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Searching nearest orgunits / Location based on the provided coordinates

Performance was measured based on the time taken to:
load 500 nearby outlets to the provided coordinates (for locator API)
URL: https://replica.psi-mis.org/locator/api/1?n=500&c={latitude},{longitude}&d={distance}
Similarly, in FHIR, we tried to load 500 nearby locations based on the coordinates provided
URL: https://fhir-dev.psi-mis.org/fhir?near={latitude}|{longitude}|{distance}|{unit}&_count=500

Summary of test results

DHIS2

FHIR

DHIS2 vs FHIR %

Average

1.41292

0.583782

142.03%

Test detailed results

logged on Nov 29/ 2022 UTC-7 09:16:00

Performance Testing for

Attempt

DHIS2 API

DHIS2 Size

FHIR API

FHIR Size

Improvement %

El Salvador

Attempt 1

1.41727

141

0.65739

500

115.59%

Attempt 2

1.39867

141

0.574834

500

143.32%

Attempt 3

1.382

141

0.568845

500

142.95%

Kenya

Attempt 1

1.43245

500

0.598346

500

139.4%

Attempt 2

1.43526

500

0.581445

500

146.84%

Attempt 3

1.49501

500

0.569503

500

162.51%

Nigeria

Attempt 1

1.51636

500

0.582592

500

160.28%

Attempt 2

1.48614

500

0.613181

500

142.37%

Attempt 3

1.63908

500

0.567279

500

188.94%

Cameroon

Attempt 1

1.69394

500

0.591673

500

186.3%

Attempt 2

1.47116

500

0.563599

500

161.03%

Attempt 3

1.49798

500

0.566068

500

164.63%

Nepal

Attempt 1

1.11843

12

0.59532

500

87.87%

Attempt 2

1.10475

12

0.567694

500

94.6%

Attempt 3

1.10523

12

0.558964

500

97.73%

Overall Average

1.41292

0.583782

142.03%

Testing Script

case_results = [{"description": "Performance Testing for", "attempt": "Attempt", "dhis2": "DHIS2 API", "dhis2_size": "DHIS2 Size", "fhir": "FHIR API", "fhir_size": "FHIR Size", "improvement": "Improvement %"}]
print("Case #2 - Getting 500 orgUnits/Location 100km around the provided coordinates")
improvements = []
dhis2_performances = []
fhir_performances = []
for country in countries:
    for i in range(1,4):
        case_result = {}
        if i == 1:
            case_result['description'] = "{}".format(country['name'])
        case_result['attempt'] = "Attempt {}".format(i)
        dhis2_url = dhis2_base_url+'n=500&c={},{}&d=1000000'.format(country['latitude'], country['longitude'])
        result = requests.get(dhis2_url, auth=dhis2_auth)
        if result.status_code == 200:
            data = result.json()
            dhis2_performances.append(result.elapsed.total_seconds())
            case_result['dhis2'] = dhis2_performances[-1]
            case_result['dhis2_size'] = len(data['outlet'])
        
        request_url = fhir_location_url+'near={}|{}|10000|km&_count=500'.format(country['latitude'], country['longitude'])
        fhirResult = requests.get(request_url, auth=fhir_auth)
        if fhirResult.status_code == 200:
            fhir_data = fhirResult.json()
            fhir_performances.append(fhirResult.elapsed.total_seconds())
            case_result['fhir'] = fhir_performances[-1]
            case_result['fhir_size'] = len(fhir_data['entry']) if 'entry' in fhir_data else 0
        
        improvements.append(((case_result['dhis2']/case_result['fhir'])-1)*100)
        case_result['improvement'] = '{}%'.format(float("{:.2f}".format(improvements[-1])))
        case_results.append(case_result)
        time.sleep(0.01)

case_result = {}
case_result['description'] = "Overall Average"
case_result['dhis2'] = np.average(dhis2_performances)
case_result['fhir'] = np.average(fhir_performances)
case_result['improvement'] = '{}%'.format(float("{:.2f}".format(((case_result['dhis2']/case_result['fhir'])-1)*100)))
case_results.append(case_result)
print(tabulate(case_results, headers='firstrow', tablefmt='pipe'))

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