semvec/pypi-packages huggingface dataset:
passql 0.3.0
Super light ORM
Requires Python: >=3.6

# PasSQL ORM - *really simple mapping for PYTHON*
#### © 2022 Vladislav Mironov

### Description

PasSQL is a library that provides simple ORM tools for executing template SQL queries from Python 3.7
<br> 
using other database interface libraries (e.g. asyncpg or PyMySQL).
dbgprint 1.0.8
A package for a python command line terminal debugger
Requires Python: >=3.6

# dbgprint

Debug Print is a handy command line print app used for debugging loops and variable changes over time.

It has features for tracking pivots in a while and for loop, and also print the information and data types of variables

Its dependencies are termcolor and colorama.

For python package: https://pypi.org/project/dbgprint/

For github repo: https://github.com/youhengzhou/dbgprint

# Download Package

`py -m pip install dbgprint -U`

## In Your Python Files

`import dbgprint`

# Commands

## Create command:

`dbgprint.data(dataContent, dataName, action)`
This will print the data's contents, the data's variable name, and the actions associated with the data at your discretion.
syngenta-digital-uoms 0.0.8
Standardized hub for unit of measure conversions across systems and dimensions.
Requires Python: >=3.0

# Syngenta Digital Units of Measure
Centralized source of canonical unit of measures for lookup and conversion

## Definitions
  * Unit of measure code (“UoM Code”): A small string/token that forms part of a controlled vocabulary (e.g., ADAPT, UN Rec 20, UCUM, QUDT) and represents a unit of measure (e.g., “meter”) 
  * Input Code Vocabulary (“UoM Voc”): A small string/token that represents the controlled vocabulary that a unit of measure code belongs to (e.g., “ADAPT”, “UCUM”).
  * Dimension: a label for a family of units of measure that represent the same phenomenon. For example, “DISTANCE” represents a phenomenon represented by “meter”, “mile”, “inch”, “millimeter”, etc. We have a controlled vocabulary of these dimensions.
  * Unit of measure System: A family of units of measure (cutting across all dimensions) that have a common cultural origin or organizing principles (e.g., “METRIC”, “IMPERIAL”).

## Features

#### Retrieve the dimension of a given unit of measure
```python
from syngenta_digital_uoms.common.vocabulary import Vocabulary

def retrieve_dimension_from_uom():
    vocabulary = Vocabulary()
    return vocabulary.get_dimension('min') # Returns 'TIME'
```

#### Retrieve list of unique dimensions from respective vocabulary
```python
from syngenta_digital_uoms.common.vocabulary import Vocabulary

def retrieve_dimensions():
    vocabulary = Vocabulary(vocab_type='adapt') # 'adapt' is the default vocabulary type
    return vocabulary.list_dimensions()
```

#### Retrieve list of all units of measure from a given dimension
```python
from syngenta_digital_uoms.common.vocabulary import Vocabulary

def retrieve_uoms_from_dimension():
    vocabulary = Vocabulary()
    return vocabulary.list_dimension_uoms('DISTANCE')
```

#### Retrieve canonical unit of measure from given dimension
```python
from syngenta_digital_uoms.common.vocabulary import Vocabulary

def retrieve_uoms_from_dimension():
    vocabulary = Vocabulary()
    return vocabulary.get_canonical_uom('DISTANCE') # Returns 'm', as meter is the canonical unit of the DISTANCE dimension.
```

  
#### Retrieve the canonical unit of measure from a given unit's dimension
```python
from syngenta_digital_uoms.util.converter import Converter

def convert_uom_to_canonical():
    converter = Converter()
    return converter.convert_uom('ft') # Returns 'm', as meter is the canonical unit of the DISTANCE dimension.
```

#### Convert a given value across units of measure
```python
from syngenta_digital_uoms.util.converter import Converter

def convert_value_across_uoms():
    converter = Converter()
    return converter.convert_value(input_uom_code='ft',
                                   input_value=100,
                                   output_uom_code='km') # Returns 0.03048, as 100 feet is equivalent to 0.03048 kilometers.
```
gumly 1.2.0
Gumly

# **Gumly**

[![APM](https://img.shields.io/apm/l/python?style=plastic)](./LICENSE)


GAVB Utilities for Machine Learning Yum

The library consists of a collection of methods that can be used in order to help Data Scientists and Machine Learning Engineers during the development of Machine Learning applications seeking to reduce the time spent and complexity of coding.


