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parameterframe

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parameterframe

A tool to manage parameters in a form of files, process them, upload to param storage, pull and reconstrut as files.

  • 0.1.6
  • PyPI
  • Socket score

Maintainers
1

Parameterframe

The module provides an interface for managing solution parameters. It allows for the structured storage and retrieval of parameter sets from a database.

import sys
import pandas as pd
import os
sys.path.append('../')
from parameterframe import ParameterFrame, MockerDatabaseConnector, SqlAlchemyDatabaseManager

Content

  1. Adding new solution and uploading it
  2. Processing new files and creating parameter set
  3. Adding parameter set to solution and commiting
  4. Uploading parameter sets
  5. Getting latest parameter set id for solution
  6. Changing parameter set status
  7. Pulling select parameter sets
  8. Reconstructing parameter se
  9. Structure of local commit tables
  10. Scores

1. Adding new solution and uploading it

# - with database connector for MockerDB
pf = ParameterFrame(
    database_connector = MockerDatabaseConnector(connection_details = {
    'base_url' : 'http://localhost:8001'})
)

when using SqlAlchemyDatabaseManager with database for the first time, it might be useful to create tables with SqlAlchemyDatabaseManager.create_tables and if schema of the database needs to be reset SqlAlchemyDatabaseManager.drop_tables

# - with SqlAlchemy database connector
pf = ParameterFrame(
    database_connector = SqlAlchemyDatabaseManager(connection_details = {
    'base_url' : 'postgresql+psycopg2://postgres:mysecretpassword@localhost:5432/mytestdb'})
)
pf.show_solutions()
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
solution_idsolution_namesolution_descriptiondeployment_datedeprecation_datemaintainerscommited_parameter_setsaospos
pf.add_solution(
    # mandatory
    solution_name="new_example_solution",
    # optional description
    solution_description="Description of new example solution.",
    deployment_date="2024-xx-xx",
    deprecation_date=None,
    maintainers="some text about maintainers credentials"
)

pf.add_solution(
    # mandatory
    solution_name="new_example_solution2",
    # optional description
    solution_description="Description of new example solution.",
    deployment_date="2024-xx-xx",
    deprecation_date=None,
    maintainers="some text about maintainers credentials"
)
Solution id for new_example_solution: b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca
Solution id for new_example_solution2: 1c0b910dc0074ea3966fbb1a96038e5eaee8dc1b873f9867830e0659b54dd311





True
pf.commit_solution(
    # either solution id or solution name should be provided
    solution_name="new_example_solution"
)

pf.commit_solution(
    # either solution id or solution name should be provided
    solution_name="new_example_solution2"
)
Commited solution description for b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca
Commited solution description for 1c0b910dc0074ea3966fbb1a96038e5eaee8dc1b873f9867830e0659b54dd311





True
pf.show_solutions()
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
solution_idsolution_namesolution_descriptiondeployment_datedeprecation_datemaintainerscommited_parameter_setsaospos
0b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8canew_example_solutionDescription of new example solution.2024-xx-xxNonesome text about maintainers credentials000
11c0b910dc0074ea3966fbb1a96038e5eaee8dc1b873f9867830e0659b54dd311new_example_solution2Description of new example solution.2024-xx-xxNonesome text about maintainers credentials000
pf.push_solution(
    # either solution id or solution name should be provided
    solution_name = "new_example_solution"
)
True

2. Processing new files and creating parameter set

params_path = "../tests/parameterframe/example_configs"
pf = ParameterFrame(
    params_path = params_path,
    database_connector = MockerDatabaseConnector(connection_details = {
    'base_url' : 'http://localhost:8001'})
)
pf = ParameterFrame(
    params_path = params_path,
    database_connector = SqlAlchemyDatabaseManager(connection_details = {
    'base_url' : 'postgresql+psycopg2://postgres:mysecretpassword@localhost:5432/mytestdb'})
)
pf.process_parameters_from_files()
True
pf.show_solutions()
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
solution_idsolution_namesolution_descriptiondeployment_datedeprecation_datemaintainerscommited_parameter_setsaospos
pf.make_parameter_set(
    parameter_set_name="test_set",
    parameter_set_description="example parameters for test purposes",
    parameter_names=['param_1','param_2','param_10', 'param_11','param_21']
)
Parameter set id for test_set: a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5

3. Adding parameter set to solution and commiting

pf.add_parameter_set_to_solution(
    solution_id = 'b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca',
    parameter_set_name="test_set")
b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca is not in solutions saved to memory!
Name pink_happy_car_642 is assigned to b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca temporarily!





