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‎README.md‎

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@@ -22,11 +22,47 @@ Using a simple list of buy/sell positions in a csv file as input, this repo aims
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## How to use
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// TODO
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1. Fork this repo, clone to local computer and create a virtual environment
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```bash
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# could alternatively use virtualenv
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conda create --name python-portfolio-tracker --file requirements.txt
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```
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2. Upload your input data containing the list of buy/sell actions in your portfolio (using the correct format specified in the [Data Input Format](#dif) below). The default location for the input data is: `data/raw/purchase_info.csv`, however, you can upload it anywhere and just reference the location (`input_data_source`) in the load data functions.
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<a id='dif'></a>
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### Data Input Format
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//TODO
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The required data input for this analysis is a `csv` file containing rows for each purchase (or disposal) of a stock in your portfolio. An example is given in the `../data/raw/purchase_info.csv` in this repository.
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The required columns are:
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- `date`: the date of your transaction
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- `action`: BUY or SELL
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- `company`: the name of the company (this is not sensitive to any further analysis and can be anything of your choosing)
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- `yahoo_ticker`: the ticker of the stock on finance.yahoo.com (note this might be different from the actual stock market ticker)
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- `currency`: the currency the stock price is denominated in
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- `num_shares`: the number of shares involved in the transaction
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- `stock_price_usd`: the stock price you bought the stock at on that day
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- `trading_costs_usd`: the trading costs incurred
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- `total_usd`: the total cost of the transaction
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- `total_shares_held`: the total number of shares held after the transaction
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Example input format:
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| | date | action | company | yahoo_ticker | currency | num_shares | stock_price_usd | trading_costs_usd | total_usd | total_shares_held |
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|---:|:-----------|:---------|:------------------|:---------------|:-----------|-------------:|------------------:|--------------------:|------------:|--------------------:|
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| 0 | 17/07/2019 | BUY | Nvidia | NVDA | USD | 39 | 166.67 | 4.95 | 6505.08 | 39 |
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| 1 | 17/07/2019 | BUY | Intel | INTC | USD | 180 | 49.91 | 4.95 | 8988.75 | 180 |
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| 2 | 17/07/2019 | BUY | Applied Materials | AMAT | USD | 268 | 45.9151 | 4.95 | 12310.2 | 268 |
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| 3 | 17/07/2019 | BUY | MKS Instruments | MKSI | USD | 120 | 76.7449 | 4.95 | 9214.34 | 120 |
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| 4 | 17/07/2019 | BUY | Synopsys | SNPS | USD | 68 | 136.808 | 4.95 | 9307.92 | 68 |
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| 5 | 17/07/2019 | BUY | SOXX ETF | SOXX | USD | 75 | 204.261 | 4.95 | 15324.5 | 75 |
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| 6 | 26/11/2019 | SELL | Nvidia | NVDA | USD | 5 | 217 | 4.95 | 1089.95 | 34 |
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| 7 | 25/03/2020 | BUY | Nvidia | NVDA | USD | 10 | 205.75 | 4.95 | 2062.45 | 44 |
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## Current limitations
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‎data/raw/~$input.xlsx‎

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‎tests/conftest.py‎

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return CalculateStockValue(
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ticker=EXAMPLE_TICKER, input_data_source=INPUT_DATA_SOURCE
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)
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‎tests/example_inputs/example_purchase_info.csv‎

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date,company,yahoo_ticker,currency,shares_purchased,price_usd,trading_costs_usd,total_usd,total_shares_held
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17/07/2019,Nvidia,NVDA,USD,39,166.67,4.95,6505.08,39
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17/07/2019,Intel,INTC,USD,180,49.91,4.95,8988.75,180
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17/07/2019,Applied Materials,AMAT,USD,268,45.9151,4.95,12310.2,268
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17/07/2019,MKS Instruments,MKSI,USD,120,76.7449,4.95,9214.34,120
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17/07/2019,Synopsys,SNPS,USD,68,136.8084,4.95,9307.92,68
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17/07/2019,SOXX ETF,SOXX,USD,75,204.2607,4.95,15324.5,75
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24/07/2019,Tokyo Electron,8035.T,JPY,100,168.4135,126.31,16967.66,100
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24/07/2019,BE Semiconductor Industries,BESI.AS,EUR,420,29.9253,100,12668.63,420
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date,action,company,yahoo_ticker,currency,num_shares,stock_price_usd,trading_costs_usd,total_usd,total_shares_held
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17/07/2019,BUY,Nvidia,NVDA,USD,39,166.67,4.95,6505.08,39
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17/07/2019,BUY,Intel,INTC,USD,180,49.91,4.95,8988.75,180
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17/07/2019,BUY,Applied Materials,AMAT,USD,268,45.9151,4.95,12310.2,268
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17/07/2019,BUY,MKS Instruments,MKSI,USD,120,76.7449,4.95,9214.34,120
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17/07/2019,BUY,Synopsys,SNPS,USD,68,136.8084,4.95,9307.92,68
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17/07/2019,BUY,SOXX ETF,SOXX,USD,75,204.2607,4.95,15324.5,75
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26/11/2019,SELL,Nvidia,NVDA,USD,5,217,4.95,1089.95,34
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25/03/2020,BUY,Nvidia,NVDA,USD,10,205.75,4.95,2062.45,44

