parameterframe 0.1.6

Description:

parameterframe 0.1.6

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

Adding new solution and uploading it
Processing new files and creating parameter set
Adding parameter set to solution and commiting
Uploading parameter sets
Getting latest parameter set id for solution
Changing parameter set status
Pulling select parameter sets
Reconstructing parameter se
Structure of local commit tables
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()


<style scoped>
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solution_id
solution_name
solution_description
deployment_date
deprecation_date
maintainers
commited_parameter_sets
aos
pos






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()


<style scoped>
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solution_id
solution_name
solution_description
deployment_date
deprecation_date
maintainers
commited_parameter_sets
aos
pos




0
b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca
new_example_solution
Description of new example solution.
2024-xx-xx
None
some text about maintainers credentials
0
0
0


1
1c0b910dc0074ea3966fbb1a96038e5eaee8dc1b873f9867830e0659b54dd311
new_example_solution2
Description of new example solution.
2024-xx-xx
None
some text about maintainers credentials
0
0
0




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()


<style scoped>
.dataframe tbody tr th:only-of-type {
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}
.dataframe tbody tr th {
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}

</style>




solution_id
solution_name
solution_description
deployment_date
deprecation_date
maintainers
commited_parameter_sets
aos
pos






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()


<style scoped>
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}
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}

</style>




solution_id
solution_name
solution_description
deployment_date
deprecation_date
maintainers
commited_parameter_sets
aos
pos




0
b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca
None
None
None
None
None
1
0.05
0.0




pf.show_parameter_sets(solution_id = 'b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca')


<style scoped>
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vertical-align: middle;
}
.dataframe tbody tr th {
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text-align: right;
}

</style>




parameter_set_id
parameter_set_name
parameter_set_description
deployment_status
insertion_datetime
commited_parameters
aos
pos




0
a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5
test_set
example parameters for test purposes
STAGING
2024-05-21 03:03:23
5
0.05
0.0




pf.show_parameters(solution_id = 'b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca',
parameter_set_id = 'a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5')


<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}

.dataframe thead th {
text-align: right;
}

</style>




parameter_id
parameter_name
parameter_description
file_name
file_type
commited_attributes
aos




0
4cea5b09e77da310c5105978f2ceea5c5d8c9c7b65d0e00b45135ea90fc011af
param_1

param_1.yaml
yaml
3
0.05


1
bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5f
param_2

param_2.yaml
yaml
6
0.05


2
9a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36be
param_10

param_10.txt
txt
9
0.00


3
ace2f31433212fbf9e764069a30a7675ca78f496d31f061d06d0a0420fc52768
param_11

param_11.dill
other
1
0.00


4
1a4f19ee9e186ee739daecbc778501c5851d3fb5d05c4a3c1200e599855e8689
param_21

param_21.ipynb
other
2
0.00




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()


<style scoped>
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solution_id
solution_name
solution_description
deployment_date
deprecation_date
maintainers
commited_parameter_sets
aos
pos






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()


<style scoped>
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solution_id
solution_name
solution_description
deployment_date
deprecation_date
maintainers
commited_parameter_sets
aos
pos




0
cec89c4cbb8c891d388407ea93d84a5cd4f996af6d5c1b0cc5fe1cb12101acf5
new_example_solution
Description of new example solution.
2024-xx-xx
None
some text about maintainers credentials
6
0.397157
0.428571




pf2.show_parameter_sets(solution_id='cec89c4cbb8c891d388407ea93d84a5cd4f996af6d5c1b0cc5fe1cb12101acf5')


<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
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}

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text-align: right;
}

</style>




parameter_set_id
parameter_set_name
parameter_set_description
deployment_status
insertion_datetime
commited_parameters
aos
pos




0
5779bbf896ebb8f09a6ea252b09f8adb1a416e8780cf1424fb9bb93dbec8deb5
green_tiny_car_749

STAGING
2024-05-15 01:36:09
3
0.025744
0.285714


1
73ece98c90d4e0bcce8b523a8e8d2bd4290c68f2a783ea279b39fe4507e42de7
blue_fuzzy_refrigerator_297

STAGING
2024-05-15 23:57:17
1
0.000000
0.000000


2
82b8c5340454adf83667e59092fedbee28213475fd58ab6b3d95b4fc60f4d45f
purple_giant_television_135

STAGING
2024-05-16 00:05:43
1
0.371413
0.142857


3
3940d6dd4c0d817625a31141874c54cf0c8d88b24994f7915deb4096b3c8d0cf
blue_tiny_television_381

STAGING
2024-05-15 00:37:50
2
0.025744
0.285714


4
dddc057bc151de9f8fb8caa834c8e13b789cf68cb53299b4c65c23f1e1310acd
red_sad_scooter_769

STAGING
2024-05-16 00:08:21
2
0.371413
0.142857


5
2f3ee8e19d91a89298d40984df5e7bdd1f1a48008b2e61c88a7f6f81b4ab23f5
silver_happy_car_441

STAGING
2024-05-16 00:03:25
1
0.000000
0.000000




pf2.show_parameters(solution_id='cec89c4cbb8c891d388407ea93d84a5cd4f996af6d5c1b0cc5fe1cb12101acf5',
parameter_set_id='3940d6dd4c0d817625a31141874c54cf0c8d88b24994f7915deb4096b3c8d0cf')


<style scoped>
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vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}

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text-align: right;
}

</style>




parameter_id
parameter_name
parameter_description
file_name
file_type
commited_attributes
aos




0
3386ebc962b1c57745ca24320bf873df6eb84a2b9cb733607d72006347bf95b8
Screenshot 2024-05-04 at 02

Screenshot 2024-05-04 at 02.59.31.png
other
35
0.0


1
5afae3951544cd3736685a3b2daa31c00106191a799b96b0c636cd35e9a416ff
uploads

uploads.zip
other
61
0.0




pf2.show_parameters(solution_id='cec89c4cbb8c891d388407ea93d84a5cd4f996af6d5c1b0cc5fe1cb12101acf5',
parameter_set_id='5779bbf896ebb8f09a6ea252b09f8adb1a416e8780cf1424fb9bb93dbec8deb5')


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}

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parameter_id
parameter_name
parameter_description
file_name
file_type
commited_attributes
aos




0
3386ebc962b1c57745ca24320bf873df6eb84a2b9cb733607d72006347bf95b8
Screenshot 2024-05-04 at 02

Screenshot 2024-05-04 at 02.59.31.png
other
35
0.0


1
4d8ca206d9bd09296b69a95f0c3c62d233282025964c356811510cc074cc2c49
1

1. AF - opis projektu.pdf
other
34
0.0


2
5afae3951544cd3736685a3b2daa31c00106191a799b96b0c636cd35e9a416ff
uploads

uploads.zip
other
61
0.0




pf2.show_parameters(solution_id='cec89c4cbb8c891d388407ea93d84a5cd4f996af6d5c1b0cc5fe1cb12101acf5',
parameter_set_id='dddc057bc151de9f8fb8caa834c8e13b789cf68cb53299b4c65c23f1e1310acd')


<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
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vertical-align: top;
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text-align: right;
}

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parameter_id
parameter_name
parameter_description
file_name
file_type
commited_attributes
aos




0
e6ae9d10f3b4d69c1ef6ff8038d13e9f0b093fc3710f2fed0259204aac2fcba4
Geekbench 6

Geekbench 6.app.zip
other
1385
0.0


1
be0886c2f5d24aa5672bf84e355d9d4adb527a36e5e973413c555200d7f3fdb2
Ollama

Ollama.app.zip
other
1400
0.0




pf2.show_parameters(solution_id='cec89c4cbb8c891d388407ea93d84a5cd4f996af6d5c1b0cc5fe1cb12101acf5',
parameter_set_id='82b8c5340454adf83667e59092fedbee28213475fd58ab6b3d95b4fc60f4d45f')


<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}

.dataframe thead th {
text-align: right;
}

</style>




parameter_id
parameter_name
parameter_description
file_name
file_type
commited_attributes
aos




0
e6ae9d10f3b4d69c1ef6ff8038d13e9f0b093fc3710f2fed0259204aac2fcba4
Geekbench 6

Geekbench 6.app.zip
other
1385
0.0




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'])


<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}

.dataframe thead th {
text-align: right;
}

</style>




solution_id
solution_name
solution_description
deployment_date
deprecation_date
maintainers




0
b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca
new_example_solution
Description of new example solution.
2024-xx-xx
None
some text about maintainers credentials




solution_parameter_set
param_set_id = 'a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5'

pd.DataFrame(pf2.commited_tables['b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca']['solution_parameter_set'][param_set_id])


