thorwhalen

api_costs = {
    'gpt-4-1106-preview': {"input": 0.01, "output": 0.03, "unit": "$/1K tokens"},
    'gpt-4-1106-vision-preview': {"input": 0.01, "output": 0.03, "unit": "$/1K tokens"},
    'gpt-4': {"input": 0.03, "output": 0.06, "unit": "$/1K tokens"},
    'gpt-4-32k': {"input": 0.06, "output": 0.12, "unit": "$/1K tokens"},
    'gpt-3.5-turbo-1106': {"input": 0.0010, "output": 0.0020, "unit": "$/1K tokens"},
    'gpt-3.5-turbo-instruct': {"input": 0.0015, "output": 0.0020, "unit": "$/1K tokens"},
    'gpt-3.5-turbo': {"training": 0.0080, "input": 0.0030, "output": 0.0060, "unit": "$/1K tokens"},
    'davinci-002': {"training": 0.0060, "input": 0.0120, "output": 0.0120, "unit": "$/1K tokens"},
    'babbage-002': {"training": 0.0004, "input": 0.0016, "output": 0.0016, "unit": "$/1K tokens"},

thorwhalen

thorwhalen

from tested import validate_codec


Empty1 = type('Empty', (), {})()
print("\nEmpty1 = type('Empty', (), {})()")
print(f"{validate_codec(Empty1)=}")


_Empty2 = type('Empty', (), {})
_Empty2.__module__ = __name__

thorwhalen

# get raw df

import qo
df = qo.get_tables_from_url('https://en.wikipedia.org/wiki/List_of_salaries_of_heads_of_state_and_government')[3]
df = df.set_index('State')


# formatting and extracting salaries

thorwhalen

thorwhalen

thorwhalen

"""
 I've often seen that “color of musical notes” thing, 
 and I always wondered about it (especially because I’d like to use it as educational support when I teach my (reluctant) 
 daughter music). 
 The mappings I see are not always consistent, but one comes up most often; 
 the one where the red-to-violet range is mapped to the C-to-B range. 
 Now this could just so happen to be correct, but the choice that C as the canonical root note of a scale seems 
 to be arbitrary, whereas red as the first color is a physical reality, leading me to think that:
- The choice of C as the root note was purposely based on the red-to-violet correspondence
- It’s a crock of s**t 

thorwhalen

from inspect import signature, Signature


class Compose:
    def __init__(self, *funcs):
        """Performs function composition.
        That is, get a callable that is equivalent to a chain of callables.
        For example, if `f`, `h`, and `g` are three functions, the function
        ```
            c = Compose(f, h, g)

thorwhalen

"""
Code that prints this table (meant to study the type-differences of different callables):

```
                                MethodType  FunctionType  has_self  qualname_levels  dunders
name                                                                                        
class method                          True         False      True                2       27
instance method                      False          True     False                2       35
static method                        False          True     False                2       35
"instantiated" class method           True         False      True                2       27

thorwhalen

"""
Prints a diagnosis (object kind and import depth) of the imports that can be obtained from the (top level) module.
That is, those objects that can by imported by doing:
```
from module import obj
```
though the object's code may be several package levels down (say module.sub1.sub2.obj).
        
```
$ python print_top_level_diagnosis.py numpy