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DHIS2 | FHIR | DHIS2 vs FHIR % | ||
---|---|---|---|---|
Average | 0.552675 554281 | 0.555544555023 | 99-0.943713% |
Test detailed results
logged on Nov 22Dec 1/ 2022 UTC-7 2008:5040:00
Performance Testing for | Attempt | DHIS2 API | FHIR API | FHIR API (with HealthcareServices), | Improvement % |
---|---|---|---|---|---|
El Salvador | Attempt - 1 | 0.566667 | 0.488375 | 0.487989 | 16.03% |
Attempt - 2 | 0.532607 | 0.437886 | 0.548295 | 21.63% | |
Attempt - 3 | 0.532142 | 0.452103 | 0.463129 | 17.7% | |
Kenya | Attempt - 1 | 0.657443 | 0.604362 | 0.625961 | 8.78% |
Attempt - 2 | 0.655574 | 0.578361 | 0.574557 | 13.35% | |
Attempt - 3 | 0.659164 | 0.573111 | 0.663475 | 15.02% | |
Nigeria | Attempt - 1 | 0.526847 | 0.570136 | 0.651838 | -7.59% |
Attempt - 2 | 0.528978 | 0.588868 | 0.620271 | -10.17% | |
Attempt - 3 | 0.536548 | 0.568277 | 0.70342 | -5.58% | |
Cameroon | Attempt - 1 | 0.372636 | 0.587497 | 0.590178 | -36.57% |
Attempt - 2 | 0.371032 | 0.584348 | 0.595724 | -36.5% | |
Attempt - 3 | 0.371502 | 0.558964 | 0.585595 | -33.54% | |
Nepal | Attempt - 1 | 0.662525 | 0.612458 | 0.682753 | 8.17% |
Attempt - 2 | 0.670834 | 0.56743 | 0.571592 | 18.22% | |
Attempt - 3 | 0.669719 | 0.553174 | 0.584597 | 21.07% | |
Overall Average | 0.554281 | 0.555023 | 0.596625 | -0.13% |
Testing Script
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##Case 1 case_1_results = [{"description": "Performance Testing for", "attempt": "Attempt", "dhis2": "DHIS2 API", "fhir": "FHIR API", "fhir_with_healthcareServices": "FHIR API (with HealthcareServices),", "improvement":"Improvement %"}] print("Case #1 - Getting 500 orgUnits/Location in the country (by ISO)") dhis2_overall_averageimprovements = 0[] fhirdhis2_overall_averageperformances = 0[] fhir_hcshsc_overall_averageperformances = 0[] improvementfhir_overallperformances = 0[] for country in countries: dhis2_section_sum = 0 fhir_section_sum = 0 fhir_hcs_section_sum = 0 improvement_section_sum = 0 for i in range(1,4): case_1_result = {} if i == 1: case_1_result['description'] = "{}".format(country['name']) case_1_result['attempt'] = "Attempt - {}".format(i) dhis2_url = dhis2_base_url+'iso2={}&number=500'.format(country['code']) result = requests.get(dhis2_url, auth=dhis2_auth) if result.status_code == 200: dhis2_performances.append(result.elapsed.total_seconds()) case_1_result['dhis2'] = result.elapsed.total_seconds()dhis2_performances[-1] request_url = fhir_location_url+'address-country={}&_count=500'.format(country['name']) fhirResult = requests.get(request_url, auth=fhir_auth) if fhirResult.status_code == 200: fhir_performances.append(fhirResult.elapsed.total_seconds()) case_1_result['fhir'] = fhirResult.elapsed.total_seconds()fhir_performances[-1] request_healthcare_url = fhir_location_url+'address-country={}&_count=500&_revinclude=HealthcareService:location'.format(country['name']) fhirHealthcareServicesResult = requests.get(request_healthcare_url, auth=fhir_auth) if fhirHealthcareServicesResult.status_code == 200: case_1_result['fhir_with_healthcareServices'] = hsc_performances.append(fhirHealthcareServicesResult.elapsed.total_seconds()) case_1_result['improvementfhir_with_healthcareServices'] = (casefhir_1hsc_result['dhis2'] / case_1_result['fhir'])*100performances[-1] case_1_results.append(case_1_result) dhis2_section_sum += improvements.append(((case_1_result['dhis2'] fhir_section_sum += / case_1_result['fhir']) - 1)*100) fhir_hcs_section_sum += case_1_result['fhir_with_healthcareServicesimprovement'] = '{}%'.format(float("{:.2f}".format(improvements[-1]))) improvementcase_section_sum += 1_results.append(case_1_result['improvement']) time.sleep(10.01) case_1_result = {} case_1_result['attemptdescription'] = "Overall Average" case_1_result['dhis2'] = np.average(dhis2_section_sum / 3 performances) case_1_result['fhir'] = np.average(fhir_section_sum / 3 performances) case_1_result['fhir_with_healthcareServices'] = np.average(fhir_hcs_section_sum / 3 hsc_performances) case_1_result['improvement'] = improvement_section_sum / 3 case_1_results.append(case_1_result) dhis2_overall_average += dhis2_section_sum / 3 fhir_overall_average += fhir_section_sum / 3 fhir_hcs_overall_average += fhir_hcs_section_sum / 3 improvement_overall += improvement_section_sum / 3 case_1_result = {} case_1_result['description'] = "Overall Average" '{}%'.format(float("{:.2f}".format(((case_1_result['dhis2'] = dhis2_overall_average / nos_countries case_1_result['fhir'] = fhir_overall_average / nos_countries case_1_result['fhir_with_healthcareServices'] = fhir_hcs_overall_average / nos_countries case_1_result['improvement'] = improvement_overall / nos_countries case_1_)-1)*100))) case_1_results.append(case_1_result) print(tabulate(case_1_results, headers='firstrow', tablefmt='fancy_gridpipe')) |