data-engineering-challenge-th
pyDag
data-engineering-challenge-th | pyDag | |
---|---|---|
1 | 2 | |
13 | 24 | |
- | - | |
0.0 | 0.0 | |
over 2 years ago | over 1 year ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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.
data-engineering-challenge-th
-
Data Engineering Projects for Beginners
Dockerizing a Python Script for Faster Web Scraping
pyDag
-
Data Engineering Projects for Beginners
Scheduling Big Data Workloads and Data Pipelines in the Cloud with pyDag
- How to build a DAG based Task Scheduling tool for Multiprocessor systems using python
What are some alternatives?
docker-livy - Dockerizing and Consuming an Apache Livy environment
distance-metrics - Distance metrics are one of the most important parts of some machine learning algorithms, supervised and unsupervised learning, it will help us to calculate and measure similarities between numerical values expressed as data points
data-engineer-challenge - Challenge Data Engineer
pyspark-on-aws-emr - The goal of this project is to offer an AWS EMR template using Spot Fleet and On-Demand Instances that you can use quickly. Just focus on writing pyspark code.
livyc - Apache Spark as a Service with Apache Livy Client
pubsub2inbox - Pubsub2Inbox is a versatile, multi-purpose tool to handle Pub/Sub messages and turn them into email, API calls, GCS objects, files or almost anything.
recommendation-system - Build a Content-Based Movie Recommender System (TF-IDF, BM25, BERT)
p_tqdm - Parallel processing with progress bars
breaking_cycles_in_noisy_hierarchies - breaking cycles in noisy hierarchies
wbz - A parallel implementation of the bzip2 data compressor in python, this data compression pipeline is using algorithms like Burrows–Wheeler transform (BWT) and Move to front (MTF) to improve the Huffman compression. For now, this tool only will be focused on compressing .csv files, and other files on tabular format.