elistrix alternatives and similar packages
Based on the "Algorithms and Data structures" category.
Alternatively, view elistrix alternatives based on common mentions on social networks and blogs.
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matrex
A blazing fast matrix library for Elixir/Erlang with C implementation using CBLAS. -
simple_bayes
A Naive Bayes machine learning implementation in Elixir. -
exconstructor
An Elixir library for generating struct constructors that handle external data with ease. -
erlang-algorithms
Implementations of popular data structures and algorithms -
remodel
:necktie: An Elixir presenter package used to transform map structures. "ActiveModel::Serializer for Elixir" -
MapDiff
Calculates the difference between two (nested) maps, and returns a map representing the patch of changes. -
merkle_tree
:evergreen_tree: Merkle Tree implementation in pure Elixir -
bloomex
:hibiscus: A pure Elixir implementation of Scalable Bloom Filters -
aja
Extension of the Elixir standard library focused on data stuctures, data manipulation and performance -
the_fuzz
String metrics and phonetic algorithms for Elixir (e.g. Dice/Sorensen, Hamming, Jaccard, Jaro, Jaro-Winkler, Levenshtein, Metaphone, N-Gram, NYSIIS, Overlap, Ratcliff/Obershelp, Refined NYSIIS, Refined Soundex, Soundex, Weighted Levenshtein) -
DeepMerge
Deep (recursive) merge for maps, keywords and others in Elixir -
exmatrix
Elixir library implementing a parallel matrix multiplication algorithm and other utilities for working with matrices. Used for benchmarking computationally intensive concurrent code. -
ecto_materialized_path
Tree structure & hierarchy for ecto models -
dataframe
Package providing functionality similar to Python's Pandas or R's data.frame() -
Conrex
An Elixir implementation of the CONREC algorithm for topographic or isochrone maps. -
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murmur
:speech_balloon: An implementation of the non-cryptographic hash Murmur3 -
bitmap
Bitmap implementation in Elixir using binaries and integers. Fast space efficient data structure for lookups -
combination
A simple combinatorics library providing combination and permutation.
Elixir and Phoenix Application Security Platform
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
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README
elistrix
A latency / fault tolerance library to help isolate your applications from an uncertain world of slow or failed services.
Modeled after Hystrix but written in Elixir.
high level goals
- simple interface to protect any function call in latency and error rate threshold mode
- metrics collection to easily identify and inspect circuit breakers in real-time
general overview
Everything starts with registering a command with Elistrix.Dispatcher. You must pass a function pointer i.e. &Some.Module.function/2. You can optionally specify custom thresholds to change the following:
- window length (the amount of time we'll keep a history of previous requests for the command)
- latency threshold (the average latency, in milliseconds, of all the requests in the current window)
- error threshold (percentage of requests that have failed of all the requests in the current window)
Once you register your command, you can call it via the dispatcher. You can pass a list of arguments to be applied to the function. Commands are executed in the caller process, to avoid complexity in Elistrix -- needing to maintain worker process pooling, needing to do weird calling convention tricks.
We track the latency of the call, and we track the return value. If your function returns something similar to :ok or :error or {:error, ....} then we can track the successes and failures, otherwise we can only track the latency of these calls.
When a command is tripped -- when either the latency or error percentage threshold is crossed -- calls to the command result in {:error, {:tripped, "reason here"}} to let the caller know the command is in a tripped state. Otherwise, the original return value of the function called is returned back.
The state of a command -- whether it's tripped or not -- is updated once every 500ms. Thus, failure conditions are realized quickly but scenarios that require faster realization aren't currently possible.
*Note that all licence references and agreements mentioned in the elistrix README section above
are relevant to that project's source code only.