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This tutorial will show you the use of PyMuPDF, MuPDF in Python, step by step. Because MuPDF supports not only PDF, but also XPS, OpenXPS, CBZ, CBR, FB2 and EPUB formats, so does PyMuPDF [1]. Nevertheless, for the sake of brevity we will only talk about PDF files.
- Installation
Notes about using a non-default MuPDF#. Using a non-default...
- Installation
For advanced combining (you can give it loop if you want to combine lots of matrices): # Advanced combining. import numpy as np. # Data. A = np.matrix('1 2 3; 4 5 6') B = np.matrix('7 8') print('Original Matrices') print(A) print(B)
- Creating Arrays Commands. Arrays in NumPy are of fixed size and homogeneous in nature. They are faster and more efficient because they are written in C language and are stored in a continuous memory location which makes them easier to manipulate.
- Initial Placeholders. Example 1: For 1-Dimensional NumPy Arrays. Initial placeholders for a Numpy 1-dimension array can be created by using various Numpy functions.
- Inspecting Properties. NumPy arrays possess some basic properties that can be used to get information about the array such as the size, length, shape, and datatype of the array.
- Saving and Loading File. Numpy arrays can be stored or loaded from a disk file with the ‘.npy‘ extension. There are various ways by which we can import a text file in a NumPy array.
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differences between NumPy arrays and the standard Python sequences: •NumPy arrays have a fixed size at creation, unlike Python lists (which can grow dynamically). Changing the size of an ndarray will create a new array and delete the original.
Jul 16, 2023 · In this comprehensive guide, we will introduce you to PyPDF2, a popular Python library for working with PDF files, and provide a step-by-step tutorial on how to use it effectively.
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Aug 17, 2023 · PyPDF2 is a free and open-source library for working with PDFs in Python. Split, merge, crop, transform, encrypt and decrypt PDFs easily. Supports PDF 1.4 to 1.7 with no dependencies other than the Python standard library.