Задание #N
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Решение #N
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трябва познание на съответния хардуер

Задание #1

Write a Python script that performs the following tasks:
1. Open and Read the Excel File:
    * Open the Excel file named input.xlsx.
    * Read the worksheet named "Concurrency", which contains an event correlation matrix structured as follows:
        * Row Labels: Event names are listed in column A, starting at cell A2.
        * Column Labels: Event names are listed in row 1, starting at cell B1.
        * Matrix Setup: Each row’s event name corresponds to the matching column’s event name (e.g., the event in A2 corresponds to the event in B1, A3 to B2, etc.).
2. Load Data into a Pandas DataFrame:
    * Load the "Concurrency" worksheet into a Pandas DataFrame.
    * Since the matrix is symmetric (the upper triangular portion mirrors the lower triangular portion), ignore the redundant lower triangular data.
3. Convert the DataFrame to a Graph Using NetworkX:
    * Create an undirected graph where each node represents an event (using the event names from the DataFrame).
    * For every cell in the DataFrame that contains a 1 (either as an integer 1 or as the string "1"), add an edge between the corresponding event nodes.
    * Do not add self-loops (i.e., do not add an edge from a node to itself).
4. Determine Event Weights:
    * use xlwings to evaluate formulas and open the worksheet "Events" from input.xlsx.
    * For each event, locate the corresponding row using the "Event ID" column and extract its weight from the "Memory" column. Where the weight is computed by a formula, but we want to have only the integer result of the computation
5. Identify Maximal Cliques:
    * Use an appropriate NetworkX function to find all maximal cliques in the graph.
    * For each maximal clique compute the aggregated weight of the clique (the sum of the weights of all events in that clique).
6. Write the Results Back to Excel:
    * In the same input.xlsx file, create or replace a worksheet named "MaximalCliques".
    * List all event names in the first row, starting form B1 and visually distinguished the row by having a gray background color
    * Add every maximal clique in a separate row, starting from A2, while writing the aggregated weight to the cell in column A and denoting a X for every cell on the row that corresponds to an event that is contained in the maximal clique
    * Format the entire column A as auto-fit column width
7. Implementation Details:
    * Use the pandas library for data manipulation.
    * Include the Python standard script entry point using if __name__ == "__main__": to ensure proper script execution.
    * import ipdb, but do not use it yet
8. Final Step - Open the File:
    * After the script has completed processing and saving the file, automatically open input.xlsx