## **Library Motivation and Description**

During the development of ML projects at GAVB, Data Scientists have the necessity to code some features for projects repeatedly. So, MLOps area identified the opportunity to create some standard functions that can help as it can be used many times by data science area in each different project.
Thus, it is possible to work with this framework that brings basically two main advantages: 
1 - Projects executed in less time than usual, due to the code reusability;
2 - Establishment of a standard coding structure for projects.

## **Functionality**

[Value Validation](https://github.com/GAVB-SERVICOS/Gumly/blob/main/exercises/value_validation.ipynb)

[Dimensionality Reduction](https://github.com/GAVB-SERVICOS/Gumly/blob/main/exercises/dimensionality_reduction.ipynb)

[Feature Engineering](https://github.com/GAVB-SERVICOS/Gumly/blob/main/exercises/feature_engineering.ipynb)

[Files](https://github.com/GAVB-SERVICOS/Gumly/blob/main/exercises/files.ipynb)

[Hyperparameter Tuning](https://github.com/GAVB-SERVICOS/Gumly/blob/main/exercises/hyperparameter_tuning.ipynb)

[Metrics](https://github.com/GAVB-SERVICOS/Gumly/blob/main/exercises/metrics.ipynb)

[Geo Location](https://github.com/GAVB-SERVICOS/Gumly/blob/main/exercises/geo_location.ipynb)

[Imbalanced](https://github.com/GAVB-SERVICOS/Gumly/blob/main/exercises/imbalanced.ipynb)

[Check Point Flow](https://github.com/GAVB-SERVICOS/Gumly/blob/main/exercises/checkpoint_flow.ipynb)


## **How to install**

```
pip install gumly
```


## **Release Notes**

Check the [CHANGELOG](https://github.com/GAVB-SERVICOS/Gumly/blob/main/CHANGELOG.md) file to keep track the release features.
syngenta-digital-uoms-test 0.0.0
Standardized hub for unit of measure conversions across systems and dimensions.
Requires Python: >=3.0

# Syngenta Digital Units of Measure
Centralized source of canonical unit of measures for lookup and conversion

## Definitions
  * Unit of measure code (“UoM Code”): A small string/token that forms part of a controlled vocabulary (e.g., ADAPT, UN Rec 20, UCUM, QUDT) and represents a unit of measure (e.g., “meter”) 
  * Input Code Vocabulary (“UoM Voc”): A small string/token that represents the controlled vocabulary that a unit of measure code belongs to (e.g., “ADAPT”, “UCUM”).
  * Dimension: a label for a family of units of measure that represent the same phenomenon. For example, “DISTANCE” represents a phenomenon represented by “meter”, “mile”, “inch”, “millimeter”, etc. We have a controlled vocabulary of these dimensions.
  * Unit of measure System: A family of units of measure (cutting across all dimensions) that have a common cultural origin or organizing principles (e.g., “METRIC”, “IMPERIAL”).

## Features

#### Retrieve the dimension of a given unit of measure
```python
from syngenta_digital_uoms.common.vocabulary import Vocabulary

def retrieve_dimension_from_uom():
    vocabulary = Vocabulary()
    return vocabulary.get_dimension('min') # Returns 'TIME'
```

#### Retrieve list of unique dimensions from respective vocabulary
```python
from syngenta_digital_uoms.common.vocabulary import Vocabulary

def retrieve_dimensions():
    vocabulary = Vocabulary(vocab_type='adapt') # 'adapt' is the default vocabulary type
    return vocabulary.list_dimensions()
```

#### Retrieve list of all units of measure from a given dimension
```python
from syngenta_digital_uoms.common.vocabulary import Vocabulary

def retrieve_uoms_from_dimension():
    vocabulary = Vocabulary()
    return vocabulary.list_dimension_uoms('DISTANCE')
```