<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}

.dataframe thead th {
text-align: right;
}

</style>




solution_id
parameter_set_id
deployment_status
insertion_datetime




0
b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca
a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5
PRODUCTION
2024-05-07 19:51:13




parameter_set
pd.DataFrame(pf2.commited_tables['b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca']\
['parameter_set']\
[param_set_id])


<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}

.dataframe thead th {
text-align: right;
}

</style>




parameter_set_id
parameter_id




0
a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5
4cea5b09e77da310c5105978f2ceea5c5d8c9c7b65d0e00b45135ea90fc011af


1
a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5
bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5f


2
a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5
9a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36be


3
a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5
ace2f31433212fbf9e764069a30a7675ca78f496d31f061d06d0a0420fc52768


4
a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5
1a4f19ee9e186ee739daecbc778501c5851d3fb5d05c4a3c1200e599855e8689




parameter_set_description
pd.DataFrame(pf2.commited_tables['b5c2e4a9bdcb57cc70bdb7310c7909cc1549550add79e3fbcc8aa1cf323cd8ca']\
['parameter_set_description']\
[param_set_id])


<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}

.dataframe thead th {
text-align: right;
}

</style>




parameter_set_id
parameter_set_name
parameter_set_description




0
a54f04d2ff154294309403206e059aec556cdcfa51120649ce663f3230a970d5
test_set
example 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])


<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}

.dataframe thead th {
text-align: right;
}

</style>




parameter_id
parameter_name
parameter_description
file_name
file_type




0
4cea5b09e77da310c5105978f2ceea5c5d8c9c7b65d0e00b45135ea90fc011af
param_1

param_1.yaml
yaml


1
bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5f
param_2

param_2.yaml
yaml


2
9a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36be
param_10

param_10.txt
txt


3
ace2f31433212fbf9e764069a30a7675ca78f496d31f061d06d0a0420fc52768
param_11

param_11.dill
other


4
1a4f19ee9e186ee739daecbc778501c5851d3fb5d05c4a3c1200e599855e8689
param_21

param_21.ipynb
other




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])


<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}

.dataframe thead th {
text-align: right;
}

</style>




parameter_id
attribute_id
previous_attribute_id




0
4cea5b09e77da310c5105978f2ceea5c5d8c9c7b65d0e00b45135ea90fc011af
ee25af17445d7622cbf61a5b9424246a1f3104704b68bd31b9b7532471d492e5
None


1
4cea5b09e77da310c5105978f2ceea5c5d8c9c7b65d0e00b45135ea90fc011af
8b5b2be24e60ba407b90967820da8a1385a6d67691a02bc663703160ef655101
None


2
4cea5b09e77da310c5105978f2ceea5c5d8c9c7b65d0e00b45135ea90fc011af
52ea872c99c586530348ba8902dcab831761673d25cf1cb0023576820289ce6b
None


3
bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5f
7d5ee0e0cd00c3703e5f346c6887baf503faaf9fe090774f6866311f4fa34179
None


4
bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5f
ee25af17445d7622cbf61a5b9424246a1f3104704b68bd31b9b7532471d492e5
7d5ee0e0cd00c3703e5f346c6887baf503faaf9fe090774f6866311f4fa34179


5
bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5f
3367512147bf19ae99c986b356af11dcdc067376aa1b79eb8ba8f61324e8dc18
7d5ee0e0cd00c3703e5f346c6887baf503faaf9fe090774f6866311f4fa34179


6
bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5f
341769820d8937a5c9f9b980eefca37f3f37fcc6fd01c6f4c930fdb9d5dd5128
7d5ee0e0cd00c3703e5f346c6887baf503faaf9fe090774f6866311f4fa34179


7
bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5f
2e8b00e571f9d835d3f022a9ff49b9779034ab21bffdcde075d9d729fabeb960
341769820d8937a5c9f9b980eefca37f3f37fcc6fd01c6f4c930fdb9d5dd5128


8
bf11768decb1d0204e2636edd05c354573d473e67f1b048369b2ee99c865bf5f
ecd93cf051988b23b3590415f4e7d550de264600d7d2af8704c973b9c98ca6a9
341769820d8937a5c9f9b980eefca37f3f37fcc6fd01c6f4c930fdb9d5dd5128


9
9a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36be
fa4e8d81f4dbe6d306aff59bea4693d325a203be5d5b9fde5d5f1e7cce26b861
None


