serverless-offline
NumPy
serverless-offline | NumPy | |
---|---|---|
18 | 272 | |
5,123 | 26,413 | |
- | 1.1% | |
8.7 | 10.0 | |
6 days ago | 1 day ago | |
JavaScript | Python | |
MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
serverless-offline
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Introducing samp-cli for local lambda debugging
Using local emulators like sam local, serverless-offline, localstack, etc.
- [Serverless] Sans serveur hors ligne avec AWS Cognito
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Ask HN: Is it ok to place an ad for my startup in my OSS?
Hi, I'm the creator of serverless-offline (https://github.com/dherault/serverless-offline), a NPM package for local serveless development on AWS.
I'm building a cool product and intend to launch Q1 2023. To gain traction from my target customers, I plan to place a discrete ad at the launch of every serverless-offline instance.
Does it seem like an ok move to you? Or is it something that repels you?
Best,
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How to build a tech product fast
As the creator of serverless-offline, I am well placed to tell you that this is the time-effective solution. Plus, it costs way less than other solutions at smaller scales. But, again, going Kubernetes or otherwise will be a problem for the future.
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There is framework for everything.
https://github.com/dherault/serverless-offline https://github.com/lambci/docker-lambda
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Serverless monitoring — the good, the bad and the ugly
What if I didn’t need to push code to AWS every time I wanted to test something? All heroes don’t wear capes. Like a knight in shining armor, Serverless Offline comes barging in to save the day! At least now I can test all my code locally before pushing it to AWS. That’s a relief.
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Migrating a classic Express.js to Serverless Framework
With classic Express servers, you can use a simple node script to get the server up and running to test locally. Serverless wants to be run in the AWS ecosystem making it. Lucky for us, David Hérault has built and continues to maintain serverless-offline allowing us to emulate our functions locally before we deploy.
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3 Steps To Faster Serverless Development
With the serverless offline plugin you can speed up local dev is by emulating AWS lambda and API Gateway locally when developing your Serverless project.
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Stop using a local environment to develop Serverless applications
Those mocks are by definition not real services so there are some behavior differences between the local environment and the cloud provider. For example, AWS API Gateway emulated by serverless-offline doesn't handle VTL locally the same as AWS does.
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A magical AWS serverless developer experience
serverless-offline (https://github.com/dherault/serverless-offline) is a great tool to use for local development of serverless applications.
It's not a complete mirror image of what you get but it's close enough in my experience.
NumPy
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In NumPy with @, dot() or matmul():
- NumPy 2.0.0 Beta1
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Element-wise vs Matrix vs Dot multiplication
In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication.
- JSON dans les projets data science : Trucs & Astuces
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JSON in data science projects: tips & tricks
Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:
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Introducing Flama for Robust Machine Learning APIs
numpy: A library for scientific computing in Python
- help with installing numpy, please
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A Comprehensive Guide to NumPy Arrays
Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy.
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Why do all the popular projects use relative imports in __init__ files if PEP 8 recommends absolute?
I was looking at all the big projects like numpy, pytorch, flask, etc.
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NumPy 2.0 development status & announcements: major C-API and Python API cleanup
I wish the NumPy devs would more thoroughly consider adding full fluent API support, e.g. x.sqrt().ceil(). [Issue #24081]
What are some alternatives?
supertest - 🕷 Super-agent driven library for testing node.js HTTP servers using a fluent API. Maintained for @forwardemail, @ladjs, @spamscanner, @breejs, @cabinjs, and @lassjs.
SymPy - A computer algebra system written in pure Python
aws-lambda-dotnet - Libraries, samples and tools to help .NET Core developers develop AWS Lambda functions.
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
docker-lambda - Docker images and test runners that replicate the live AWS Lambda environment
blaze - NumPy and Pandas interface to Big Data
bref - Serverless PHP on AWS Lambda
SciPy - SciPy library main repository
sst - Build modern full-stack applications on AWS
Numba - NumPy aware dynamic Python compiler using LLVM
Sequelize - Feature-rich ORM for modern Node.js and TypeScript, it supports PostgreSQL (with JSON and JSONB support), MySQL, MariaDB, SQLite, MS SQL Server, Snowflake, Oracle DB (v6), DB2 and DB2 for IBM i.
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).