ggravlingen / pypmanager Goto Github PK

Summarize transactions in funds into a simple portfolio report.

The overview page:

The general ledger:

I have been looking for a library where I can download a set of transactions from my broker and pension fund manager and compile them into a report giving me an overview of all holdings.

Alternative solutions expected me to store my data in the cloud. I don't want that, so I wrote this local-only library. The only thing cloud is that the library allows you to fetch market data from the Internet.

There are other ways of getting this to work, this is how I use it:

• Clone the library from GitHub: git clone https://github.com/ggravlingen/pypmanager.git
• Install Docker Desktop
• Install VSCode from Microsoft and the Dev Containers extension.
• Open the library in VSCode and choose the option to open the folder in a container.

There is currently support for three types of data: Avanza, Lysa and custom. For Avanza and Lysa, just download the transactions in CSV-format and place them in the data-folder in the root of this library.

The custom format allows you to run the calculations on any set of transactions as long as the correct format is followed:

transaction_date;transaction_type;name;isin_code;no_traded;price;amount;commission;currency
2021-02-15;buy;Fund A;NO0010000000;1000;100;-100000;-2,200;NOK
2021-02-15;sell;Fund A;NO0010000000;1000;100;100000;-2,200;NOK

Save the data as other.csv in the data folder.

transaction_format may be any of buy, sell, interest, dividend and tax.

I have provided a few data sources built-in. Configuration is done by appending config/market_data.yaml with the securities you want to download data for.

When the configuration file is updated, you can simply type python -m pypmanager -l to download all data.

In VSCode, click the Run and debug option. Press play next to Python: FastAPI. Navigate to http://localhost:8001/ in your browser.

• Calculate IRR per security and on a total.
• Split the overview by account or maybe tag.
• Investments made in other currencies
• Support other online brokers by extending the DataLoader class.
• Adding scrapers to download historical closing data.
• Output the result as well-formatted HTML instead of in a CLI table.
• Allow setting an arbitrary date to calculate the value of the portfolio.

Transactions are loaded using a loader class in the pypmanager.loader_transaction. A loader class should inherit from the pypmanager.loader_transaction.TransactionLoader class, which does some normalising of data.

The helper function pypmanager.helpers.download_market_data loads all sources in config.market_data.yaml and parses each source using its associated loader class. Each loader class should inherit from pypmanager.loader_market_data.base_loader.BaseMarketDataLoader. A loader class typically fetches data from a JSON endpoint or HTML-table and parses it so that it fits into the pypmanager.loader_market_data.models.SourceData dataclass.

Historical market data is written, rather naively, to the data/market_data.csv file.

The general ledger, which we can load using the helper pypmanager.helpers.get_general_ledger, is a Pandas dataframe. The dataframe contains each loaded transaction but split into separate components for the transaction's effect on your equity, cash balance, PnL, and so on.

Any PnL effect is written to the cash record of the general ledger.