semvec/pypi-packages huggingface dataset:
StringCalculator 0.0.5
String Calculator
Requires Python: <4,>=3.7
Keywords: string, calculator

# StringCalculator
 Calculator that solves string math expression

`pip install StringCalculator`

```
from StringCalculator import SolveMathProblem

result = SolveMathProblem("5^5*6+3-15")

print(result)
```
output:
> 18738.0
stickydata 0.1
package for correcting partitioning delays using deconvolution

# stickydata
A package for correcting partitioning delays using deconvolution

Manuscript *in prep* for Environmental Science and Technology Air

## Installation

`pip install stickydata`

## Getting Started

The package currently supports deconvolution of single and double-exponential instrument response function. The relevant functions in the package are:
- Deconvolve_SingleExp
- Deconvolve_DblExp
- Deconvolve_DblExp_VariableIRF 

## Future Updates
Please contact demetriospagonis@weber.edu to discuss future updates
catway 1.1
Create tempmail based on https://mail.catway.org :D
Requires Python: >=3.8

# Install :
```commandline
pip install -U catway
```

# How to use :
- 1 - Send email to your custom email, for example: ``sadf@catway.org``
- 2 - Get inbox:

```python
from catway import CatMail

def main():
    with CatMail("sadf@catway.org") as email:
        for mail in email.get_inboxes():
            print(mail)
            print(email.get_inbox(mail.id))

main()
```
dottable-dict 0.0.5.1
Your everyday dictionary, with the special ability to be accessed using dot-notation
Requires Python: >=3.10

# Dottable Dictionary
Your everyday dictionary, with the special ability to be accessed using dot-notation.

Use dottable dictionaries to turn this: \
`d["somekey"]["some_inner_key"]["some_internal_key"]`\
to this:\
`d.somekey.some_inner_key.some_internal_key`.

## Background
The basic idea behind this package was to migrate JavaScript's dot-notation access to Python dictionaries.
In many (maybe most) cases, dictionaries are used with keys which can serve as identifiers (for more on those take a look [here](https://docs.python.org/3/library/stdtypes.html#str.isidentifier)).\
By taking advantage of this, dictionary access can be as intuitive as accessing properties within an object (rather than being constrained to using strings).

Importantly - dottable dictionaries are first and foremost **dictionaries**.
Therefore, they implement the same basic functionalities as native `dict` objects, and are generally designed to interact with them as seamlessly as possible, such that using dottable dictionaries should be compatible with existing code and/or any external module/package.

## Functionality
### Dictionary functionality
Some basic native `dict` functionalities which are implemented in dottable dictionaries:
- `copy()`
- `update()`
- `keys()`, `values()`, `items()`
- `in` operator (`__contains__()`)
- Iterability (`__iter__`)
- TBD: `setdefault`


### Extra functionality
Some extra functionality (extending native `dict` functionality):
- Adding & merging: merging mappings to get a unified view of all values (also availble using the `+` operator)
- Access by complex string paths - set/get properties using a dot-separated path (e.g., `["a"]["b"]["c"]` <-> `"a.b.c"`). This can be useful for dynamically accessing properties in objects with complex data schemas.
- Immutable copies - generating an immutable copy of the current state of the mapping. This is also used to allow a pseudo-hash of the mapping (i.e., hash of the current state)

### Conversions
Dottable dictionaries can be directly (recursively) converted to native `dict` objects by using the `simple_dict` property.