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In the previous post we saw how a Go service can call a Python service using gRPC. Using gRPC to connect a Go and Python program together can be a great choice, but there’s a complexity price that goes with it. You need to manage one more service, deployment becomes more complex, and you need monitoring plus alerting for each service. Compared to a monolithic application, there is an order of magnitude more complexity.
In this post, we’re going to reduce the complexity of using gRPC by writing a shared library in Go that a Python program can consume directly. With this approach, there’s no networking involved and depending on the data types, no marshalling as well. Out of the several approaches of calling functions from a shared library in Python, we decided to use Python’s ctypes module.
Note: ctypes uses libffi under the hood. If you want to read some really scary C code - head over to the repo and start reading. :)
I’ll also show my workflow that is one of the big factors in my productivity. We’ll first write “pure” Go code, then write code to export it to a shared library. Then we’ll switch to the Python world and use Python’s interactive prompt to Play around with the code. Once we’re happy, we’ll use what we’ve learned in the interactive prompt to write a Python module.
Imagine you have a directory with data files, and you need to validate the integrity of these files. The directory contains a
sha1sum.txt file with a sha1 digital signature for every file. Go, with its concurrency primitives and ability to use all the cores of your machine, is much better suited to this task than Python.
Listing 1: sha1sum.txt
6659cb84ab403dc85962fc77b9156924bbbaab2c httpd-00.log 5693325790ee53629d6ed3264760c4463a3615ee httpd-01.log fce486edf5251951c7b92a3d5098ea6400bfd63f httpd-02.log b5b04eb809e9c737dbb5de76576019e9db1958fd httpd-03.log ff0e3f644371d0fbce954dace6f678f9f77c3e08 httpd-04.log c154b2aa27122c07da77b85165036906fb6cbc3c httpd-05.log 28fccd72fb6fe88e1665a15df397c1d207de94ef httpd-06.log 86ed10cd87ac6f9fb62f6c29e82365c614089ae8 httpd-07.log feaf526473cb2887781f4904bd26f021a91ee9eb httpd-08.log 330d03af58919dd12b32804d9742b55c7ed16038 httpd-09.log
Listing 1 shows an example of a digital signature file. It provides hash codes for all the different log files contained in the directory. This file can be used to verify that a log file was downloaded correctly or has not been tampered with. We’ll write Go code to calculate the hash code of each log file and then match it against the hash code listed in the digital signature file.
To speed this process up, we’ll calculate the digital signature of each file in a separate goroutine, spreading the work across all of the CPUs on our machine.
Michael #1: VS Code Device Simulator
pytest-check: stop on fail works fine, but failing tests marked with xfail show up as xpass. Gonna have to look into that. And might have to recruit Anthony to help out again.
pip install pytest==6.0.0rc1
pip install tinydb==3.15.2to get the tasks project to run right. I should have pinned that in the original setup.py.
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
No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas.
By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities.
Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly.
Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.
Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions.
Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events.
Simple to read and compose
Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building.
The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties.
Utilized by the best
Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player.
Massive community support
Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions.
Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking.
Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.
The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.
Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential.
The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.
#python development services #python development company #python app development #python development #python in web development #python software development
Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?
In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.
Swapping value in Python
Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead
>>> FirstName = "kalebu" >>> LastName = "Jordan" >>> FirstName, LastName = LastName, FirstName >>> print(FirstName, LastName) ('Jordan', 'kalebu')
#python #python-programming #python3 #python-tutorials #learn-python #python-tips #python-skills #python-development
Today you’re going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates.
In many situations you may find yourself having duplicates files on your disk and but when it comes to tracking and checking them manually it can tedious.
Heres a solution
Instead of tracking throughout your disk to see if there is a duplicate, you can automate the process using coding, by writing a program to recursively track through the disk and remove all the found duplicates and that’s what this article is about.
But How do we do it?
If we were to read the whole file and then compare it to the rest of the files recursively through the given directory it will take a very long time, then how do we do it?
The answer is hashing, with hashing can generate a given string of letters and numbers which act as the identity of a given file and if we find any other file with the same identity we gonna delete it.
There’s a variety of hashing algorithms out there such as
#python-programming #python-tutorials #learn-python #python-project #python3 #python #python-skills #python-tips
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.
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
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