‎tests/example_inputs/missing_data.csv‎

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date,company,yahoo_ticker,currency,shares_purchased,purchase_price_usd,trading_costs_usd,total_cost_usd,total_shares_held
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17/07/2019,Nvidia,NVDA,USD,39,166.67,4.95,6505.08,39
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17/07/2019,Intel,INTC,USD,180,,4.95,8988.75,180
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17/07/2019,Applied Materials,AMAT,USD,268,45.9151,4.95,12310.2,268
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17/07/2019,,MKSI,USD,120,76.7449,4.95,9214.34,120
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17/07/2019,Synopsys,SNPS,USD,68,136.8084,4.95,,68
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17/07/2019,SOXX ETF,,USD,75,204.2607,4.95,15324.5,75
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24/07/2019,Tokyo Electron,8035.T,JPY,100,168.4135,126.31,16967.66,100
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24/07/2019,BE Semiconductor Industries,BESI.AS,EUR,420,29.9253,100,12668.63,420
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17/07/2019,Synopsys,SNPS,USD,68,136.8084,4.95,9307.92,68
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date,action,company,yahoo_ticker,currency,num_shares,stock_price_usd,trading_costs_usd,total_cost_usd,total_shares_held
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17/07/2019,BUY,Nvidia,NVDA,USD,39,166.67,4.95,6505.08,39
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17/07/2019,BUY,Intel,INTC,USD,180,,4.95,8988.75,180
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17/07/2019,BUY,Applied Materials,AMAT,USD,268,45.9151,4.95,12310.2,268
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17/07/2019,BUY,,MKSI,USD,120,76.7449,4.95,9214.34,120
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17/07/2019,BUY,Synopsys,SNPS,USD,68,136.8084,4.95,,68
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17/07/2019,BUY,SOXX ETF,,USD,75,204.2607,4.95,15324.5,75
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24/07/2019,BUY,Tokyo Electron,8035.T,JPY,100,168.4135,126.31,16967.66,100
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24/07/2019,BUY,BE Semiconductor Industries,BESI.AS,EUR,420,29.9253,100,12668.63,420
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17/07/2019,BUY,Synopsys,SNPS,USD,68,136.8084,4.95,9307.92,68

