symbiote alternatives and similar packages
Based on the "Data" category.
Alternatively, view symbiote alternatives based on common mentions on social networks and blogs.
-
semantic-source
Parsing, analyzing, and comparing source code across many languages -
lens
Lenses, Folds, and Traversals - Join us on web.libera.chat #haskell-lens -
-
text
Haskell library for space- and time-efficient operations over Unicode text. -
code-builder
Packages for defining APIs, running them, generating client code and documentation. -
compendium-client
Mu (μ) is a purely functional framework for building micro services. -
unordered-containers
Efficient hashing-based container types -
cassava
A CSV parsing and encoding library optimized for ease of use and high performance -
-
holmes
A reference library for constraint-solving with propagators and CDCL. -
binary
Efficient, pure binary serialisation using ByteStrings in Haskell. -
resource-pool
A high-performance striped resource pooling implementation for Haskell -
-
primitive
This package provides various primitive memory-related operations. -
-
-
-
discrimination
Fast linear time sorting and discrimination for a large class of data types -
-
reflection
Reifies arbitrary Haskell terms into types that can be reflected back into terms -
IORefCAS
A collection of different packages for CAS based data structures. -
-
dependent-map
Dependently-typed finite maps (partial dependent products) -
dependent-sum
Dependent sums and supporting typeclasses for comparing and displaying them -
streaming
An optimized general monad transformer for streaming applications, with a simple prelude of functions -
-
orgmode-parse
Attoparsec parser combinators for parsing org-mode structured text! -
text-icu
This package provides the Haskell Data.Text.ICU library, for performing complex manipulation of Unicode text. -
-
-
-
scientific
Arbitrary-precision floating-point numbers represented using scientific notation -
-
uuid-types
A Haskell library for creating, printing and parsing UUIDs
Access the most powerful time series database as a service
Do you think we are missing an alternative of symbiote or a related project?
|
Static code analysis for 29 languages.
sponsored
www.sonarqube.org
|
Popular Comparisons
-
CBORvsprotobuf
-
network-addressvsradius
-
textvsattempt
-
json-autotypevsbase58string
-
boringvsbinary
|
SaaSHub - Software Alternatives and Reviews
sponsored
www.saashub.com
|
README
Symbiote
Iteration of the Symbiotic-Data Test Suite.
This project aims to be a network agnostic and data format agnostic serialization verifier - it's main purpose is to verify that data, operations on that data, and serialization of that data is all consistent for multiple platforms. This project defines a trivial protocol that can be re-implemented in any platform, over any network medium.
How the Protocol Works
It's a pretty simple idea:
Setting
Basically, the test suite envolves two peers - we'll call them Peer A and Peer B, and they're connected by some network. Likewise, they are both using (possibly different) systems, which we've denoted as Lang A (like Haskell) and Lang B (like PureScript / JavaScript).
The goal of this suite is to ensure that the same idea defined on these different platforms have the same representation - both operationally (i.e., QuickCheck laws) and through some encoding (like printing the data to JSON or a ByteString).
In the diagram above, each system has some idea of what "Type T" looks and feels like, but could be completely different implementations on each system. Again, though, we care about their outcome being identical; so we disambiguate the idea from the data.
Protocol
The first step in the protocol is for the generating party (Peer A) to generate an instance of Type T, and an operation on that type - this operation, too, needs a serialization implementation (but for most intents and purposes, the implementation will be only for the scope of use with this test suite).
Peer A then does two things: it serializes both the operation and instance to the network-acceptable format, and it "performs" the operation on that instance to get an expected result. Basically, Peer A is using Peer B as a remote procedure call for that operation, and verifying that the result obtained remotely is identical to the result obtained locally.
Remote Procedure Call
As just stated, Peer A then sends the serialized instance and operation to Peer B over that network, where Peer B decodes the data, and performs the operation. Peer B then encodes the result, and sends it back to Peer A.
Verification
Peer A now receives the performed data from Peer B, and can now decode it, and test to see if it is equal to the expected result. If it is, it will tell Peer B that it's "their turn" to generate data.
All of this relies on QuickCheck to generate the data - with the size of the generated data increasing at each step, until a maximum is reached (which is clarified in the documentation).
For an example, check out the tests - they are performed both locally in an asynchronous channel, and remotely with its sister package - purescript-symbiote.