True
pf.commit_solution(solution_name="pink_happy_car_642",
                    parameter_set_names=["test_set"])
Commited solution tables for b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca





True
pf.show_solutions()
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
solution_idsolution_namesolution_descriptiondeployment_datedeprecation_datemaintainerscommited_parameter_setsaospos
0b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8caNoneNoneNoneNoneNone10.050.0
pf.show_parameter_sets(solution_id = 'b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca')
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
parameter_set_idparameter_set_nameparameter_set_descriptiondeployment_statusinsertion_datetimecommited_parametersaospos
0a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5test_setexample parameters for test purposesSTAGING2024-05-21 03:03:2350.050.0
pf.show_parameters(solution_id = 'b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca',
                   parameter_set_id = 'a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5')
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
parameter_idparameter_nameparameter_descriptionfile_namefile_typecommited_attributesaos
04cea5b09e77da310c5105978f2ceea5c5d8c9c7b65d0e00b45135ea90fc011afparam_1param_1.yamlyaml30.05
1bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5fparam_2param_2.yamlyaml60.05
29a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36beparam_10param_10.txttxt90.00
3ace2f31433212fbf9e764069a30a7675ca78f496d31f061d06d0a0420fc52768param_11param_11.dillother10.00
41a4f19ee9e186ee739daecbc778501c5851d3fb5d05c4a3c1200e599855e8689param_21param_21.ipynbother20.00

4. Uploading parameter sets

pf.push_solution(solution_id='b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca',
                 parameter_set_names=["test_set"])
True

5. Getting latest parameter set id for solution

# - with database connector for MockerDB
pf = ParameterFrame(
    database_connector = MockerDatabaseConnector(connection_details = {
    'base_url' : 'http://localhost:8001'})
)
# - with SqlAlchemy database connector
pf = ParameterFrame(
    database_connector = SqlAlchemyDatabaseManager(connection_details = {
    'base_url' : 'postgresql+psycopg2://postgres:mysecretpassword@localhost:5432/mytestdb'})
)
pf.get_parameter_set_id_for_solution(solution_id='b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca',
                                                        deployment_status="STAGING")
['a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5']
pf.get_deployment_status(solution_id='b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca',
                         parameter_set_id='a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5')
'STAGING'

6. Changing parameter set status

# - with database connector for MockerDB
pf = ParameterFrame(
    database_connector = MockerDatabaseConnector(connection_details = {
    'base_url' : 'http://localhost:8001'})
)
# - with SqlAlchemy database connector
pf = ParameterFrame(
    database_connector = SqlAlchemyDatabaseManager(connection_details = {
    'base_url' : 'postgresql+psycopg2://postgres:mysecretpassword@localhost:5432/mytestdb'})
)
pf.database_connector.modify_parameter_set_status(
    solution_id='b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca',
    parameter_set_ids = 'a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5',
    current_deployment_status = "PRODUCTION",
    new_deployment_status = "STAGING"
)
True
pf.change_status_from_staging_to_production(
    solution_id='b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca',
    parameter_set_id='a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5'
)
b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca + a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5 : STAGING -> PRODUCTION
pf.get_deployment_status(solution_id='b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca',
                         parameter_set_id='a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5')
'PRODUCTION'
pf.change_status_from_production_to_archived(
    solution_id='b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca',
    parameter_set_id='a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5'
)
b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca + a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5 : PRODUCTION -> ARCHIVED
pf.get_deployment_status(solution_id='b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca',
                         parameter_set_id='a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5')
'ARCHIVED'
pf.change_status_from_archived_production(
    solution_id='b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca',
    parameter_set_id='a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5'
)
No deployed parameter_set_ids with PRODUCTION from selected!
b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca + a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5 : ARCHIVED -> PRODUCTION
pf.get_deployment_status(solution_id='b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca',
                         parameter_set_id='a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5')
'PRODUCTION'

