NumPy loadtxt and savetxt — Reading and Writing Array Data

import numpy as np

# Save to text
data = np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
np.savetxt('data.csv', data, delimiter=',', header='a,b,c', fmt='%.2f')

# Load from text
loaded = np.loadtxt('data.csv', delimiter=',', skiprows=1)
print(loaded)
# [[1. 2. 3.]
#  [4. 5. 6.]]

# Load specific columns
col_a = np.loadtxt('data.csv', delimiter=',', skiprows=1, usecols=0)
print(col_a)  # [1. 4.]

import numpy as np

arr = np.random.randn(1000, 100)

# Save as binary .npy — much faster than CSV for large arrays
np.save('array.npy', arr)
loaded = np.load('array.npy')
print(loaded.shape)   # (1000, 100)
print(np.allclose(arr, loaded))  # True

# Multiple arrays in one file
np.savez('bundle.npz', features=arr, labels=np.zeros(1000))
bundle = np.load('bundle.npz')
print(list(bundle.keys()))  # ['features', 'labels']
print(bundle['features'].shape)  # (1000, 100)

package io.thecodeforge.io;

import org.springframework.stereotype.Component;
import java.io.InputStream;
import java.nio.file.Files;
import java.nio.file.Path;

@Component
public class NpyIngestionHandler {

    /**
     * Processes a .npy file generated by NumPy.
     * In production, this would use a library like JNumPy or ND4J
     * to handle the header parsing and data mapping.
     */
    public void handleUpload(Path path) throws Exception {
        try (InputStream is = Files.newInputStream(path)) {
            byte[] header = new byte[128]; // .npy files have a fixed-length header
            int bytesRead = is.read(header);
            System.out.println("Ingested binary tensor of size: " + Files.size(path) + " bytes");
        }
    }
}

# Optimized Docker configuration for Data Science I/O
FROM python:3.11-slim

LABEL maintainer="engineering@thecodeforge.io"

WORKDIR /data_storage

# NumPy requires minimal overhead, but we ensure /tmp is fast for scratch data
VOLUME /data_storage

COPY requirements.txt .
RUN pip install --no-cache-dir numpy

COPY process_io.py .

CMD ["python", "process_io.py"]