Remove DataBundle.tables; instead overwrite DataBundle.data and use new property mode

[ludwiglierhammer]

Current status

Write data to new property DataBundle.tables after calling function method DataBundle.map_model.
Object DataBundle then contains data, mask and tables.
Processing huge data could explode the memory.
In addition, having both DataBundel.data and DataBundle.tables could lead to some confusion.

Solution

• function method DataBundle.map_model overwrites DataBundle.data
• funciton method DataBundle.map_model deletes DataBundle.mask
• optionally, DataBundle.map_model does not overwrite DataBundle.data and does not delete DataBundle.mask but returns mapped tables as a pd.DataFrame

Questions

@jtsiddons: What do you think about this idea?

[codecov-commenter]

Codecov Report

Attention: Patch coverage is 79.27928% with 23 lines in your changes missing coverage. Please review.

Project coverage is 84.10%. Comparing base (87403d8) to head (dd251a5).
Report is 78 commits behind head on main.

Files with missing lines	Patch %	Lines
cdm_reader_mapper/core/databundle.py	69.04%	13 Missing ⚠️
cdm_reader_mapper/cdm_mapper/reader.py	80.95%	8 Missing ⚠️
cdm_reader_mapper/core/reader.py	90.90%	1 Missing ⚠️
cdm_reader_mapper/core/writer.py	88.88%	1 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #238      +/-   ##
==========================================
- Coverage   84.23%   84.10%   -0.14%     
==========================================
  Files          76       78       +2     
  Lines        2817     2863      +46     
==========================================
+ Hits         2373     2408      +35     
- Misses        444      455      +11     

Flag	Coverage Δ
unittests	84.10% <79.27%> (-0.14%)	⬇️

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[ludwiglierhammer]

@jtsiddons: I implemented two general functions with parameter mode:

• cdm_reader_mapper.read:
  • mode == "mdf": calls cdm_reader_mapper.read_mdf
  • mode == "data": calls cdm_reader_mapper.read_data
  • mode == "tables": calls cdm_reader_mapper.read_tables
• cdm_reader_mapper.write:
  • mode == "data": calls cdm_reader_mapper.write_data
  • mode == "tables": calls cdm_reader_mapper.write_tables

[jtsiddons]

@jtsiddons: I implemented two general functions with parameter mode:

* `cdm_reader_mapper.read`:
  
  * `mode` == "mdf": calls `cdm_reader_mapper.read_mdf`
  * `mode` == "data": calls `cdm_reader_mapper.read_data`
  * `mode` == "tables": calls `cdm_reader_mapper.read_tables`

* `cdm_reader_mapper.write`:
  
  * `mode` == "data":  calls `cdm_reader_mapper.write_data`
  * `mode` == "tables":  calls `cdm_reader_mapper.write_tables`

To be clear, read and write are wrapper functions that call the appropriate function based on the mode argument?

Will the read_mdf, etc functions still be accessible in the same way as before?

[ludwiglierhammer]

@jtsiddons: I implemented two general functions with parameter mode:

* `cdm_reader_mapper.read`:
  
  * `mode` == "mdf": calls `cdm_reader_mapper.read_mdf`
  * `mode` == "data": calls `cdm_reader_mapper.read_data`
  * `mode` == "tables": calls `cdm_reader_mapper.read_tables`

* `cdm_reader_mapper.write`:
  
  * `mode` == "data":  calls `cdm_reader_mapper.write_data`
  * `mode` == "tables":  calls `cdm_reader_mapper.write_tables`

To be clear, read and write are wrapper functions that call the appropriate function based on the mode argument?

Will the read_mdf, etc functions still be accessible in the same way as before?

Exactly, read and write are just wrapper functions. The other functions will still be accessible.