![]() ![]() Or you can tell GNUCash to skip the compression. In short, the xml file, (And I'm speculating the sqlite file) is compressed and you need to decompress them before you can edit them. Once you have edited and saved the file, you don't have to gzip it yourself GnuCash will do this upon the next save. In this case, the original file, "foobar" is intact. When you intend to make some manual changes, as we have done, make sure to have a backup of your original file somewhere in case you get something wrong. After > these two commands have been entered, you can open the resulting file "foobar-copy" > in a text editor. Where you need to replace "foobar" by your actual file name, of course. In order to have a look at your data by a text editor, you need to open a terminal window (console window) and enter the following commands: mv foobar foobar-copy.gz This is switched on or off according to the preference setting in Edit->Preferences->General where you can set or unset the checkmark at File compression. Profitability test use special GnuCash book file in test/data/xirr-test.The file itself is XML data but in compressed form (compressed by the program gzip). Set this options in src/test/basetest.py bookfile_sql = your_sql_base bookfile_xml = your_xml_base dir_testdata = folder_for_test_data Then all testing function use external folder.įor create test data, save sql book file and xml book file into any folder. Groups only 1 level, into 2 rows and 1 column:Īll my testing data is real. Group accounts for 0 and 1 level, into 2 rows and 2 columns (Multiindex dataframe): Glevel - how group accounts by levels: array of levels or single int level The costs of servicing the account (per annum) Capital Dividends, interests on other account, etc Expense The total return on asset taking into account the costs Money flow xlsx file after launch command line toolĪll results are displayed in percent per annum: Total open_book_file ( your_gnucash_file ) # Get return on assets gcrep. If you mark the account %no_invest% in notes, it and its descendants will not be considered in calculating the yield # open gnucash book import gnucashreport gcrep = GCReport () gcrep. Then the account and its descendants will be taken into when calculating profitability. The IIF output from GnuCashToQIF should import properly into QuickBooks versions that support the import of IIF files. You should mark the account of incomes and expenses for calculation of yield. You can calculate the portfolio return of the stock or all of the assets. You can calculate the yield for all time or a specified period. The library may consider the profitability of accounts taking into account the hierarchy.Īny asset accounts: deposit, liability, bank, not only stock. > gcrep.all_reports_excel('v:/tables/ex-test.xlsx', glevel=1) Personal inflation (annual expenditure growth) Income, expense, profit, assets, loans, equity by years on each full year ![]() Income, expense, profit, assets, loans, equity by months each year (sheet on each year) > dataframe_to_excel(gcrep.df_splits, 'v:/tables/splits.xlsx') Save all splits to Excel (with account name, decription, currency mnemonic and other) > from gnucashreport.utils import dataframe_to_excel Open gnucash book (sql or xml) > gcrep.open_book_file('v:/gnucash-base/sqlite/GnuCash-base.gnucash', open_if_lock=True) (As all_reports_excel function) Examples > import gnucashreport Open sqlite base even if opened other user Level to group accounts, may be multiple (–glevel 0 –glevel 1) -open_if_lock Path to xlsx file for saving reports -glevel glevel Library contain the simple cli tool, usage: gcreport gnucash_file xlsx_file gnucash_file Pandas need install before, because numpy have installation thru install_requires directive issue Simple command line tool Install gnucashreport: pip install gnucashreport Install Python version 3 (version 2 should work, but I have not tested) Then data are processed only thru Pandas. GnuCash python bindings not use, because it platform depended and unstable.Īll data from GnuCash loads into DataFrames as is, table to table. The library is cross-platform, Excel is not required, you can use LibreOffice/OpenOffice No cycles for calculation, less errors, less code. It connects directly to the GnuCash book (xml or sql) and Pandas use to building reports. Creating a file to store your data is the first step, and this chapter will walk. Python library for get reports from GnuCash to xlsx files. The main building blocks of GnuCash are files, accounts, and transactions. ![]()
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