Welcome file

spree-tools

data

This directory contains simulated user sessions realized on the spree storefront API https://api.spreecommerce.org/docs/api-v2/YXBpOjMxMjQ5NjA-storefront-api

spree_400-steps_w_responses.json : 400 events from 20~ sessions with responses
spree_5000_session_wo_responses_agilkia.json : 5000 sessions without responses in agilkia format
spree_5000_sessions_wo_responses.json : 5000 sessions, raw format

pyspree

Python bindings around storefront API to generate a simulated dataset of users sessions

dataset2agilkia.py

Convert a raw spree simulated user sessions file into an agilkia file, translating http request into domain-knowledge action For example :

Post '/api/v2/storefront/account/addresses' is converted into "CreateAnAddress"

Code snippet :

   import json  
    from pyspreetools.dataset2agilkia import read_traces_dictionary  
    f = open('pyspreetools/data/spree_5000_sessions_wo_responses.json')  
    data = json.load(f)  
    f.close()  
    traceset = read_traces_dictionary(data)  
    print(traceset)  
    traceset.save_to_json(Path("data/spree_5000_session_wo_responses_agilkia.json"))

samplequality.py

Every function from this module takes as input an abstract traceset whose format is list_of_list or a GROUPED agilkia.Traceset object.

code snippet :

 from pyspreetools.samplequality import executability  
  
from agilkia import TraceSet  
from pathlib import Path  
traceset=TraceSet.load_from_json(Path('./pyspreetools/data/spree_5000_session_wo_responses_agilkia.json'))  
traceset=traceset.with_traces_grouped_by('sessionID',property=True)  
traceset.traces = traceset.traces[1:5]  
print(executability(traceset))  
list_of_traces=[['createACart|201', 'listAllTaxons|200', 'listAllProducts_SpecificTaxonFilter_SortByPrice|200', 'retrieveAProduct|200', 'addAnItemToCart|200', 'retrieveACart|200', 'setLineItemQuantity|200', 'listAllTaxons|200', 'listAllProducts_SpecificTaxonFilter_SortByPrice|200', 'retrieveAProduct|200', 'listAllTaxons|200', 'listAllProducts_SpecificTaxonFilter_SortByPrice|200', 'listAllTaxons|200'], ['createACart|201', 'listAllTaxons|200', 'listAllProducts_SpecificTaxonFilter_SortByPrice|200', 'retrieveAProduct|200', 'listAllTaxons|200', 'listAllProducts_SpecificTaxonFilter_SortByPrice|200', 'listAllProducts_SpecificTaxonFilter|200', 'listAllTaxons|200', 'listAllProducts_SpecificTaxonFilter_SortByPrice|200', 'retrieveAProduct|200', 'listAllTaxons|200'], ['createACart|201', 'listAllTaxons|200', 'listAllProducts_SpecificTaxonFilter_SortByPrice|200', 'listAllProducts_SpecificTaxonFilter|200', 'retrieveAProduct|200', 'listAllTaxons|200', 'listAllProducts_SpecificTaxonFilter_SortByPrice|200', 'retrieveAProduct|200', 'listAllTaxons|200'], ['createACart|201', 'listAllTaxons|200', 'listAllProducts_SpecificTaxonFilter_SortByPrice|200', 'listAllProducts_SpecificTaxonFilter|200', 'listAllTaxons|200', 'listAllProducts_SpecificTaxonFilter_SortByPrice|200', 'listAllProducts_SpecificTaxonFilter|200', 'retrieveAProduct|200', 'listAllTaxons|200', 'listAllProducts_SpecificTaxonFilter_SortByPrice|200', 'retrieveAProduct|200', 'listAllProducts_SpecificTaxonFilter_SortByPrice|200', 'listAllTaxons|200']]  
print(executability(list_of_traces))

Each action or event should be encoded in this fashion action+separative_token+return_code

Executability takes as input an abstract traceset and return the executability of the traceset : How many traces are well formed and can be executed as successful tests on the spree api.

simulation.py

Script to generate fake user session on the spree API. The state machine of the simulation is described in pypree/UserSimulator.py Code snippet :

from pyspreetools.simulation import simulation  
  
config_dict = {  
    "base_url": "https://demo.spreecommerce.org/",  
  "logging": True,  
  "log_file": "./logs/log.json",  
  "test_mode": True,  
  "verbose": False,  
  "sleep_time": 0.2  
}  
  
simulation(config_dict=config_dict,number_of_sessions=2)

spree-tools data

This directory contains simulated user sessions realized on the spree storefront API https://api.spreecommerce.org/docs/api-v2/YXBpOjMxMjQ5NjA-storefront-api

spree_400-steps_w_responses.json : 400 events from 20~ sessions with responses
spree_5000_session_wo_responses_agilkia.json : 5000 sessions without responses in agilkia format
spree_5000_sessions_wo_responses.json : 5000 sessions, raw format

pyspree

Python bindings around storefront API to generate a simulated dataset of users sessions dataset2agilkia.py

Convert a raw spree simulated user sessions file into an agilkia file, translating http request into domain-knowledge action For example :

Post '/api/v2/storefront/account/addresses’ is converted into
“CreateAnAddress”

Code snippet :

import json
from pyspreetools.dataset2agilkia import read_traces_dictionary
f = open('pyspreetools/data/spree_5000_sessions_wo_responses.json')
data = json.load(f)
f.close()
traceset = read_traces_dictionary(data)
print(traceset)
traceset.save_to_json(Path("data/spree_5000_session_wo_responses_agilkia.json"))

samplequality.py

Every function from this module takes as input an abstract traceset whose format is list_of_list or a GROUPED agilkia.Traceset object.

code snippet :

from pyspreetools.samplequality import executability

Each action or event should be encoded in this fashion action+separative_token+return_code

Executability takes as input an abstract traceset and return the executability of the traceset : How many traces are well formed and can be executed as successful tests on the spree api. simulation.py

Script to generate fake user session on the spree API. The state machine of the simulation is described in pypree/UserSimulator.py Code snippet :

from pyspreetools.simulation import simulation

config_dict = {
"base_url": "https://demo.spreecommerce.org/",
"logging": True,
"log_file": "./logs/log.json",
"test_mode": True,
"verbose": False,
"sleep_time": 0.2
}

simulation(config_dict=config_dict,number_of_sessions=2)

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PHILAE-PROJECT/pyspreetools

spree-tools

data

pyspree

dataset2agilkia.py

samplequality.py

simulation.py