This module is based on the s3git-go package that is invoked via foreign function interface (FFI).
DISCLAIMER: This software is still under development (although the storage format/model is stable) -- use at your own peril for now
Note that the API is not stable yet, you can expect minor changes/extensions
Please make sure you have a working Golang environment installed, otherwise you cannot build the shared library. See install golang for setting up a working Golang environment.
Also the s3git-go package needs to be available locally (
go get -d github.com/s3git/s3git-go).
$ go build -buildmode=c-shared -o s3git-py.so
Here are some common examples of typical tasks.
$ python3 >>> import s3git >>> repo = s3git.init_repository('.') >>> repo.add('hello s3git') >>> repo.commit('My first s3git commit from Python') >>> exit() $ s3git log --pretty 113b9e900588fd830deed131c0f2f2cdd88b4751286ecc4967d0d4990aff6821c2426425955ec104797b142e93204a604e4ba420b3b617724237476128333de8 My first s3git commit from Python $ s3git ls c518dc5f1d95258dc91f6d285e7ea7300f37dea4dd517173f2e23afe0cb52bc9d8eb18683cdcf377e96a2d5a81585e61f6d27fa5d017cad53836bd050e9f105f $ s3git cat c518dc5f1d95258dc91f6d285e7ea7300f37dea4dd517173f2e23afe0cb52bc9d8eb18683cdcf377e96a2d5a81585e61f6d27fa5d017cad53836bd050e9f105f hello s3git
>>> import s3git >>> repo = s3git.clone('s3://s3git-spoon-knife', '.', access='AKIAJYNT4FCBFWDQPERQ', secret='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') >>> for l in repo.list(''): >>> print(l)
>>> import s3git >>> repo = s3git.init_repository('.') >>> repo.add('hello s3git') >>> repo.add('Python rocks') >>> repo.add(open('local-file.txt', 'rb')) >>> for l in repo.list(''): >>> repo.get(l).read()
>>> import s3git >>> repo = s3git.init_repository('.') >>> repo.add('string 1') >>> repo.commit('first commit') >>> repo.add('string 2') >>> repo.commit('second commit') >>> for c in repo.list_commits(): >>> print(c['Message'])
>>> import s3git >>> repo = s3git.init_repository('.') >>> repo.add('just some stuff') >>> repo.add('more stuff') >>> repo.add('and yet more stuff') >>> repo.commit('initial commit') >>> repo.remote_add('primary', 's3://s3git-spoon-knife', access='AKIAJYNT4FCBFWDQPERQ', secret='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') >>> repo.push()
>>> import s3git >>> repo = s3git.init_repository('.') >>> repo.snapshot_create("Initial snapshot") >>> repo.snapshot_list("")
Contributions are welcome, please submit a pull request for any enhancements.
A multi-cloud approach is nothing but leveraging two or more cloud platforms for meeting the various business requirements of an enterprise. The multi-cloud IT environment incorporates different clouds from multiple vendors and negates the dependence on a single public cloud service provider. Thus enterprises can choose specific services from multiple public clouds and reap the benefits of each.
Given its affordability and agility, most enterprises opt for a multi-cloud approach in cloud computing now. A 2018 survey on the public cloud services market points out that 81% of the respondents use services from two or more providers. Subsequently, the cloud computing services market has reported incredible growth in recent times. The worldwide public cloud services market is all set to reach $500 billion in the next four years, according to IDC.
By choosing multi-cloud solutions strategically, enterprises can optimize the benefits of cloud computing and aim for some key competitive advantages. They can avoid the lengthy and cumbersome processes involved in buying, installing and testing high-priced systems. The IaaS and PaaS solutions have become a windfall for the enterprise’s budget as it does not incur huge up-front capital expenditure.
However, cost optimization is still a challenge while facilitating a multi-cloud environment and a large number of enterprises end up overpaying with or without realizing it. The below-mentioned tips would help you ensure the money is spent wisely on cloud computing services.
Most organizations tend to get wrong with simple things which turn out to be the root cause for needless spending and resource wastage. The first step to cost optimization in your cloud strategy is to identify underutilized resources that you have been paying for.
Enterprises often continue to pay for resources that have been purchased earlier but are no longer useful. Identifying such unused and unattached resources and deactivating it on a regular basis brings you one step closer to cost optimization. If needed, you can deploy automated cloud management tools that are largely helpful in providing the analytics needed to optimize the cloud spending and cut costs on an ongoing basis.
Another key cost optimization strategy is to identify the idle computing instances and consolidate them into fewer instances. An idle computing instance may require a CPU utilization level of 1-5%, but you may be billed by the service provider for 100% for the same instance.
Every enterprise will have such non-production instances that constitute unnecessary storage space and lead to overpaying. Re-evaluating your resource allocations regularly and removing unnecessary storage may help you save money significantly. Resource allocation is not only a matter of CPU and memory but also it is linked to the storage, network, and various other factors.
The key to efficient cost reduction in cloud computing technology lies in proactive monitoring. A comprehensive view of the cloud usage helps enterprises to monitor and minimize unnecessary spending. You can make use of various mechanisms for monitoring computing demand.
For instance, you can use a heatmap to understand the highs and lows in computing visually. This heat map indicates the start and stop times which in turn lead to reduced costs. You can also deploy automated tools that help organizations to schedule instances to start and stop. By following a heatmap, you can understand whether it is safe to shut down servers on holidays or weekends.
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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:
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
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.
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The moving of applications, databases and other business elements from the local server to the cloud server called cloud migration. This article will deal with migration techniques, requirement and the benefits of cloud migration.
In simple terms, moving from local to the public cloud server is called cloud migration. Gartner says 17.5% revenue growth as promised in cloud migration and also has a forecast for 2022 as shown in the following image.
#cloud computing services #cloud migration #all #cloud #cloud migration strategy #enterprise cloud migration strategy #business benefits of cloud migration #key benefits of cloud migration #benefits of cloud migration #types of cloud migration