test for provable primes.
In this screencast, we will learn how to turn your Python code into a Windows executable file using the PyInstaller project.
You can also read the chapter this video is based on here or get the book on Leanpub
This week we welcome Lorena Mesa (@loooorenanicole) as our PyDev of the Week! Lorena is an organizer for the PyLadies Chicago group and a director at the Python Software Foundation. You can check out some of the things that she is up to on her blog or via her Github page. Let’s spend a few moments getting to know her better!
Hmmm…I have been told that I’m a bit eclectic. So let’s start with the basics. In my day-to-day gig I am a proud member of GitHub’s software intelligence systems team as a data engineer. In my extra hours I do such things as co-organize PyLadies Chicago and serve as a Director for the Python Software Foundation.
Time for a news brief! This compilation of notable quotes come as part our research on Big Data. Listen in to learn about the languages and tools devs are using for their Big Data apps. (Hint: R, Python, and Hadoop feature pretty prominently.)
These podcasts are compiled from conversations our analyst Tom Smith has had with industry experts from around the world as part of his work on our research guides.
Machine learning is no doubt the most trending topic right now, and python is the most used versatile language in machine learning.
In this article, I’ll tell you about some of the most used python function maps in machine learning.
Here's an oversimplified survey of cryptographic hash functions: everyone used to use MD5, now they use some variation on SHA.
There's some truth to that. MD5 was very popular and remains popular years after it was proven insecure. And now, variations on SHA like SHA1 and SHA256 are commonly used. But there are a lot more cryptographic hash functions in common use.
Original article published by Cristián Rojas at Hackmetrix Blog
The EQUIFAX USA event of 2017 put a spotlight an under-considered aspect of software security: it’s not just our code that we need to secure. The facts of the case are widely known, but its cause? Not so much. Little is said about the fact that this leak would not have taken place if the developers of the EQUIFAX application had upgraded their Apache Struts web framework to a more secure version.
Now that we have shown that it is easy to do standard NLP, next up is Deep Learning. As you can see, NLP, Machine Learning, Deep Learning, and more are all in your reach for building your own AI as a Service using tools from Cloudera. These can run in public or private clouds at scale. Now you can run and integrate machine learning services, computer vision APIs, and anything you have created in-house with your own Data Scientists. The YOLO pre-trained model will download the image to /tmp from the URL to process it. The Python 3 script will also download the GLUONCV model for YOLO3.
Using Pre-trained Model:
Consider the following code:
def max(m: int, n: int) -> int:
if m >= n:
return m
elif n >= m:
return n
else:
raise Exception(f"Design Error: {vars()}")
Prior to beginning any project, most development teams go through several meetings to decide the best language for their software. Many times this discussion boils down to Python and Golang. In this Golang vs. Python blog, I'll be comparing the two languages head-on, on various parameters that will help you decide as a developer which language is best suited for you. The parameters of comparison are:
Now let's get started. Before we get around to comparing Golang vs. Python, let me give you a brief introduction to both these languages.
Welcome to the world of machine learning with scikit-learn. Machine learning can be overwhelming at times, and this is partly due to a large number of tools that are available on the market. This post will simplify this process of tool selection down to one — scikit-learn.
In this series, you will learn how to construct an end-to-end machine learning pipeline using some of the most popular algorithms that are widely used in industry and professional competitions, such as Kaggle.
In this screencast, we will learn how to turn your Python application into a Windows installer using Inno Setup.
While developing your lambda functions, debugging may become a problem. As a person who benefits a lot from step-by-step debugging, I had difficulty debugging lambda functions. I got lost in the logs. Redeploying and trying again with different parameters over and over... then, I found the AWS Serverless Application Model (SAM) Command Line Interface (CLI). The AWS SAM CLI lets you debug your AWS Lambda functions in a good, old, step-by-step way.
If you don’t know AWS SAM CLI, you should definitely check it out here. Basically, using SAM CLI, you can locally run and test your Lambda functions in a local environment that simulates the AWS runtime environment. Without the burden of redeploying your application after each change, you can develop faster in an iterative way.