10
9a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36be
c26e7e96f0f3647c159b0934f4dc55207ac059abb56005d7a8acd8344ef14798
fa4e8d81f4dbe6d306aff59bea4693d325a203be5d5b9fde5d5f1e7cce26b861


11
9a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36be
f7cd339f77c1799f399d8ebcbb27f2d41a448622254d64e9270ae2316211ac1d
c26e7e96f0f3647c159b0934f4dc55207ac059abb56005d7a8acd8344ef14798


12
9a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36be
15a33fe62774a1857b404f453ba1195eb4355e10bc9519f2f991dd7ba8db19b7
f7cd339f77c1799f399d8ebcbb27f2d41a448622254d64e9270ae2316211ac1d


13
9a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36be
99761e3d58bc213dc3ab33f2dc8dabe5f97d3aea6b59cd367d40b76937f49aa6
15a33fe62774a1857b404f453ba1195eb4355e10bc9519f2f991dd7ba8db19b7


14
9a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36be
036a9c122c1f4c9304afa23c4d1fce5224c270a206889afa689f3efb36ff368d
99761e3d58bc213dc3ab33f2dc8dabe5f97d3aea6b59cd367d40b76937f49aa6


15
9a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36be
e72aa8015688052f4e7fddbf4c74e5bf2bd74239ebf3902a5fdc008ecb03aa46
036a9c122c1f4c9304afa23c4d1fce5224c270a206889afa689f3efb36ff368d


16
9a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36be
0ae8eda3dbeedbc17e27a679c5426dd3af1434f7c37b4ecd3b2fb5c492272b75
e72aa8015688052f4e7fddbf4c74e5bf2bd74239ebf3902a5fdc008ecb03aa46


17
9a4a3ace265c9bf2facc0044ca24260c42805c6e7b2a608dfd2f56a54d9d36be
cedcfbb0d95798514b6aaf30118fff7b46f863f1bc8b80bb2ddd2145e5b3f318
0ae8eda3dbeedbc17e27a679c5426dd3af1434f7c37b4ecd3b2fb5c492272b75


18
ace2f31433212fbf9e764069a30a7675ca78f496d31f061d06d0a0420fc52768
ace2f31433212fbf9e764069a30a7675ca78f496d31f061d06d0a0420fc52768
None


19
1a4f19ee9e186ee739daecbc778501c5851d3fb5d05c4a3c1200e599855e8689
87d93e1862f0f58199c3fcb7114b92fe59f03581804b1c8419868fb00ff8a469
None


20
1a4f19ee9e186ee739daecbc778501c5851d3fb5d05c4a3c1200e599855e8689
b4a705d09aa0361f4db453da32abb05a5c4e0249d6180d2b8a58d72d08dbd6a0
87d93e1862f0f58199c3fcb7114b92fe59f03581804b1c8419868fb00ff8a469


21
1a4f19ee9e186ee739daecbc778501c5851d3fb5d05c4a3c1200e599855e8689
e4e2c33a2ea67f34bf3ac1e9d99edaad501c7dc4ea82f4b60e9d959418d8438d
b4a705d09aa0361f4db453da32abb05a5c4e0249d6180d2b8a58d72d08dbd6a0


22
1a4f19ee9e186ee739daecbc778501c5851d3fb5d05c4a3c1200e599855e8689
777abf12375b7f605b21535eb0d6232ce99581c6d2b1179af976cd0708ad27ff
e4e2c33a2ea67f34bf3ac1e9d99edaad501c7dc4ea82f4b60e9d959418d8438d




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])


<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}

.dataframe thead th {
text-align: right;
}

</style>




attribute_id
previous_attribute_id
attribute_name
attribute_value
attribute_value_type




0
ee25af17445d7622cbf61a5b9424246a1f3104704b68bd31b9b7532471d492e5
None
name
Some name
str


1
8b5b2be24e60ba407b90967820da8a1385a6d67691a02bc663703160ef655101
None
age
111
int


2
52ea872c99c586530348ba8902dcab831761673d25cf1cb0023576820289ce6b
None
country
Some land
str


3
ee25af17445d7622cbf61a5b9424246a1f3104704b68bd31b9b7532471d492e5
None
name
Some name
str