#### Retrieve canonical unit of measure from given dimension
```python
from syngenta_digital_uoms.common.vocabulary import Vocabulary

def retrieve_uoms_from_dimension():
    vocabulary = Vocabulary()
    return vocabulary.get_canonical_uom('DISTANCE') # Returns 'm', as meter is the canonical unit of the DISTANCE dimension.
```

  
#### Retrieve the canonical unit of measure from a given unit's dimension
```python
from syngenta_digital_uoms.util.converter import Converter

def convert_uom_to_canonical():
    converter = Converter()
    return converter.convert_uom('ft') # Returns 'm', as meter is the canonical unit of the DISTANCE dimension.
```

#### Convert a given value across units of measure
```python
from syngenta_digital_uoms.util.converter import Converter

def convert_value_across_uoms():
    converter = Converter()
    return converter.convert_value(input_uom_code='ft',
                                   input_value=100,
                                   output_uom_code='km') # Returns 0.03048, as 100 feet is equivalent to 0.03048 kilometers.
```
syngenta-digital-uoms-2 0.0.0
Standardized hub for unit of measure conversions across systems and dimensions.
Requires Python: >=3.0

# Syngenta Digital Units of Measure
Centralized source of canonical unit of measures for lookup and conversion

## Definitions
  * Unit of measure code (“UoM Code”): A small string/token that forms part of a controlled vocabulary (e.g., ADAPT, UN Rec 20, UCUM, QUDT) and represents a unit of measure (e.g., “meter”) 
  * Input Code Vocabulary (“UoM Voc”): A small string/token that represents the controlled vocabulary that a unit of measure code belongs to (e.g., “ADAPT”, “UCUM”).
  * Dimension: a label for a family of units of measure that represent the same phenomenon. For example, “DISTANCE” represents a phenomenon represented by “meter”, “mile”, “inch”, “millimeter”, etc. We have a controlled vocabulary of these dimensions.
  * Unit of measure System: A family of units of measure (cutting across all dimensions) that have a common cultural origin or organizing principles (e.g., “METRIC”, “IMPERIAL”).

## Features

#### Retrieve the dimension of a given unit of measure
```python
from syngenta_digital_uoms.common.vocabulary import Vocabulary

def retrieve_dimension_from_uom():
    vocabulary = Vocabulary()
    return vocabulary.get_dimension('min') # Returns 'TIME'
```

#### Retrieve list of unique dimensions from respective vocabulary
```python
from syngenta_digital_uoms.common.vocabulary import Vocabulary

def retrieve_dimensions():
    vocabulary = Vocabulary(vocab_type='adapt') # 'adapt' is the default vocabulary type
    return vocabulary.list_dimensions()
```

#### Retrieve list of all units of measure from a given dimension
```python
from syngenta_digital_uoms.common.vocabulary import Vocabulary

def retrieve_uoms_from_dimension():
    vocabulary = Vocabulary()
    return vocabulary.list_dimension_uoms('DISTANCE')
```

#### Retrieve canonical unit of measure from given dimension
```python
from syngenta_digital_uoms.common.vocabulary import Vocabulary

def retrieve_uoms_from_dimension():
    vocabulary = Vocabulary()
    return vocabulary.get_canonical_uom('DISTANCE') # Returns 'm', as meter is the canonical unit of the DISTANCE dimension.
```

  
#### Retrieve the canonical unit of measure from a given unit's dimension
```python
from syngenta_digital_uoms.util.converter import Converter

def convert_uom_to_canonical():
    converter = Converter()
    return converter.convert_uom('ft') # Returns 'm', as meter is the canonical unit of the DISTANCE dimension.
```

#### Convert a given value across units of measure
```python
from syngenta_digital_uoms.util.converter import Converter

def convert_value_across_uoms():
    converter = Converter()
    return converter.convert_value(input_uom_code='ft',
                                   input_value=100,
                                   output_uom_code='km') # Returns 0.03048, as 100 feet is equivalent to 0.03048 kilometers.
```