setprint 0.1.13

A Python package for organizing and visualizing list hierarchies.

SetPrint - Simplify Formatting and Display of High-Dimensional Data!

SetPrint is a Python library designed to easily format and display multi-dimensional data in lists.
Even for data structures with mixed dimensions, you no longer need to manually adjust spaces or formatting. It automatically achieves beautiful formatting!

Documentation

• 日本語のドキュメント

Features

• Support for Flexible Data Structures: Automatically formats multi-dimensional lists and mixed data structures.
• Great for Debugging: Organizes and displays the structure and contents of data during execution in an easy-to-understand way.
• Flexible Formatting: Visually organizes data hierarchy and content with guided formatting.

Methods

• set_list Method

  • The set_list method of the SetPrint class provides a feature to easily format and output multi-dimensional lists and complex data structures in a visually comprehensible format.
    Using this method enables optimal formatting tailored to the dimensions of the data.

  • Parameters

    • guide (bool): Enables or disables the guide display.

      • If True, outputs a guide containing dimension and index information.

    • keep_start (int): The dimension where flattening begins.

      • Example: keep_start=1 expands the first dimension in the Y direction.

    • keeplen (int): The range of dimensions to flatten.

      • Dimensions outside the specified range are boxed in the X direction.

  • Return Values

    • input_list : The original list before formatting.
    • grid_slice : A list containing the formatted text information, with each line stored individually. It can be written directly to a text file to check the results.
    • grid_block : A list maintaining the block-shaped format of the structured data.
    • block_Xlines_data: Data used for displaying detailed indices with the GuidePrint function.

    Relationship Between keep_start and Data Formatting

    The keep_start parameter specifies the dimension where formatting begins and organizes data in the most suitable format based on its structure and use case. Below are examples of how keep_start values affect formatting and their corresponding data types.

    Recommended Settings

  1. keep_start=1

     • Use Case: Data expanding in the Y direction (e.g., logs or image data).
     • Description: Formats data along the first dimension in the Y direction while maintaining the X direction as-is.
     • Example (Debug Log):

       logs = [
           ["Value", 30, "is", "less than", 50],
           [["Action", "Process"], ["Details", "Valid range"]],
           [["Value", 90], ["Condition", ["greater than", 50]], ["Action", "Alert"]],
       ]
       

     • Formatted Result:

       Formatted Log:
       =================================================================================================================================
       
       |  ►list [ Value   ------ -------      30   --------- -----------   ------------ --        is   ------ -----   less than 50 ]   |
       |  ►list [ ►list { Action Process ) ►list {   Details Valid range   ------------ --   ) -----   ------ -----   --------- -- ]   |
       |  ►list [ ►list {  Value      90 ) ►list { Condition       ►list { greater than 50 ) ) ►list { Action Alert ) --------- -- ]   |
       
       =================================================================================================================================
       

     • Execution Example:

       from setprint import SetPrint
       
       # Format and display the data
       list_data = SetPrint(logs)
       set_datas = list_data.set_list(guide=False, keep_start=1, keeplen=10)
       
       print("\nFormatted Log:")
       for line in set_datas['grid_slice']:
           print(line[:-1])  # Output formatted log
       

  2. keep_start=2

     • Use Case: Information divided in the X direction (e.g., tabular data).
     • Description: Formats data along the second dimension in the X direction, emphasizing separation in the Y direction.
     • Example (Tabular Data):

       data = [
           ["Name", "Age", "Country"],
           ["Alice", 30, "USA"],
           ["Bob", 25, "UK"]
       ]
       

     • Formatted Result:

       Formatted Table:
       ====================================
         {} |  {n}                        |
            |-----------------------------|
            :                             :
            |  data_type: <class 'list'>  |
            |  data_type: <class 'list'>  |
            |  data_type: <class 'list'>  |
       
       ====================================
        {0} |  [0]{n}                     |
            |-----------------------------|
            :                             :
            |     Name                    |
            |      Age                    |
            |  Country                    |
       
       ====================================
        {1} |  [1]{n}                     |
            |-----------------------------|
            :                             :
            |  Alice                      |
            |     30                      |
            |    USA                      |
       
       ====================================
        {2} |  [2]{n}                     |
            |-----------------------------|
            :                             :
            |  Bob                        |
            |   25                        |
            |   UK                        |
       
       ====================================
       

     • Execution Example:

       list_data = SetPrint(data)
       set_datas = list_data.set_list(guide=True, keep_start=2)
       
       for line in set_datas['grid_slice']:
           print(line[:-1])
       

  3. keep_start=3

     • Use Case: Data separated in both Y and X directions (e.g., matrices or 3D arrays).

     • Description: Organizes data based on the third dimension, retaining overall structure while arranging information in both Y and X directions.

     • Example Input Data:

       data = [
           [[1, 2], [3, 4]],
           [[5, 6], [7, 8]]
       ]
       

     • Formatted Result:

       Formatted Matrix:
       ====================================
         {} |  {n}                        |
            |-----------------------------|
            :                             :
            |  data_type: <class 'list'>  |
            |  data_type: <class 'list'>  |
       
       ================================================================
        {0} |  [0]{n}                     |  [0][0]{n}  |  [0][1]{n}  |
            |-----------------------------|-------------|-------------|
            :                             :             :             :
            |  data_type: <class 'list'>  |  1          |  3          |
            |  data_type: <class 'list'>  |  2          |  4          |
       
       ================================================================
        {1} |  [1]{n}                     |  [1][0]{n}  |  [1][1]{n}  |
            |-----------------------------|-------------|-------------|
            :                             :             :             :
            |  data_type: <class 'list'>  |  5          |  7          |
            |  data_type: <class 'list'>  |  6          |  8          |
       
       ================================================================
       

     • Execution Example:

       list_data = SetPrint(data)
       set_datas = list_data.set_list(guide=False, keep_start=3, keeplen=10)
       
       print("\nFormatted Log:")
       for line in set_datas['grid_slice']:
           print(line[:-1])  # Output formatted log
       

• SetPrint.pick_guideprint(output_path)

  pick_guideprint operates as follows:

  • Move between blocks: Use the f, h, g, and t keys to navigate between different blocks.
  • Move within a block: Use the a, d, s, and w keys to navigate within the current block.
  • Directions: ← → ↓ ↑

  Displayed Information:

  • index: The index of the currently selected data (e.g., {y}[x0][x1][x2]).
  • value: The value stored in the currently selected index. The value is displayed in green, and the data type is displayed in blue.

