Hello there! In this unit, we're offering an engaging coding lesson that highlights the performance efficiencies offered by the utilization of HashMaps in Python. We'll address an array-based problem that requires us to make an optimal choice to minimize the size of our array. Excited? So am I! Let's get started.

In this unit's task, we'll manipulate an array of integers. You are required to construct a Python function titled minimal_max_block(). This function should accept an array as an input and compute an intriguing property related to contiguous blocks within the array.

More specifically, you must select a particular integer, k, from the array. Once you've selected k, the function should remove all occurrences of 'k' from the array, thereby splitting it into several contiguous blocks, or remaining sub-arrays. A unique feature of k is that it is chosen such that the maximum length among these blocks is minimized.

For instance, consider the array [1, 2, 2, 3, 1, 4, 4, 4, 1, 2, 5]. If we eliminate all instances of 2 (our k), the remaining blocks would be [1], [3, 1, 4, 4, 4, 1], [5], with the longest containing 6 elements. Now, if we instead remove all instances of 1, the new remaining blocks would be , , , the longest of which contains 3 elements. As such, the function should return 1 in this case, as it leads to a minimal maximum block length.