7. Pulling select parameter sets

params_path = "../tests/parameterframe/example_configs"
# - with database connector for MockerDB
pf2 = ParameterFrame(
    params_path = params_path,
    database_connector = MockerDatabaseConnector(connection_details = {
    'base_url' : 'http://localhost:8001'})
)
# - with SqlAlchemy database connector
pf2 = ParameterFrame(
    params_path = params_path,
    database_connector = SqlAlchemyDatabaseManager(connection_details = {
    'base_url' : 'postgresql+psycopg2://postgres:mysecretpassword@localhost:5432/mytestdb'})
)
pf2.show_solutions()
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
solution_idsolution_namesolution_descriptiondeployment_datedeprecation_datemaintainerscommited_parameter_setsaospos

When pulling information with database handler, one could pull specific parameter sets, solutions and everything.

pf2.pull_solution(solution_id='b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca',
                  # optionally specify parameter_set_id
                 parameter_set_id='a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5')
HTTP Request: POST http://localhost:8001/search "HTTP/1.1 200 OK"
HTTP Request: POST http://localhost:8001/search "HTTP/1.1 200 OK"
HTTP Request: POST http://localhost:8001/search "HTTP/1.1 200 OK"
No data was found with applied filters!
No solutions with b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca could be pulled!





True
pf2.pull_solution(solution_id='b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca',
                  # optionally specify parameter_set_id
                 parameter_set_id=None)
No solutions with b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca could be pulled!
No parameter sets were pulled for solution_id b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca
Nothing was pulled for b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca





True
pf2.pull_solution(
    # optional parameter to skip pull of attributes if data pulled just for show_ methods
    pull_attribute_values = False
)
True
pf2.show_solutions()
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
solution_idsolution_namesolution_descriptiondeployment_datedeprecation_datemaintainerscommited_parameter_setsaospos
0cec89c4cbb8c891d388407ea93d84a5cd4f996af6d5c1b0cc5fe1cb12101acf5new_example_solutionDescription of new example solution.2024-xx-xxNonesome text about maintainers credentials60.3971570.428571
pf2.show_parameter_sets(solution_id='cec89c4cbb8c891d388407ea93d84a5cd4f996af6d5c1b0cc5fe1cb12101acf5')
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
parameter_set_idparameter_set_nameparameter_set_descriptiondeployment_statusinsertion_datetimecommited_parametersaospos
05779bbf896ebb8f09a6ea252b09f8adb1a416e8780cf1424fb9bb93dbec8deb5green_tiny_car_749STAGING2024-05-15 01:36:0930.0257440.285714
173ece98c90d4e0bcce8b523a8e8d2bd4290c68f2a783ea279b39fe4507e42de7blue_fuzzy_refrigerator_297STAGING2024-05-15 23:57:1710.0000000.000000
282b8c5340454adf83667e59092fedbee28213475fd58ab6b3d95b4fc60f4d45fpurple_giant_television_135STAGING2024-05-16 00:05:4310.3714130.142857
33940d6dd4c0d817625a31141874c54cf0c8d88b24994f7915deb4096b3c8d0cfblue_tiny_television_381STAGING2024-05-15 00:37:5020.0257440.285714
4dddc057bc151de9f8fb8caa834c8e13b789cf68cb53299b4c65c23f1e1310acdred_sad_scooter_769STAGING2024-05-16 00:08:2120.3714130.142857
52f3ee8e19d91a89298d40984df5e7bdd1f1a48008b2e61c88a7f6f81b4ab23f5silver_happy_car_441STAGING2024-05-16 00:03:2510.0000000.000000
pf2.show_parameters(solution_id='cec89c4cbb8c891d388407ea93d84a5cd4f996af6d5c1b0cc5fe1cb12101acf5',
                    parameter_set_id='3940d6dd4c0d817625a31141874c54cf0c8d88b24994f7915deb4096b3c8d0cf')
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
parameter_idparameter_nameparameter_descriptionfile_namefile_typecommited_attributesaos
03386ebc962b1c57745ca24320bf873df6eb84a2b9cb733607d72006347bf95b8Screenshot 2024-05-04 at 02Screenshot 2024-05-04 at 02.59.31.pngother350.0
15afae3951544cd3736685a3b2daa31c00106191a799b96b0c636cd35e9a416ffuploadsuploads.zipother610.0
pf2.show_parameters(solution_id='cec89c4cbb8c891d388407ea93d84a5cd4f996af6d5c1b0cc5fe1cb12101acf5',
                    parameter_set_id='5779bbf896ebb8f09a6ea252b09f8adb1a416e8780cf1424fb9bb93dbec8deb5')
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
parameter_idparameter_nameparameter_descriptionfile_namefile_typecommited_attributesaos
03386ebc962b1c57745ca24320bf873df6eb84a2b9cb733607d72006347bf95b8Screenshot 2024-05-04 at 02Screenshot 2024-05-04 at 02.59.31.pngother350.0
14d8ca206d9bd09296b69a95f0c3c62d233282025964c356811510cc074cc2c4911. AF - opis projektu.pdfother340.0
25afae3951544cd3736685a3b2daa31c00106191a799b96b0c636cd35e9a416ffuploadsuploads.zipother610.0
pf2.show_parameters(solution_id='cec89c4cbb8c891d388407ea93d84a5cd4f996af6d5c1b0cc5fe1cb12101acf5',
                    parameter_set_id='dddc057bc151de9f8fb8caa834c8e13b789cf68cb53299b4c65c23f1e1310acd')
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
parameter_idparameter_nameparameter_descriptionfile_namefile_typecommited_attributesaos
0e6ae9d10f3b4d69c1ef6ff8038d13e9f0b093fc3710f2fed0259204aac2fcba4Geekbench 6Geekbench 6.app.zipother13850.0
1be0886c2f5d24aa5672bf84e355d9d4adb527a36e5e973413c555200d7f3fdb2OllamaOllama.app.zipother14000.0
pf2.show_parameters(solution_id='cec89c4cbb8c891d388407ea93d84a5cd4f996af6d5c1b0cc5fe1cb12101acf5',
                    parameter_set_id='82b8c5340454adf83667e59092fedbee28213475fd58ab6b3d95b4fc60f4d45f')
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
parameter_idparameter_nameparameter_descriptionfile_namefile_typecommited_attributesaos
0e6ae9d10f3b4d69c1ef6ff8038d13e9f0b093fc3710f2fed0259204aac2fcba4Geekbench 6Geekbench 6.app.zipother13850.0

8. Reconstructing parameter set

os.listdir("../tests/parameterframe/reconstructed_files")
[]
pf2.reconstruct_parameter_set(
    solution_name = "new_example_solution",
    parameter_set_name = "test_set",
    params_path = "../tests/parameterframe/reconstructed_files"
)

os.listdir("../tests/parameterframe/reconstructed_files")
['param_2.yaml',
 'param_11.dill',
 'param_1.yaml',
 'param_10.txt',
 'param_21.ipynb']

9. Structure of commit tables

solution_description
pd.DataFrame(pf2.commited_tables['b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca']['solution_description'])
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
solution_idsolution_namesolution_descriptiondeployment_datedeprecation_datemaintainers
0b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8canew_example_solutionDescription of new example solution.2024-xx-xxNonesome text about maintainers credentials
solution_parameter_set
param_set_id = 'a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5'

