cabal-version: 3.0
name: dataframe-hasktorch
version: 0.2.0.2
synopsis: Converts between dataframes and hasktorch tensors
description:
This package provides seamless conversion between dataframes and hasktorch tensors,
bridging the gap between data manipulation and machine learning workflows.
Key features:
* Convert dataframes to floating-point or integer tensors for ML training
* Automatic handling of multi-column and single-column dataframes
* Smart dimensional handling (1D tensors for single columns, 2D for multiple)
* Type-safe conversions with comprehensive error handling
Typical workflow: load and transform data using dataframes, then convert to
tensors for training neural networks with hasktorch.
license: MIT
license-file: LICENSE
author: Michael Chavinda
maintainer: mschavinda@gmail.com
category: Data
build-type: Simple
extra-doc-files: CHANGELOG.md
common warnings
ghc-options: -Wall
library
import: warnings
exposed-modules: DataFrame.Hasktorch
build-depends: base >= 4.11 && < 5,
vector ^>= 0.13,
dataframe-core ^>= 1.1,
dataframe-operations ^>= 1.1.1,
hasktorch >= 0.2.1.6 && < 0.3
if impl(ghc >= 9.12)
build-depends: ghc-typelits-natnormalise == 0.9.3
else
build-depends: ghc-typelits-natnormalise >= 0.7.7 && < 0.9
hs-source-dirs: src
default-language: Haskell2010
test-suite dataframe-hasktorch-test
import: warnings
default-language: Haskell2010
type: exitcode-stdio-1.0
hs-source-dirs: test
main-is: Main.hs
build-depends:
base >= 4.11 && < 5,
dataframe-hasktorch