tributary | Streaming reactive and dataflow graphs in Python | Stream Processing library
kandi X-RAY | tributary Summary
kandi X-RAY | tributary Summary
Tributary is a library for constructing dataflow graphs in python. Unlike many other DAG libraries in python (airflow, luigi, prefect, dagster, dask, kedro, etc), tributary is not designed with data/etl pipelines or scheduling in mind. Instead, tributary is more similar to libraries like mdf, pyungo, streamz, or pyfunctional, in that it is designed to be used as the implementation for a data model. One such example is the greeks library, which leverages tributary to build data models for options pricing.
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Top functions reviewed by kandi - BETA
- Start a subprocess
- Set the value
- Adds a key to the node
- Create a StreamEnd instance
- Return a dagre graph
- Determine if the cache is dirty
- Return a graph representation of a node
- Create a functional pipeline
- Submit a function to a given function
- Construct a lazy graph
- Calculate the average of two nodes
- Stop the process
- Throttle the given node
- Create an interval node
- Construct a StreamingGraph from expr
- Sum operator
- Calculate the rolling average
- Create a window node
- Return graphviz representation of node
- Compute MACD
- Calculate the RSI of a node
- Expire a node
- Unroll a DataFrame
- Create an if node
- Save the object to disk
- Run the task
tributary Key Features
tributary Examples and Code Snippets
Community Discussions
Trending Discussions on tributary
QUESTION
I want to replace words in a vector based on original and replacement words in another dataframe. As an example:
A vector of strings to be altered:
...ANSWER
Answered 2021-Dec-14 at 05:54Here is one sub
approach which makes just a single replacement:
QUESTION
I am trying to streamline the process of auditing chemistry laboratory data. When we encounter data where an analyte is not detected I need to change the recorded result to a value equal to 1/2 of the level of detection (LOD) for the analytical method. I have LOD's contained within another dataframe to be used as a lookup table.
I have multiple columns representing data from different analytical tests, each with it's own unique LOD. Here's an example of the type of data I am working with:
...ANSWER
Answered 2021-Oct-23 at 04:30Perhaps this helps
QUESTION
Im not sure why but I cant seem to get this footer to go properly to the bottom, my body seems to only be going halfway up the page? I wrapped the whole thing in main to see if that would fix it if I set a height on that, it seemingly only goes the same height every single time. Its like its not catching the viewport or something and causing it to only go about half way up. Also please be easy im a new coder so if your awnser has just general advice to improve im all about it. Thanks ahead of time!
...ANSWER
Answered 2021-May-24 at 00:16The line max-height: 100vh
in #tribute-info is the cause of this. If you remove it, the footer will display correctly at the bottom.
In addition, the
, not between
and
.
QUESTION
I have data set of 20 year measurements (14600x6) and need to get a geometric mean value of $tu
per $name
and $trophic
. Originally, I had my df split in three dfs and I did as follow:
Old code based on split df!!!
...ANSWER
Answered 2021-Feb-24 at 20:43If you can use tidy verse, this is one way to accomplish what you want:
QUESTION
I would like to train the spacy text classifier using labels and words from a dataframe. But I can't get right the training_data and pass it to train.
Dataframe example:
...ANSWER
Answered 2020-Sep-04 at 19:37So I make the training_data format with this code, it seems is taking 4 hours per each training though.
QUESTION
TLDR; How can I bulk format my JSON file for ingestion to Elasticsearch?
I am attempting to ingest some NOAA data into Elasticsearch and have been utilizing NOAA Python SDK.
I have written the following Python script to load the data and store it in a JSON format.
...ANSWER
Answered 2020-May-06 at 17:09I suspect this line to result in an error later on json.dumps(json_in.read())
. json.dumps
returns a string. When you iterate over a string, like you do in the next line, then you iterate over the chars.
I think what you actually want is the following. It saves every feature
of alert["features“]
as a new line in json format.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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