pd.DataFrame(pf2.commited_tables['b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca']['solution_parameter_set'][param_set_id])
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
solution_idparameter_set_iddeployment_statusinsertion_datetime
0b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8caa54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5PRODUCTION2024-05-07 19:51:13
parameter_set
pd.DataFrame(pf2.commited_tables['b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca']\
    ['parameter_set']\
        [param_set_id])
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
parameter_set_idparameter_id
0a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d54cea5b09e77da310c5105978f2ceea5c5d8c9c7b65d0e00b45135ea90fc011af
1a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5f
2a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d59a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36be
3a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5ace2f31433212fbf9e764069a30a7675ca78f496d31f061d06d0a0420fc52768
4a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d51a4f19ee9e186ee739daecbc778501c5851d3fb5d05c4a3c1200e599855e8689
parameter_set_description
pd.DataFrame(pf2.commited_tables['b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca']\
    ['parameter_set_description']\
        [param_set_id])
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
parameter_set_idparameter_set_nameparameter_set_description
0a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5test_setexample parameters for test purposes
parameter_description
pd.DataFrame([tab for param_id, tab_list in pf2.commited_tables['b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca']\
    ['parameter_description']\
        [param_set_id].items()\
            for tab in tab_list])
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
parameter_idparameter_nameparameter_descriptionfile_namefile_type
04cea5b09e77da310c5105978f2ceea5c5d8c9c7b65d0e00b45135ea90fc011afparam_1param_1.yamlyaml
1bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5fparam_2param_2.yamlyaml
29a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36beparam_10param_10.txttxt
3ace2f31433212fbf9e764069a30a7675ca78f496d31f061d06d0a0420fc52768param_11param_11.dillother
41a4f19ee9e186ee739daecbc778501c5851d3fb5d05c4a3c1200e599855e8689param_21param_21.ipynbother
parameter_attribute
pd.DataFrame([tab for param_id, tab_list in pf2.commited_tables['b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca']\
    ['parameter_attribute']\
        [param_set_id].items() \
            for tab in tab_list])
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
parameter_idattribute_idprevious_attribute_id
04cea5b09e77da310c5105978f2ceea5c5d8c9c7b65d0e00b45135ea90fc011afee25af17445d7622cbf61a5b9424246a1f3104704b68bd31b9b7532471d492e5None
14cea5b09e77da310c5105978f2ceea5c5d8c9c7b65d0e00b45135ea90fc011af8b5b2be24e60ba407b90967820da8a1385a6d67691a02bc663703160ef655101None
24cea5b09e77da310c5105978f2ceea5c5d8c9c7b65d0e00b45135ea90fc011af52ea872c99c586530348ba8902dcab831761673d25cf1cb0023576820289ce6bNone
3bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5f7d5ee0e0cd00c3703e5f346c6887baf503faaf9fe090774f6866311f4fa34179None
4bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5fee25af17445d7622cbf61a5b9424246a1f3104704b68bd31b9b7532471d492e57d5ee0e0cd00c3703e5f346c6887baf503faaf9fe090774f6866311f4fa34179
5bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5f3367512147bf19ae99c986b356af11dcdc067376aa1b79eb8ba8f61324e8dc187d5ee0e0cd00c3703e5f346c6887baf503faaf9fe090774f6866311f4fa34179
6bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5f341769820d8937a5c9f9b980eefca37f3f37fcc6fd01c6f4c930fdb9d5dd51287d5ee0e0cd00c3703e5f346c6887baf503faaf9fe090774f6866311f4fa34179
7bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5f2e8b00e571f9d835d3f022a9ff49b9779034ab21bffdcde075d9d729fabeb960341769820d8937a5c9f9b980eefca37f3f37fcc6fd01c6f4c930fdb9d5dd5128
8bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5fecd93cf051988b23b3590415f4e7d550de264600d7d2af8704c973b9c98ca6a9341769820d8937a5c9f9b980eefca37f3f37fcc6fd01c6f4c930fdb9d5dd5128
99a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36befa4e8d81f4dbe6d306aff59bea4693d325a203be5d5b9fde5d5f1e7cce26b861None
109a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36bec26e7e96f0f3647c159b0934f4dc55207ac059abb56005d7a8acd8344ef14798fa4e8d81f4dbe6d306aff59bea4693d325a203be5d5b9fde5d5f1e7cce26b861
119a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36bef7cd339f77c1799f399d8ebcbb27f2d41a448622254d64e9270ae2316211ac1dc26e7e96f0f3647c159b0934f4dc55207ac059abb56005d7a8acd8344ef14798
129a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36be15a33fe62774a1857b404f453ba1195eb4355e10bc9519f2f991dd7ba8db19b7f7cd339f77c1799f399d8ebcbb27f2d41a448622254d64e9270ae2316211ac1d
139a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36be99761e3d58bc213dc3ab33f2dc8dabe5f97d3aea6b59cd367d40b76937f49aa615a33fe62774a1857b404f453ba1195eb4355e10bc9519f2f991dd7ba8db19b7
149a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36be036a9c122c1f4c9304afa23c4d1fce5224c270a206889afa689f3efb36ff368d99761e3d58bc213dc3ab33f2dc8dabe5f97d3aea6b59cd367d40b76937f49aa6
159a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36bee72aa8015688052f4e7fddbf4c74e5bf2bd74239ebf3902a5fdc008ecb03aa46036a9c122c1f4c9304afa23c4d1fce5224c270a206889afa689f3efb36ff368d
169a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36be0ae8eda3dbeedbc17e27a679c5426dd3af1434f7c37b4ecd3b2fb5c492272b75e72aa8015688052f4e7fddbf4c74e5bf2bd74239ebf3902a5fdc008ecb03aa46
179a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36becedcfbb0d95798514b6aaf30118fff7b46f863f1bc8b80bb2ddd2145e5b3f3180ae8eda3dbeedbc17e27a679c5426dd3af1434f7c37b4ecd3b2fb5c492272b75
18ace2f31433212fbf9e764069a30a7675ca78f496d31f061d06d0a0420fc52768ace2f31433212fbf9e764069a30a7675ca78f496d31f061d06d0a0420fc52768None
191a4f19ee9e186ee739daecbc778501c5851d3fb5d05c4a3c1200e599855e868987d93e1862f0f58199c3fcb7114b92fe59f03581804b1c8419868fb00ff8a469None
201a4f19ee9e186ee739daecbc778501c5851d3fb5d05c4a3c1200e599855e8689b4a705d09aa0361f4db453da32abb05a5c4e0249d6180d2b8a58d72d08dbd6a087d93e1862f0f58199c3fcb7114b92fe59f03581804b1c8419868fb00ff8a469
211a4f19ee9e186ee739daecbc778501c5851d3fb5d05c4a3c1200e599855e8689e4e2c33a2ea67f34bf3ac1e9d99edaad501c7dc4ea82f4b60e9d959418d8438db4a705d09aa0361f4db453da32abb05a5c4e0249d6180d2b8a58d72d08dbd6a0
221a4f19ee9e186ee739daecbc778501c5851d3fb5d05c4a3c1200e599855e8689777abf12375b7f605b21535eb0d6232ce99581c6d2b1179af976cd0708ad27ffe4e2c33a2ea67f34bf3ac1e9d99edaad501c7dc4ea82f4b60e9d959418d8438d
attribute_values
pd.DataFrame([tab for param_id, tab_list in pf2.commited_tables['b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca']\
    ['attribute_values']\
        [param_set_id].items() \
            for tab in tab_list])
.dataframe tbody tr th:only-of-type { vertical-align: middle; } .dataframe tbody tr th { vertical-align: top; } .dataframe thead th { text-align: right; }
attribute_idprevious_attribute_idattribute_nameattribute_valueattribute_value_type
