Add pytest tests

tests/test_fund.py

@@ -0,0 +1,190 @@
+import datetime
+import pytest
+import time
+
+from mstarpy import Funds, search_field, Stock
+
+@pytest.fixture
+def funds_collection(): 
+    test_fund_details =  [
+        {
+            "isin": "GB00B784NS11",
+            "name": "AXA Framlington Biotech Fund GBP Z Acc",
+            "id": "F00000P77J",
+            "country": "gb",
+            "url": "https://www.morningstar.co.uk/uk/funds/snapshot/snapshot.aspx?id=F00000P77J"
+        },
+        {
+            "isin": "LU1148874552",
+            "name": "New Millennium - Balanced World Conservative L",
+            "id": "F00000VE3V",
+            "country": "it",
+            "url": "https://www.morningstar.it/it/funds/snapshot/snapshot.aspx?id=F00000VE3V"
+        },
+        {
+            "isin": "LU0816332745",
+            "name": "LGT (Lux) I Cat Bond Fund B USD",
+            "id": "F00000OVML",
+            "country": "IT",
+            "url": "https://www.morningstar.it/it/funds/snapshot/snapshot.aspx?id=F00000OVML"
+        }
+    ]
+    return test_fund_details 
+
+def test_fund_details(funds_collection):
+    for item in funds_collection:
+        fund = Funds(item["id"], country=item["country"])
+        assert fund.name == item["name"]
+        assert fund.isin == item["isin"]
+
+def test_key_stats(funds_collection):
+    for item in funds_collection:
+        fund = Funds(item["id"], country=item["country"])
+        values = fund.keyStats()
+        values[4].get("ISIN") == item["isin"]
+        time.sleep(1)
+
+def test_carbon_metrics(funds_collection):
+    for item in funds_collection:
+        fund = Funds(item["id"], country=item["country"])
+        data_dict = fund.carbonMetrics()
+        assert "categoryName" in data_dict
+        assert "fossilFuelInvolvementPct" in data_dict
+        assert "portfolioCarbonRiskScore" in data_dict
+
+@pytest.fixture
+def funds_nav():
+    nav ={
+        "id": "F00000TW95",
+        "start_date": datetime.date(2022,4,11),
+        "end_date": datetime.date(2022,4,25),
+        "history": [
+            {'nav': 12.46, 'totalReturn': 14.93951, 'date': '2022-04-11'},
+            {'nav': 12.47, 'totalReturn': 14.9515, 'date': '2022-04-12'},
+            {'nav': 12.53, 'totalReturn': 15.02344, 'date': '2022-04-13'},
+            {'nav': 12.59, 'totalReturn': 15.09538, 'date': '2022-04-14'},
+            {'totalReturn': 15.09538, 'date': '2022-04-15'},
+            {'nav': 12.54, 'totalReturn': 15.03543, 'date': '2022-04-19'},
+            {'nav': 12.49, 'totalReturn': 14.97548, 'date': '2022-04-20'},
+            {'nav': 12.47, 'totalReturn': 14.9515, 'date': '2022-04-21'},
+            {'nav': 12.53, 'totalReturn': 15.02344, 'date': '2022-04-22'},
+            {'nav': 12.61, 'totalReturn': 15.11936, 'date': '2022-04-25'},
+        ]
+    }
+    return nav
+
+def test_fund_nav(funds_nav):
+    fund = Funds(funds_nav["id"])
+    start_date = funds_nav["start_date"] 
+    end_date = funds_nav["end_date"]
+    history = fund.nav(start_date, end_date)
+    assert history == funds_nav["history"]
+
+
+def test_fund_invetment_look_up():
+    funds_details = Funds("myria").investmentLookup()
+    keys = [
+        "Id", "InceptionDate", "Isin", "InvestmentType",
+        "Type", "Name", "Domicile", "Currency", "RiskAndRating",
+        "LastPrice", "Benchmark"
+        ]
+    assert len(set(keys) - set(funds_details.keys())) == 0
+
+
+def test_fund_multiple_request_method():
+    funds = Funds("LU1085283973", country="fr")
+    funds.code
+    funds.isin
+    funds.name
+    funds.asset_type
+    funds.allocationMap()
+    funds.allocationWeighting()
+    funds.analystRating()
+    funds.analystRatingTopFunds()
+    funds.analystRatingTopFundsUpDown()
+    funds.benchmark()
+    funds.carbonMetrics()
+    funds.category()
+    funds.categoryAnnualPerformance()
+    funds.categoryCumulativePerformance()
+    funds.costIllustration()
+    funds.couponRange()
+    funds.creditQuality()
+    funds.dataPoint("TenforeId")
+    funds.distribution()
+    funds.equityStyle()
+    funds.equityStyleBoxHistory()
+    funds.esgData()
+    funds.factorProfile()
+    funds.feeLevel()
+    funds.financialMetrics()
+    funds.fixedIncomeStyle()
+    funds.fixedincomeStyleBoxHistory()
+    funds.fundsAnnualPerformance()
+    funds.fundsAnnualRank()
+    funds.fundsCumulativePerformance()
+    funds.graphData()
+    funds.historicalData()
+    funds.holdings()
+    funds.indexAnnualPerformance()
+    funds.indexCumulativePerformance()
+    funds.investmentStrategy()
+    funds.marketCapitalization()
+    funds.maturitySchedule()
+    funds.maxDrawDown()
+    funds.morningstarAnalyst()
+    funds.multiLevelFixedIncomeData()
+    funds.otherFee()
+    funds.ownershipZone()
+    funds.parentMstarRating()
+    funds.parentSummary()
+    funds.people()
+    funds.position()
+    funds.productInvolvement()
+    funds.proxyVotingManagement()
+    funds.proxyVotingShareHolder()
+    funds.regionalSector()
+    funds.regionalSectorIncludeCountries()
+    funds.riskReturnScatterplot()
+    funds.riskReturnSummary()
+    funds.riskVolatility()
+    # Only support fundType="FO" and countryId = "USA"
+    # funds.salesFees()
+    funds.sector()
+    funds.starRatingFundAsc()
+    funds.starRatingFundDesc()
+    funds.taxes()
+    funds.trailingReturn()
+
+def test_fund_web_requests():
+    funds = Funds("LU1085283973", country="fr")
+    funds.AnnualPerformance(cat="funds")
+    time.sleep(1)
+    funds.contact()
+    time.sleep(1)
+    funds.CumulativePerformance(cat="funds")
+    time.sleep(1)
+    funds.fees() 
+    time.sleep(1)
+    funds.fundsQuarterlyPerformance()
+    time.sleep(1)
+    funds.objectiveInvestment()
+    time.sleep(1)
+    funds.referenceIndex('category')
+
+
+def test_fund_retrieve_data_point():
+    funds = Funds("LU1085283973", country="fr")
+    fields = [
+        'FeeLevel',
+        'fundshareClassId'
+        ]
+    response_list = funds.dataPoint(field=fields)
+    diff = set(fields) - set(response_list[0].keys())
+    assert len(diff) == 0
+
+
+
+
+
+