reddit_sse_stream
vaex
reddit_sse_stream | vaex | |
---|---|---|
6 | 7 | |
47 | 8,178 | |
- | 0.2% | |
0.0 | 5.4 | |
almost 2 years ago | about 1 month ago | |
Python | Python | |
MIT License | MIT 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.
reddit_sse_stream
-
Pushshift Live Again and How Moderators Can Request Pushshift Access
Will you still be providing the SSE Stream API using this new bearer token authentication?
-
Thoughts on a pushshift alternative
Pushshift used to have this https://github.com/pushshift/reddit_sse_stream
-
Introducing Sunbelt, a new service similar to Pushshift
while the point of pushshift is absolute collection of data, it also had the https://github.com/pushshift/reddit_sse_stream for getting notified of new posts, which was a godsend for bots (moderation and i guess otherwise) during the short time it worked correctly
-
https://np.reddit.com/r/rust/comments/lxkylx/how_to_use_async_sse_to_read_from_a_remote_sse/gpzq5wn/
use std::io::{Error, ErrorKind}; use futures::prelude::*; #[tokio::main] async fn main() { let url = "http://stream.pushshift.io"; let stream = reqwest::get(url) .await .unwrap() .bytes_stream(); let mut reader = async_sse::decode( stream .map_err(|e| Error::new(ErrorKind::Other, e)) .into_async_read() ); let event = reader.next().await.unwrap(); println!("{:?}", event); }
-
How to use async_sse to read from a remote SSE stream?
async fn main() { let url = "http://stream.pushshift.io";
vaex
-
preprocessing millions of records - how to speed up the processing
Try vaex, vaex, using lazy evaluation and parallel calculations, you should be fine.
-
High performance (for the consumer) time series storage?
I'd recommend QuestDB. Worked with it multiple times for different algorithmic trading needs and it didn't disappoint. If you want to load data fast, I'd recommend this Python library.
-
Python Pandas vs Dask for csv file reading
How about vaex?
- Polars: Lightning-fast DataFrame library for Rust and Python
-
For stocks, what historical data do you store and how do you store it?
You might find vaex (https://github.com/vaexio/vaex) interesting if you work with HDF5.
- I wrote one of the fastest DataFrame libraries
-
A Hybrid Apache Arrow/Numpy DataFrame with Vaex Version 4.0
My guess is that should be possible, feel free to hop onto https://github.com/vaexio/vaex/discussions !
What are some alternatives?
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
data.table - R's data.table package extends data.frame:
minimal-pandas-api-for-polars - pip install minimal-pandas-api-for-polars
rust-dataframe - A Rust DataFrame implementation, built on Apache Arrow
visidata - A terminal spreadsheet multitool for discovering and arranging data
umap - Uniform Manifold Approximation and Projection
db-benchmark - reproducible benchmark of database-like ops
dtplyr - Data table backend for dplyr
TypedTables.jl - Simple, fast, column-based storage for data analysis in Julia
explorer - Series (one-dimensional) and dataframes (two-dimensional) for fast and elegant data exploration in Elixir
minimal-pandas-api-for-pola
Datamancer - A dataframe library with a dplyr like API