0ee25af17445d7622cbf61a5b9424246a1f3104704b68bd31b9b7532471d492e5NonenameSome namestr
18b5b2be24e60ba407b90967820da8a1385a6d67691a02bc663703160ef655101Noneage111int
252ea872c99c586530348ba8902dcab831761673d25cf1cb0023576820289ce6bNonecountrySome landstr
3ee25af17445d7622cbf61a5b9424246a1f3104704b68bd31b9b7532471d492e5NonenameSome namestr
47d5ee0e0cd00c3703e5f346c6887baf503faaf9fe090774f6866311f4fa34179Noneemployee{'name': 'Some name', 'id': 10293, 'contact': {'email': 'some.name...dict
53367512147bf19ae99c986b356af11dcdc067376aa1b79eb8ba8f61324e8dc18Noneid10293int
6341769820d8937a5c9f9b980eefca37f3f37fcc6fd01c6f4c930fdb9d5dd5128Nonecontact{'email': 'some.name@example.com', 'phone': '+1234567890'}dict
72e8b00e571f9d835d3f022a9ff49b9779034ab21bffdcde075d9d729fabeb960Noneemailsome.name@example.comstr
8ecd93cf051988b23b3590415f4e7d550de264600d7d2af8704c973b9c98ca6a9Nonephone+1234567890str
9fa4e8d81f4dbe6d306aff59bea4693d325a203be5d5b9fde5d5f1e7cce26b861None0\X/Fc7;/v`6joU5z*n{35zFB<<6BMC,}/_04],>v$Jr2&0M_7qU'IY#6uO\$kEr.)Z...str
10c26e7e96f0f3647c159b0934f4dc55207ac059abb56005d7a8acd8344ef14798None1A7J+1x5|?r]2zg54nxoa>W*loh8Np~*9+*KxWLuD/Z5g!=DN>}c#]Dt->tiov?|Ms....str
11f7cd339f77c1799f399d8ebcbb27f2d41a448622254d64e9270ae2316211ac1dNone2LUs%<HRbNA_4:yYTh!!x&oFZ201sQ7;~Q_IYr"lGRMd=xx,r}|n8zHIP6%JN)",vQI...str
1215a33fe62774a1857b404f453ba1195eb4355e10bc9519f2f991dd7ba8db19b7None3b&z(/Z{s@U>@o!}{+(mmygo}u~AHgdu>:jz4fNBm0;Q6'o+f%H/z3^8Hh!w<#z.~21...str
1399761e3d58bc213dc3ab33f2dc8dabe5f97d3aea6b59cd367d40b76937f49aa6None4.#;5Cu]5~8ZmYBLI4w)|h=)C<(#`KSoM,`7n?dun7]LX>j7/U>Jf||4`AN_u*W!*3)...str
14036a9c122c1f4c9304afa23c4d1fce5224c270a206889afa689f3efb36ff368dNone50S)*}6"i)kUg3=n:}>Ji)!"BTbzsdgps8{cR]`.41QJ<O{wr[}}gGan_O63D0WBr]<...str
15e72aa8015688052f4e7fddbf4c74e5bf2bd74239ebf3902a5fdc008ecb03aa46None6Xb;IgM/`T:VY*6XQ:nvB3)>@32w8H-cD"g>x`MlWp_TnuyCaz62e??md<8tR$Q=X7<...str
160ae8eda3dbeedbc17e27a679c5426dd3af1434f7c37b4ecd3b2fb5c492272b75None7pq.%\nmm;M!^cyS|ApMpnjUS<#Ov?e+n"wX/to.wjifCG.fKK@6gI+Wvax&}j18R8p...str
17cedcfbb0d95798514b6aaf30118fff7b46f863f1bc8b80bb2ddd2145e5b3f318None8+-;Zt=exstr
18ace2f31433212fbf9e764069a30a7675ca78f496d31f061d06d0a0420fc52768None0b'\x80\x04\x95h\x00\x00\x00\x00\x00\x00\x00}\x94(\x8c\x07integer\x...bytes
1987d93e1862f0f58199c3fcb7114b92fe59f03581804b1c8419868fb00ff8a469None0b'{\n "cells": [\n {\n "cell_type": "markdown",\n "metadata":...bytes
20b4a705d09aa0361f4db453da32abb05a5c4e0249d6180d2b8a58d72d08dbd6a0None1xt/plain": [\n "4"\n ]\n },\n "execution_count"...bytes
21e4e2c33a2ea67f34bf3ac1e9d99edaad501c7dc4ea82f4b60e9d959418d8438dNone2"language": "python",\n "name": "python3"\n },\n "language_...bytes
22777abf12375b7f605b21535eb0d6232ce99581c6d2b1179af976cd0708ad27ffNone3r": "python",\n "pygments_lexer": "ipython3",\n "version": "3....bytes

10. Scores

I. Attribute overlap ratio

AOR represents an overlap ratio between attribute ids that:

  • belong to a parameter within parameter set
  • belong to a parameter sets within solution
  • belong to a solution within solutions

The score is between $0$ and $1$, and the greater the score, the greater is an overlap between attribute ids within select group and non unique attribute ids.

II. Parameter overlap ratio

POR represents an overlap ratio between parameter ids that:

  • belong to a parameter sets within solution
  • belong to a solution within solutions

The score is between $0$ and $1$, and the greater the score, the greater is an overlap between parameter ids within select group and non unique parameter ids.

Keywords

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