‎tests/example_inputs/too_many_tickers.csv‎

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date,company,yahoo_ticker,currency,shares_purchased,purchase_price_usd,trading_costs_usd,total_cost_usd,total_shares_held
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17/07/2019,Nvidia,NVDA,USD,39,166.67,4.95,6505.08,39
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17/07/2019,Intel,INTC,USD,180,49.91,4.95,8988.75,180
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17/07/2019,Applied Materials,AMAT,USD,268,45.9151,4.95,12310.2,268
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17/07/2019,MKS Instruments,MKSI,USD,120,76.7449,4.95,9214.34,120
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17/07/2019,Synopsys,SNPS,USD,68,136.8084,4.95,9307.92,68
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17/07/2019,SOXX ETF,SOXX,USD,75,204.2607,4.95,15324.5,75
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24/07/2019,Tokyo Electron,8035.T,JPY,100,168.4135,126.31,16967.66,100
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24/07/2019,BE Semiconductor Industries,BESI.AS,EUR,420,29.9253,100,12668.63,420
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17/07/2019,Synopsys,SNPS,USD,68,136.8084,4.95,9307.92,68
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17/07/2019,Microsoft,MSFT,USD,75,204.2607,4.95,15324.5,75
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24/07/2019,Tesla,TSLA,USA,100,168.4135,126.31,16967.66,100
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24/07/2019,Diversified Gas and Oil,DGOC.L,GBX,420,29.9253,100,12668.63,420
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17/07/2019,BP,BP.L,GBX,68,136.8084,4.95,9307.92,68
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17/07/2019,Ford,F,USD,75,204.2607,4.95,15324.5,75
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24/07/2019,Facebook,FB,USD,100,168.4135,126.31,16967.66,100
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24/07/2019,Snap,SNAP,USD,420,29.9253,100,12668.63,420
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17/07/2019,Apple,APPL,USD,68,136.8084,4.95,9307.92,68
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17/07/2019,Amazon,AMZN,USD,75,204.2607,4.95,15324.5,75
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24/07/2019,ASML,ASML,JPY,100,168.4135,126.31,16967.66,100
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24/07/2019,Google,GOOG,USD,420,29.9253,100,12668.63,420
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24/07/2019,Mastercard,MA,USD,420,29.9253,100,12668.63,420
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date,action,company,yahoo_ticker,currency,num_shares,stock_price_usd,trading_costs_usd,total_cost_usd,total_shares_held
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17/07/2019,BUY,Nvidia,NVDA,USD,39,166.67,4.95,6505.08,39
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17/07/2019,BUY,Intel,INTC,USD,180,49.91,4.95,8988.75,180
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17/07/2019,BUY,Applied Materials,AMAT,USD,268,45.9151,4.95,12310.2,268
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17/07/2019,BUY,MKS Instruments,MKSI,USD,120,76.7449,4.95,9214.34,120
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17/07/2019,BUY,Synopsys,SNPS,USD,68,136.8084,4.95,9307.92,68
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17/07/2019,BUY,SOXX ETF,SOXX,USD,75,204.2607,4.95,15324.5,75
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24/07/2019,BUY,Tokyo Electron,8035.T,JPY,100,168.4135,126.31,16967.66,100
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24/07/2019,BUY,BE Semiconductor Industries,BESI.AS,EUR,420,29.9253,100,12668.63,420
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17/07/2019,BUY,Synopsys,SNPS,USD,68,136.8084,4.95,9307.92,68
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17/07/2019,BUY,Microsoft,MSFT,USD,75,204.2607,4.95,15324.5,75
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24/07/2019,BUY,Tesla,TSLA,USA,100,168.4135,126.31,16967.66,100
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24/07/2019,BUY,Diversified Gas and Oil,DGOC.L,GBX,420,29.9253,100,12668.63,420
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17/07/2019,BUY,BP,BP.L,GBX,68,136.8084,4.95,9307.92,68
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17/07/2019,BUY,Ford,F,USD,75,204.2607,4.95,15324.5,75
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24/07/2019,BUY,Facebook,FB,USD,100,168.4135,126.31,16967.66,100
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24/07/2019,BUY,Snap,SNAP,USD,420,29.9253,100,12668.63,420
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17/07/2019,BUY,Apple,APPL,USD,68,136.8084,4.95,9307.92,68
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17/07/2019,BUY,Amazon,AMZN,USD,75,204.2607,4.95,15324.5,75
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24/07/2019,BUY,ASML,ASML,JPY,100,168.4135,126.31,16967.66,100
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24/07/2019,BUY,Google,GOOG,USD,420,29.9253,100,12668.63,420
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24/07/2019,BUY,Mastercard,MA,USD,420,29.9253,100,12668.63,420

‎tests/test_data_loader.py‎

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from src.data_loader import StockPriceLoader
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TICKERS = ["NVDA", "INTC", "AMAT", "MKSI", "SNPS", "SOXX", "8035.T", "BESI.AS"]
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TICKERS = ["NVDA", "INTC", "AMAT", "MKSI", "SNPS", "SOXX"]
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START_DATE = datetime.datetime(2019, 7, 17)
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‎tests/test_portfolio_value.py‎

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class TestCalculateStockValue:
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"""Test CalculateStockValue class"""
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def test__get_stock_metadata(self, nvda_stock_value):
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"""Test output of stock metadata"""
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assert nvda_stock_value.metadata["company"] == "Nvidia"
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assert calc_portfolio_value(
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input_data_source="./tests/example_inputs/example_purchase_info.csv"
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)
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