Metadata-Version: 2.1
Name: tributary
Version: 0.1.0
Summary: Analytics library
Home-page: https://github.com/timkpaine/tributary
Author: Tim Paine
Author-email: timothy.k.paine@gmail.com
License: Apache 2.0
Description: # <a href="https://tributary.readthedocs.io"><img src="docs/img/icon.png" width="300"></a>
        Python Data Streams
        
        [![Build Status](https://dev.azure.com/tpaine154/tributary/_apis/build/status/timkpaine.tributary?branchName=master)](https://dev.azure.com/tpaine154/tributary/_build/latest?definitionId=2&branchName=master)
        [![GitHub issues](https://img.shields.io/github/issues/timkpaine/tributary.svg)](https://github.com/timkpaine/tributary/issues)
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        [![PyPI](https://img.shields.io/pypi/v/tributary.svg)](https://pypi.python.org/pypi/tributary)
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        ![](https://raw.githubusercontent.com/timkpaine/tributary/master/docs/img/example.gif)
        
        
        # Installation
        Install from pip:
        
        `pip install tributary`
        
        or from source
        
        `python setup.py install`
        
        # Stream Types
        Tributary offers several kinds of streams:
        
        ## Streaming
        These are synchronous, reactive data streams, built using asynchronous python generators. They are designed to mimic complex event processors in terms of event ordering.
        
        ## Functional
        These are functional streams, built by currying python functions (callbacks). 
        
        ## Lazy
        These are lazily-evaluated python streams, where outputs are propogated only as inputs change. They are implemented as directed acyclic graphs.
        
        # Examples
        - [Streaming](docs/examples/streaming/streaming.md): In this example, we construct a variety of forward propogating reactive graphs.
        - [Lazy](docs/examples/lazy/lazy.md): In this example, we construct a variety of lazily-evaluated directed acyclic computation graphs. 
        
        # Graph Visualization
        You can visualize the graph with Graphviz. All streaming and lazy nodes support a `graphviz` method.
        
        Streaming and lazy nodes also support [ipydagred3](https://github.com/timkpaine/ipydagred3) for live update monitoring.
        
        ## Streaming
        ![](https://raw.githubusercontent.com/timkpaine/tributary/master/docs/img/streaming/dagred3.gif)
        
        Here green indicates executing, yellow indicates stalled for backpressure, and red indicates that `StreamEnd` has been propogated (e.g. stream has ended).
        
        ## Lazy
        ![](https://raw.githubusercontent.com/timkpaine/tributary/master/docs/img/lazy/dagred3.gif)
        
        Here green indicates executing, and red indicates that the node is dirty. Note the the determination if a node is dirty is also done lazily (we can check with `isDirty` whcih will update the node's graph state.
        
        # Sources and Sinks
        ## Sources
        - Python Function/Generator/Async Function/Async Generator
        - Random
        - File
        - Kafka
        - Websocket
        - Http
        - SocketIO
        
        ## Sinks
        - File
        - Kafka
        - Http
        - Websocket
        - SocketIO
        
        # Transforms
        ## Modulate
        - Delay - Streaming wrapper to delay a stream
        - Apply - Streaming wrapper to apply a function to an input stream
        - Window - Streaming wrapper to collect a window of values
        - Unroll - Streaming wrapper to unroll an iterable stream
        - UnrollDataFrame - Streaming wrapper to unroll a dataframe into a stream
        - Merge - Streaming wrapper to merge 2 inputs into a single output
        - ListMerge - Streaming wrapper to merge 2 input lists into a single output list
        - DictMerge - Streaming wrapper to merge 2 input dicts into a single output dict. Preference is given to the second input (e.g. if keys overlap)
        - Reduce - Streaming wrapper to merge any number of inputs
        
        ## Calculations
        ### Arithmetic Operators
        - Noop
        - Negate
        - Invert
        - Add
        - Sub
        - Mult
        - Div
        - RDiv
        - Mod
        - Pow
        - Sum
        - Average
        
        ### Boolean Operators
        - Not
        - And
        - Or
        
        ### Comparators
        - Equal
        - NotEqual
        - Less
        - LessOrEqual
        - Greater
        - GreaterOrEqual
        
        ### Math
        - Log
        - Sin
        - Cos
        - Tan
        - Arcsin
        - Arccos
        - Arctan
        - Sqrt
        - Abs
        - Exp
        - Erf
        
        ## Converters
        - Int
        - Float
        - Bool
        - Str
        
        ## Python Builtins
        - Len
        
        ## Rolling
        - RollingCount - Node to count inputs
        - RollingMin - Node to take rolling min of inputs
        - RollingMax - Node to take rolling max of inputs
        - RollingSum - Node to take rolling sum inputs
        - RollingAverage - Node to take the running average
        
        ## Node Type Converters
        - Lazy->Streaming
        
Keywords: analytics tools plotting
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
Provides-Extra: dev
