torsh-tensor 0.1.2

Tensor implementation for ToRSh with PyTorch-compatible API
Documentation 
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//! Data Science Format Implementations
//!
//! This module provides serialization support for data science formats,
//! particularly Arrow and Parquet which are optimized for analytical workloads
//! and provide excellent compression and query performance.

// Imports needed by both real implementations and stubs
#[allow(unused_imports)]
use super::common::{SerializationFormat, SerializationOptions, TensorMetadata};
#[allow(unused_imports)]
use crate::{Tensor, TensorElement};
#[allow(unused_imports)]
use std::path::Path;
#[allow(unused_imports)]
use torsh_core::error::{Result, TorshError};

/// Arrow format implementation
#[cfg(feature = "serialize-arrow")]
pub mod arrow {
    use super::*;

    /// Serialize tensor to Arrow format
    ///
    /// Creates an Arrow file with columnar data layout optimized for
    /// analytical workloads and zero-copy reads.
    ///
    /// # Arguments
    /// * `tensor` - Tensor to serialize
    /// * `path` - Output file path
    /// * `options` - Serialization options
    ///
    /// # Returns
    /// * `Result<()>` - Ok if successful, error otherwise
    pub fn serialize_arrow<T: TensorElement>(
        tensor: &Tensor<T>,
        _path: &Path,
        options: &SerializationOptions,
    ) -> Result<()> {
        // TODO: Implement Arrow serialization using arrow-rs crate
        let _metadata = TensorMetadata::from_tensor(
            tensor,
            options,
            SerializationFormat::Arrow,
            tensor.numel() * std::mem::size_of::<T>(),
        );

        Err(TorshError::SerializationError(
            "Arrow serialization not yet implemented".to_string(),
        ))
    }

    /// Deserialize tensor from Arrow format
    ///
    /// # Arguments
    /// * `path` - Input file path
    ///
    /// # Returns
    /// * `Result<Tensor<T>>` - Deserialized tensor or error
    pub fn deserialize_arrow<T: TensorElement>(path: &Path) -> Result<Tensor<T>> {
        let _ = path;
        Err(TorshError::SerializationError(
            "Arrow deserialization not yet implemented".to_string(),
        ))
    }
}

/// Parquet format implementation
#[cfg(feature = "serialize-arrow")]
pub mod parquet {
    use super::*;

    /// Serialize tensor to Parquet format
    ///
    /// Creates a Parquet file with compressed columnar storage
    /// optimized for big data analytics.
    ///
    /// # Arguments
    /// * `tensor` - Tensor to serialize
    /// * `path` - Output file path
    /// * `options` - Serialization options
    ///
    /// # Returns
    /// * `Result<()>` - Ok if successful, error otherwise
    pub fn serialize_parquet<T: TensorElement>(
        tensor: &Tensor<T>,
        _path: &Path,
        options: &SerializationOptions,
    ) -> Result<()> {
        // TODO: Implement Parquet serialization using parquet-rs crate
        let _metadata = TensorMetadata::from_tensor(
            tensor,
            options,
            SerializationFormat::Parquet,
            tensor.numel() * std::mem::size_of::<T>(),
        );

        Err(TorshError::SerializationError(
            "Parquet serialization not yet implemented".to_string(),
        ))
    }

    /// Deserialize tensor from Parquet format
    ///
    /// # Arguments
    /// * `path` - Input file path
    ///
    /// # Returns
    /// * `Result<Tensor<T>>` - Deserialized tensor or error
    pub fn deserialize_parquet<T: TensorElement>(path: &Path) -> Result<Tensor<T>> {
        let _ = path;
        Err(TorshError::SerializationError(
            "Parquet deserialization not yet implemented".to_string(),
        ))
    }
}

/// Stub implementations when Arrow feature is not enabled
#[cfg(not(feature = "serialize-arrow"))]
pub mod arrow {
    use super::*;

    pub fn serialize_arrow<T: TensorElement>(
        _tensor: &Tensor<T>,
        _path: &Path,
        _options: &SerializationOptions,
    ) -> Result<()> {
        Err(TorshError::SerializationError(
            "Arrow serialization requires the 'serialize-arrow' feature to be enabled".to_string(),
        ))
    }

    pub fn deserialize_arrow<T: TensorElement>(_path: &Path) -> Result<Tensor<T>> {
        Err(TorshError::SerializationError(
            "Arrow deserialization requires the 'serialize-arrow' feature to be enabled"
                .to_string(),
        ))
    }
}

#[cfg(not(feature = "serialize-arrow"))]
pub mod parquet {
    use super::*;

    pub fn serialize_parquet<T: TensorElement>(
        _tensor: &Tensor<T>,
        _path: &Path,
        _options: &SerializationOptions,
    ) -> Result<()> {
        Err(TorshError::SerializationError(
            "Parquet serialization requires the 'serialize-arrow' feature to be enabled"
                .to_string(),
        ))
    }

    pub fn deserialize_parquet<T: TensorElement>(_path: &Path) -> Result<Tensor<T>> {
        Err(TorshError::SerializationError(
            "Parquet deserialization requires the 'serialize-arrow' feature to be enabled"
                .to_string(),
        ))
    }
}