  Parameters

  The pick_guideprint function accepts the following parameter:

  • output_path: (Required) The path to the linked text file.

  Execution Example

  • python

  # from setprint import SetPrint
  # list_data = setprint( `list` )
  # list_data.SET_list(guide=True,keep_start=1,keeplen=10)
  
  list_data.pick_guideprint( 'output_path' )
  

  Execution Result

  • txt_file

      ►list { [0][0] [0][1] [0][2]    ---------  ---------   [0][3]   --------- -----   ------------ ------------     ------ ------ ) 
     ------------------------------- ┏         ┓ -------------------------------------------------------------------------------------
      ►list { [1][0] [1][1]  ►list {  [1][2][0]  [1][2][1] ) [1][3]   --------- -----   ------------ ------------     ------ ------ ) 
     ------------------------------- ┗         ┛ -------------------------------------------------------------------------------------
      ►list { [2][0] [2][1] [2][2]    ---------  ---------    ►list { [2][3][0] ►list { [2][3][1][0] [2][3][1][1] ) ) [2][4] [2][5] ) 
      ►list { [3][0] [3][1] [3][2]    ---------  ---------   [3][3]   --------- -----   ------------ ------------     [3][4] ------ ) 
        [4]   ------ ------ ------    ---------  ---------   ------   --------- -----   ------------ ------------     ------ ------   
  

  • terminal

  index \ {1}[2][0]
  value \ [1][2][0] : str
  

• SetPrint.bloks_border_print()

  A function that allows you to create boxes, like the output result of setlist, and input strings into them.

  Parameters

  • All_blocks: (Required) A list array containing the content to be displayed.
  • line_title: (Required) The titles of the blocks in the Y-direction.
  • guide : (Required) Specifies whether to include titles. Accepts True or False.

  Example of All_blocks Storage

      '''
      # 1D corresponds to the Y-direction (blocks: rows)
      # 2D corresponds to the X-direction
      # 3D corresponds to the Y-direction (content: rows)
      ! All storage locations must be in the third dimension.
      '''
      
                                          Column 1                        Column 2                        Column 3
      All_blocks = [  
                      1step[ ['block_title','1line','2line'], ['1_2','1_txt','2_txt'] ]
                      2step[ ['2_1','1_data','2_data'],       ['2_2','1_line','2_line','3_line'], ['2_3','1_txt','2_txt']]
                      3step[ ['3_1','1_txt','2_txt']]
  
                  ]
  
      line_title = ['1step','2step','3step']
  

  
              A visual representation of the relationship    　　　　  |
              between the output result and `All_blocks`       　　　　|                       Output Result  
                                                                   　 |
      [                                                            　 |
                                                                   　 |
                       Column 1       Column 2  　   Column 3         |            
         ========================================                   　|      =====================================
          _____ [ ｜["block_title",｜["1_2",     ｜           　       |       {1step} |  block_title  |  1_2     |
                  ｜---------------｜------------｜           　       |               |---------------|----------|
                  ：               ：            ：           　       |               :               :          :
                  ｜ '1line',      ｜ '1_txt',   ｜           　       |               |  1line        |  1_txt   |
                  ｜ '2line' ],    ｜ '2_txt' ], ｜ ],         　      |               |  2line        |  2_txt   |
                                                                   　 |
         =====================================================      　|      ===============================================
          _____ [ ｜["2-1",        ｜["2-2",     ｜["2_3",    ｜       |       {2step} |  2_1          |  2_2     |  2_3    |
                  ｜---------------｜------------｜-----------｜       |               |---------------|----------|---------|
                  ：               ：            ：           ：       |               :               :          :         :
                  ｜ '1_data',     ｜ '1_line',  ｜ '1_txt',  ｜       |               |  1_data       |  1_line  |  1_txt  |
                  ｜ '2_data' ],   ｜ '2_line',  ｜ '2_txt' ],｜       |               |  2_data       |  2_line  |  2_txt  |
                  ｜               ｜ '3_line' ],｜           ｜ ],    |               |               |  3_line  |         |
                                                                   　 |
         =====================================================      　|      ===============================================
          _____ [ ｜["3-1",        ｜            　           　       |       {3step} |  3_1          |
                  ｜---------------｜            　           　       |               |---------------|
                  ：               ：            　           　       |               :               :
                  ｜ '1_txt',      ｜            　           　       |               |  1_txt        |
                  ｜ '2_txt' ],    ｜ ]          　           　       |               |  2_txt        |
                  　            　               　           　       |
         ===========================                                　|      ==========================
      ]  
  

  Return Value

  • grid_slice: A list containing the formatted text information. Each line is stored individually, allowing it to be directly written to a text file for review.

  Execution Example

  • python

  # from setprint import SetPrint
  
  list_data = setprint( `All_blocks` )
  grid_slice = blocks_border_print(line_title = line_title,　guide=True):
  
  with open('output_path','w') as f:
      for line in grid_slice:
          f.write(line)