Benthos
Pandas
Our great sponsors
Benthos | Pandas | |
---|---|---|
76 | 393 | |
7,516 | 41,863 | |
3.9% | 1.3% | |
9.6 | 10.0 | |
5 days ago | 5 days ago | |
Go | Python | |
MIT License | BSD 3-clause "New" or "Revised" License |
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.
Benthos
- Ask HN: Who is hiring? (December 2023)
- Structured Logging with Slog
- Fancy stream processing made operationally mundane
- Benthos: Fancy stream processing made operationally mundane
-
Any golang library to batch process a queue ?
I’ve used https://www.benthos.dev/ and it’s really easy and well implemented. The author is also very responsive
-
Show HN: Arroyo – Write SQL on streaming data
Looks cool. What is the difference between this tools and benthos (https://www.benthos.dev/)?
- Benthos: Open-source stream processing tool
-
book about golang and kafka
You might want to gradually replace that one with https://github.com/twmb/franz-go because Shopify is looking to find a new owner for Sarama and, until or if they do, it seems to be falling behind with maintenance: https://github.com/Shopify/sarama/issues/2461 For example, they still haven’t addressed this breaking change https://github.com/Shopify/sarama/issues/2358. franz-go has worked well so far in Benthos https://github.com/benthosdev/benthos/tree/main/internal/impl/kafka and it will likely end up as the only implementation once the Sarama-based one will be deprecated
- Show HN: Open-source Auth0 alternative Ory Kratos v0.13 released – nearing v1.0
-
Go in depth youtube channels?
I upload a mix of code reviews and live streams on https://www.youtube.com/@Jeffail, mostly building https://www.benthos.dev out in the open so the content ranges from beginner friendly stuff to more advanced things like stream processing, parser combinators, etc.
Pandas
-
Deploying a Serverless Dash App with AWS SAM and Lambda
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail. Instead, we'll focus on what's necessary to make it run serverless.
-
Help Us Build Our Roadmap – Pydantic
there is pull request to integrate in both pydantic extra types and into pandas cose [1]
-
Stuff I Learned during Hanukkah of Data 2023
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts.
-
Introducing Flama for Robust Machine Learning APIs
pandas: A library for data analysis in Python
-
Exploring Open-Source Alternatives to Landing AI for Robust MLOps
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks.
-
Mastering Pandas read_csv() with Examples - A Tutorial by Codes With Pankaj
Pandas, a powerful data manipulation library in Python, has become an essential tool for data scientists and analysts. One of its key functions is read_csv(), which allows users to read data from CSV (Comma-Separated Values) files into a Pandas DataFrame. In this tutorial, brought to you by CodesWithPankaj.com, we will explore the intricacies of read_csv() with clear examples to help you harness its full potential.
-
What Would Go in Your Dream Documentation Solution?
So, what I'd like to do is write a documentation package in Python to recreate what I've lost. I plan to build upon the fantastic python-docx and docxtpl packages, and I'll probably rely on pandas from much of the tabular stuff. Here are the features I intend to include:
-
How do people know when to use what programming language?
Weirdly most of my time spent with data analysis was in the C layers in pandas.
- Read files from s3 using Pandas/s3fs or AWS Data Wrangler?
-
10 Github repositories to achieve Python mastery
Explore here.
What are some alternatives?
Confluent Kafka Golang Client - Confluent's Apache Kafka Golang client
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
appsmith - Platform to build admin panels, internal tools, and dashboards. Integrates with 25+ databases and any API.
tensorflow - An Open Source Machine Learning Framework for Everyone
watermill - Building event-driven applications the easy way in Go.
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
sarama - Sarama is a Go library for Apache Kafka. [Moved to: https://github.com/IBM/sarama]
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
salsa - A generic framework for on-demand, incrementalized computation. Inspired by adapton, glimmer, and rustc's query system.
Keras - Deep Learning for humans
azure-event-hubs-go - Golang client library for Azure Event Hubs https://azure.microsoft.com/services/event-hubs
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration