By default, python stores a decimal as `float`, a 64-bit floating-point number. Though this theoretically achieves a value range of about 2.2e-308 ~ 1.8e+308, the precision is much worse due to how decimals are stored in `float`: it uses base 2 (binary) fractions. For example, 1/2 is 0.1, and 1/8 is 0.001. Just like we will eventually hit a precision limit when trying to store 1/3 in a base 10 fraction as 0.3333..., not all numbers within the range value of `float` can be represented exactly: 1/10 in base 2 would become a repeating 0.00011001100.... Therefore, when your input are as small as 1e-15, such errors become significant to the result and cause the difference from the actual derivative.
To solve this problem, you can use the `decimal` module of python which provides exactly represented decimal numbers. An example is as follows:

```python
from decimal import Decimal, getcontext

#set the precision of the decimal. Default is 28
getcontext().prec = 26

#Convert other variables to Decimal. However, float would bring in the precision problem
a = Decimal("1.2375")  #Decimal('1.2375')
b = Decimal(1)/Decimal(7) #Decimal('0.14285714285714285714285714')
c = Decimal(6.325) #Decimal('6.32500000000000017763568394')
```
spam fails_task lang_mismatch pii not_appropriate hate_speech sexual_content quality toxicity humor helpfulness creativity violence