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The Curious Case of Netflix’s Metaflow Python Framework

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Almost everyone with the power of the Internet has heard about Netflix. The cloud based video streaming platform is known for many reasons. Be it the amazing series of shows or thought provoking movies, Netflix has totally aced the video content zone like a pro. For this reason a lot of people these days are buying subscriptions to Netflix and letting the best of content entertain them. As people watch their favourite shows and programs on Netflix, seldom do they know what goes behind them.

Just like any other digital organizations, Netflix makes use of programming languages for its background processes. One of the most popular of these is everyone’s favourite Python. The popularity of Python is growing with each passing day, with companies incorporating it for their business processes in one form or the other. In fact, IEEE’s 2019 list of popular programming languages ranks Python as the most widely used programming language. The surprise came from the fact that Python beat JAVA, which was the world’s favourite language for the longest amount of time.

Why Python?

Today there are more than 8 million Python developers to hire across the world who use the language for a variety of purposes. Be it enterprise development, machine learning model implementation, data science or scientific applications, Python is being used in all walks of life both as a development and scripting programming language.

There are many reasons why companies from all across the world love Python. It is easy to understand, scalable and has infinite inbuilt libraries that can be used for a variety of purposes. In other words, Python helps an organization accomplish a lot more with only a few lines of code. It helps them solve plenty of complex and rigorous computational problems with ease. One of the most important factors, however, is that Python is one of the easiest languages to learn and implement. Developers love the fact that they can learn Python both as beginners and as pros and accomplish a lot of goals with only a few lines of code. Apart from this, Python is fast, high-level and has an amazing community which keeps adding frameworks to the language.

How Netflix Uses Python?

When it comes to Netflix, just like any other organization, it harnesses the best of Python for their video streaming platform. It recently revealed how it uses Python for day to activities in its backend. Right from operation management to analysis, security and networking, Netflix has got the fastest growing language doing all sorts of jobs in its organization. Believe it or not but Netflix has even got its very own Python framework that it turned open source recently. The framework is known as Metaflow, and helps Netflix developers manage real-life data science projects with ease.

Netflix relies on a mix of well-known packages along with some of the inhouse software libraries for its functioning. Even though fundamentally Python runs on Amazon Web Services Cloud platform it uses Python in every corner of its online streaming business. Netflix’s engineers recently pointed it out that they use Python through the full content lifecycle, right from deciding which content to fund to operating the CDN that serves final video to over 148 million subscribers.

In operations Netflix quintessentially uses python libraries NumPy SciPy to perform numerical analysis, while rq to run asynchronous workloads. Similarly it uses Pandas, Ruptures along with NumPy and SciPy to help analyze thousands of signals after an alert. Apart from this Python is excessively used to develop a time series correlation system and distributed worker system to paralyze the large analytic workloads faced by the video streaming platform. But this isn’t the end of it. Python’s key role in Netflix lies in automating multiple tasks and managing data science projects in a seamless manner.

The Metaflow Framework

Metaflow was quintessentially developed by Netflix to boost the productivity of data scientists who work on a wide variety of projects right from classical statistics to deep learning. It works by providing a unified API to the infrastructure stack, which is then required to execute data science projects from prototype to production.

The team at Netflix points out that over the past two years Metaflow has been used internally at Netflix to build and manage hundreds of data science projects, be it in the data science domain or natural language processing. The organization wants its data scientists to be curious and take smart risks that have the guts for high business impact.

When Metaflow was in its inception, the machine learning infrastructure team gathered and asked themselves a fundamental question- What is the hardest thing as a data scientist at Netflix? Soon they realized that everything that a data scientist wanted to do was already doable, but wasn’t as easy as it seemed. Therefore, instead of developing new technical feats, Netfliz created Metaflow to make common data science operations extremely easy.

Metaflow thus focuses its energy on improving the productivity of data scientists by being fanatically human centric. It provided a unified approach to navigating the stack. Even though the new framework is prescriptive about the lower levels of the stack, it is far less opinionated about the actual data science at the top of the stack. The best thing withMetaflow being open source is that developers can now use it along with their favourite machine learning and data science libraries like PyTorch, Scikit-Learn, Tensorflow etc.

Conclusion

Metaflow can really help data scientists reduce their burden by writing models and business logic as idiomatic Python code. It leverages the existing infrastructure at Netflix whenever possible. The biggest relief comes from the fact that finally we have a framework that might not be able to do something new but is integrated full-stack and human centric API. Metaflow is also available on Amazon Web Services as a cloud- native framework, leveraging the elasticity of cloud by design itself, both in terms of computing and storage.