4
7d5ee0e0cd00c3703e5f346c6887baf503faaf9fe090774f6866311f4fa34179
None
employee
{'name': 'Some name', 'id': 10293, 'contact': {'email': 'some.name...
dict


5
3367512147bf19ae99c986b356af11dcdc067376aa1b79eb8ba8f61324e8dc18
None
id
10293
int


6
341769820d8937a5c9f9b980eefca37f3f37fcc6fd01c6f4c930fdb9d5dd5128
None
contact
{'email': '[email protected]', 'phone': '+1234567890'}
dict


7
2e8b00e571f9d835d3f022a9ff49b9779034ab21bffdcde075d9d729fabeb960
None
email
[email protected]
str


8
ecd93cf051988b23b3590415f4e7d550de264600d7d2af8704c973b9c98ca6a9
None
phone
+1234567890
str


9
fa4e8d81f4dbe6d306aff59bea4693d325a203be5d5b9fde5d5f1e7cce26b861
None
0
\X/Fc7;/v`6joU5z*n{35zFB<<6BMC,}/_04],>v$Jr2&0M_7qU'IY#6uO$kEr.)Z...
str


10
c26e7e96f0f3647c159b0934f4dc55207ac059abb56005d7a8acd8344ef14798
None
1
A7J+1x5|?r]2zg54nxoa>W*loh8Np~*9+*KxWLuD/Z5g!=DN>}c#]Dt->tiov?|Ms....
str


11
f7cd339f77c1799f399d8ebcbb27f2d41a448622254d64e9270ae2316211ac1d
None
2
LUs%<HRbNA_4:yYTh!!x&oFZ201sQ7;~Q_IYr"lGRMd=xx,r}|n8zHIP6%JN)",vQI...
str


12
15a33fe62774a1857b404f453ba1195eb4355e10bc9519f2f991dd7ba8db19b7
None
3
b&z(/Z{s@U>@o!}{+(mmygo}u~AHgdu>:jz4fNBm0;Q6'o+f%H/z3^8Hh!w<#z.~21...
str


13
99761e3d58bc213dc3ab33f2dc8dabe5f97d3aea6b59cd367d40b76937f49aa6
None
4
.#;5Cu]5~8ZmYBLI4w)|h=)C<(#`KSoM,`7n?dun7]LX>j7/U>Jf||4`AN_u*W!*3)...
str


14
036a9c122c1f4c9304afa23c4d1fce5224c270a206889afa689f3efb36ff368d
None
5
0S)*}6"i)kUg3=n:}>Ji)!"BTbzsdgps8{cR]`.41QJ<O{wr[}}gGan_O63D0WBr]<...
str


15
e72aa8015688052f4e7fddbf4c74e5bf2bd74239ebf3902a5fdc008ecb03aa46
None
6
Xb;IgM/`T:VY*6XQ:nvB3)>@32w8H-cD"g>x`MlWp_TnuyCaz62e??md<8tR$Q=X7<...
str


16
0ae8eda3dbeedbc17e27a679c5426dd3af1434f7c37b4ecd3b2fb5c492272b75
None
7
pq.%\nmm;M!^cyS|ApMpnjUS<#Ov?e+n"wX/to.wjifCG.fKK@6gI+Wvax&}j18R8p...
str


17
cedcfbb0d95798514b6aaf30118fff7b46f863f1bc8b80bb2ddd2145e5b3f318
None
8
+-;Zt=ex
str


18
ace2f31433212fbf9e764069a30a7675ca78f496d31f061d06d0a0420fc52768
None
0
b'\x80\x04\x95h\x00\x00\x00\x00\x00\x00\x00}\x94(\x8c\x07integer\x...
bytes


19
87d93e1862f0f58199c3fcb7114b92fe59f03581804b1c8419868fb00ff8a469
None
0
b'{\n "cells": [\n {\n "cell_type": "markdown",\n "metadata":...
bytes


20
b4a705d09aa0361f4db453da32abb05a5c4e0249d6180d2b8a58d72d08dbd6a0
None
1
xt/plain": [\n "4"\n ]\n },\n "execution_count"...
bytes


21
e4e2c33a2ea67f34bf3ac1e9d99edaad501c7dc4ea82f4b60e9d959418d8438d
None
2
"language": "python",\n "name": "python3"\n },\n "language_...
bytes


22
777abf12375b7f605b21535eb0d6232ce99581c6d2b1179af976cd0708ad27ff
None
3
r": "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.