semvec/pypi-packages huggingface dataset:
sensoterra 2.0.1
Query Sensoterra probes using the Customer API
Requires Python: >=3.11
Keywords: Sensoterra, soil moisture, probe, sensor

# Sensoterra

Package to retrieve Sensoterra probe data by polling the Sensoterra Customer API using async/await.

## Example code

When the email and password are always available:

```python
import time
import asyncio

from sensoterra.customerapi import CustomerApi

async def main(email, password):
  api = CustomerApi(email, password)
  api.set_language("en")

  while True:
    api.poll()

    for probe in api.probes():
        print(probe)
        for sensor in probe.sensors():
            print(sensor)
        print()

    time.sleep(900)
    print('-' * 70)

asyncio.run(main("me@example.com", "secret"))
```

Otherwise request a authentication token:

```python
from datetime import datetime

async def get_token(email, password):
  api = CustomerApi(email, password)
  api.set_language("en")

  tag = "My Application"
  scope = "READONLY"
  expiration = datetime(2038, 1, 1, 0, 0)
  token = await api.get_token(tag, scope, expiration)
```
And use this token:
```python
async def main(email, password):
  token = await get_token(email, password)

  api = CustomerApi()
  api.set_language("en")
  api.set_token(token)

  while True:
    probes = await api.poll()

    for probe in probes:
        print(probe)
        for sensor in probe.sensors():
            print(sensor)
        print()

    time.sleep(900)
    print('-' * 70)
```

## Changelog

[CHANGELOG](CHANGELOG.md)
gg-fpga 0.0.19
FPGA ultra low latency options triggering
Requires Python: >=3.8

# gg-fpga
FPGA / Python simulation and output focused on exchange binary  
protocol parsing and specifics of byte layout for msg types.  
Uses SystemVerilog and Python and currently supports interfacing  
with excel and matplotlib.pyplot.  

### Note:
Currently set up to only work easily on Linux platforms.  

In addition to dependencies in pyproject, also requires:   
  - iverilog  

And, for simulation:  
- verilator (only easily installable for Linux systems)  

(can use other simulators as well: set in module 'run' as different default or set in env as SIM=\<your simulator choice\>)
automize_science 1.0.2
Automize Science is a Python package designed to elaborate data into graphs coming from lipid extractions (LC/MS).

# Automize Science

## What is it

Automize Science is a Python package designed to elaborate data into graphs coming from lipid extractions (LC/MS).
Starting from a file containing the **pmol/mg** values per each sample, this package streamlines the process of data
analysis and visualization.

## Features

Automize Science includes the following features:

- Data Sanitization: Clean and prepare data for analysis, removing internal standard samples and non value samples.
- Data Normalization: Normalize values with log10 to ensure consistency across samples.
- Normality Check: Use the Shapiro-Wilk test to check for normality of residuals.
- Equality of Variance Check: Use Levene's test to assess the equality of variances.
- Statistical Significance Annotation: Annotate boxplots with significance levels using t-test, Welch's t-test, or
  Mann-Whitney test depending on the data requirements, through the starbars package.
- Visualization Tools: Create boxplots to aid in data interpretation.

## Installation

You can install the package via pip:

```
pip install automize_science
```

\
Alternatively, you can install the package from the source:

```
git clone https://github.com/elide-b/automize-science.git
cd automize-science
pip install .
```

## Usage

Here is one example of how to use Automize Science:

```
import automize_science 

# Example usage
df = automize_science.data_workflow(
    file_path="My project.xlsx",
    data_sheet="Data Sheet",
    mice_sheet="Mice Sheet",
    output_path="C:/Users/[YOUR-USERNAME]/Documents/example",
    control_name="CM",
)

automize_science.zscore_graph_region(
    df_final=df,
    control_name="CM",
    experimental_name="EM",
    output_path="C:/Users/[YOUR-USERNAME]/Documents/example",
    palette="Set2",
    show=True,
)
```

Returns graphs.

## Examples

For more detailed examples, please check the [example](https://github.com/elide-b/automize-science/tree/master/example)
folder.

## Contributing

We welcome contributions!
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also
simply open an issue with the tag **"enhancement"**.

To contribute:

1. Fork the repository.
2. Create a new branch (`git checkout -b feature-branch`).
3. Commit your changes (`git commit -m 'Add some amazing feature'`).
4. Push to the branch (`git push origin feature-branch`)
5. Open a pull request

## License

Distributed under the MIT License. See `LICENSE.txt` for more information.