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Aditya Raj
2 years ago
Netflix and Chill! But what happens behind the screen and at the servers of Netflix, which is giving you the experience to chill. Let’s see.
Nowadays, Python programming is being used in every aspect of the digital ecosystem. From data science to web development, from machine learning to DevOps, Python is one of the most popular languages. Netflix is one of the companies that is using Python programming in every aspect of their work. Netflix uses Python through its full content lifecycle. In this article, we will look at various ways Netflix uses Python programming. We will also see what backend language Netflix uses to develop its entire framework. In the end, we will also see how we can use Netflix API in Python.
Table of Content
What Programming Language does Netflix use?
How Netflix uses Python Programming?
- Machine learning
- Demand Engineering
- Information Security
- Recommendation Systems
- Orchestration
- Experimentation
- Video Encoding and Media Cloud Engineering
- Animation and NVFX
- Monitoring, Alerting, and auto-remediation
- Notebooks
- Content Delivery
How to use Netflix API in Python?
Conclusion
What Programming Language does Netflix use?
Netflix uses Python programming language in a majority of its tasks but everything cannot be done using a single language. There are many other languages used by Netflix to facilitate different tasks. Netflix uses Java and Scala to implement many of its backend tasks. To design its web application, Javascript has been used. Other programming languages and technologies used by Netflix include Node.js, React, MySQL, PostgreSQL, Amazon RDS, Presto, CloudBees, Pig, Amazon EC2, Amazon S3, Cassandra, and others.
How Netflix uses Python Programming?
Netflix uses python for almost every operation in its content lifecycle. From recommender systems to security management and vulnerability detection, Netflix uses Python programming. In this section, we will look at how Netflix uses Python programming to serve its large user base.
Machine learning
Netflix uses machine learning in hundreds of tasks across the company. It uses Metaflow, a python framework, to execute its machine learning projects from the prototype stage to production. Metaflow leverages parallel programming and optimized python codes to handle millions of data points in the memory and orchestrates the computation over thousands of CPUs.
Statistical Analysis
The CORE team at Netflix uses Python in their statistical analysis tasks. They use different mathematical and statistical libraries such as Numpy, Scipy, Pandas, and Ruptures to automate the analysis of signals received at alerting systems. Netflix has also developed a time series correlation system to parallelize large amounts of data analysis tasks.
Demand Engineering
Demand engineering is responsible for traffic distribution, fleet efficiency, regional failovers, and capacity operations of the Netflix cloud. The tools used for demand engineering in Netflix are built using Python programming with libraries like Numpy, Scipy, boto3, RQ, and Flask APIs.
Information Security
The information security team in Netflix uses Python programming to perform tasks like risk classification, vulnerability identification, security automation to accomplish various high leverage goals. Open source projects like Security Monkey and Prism have been developed using python programming to perform various tasks in the information security domain.
Recommendation Systems
Netflix uses Python extensively in its personalization machine learning infrastructure to train ML models. They use many python libraries such as TensorFlow, Keras, PyTorch, XGBoost, and LightGBM with Numpy, Scipy, Sklearn, Matplotlib, pandas, and CVXPY to facilitate tasks such as movie recommendation.
Orchestration
The big data orchestration team at Netflix is responsible for providing tools for scheduling and executing ETL and Adhoc pipelines. Various components in the orchestration service at Netflix use python programming. For Example, The scheduler uses Jupyter notebooks with papermill to provide job types in templates. It helps their users to have a standard and easy way to express the tasks that need to be performed.
Experimentation
The engineers in the scientific computing department for experimentation in Netflix are creating a platform to analyze AB tests and other experiments. Netflix is experimenting with data, statistics, and visualization. Using Metrics Repo, which is based on PyPika, Netflix Engineers have developed a system where contributors can write reusable SQL queries which accept parameters. This tool serves as an entry point for any new analysis.
To develop new models for causal inference, Netflix uses the Causal Models library, which is developed using Python and R programming. To perform statistical calculations, Netflix uses PyArrow and RPy2. The Visualizations library used by Netflix is based on Plotly. It helps them to produce outputs that are consistent with their platforms.
Video Encoding and Media Cloud Engineering
Netflix uses Python for projects such as VMAF and mezzFS. With the media map-reduce platform Archer, Netflix has built computer vision applications using Python programming. Netflix also has outsourced tools designed in Python to help develop projects like Pickley and Setupmeta.
Animation and NVFX
Netflix engineers use Python programming to create all the industry-standard animation and VFX content. Netflix’s integrations with Nuke and Maya are implemented using python, and most of the shotgun tools in Netflix are also programmed in Python.
Monitoring, Alerting, and auto-remediation
The insight engineers at Netflix are responsible for building and operating tools for diagnostics, alerting, operational insight, and auto-remediation. They are using the Spectator python client library to record dimensional time series metrics. Netflix engineers have also built various python libraries to interact with different platform-level services.
Notebooks
Netflix engineers use Jupyter notebooks very extensively. They use Python as the primary language to develop, debug, explore and prototype different tasks. Engineers at Netflix have built custom extensions for the Jupyter server that allows them to manage different tasks such as logging, publishing, cloning, and archiving notebooks.
Content Delivery
Netflix’s content delivery network is named Open Connect. Various software is used in designing, building, and operating the network, and most of them are written using Python. Most of the network devices used by Netflix are managed by applications written in Python programming language.
How to use Netflix API in Python?
Official Netflix was deprecated in 2014. But, we can use the unofficial version of Netflix API developed by uNoGS.com. With Unofficial Netflix Online Global Search(uNoGS) API, we can search for different web series and movies in the global Netflix catalogue. To use the Netflix API, you must have a working knowledge of the Python programming language. The unofficial Netflix API is available at RapidAPI.com, and you can use it by following the below-mentioned steps.
- Sign Up for the free RapidAPI user account.
- Navigate to the Netflix API documentation page by searching for the term “Netflix” in the search bar at RapidAPI.com
- Subscribe for a suitable pricing plan. You can make 100 requests per day with a free premium account. Beyond that, you will be charged $0.1 per request. So use a suitable plan.
- There are 14 endpoints such as new release per country, list countries, season change, load title details, load episode details, weekly episodes, load IMDB info, etc. Choose the desired endpoint.
- Click at the code snippet dropdown and select Python programming language.
- After selecting language, choose a library from http.client, requests, or Unirest according to your preference. After that, a code snippet will be generated.
- Copy the generated code and paste it into your application or website where you want to use the Netflix API.
In this article, we have discussed what programming language Netflix uses. Then we saw how Netflix is using Python in various programming applications. Finally, we also talked about a way to use Netflix API in Python. You can follow the steps discussed in this article to integrate Netflix API into your website using Python programming.
We hope you enjoyed the article. If you have any related queries, feel free to ask in the comment section below.
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