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One may think that successful machinery transport is just as easy as shipping other items. Though moving them from one place to another indeed follows the same shipping principles applied globally, there are still some exceptions, especially for some heavy machinery. With that being said, any organization needs to be aware of the important practices that encompass machinery shipping. Machinery Transport 101: How to Transport Machinery and Their Parts Successfully shipping any type of machinery and its parts require individuals to determine the proper mode, carrier, and packaging needed to transport such materiel. The following practices always take precedence when transporting such assets: • Apperceiving the machinery for transport. An initial assessment of the machinery to be transported must be completed before the transport itself takes place. The clients must take note of any features that could affect freight capacities like weight and dimensions. The key here is to understand the type of machinery that needs to be shipped. Researching how other clients and carriers have moved them in the past can ensure a shipment’s success. • Packing the materiel accordingly. Transporting heavy machinery cannot be compared with regular freight movement where small items are packed in boxes filled with protective material such as bubble wrap. It often brings with it more machinery shipping packaging regulations compared to regular transport. Planning and proper handling of heavy machinery are indeed needed. There is a delicate balance to maintain between a client’s shipping needs and the carrier’s packaging requirements. Some carriers have strict regulations, requiring every machinery fit for transport to be stored in container vans, which adds rental costs to the client’s expenses. Aside from that, knowing the kind of work needed to load the equipment is necessary as well. For instance, loading docks and cranes might be needed to get heavy equipment on the back of a trailer truck. • Determining the Suitable Mode. Knowing the difference between FTL and LTL is important for determining the appropriate mode to use. FTL (full-truckload) service means that an entire truck is necessary to fully transport the cargo, while LTL (less-than-truckload) means that the shipment can be moved using a relatively smaller vessel. With that said, clients must consider their preferred mode for transporting their machinery. • Selecting the “Right” Carrier. Now, this one is a combination of what the sender currently knows about shipping machinery and the most relevant carrier available to them. Depending on the type of machinery a client or a company wants to ship, finding the right freight movement company could prove to be difficult. Regardless, the aim is to find a carrier that’s specialized and known for reliable machinery transport and especially the particular machinery they need transported. For instance, shipping heavy machinery would be handled better by international carriers who specialize in the movement of heavy machinery like bulldozers, backhoe loaders, heavy hydraulics, etc. The efficiency and rate of shipping success increase exponentially with these specialized carriers, not to mention they also reduce the risk of unanticipated costs and damages. Knowing the Different Shipping Modes Since we’ve previously talked a bit about the shipping modes, let’s go through all of them and compare what each can provide clients. It’s vital to know about the various shipping modes because they’re all dependent on timing, cost, and size of the shipment. Taking the time to read through each mode would help you decide which one is the most suitable in your case. • Full Truckload (FTL) – This mode necessitates the use of a whole trailer, with the shipment’s overall weight reaching over 6,804 kilograms (15,000 pounds). • Less than Truckload (LTL) – This mode is used when the shipment weighs between 68 (150 pounds) and 6,804 kilograms but doesn’t need a full trailer. • Partial Truckload (PTL) – This mode is used when the shipment’s weight is over 2,268 kilograms (5,000 pounds). However, you may need to split the expenses of a truck with other clients. • Intermodal – This mode is used when there’s a need (or preference) for combining various transportation modes such as rails, trucks, or ships. One could say that this works best for reliable machinery transport overseas, in vast territories such as Australia. • Expedited – This mode is used when time is of the essence for shipping heavy machinery. Keep in the mind that additional costs may arise from selecting this mode. • Flatbed – This mode is used when the shipment must be loaded from the side or needs dimensional flexibility. Evaluate the Machinery’s Extent of Liability In every shipment that carriers make and every mode of transport, there is a limited liability coverage set for moving all kinds of freight. Both the client and the freight service must come to an agreement to evaluate this extent. The liability coverage is determined by the carrier and is reliant on the type of commodity to be moved. For example, LTL covers a fixed amount of payment per kilogram of shipped freight. Keep in mind that understanding a carrier’s liability for loss of cargo and the limits of their liability coverage offers are good practice. It helps you get a better picture of how they run things and if they’re the right carrier for you. Now that you have an idea how machinery transport and how important practices in general freight shipment work, you can now select the right international transport service for you, to effectively increase your chances of your machinery being shipped successfully. Remember, successful freight movement isn’t just up to the carrier; clients have a very important role to play too.
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