shrubbery | shrubbery is collection of reusable utilities for django

What you call line is in fact the file - not a text line.

Doing low = line.lower() on it should not even work:

Exception has occurred: AttributeError
'_io.TextIOWrapper' object has no attribute 'lower'

Try

After adding an exception breakpoint, I found that it had something to do with _appTintColor in the ResearchKit library.

This line of code in ORKNavigationContainerView.m:

_appTintColor = [[UIApplication sharedApplication].delegate window].tintColor;

did not work and I'm assuming this is because SceneDelegate.swift was introduced in iOS 13, which is where I'm programmatically setting the window and root view controller (as opposed to doing it in AppDelegate).

If you change it to something like this:

include_dirs is for C/C++ headers, not Cython pxd files.

In general it is best to keep related pyx/pxd files together in same directory, ie Shrubbing.pyx and Shrubbing.pxd should be in same directory.

To then use that from other modules, include a __init__.pxd and cimport via the name used in the Extension, eg pyx.Shrubbing as you would with Python modules.

If importing in python (not cimport), __init__.py should be included as well.

When using in the same module, OTOH, the .pxd needs to be available at runtime of that module, which means including it in Python search path.

If you want to organise the pxd files into separate dirs then link them symbolically within the module directory to make them available to the module, the dir containing an __init__.pxd or .py file.

It's a bit messy as Cython does not currently support relative imports, hence the need for linking when wanting to import from another dir.

See documentation for more details.

Relational databases (RDBMS) aim to store data into related, logical groupings with a system of primary key/foreign keys to normalize storage which among other advantages maintains referential integrity (i.e., no orphaned records) and avoids repetition of stored data. For your situation, consider the following:

1. DATABASE DESIGN: Understand the workflow or "story" of your data pieces (e.g., which comes first/after in data entry) and construct the necessary schema of tables. Classic Database 101 example is the Customers-Products-Orders where many customers can purchase multiple products to fill many orders (1-to-many and many-to-many relationships) where primary keys of parent tables are the foreign key of child tables. Hence, aim for a schema layout as below from this SO answer.

   For your needs, your schema may involve Contributors, Regions, Cities, Markets, Company (Ticker), and Prices. This step will make use of DDL commands (CREATE TABLE, CREATE INDEX, CREATE SCHEMA) which can be run in pyodbc cursors or sqlAlchemy engine calls, sufficing the connected user has such privileges.

   But typically, database design commands are run in a specialized admin console/IDE or command line tools and not application layer code like Python such as SQL Server's Management Studio or sqlcmd; similarly, Oracle's SQL Developer/sqlplus, MySQL's Workbench/cli or PostgreSQL's PgAdmin/psql. Below is example of setup for Prices table:

Use the dict structure. You can access a set of (key,value) tuples with .items(), and iterate over those pairs:

From the numba docs:

"All methods of a jitclass is compiled into nopython functions. The data of a jitclass instance is allocated on the heap as a C-compatible structure so that any compiled functions can have direct access to the underlying data, bypassing the interpreter."

As DavidW pointed out, Shrubbery is a Python type not a C type so you cannot use in a jitclass.

You could jit the individual methods though.

You can use array.reduce: