semvec/pypi-packages huggingface dataset:
infrasonar-selenium 1.0.2
Library for building InfraSonar Selenium tests
Keywords: monitoring, infrasonar, agent, selenium

[![CI](https://github.com/infrasonar/selenium/workflows/CI/badge.svg)](https://github.com/infrasonar/selenium/actions)
[![Release Version](https://img.shields.io/github/release/infrasonar/selenium)](https://github.com/infrasonar/selenium/releases)

# InfraSonar Selenium Test Suite

## Requirements

* Python (3.12 or higher)
* Docker

## Usage

Make sure the lib is installed:
```bash
pip install infrasonar_selenium
```

Start Selenium:
```bash
docker run -d -p 4444:4444 -p 7900:7900 --shm-size="2g" selenium/standalone-chrome
```

Write a test: _(for example, save the following to `mytest.py`)_

```python
from infrasonar_selenium import TestBase
from selenium import webdriver
from selenium.webdriver.common.by import By


class MyTest(TestBase):

    description = 'Example test'
    url = 'https://www.selenium.dev/selenium/web/web-form.html'
    version = 'v0'

    @classmethod
    def test(cls, driver: webdriver.Remote):
        title = driver.title
        assert title == "Web form"

        driver.implicitly_wait(0.5)

        text_box = driver.find_element(by=By.NAME, value="my-text")
        submit_button = driver.find_element(by=By.CSS_SELECTOR, value="button")

        text_box.send_keys("Selenium")
        submit_button.click()

        message = driver.find_element(by=By.ID, value="message")
        value = message.text

        assert value == "Received!"


export = MyTest

if __name__ == '__main__':
    MyTest().print_run()  # Prints the output
```

Start the test:
```bash
python mytest.py
```


With the following link you can view your scripts in action:

http://localhost:7900/?autoconnect=1&resize=scale&password=secret

> The same applies for scripts running with InfraSonar, except replace `localhost` with your appliance server address.
aa-skyhookintel 0.1.4
Skyhook Intel app for Alliance Auth.
Requires Python: >=3.10

# Skyhook Intel

AA module for gathering skyhook timers.

[![release](https://img.shields.io/pypi/v/aa-skyhookintel?label=release)](https://pypi.org/project/aa-skyhookintel/)
[![python](https://img.shields.io/pypi/pyversions/aa-skyhookintel)](https://pypi.org/project/aa-skyhookintel/)
[![django](https://img.shields.io/pypi/djversions/aa-skyhookintel?label=django)](https://pypi.org/project/aa-skyhookintel/)
[![license](https://img.shields.io/badge/license-MIT-green)](https://gitlab.com/r0kym/aa-skyhookintel/-/blob/master/LICENSE)

## Features:

- Load skyhooks in a constellation/region through admin commands
- Displays Skyhooks with and without timers in separate tables
- Extracts data from the information on the skyhook in space window that can be copied to a clipboard
- Automatically populates times in the timberboard or structuretimers application

### Screenshots

## Installation

### Step 1 - Check prerequisites

Skyhook Intel is a plugin for Alliance Auth. If you don't have Alliance Auth running already, please install it first before proceeding. (see the official [AA installation guide](https://allianceauth.readthedocs.io/en/latest/installation/auth/allianceauth/) for details)

### Step 2 - Install app

Make sure you are in the virtual environment (venv) of your Alliance Auth installation. Then install the newest release from PyPI:

```bash
pip install aa-skyhookintel
```

### Step 3 - Configure Auth settings

Configure your Auth settings (`local.py`) as follows:

- Add `'skyhookintel'` to `INSTALLED_APPS`

### Step 4 - Finalize App installation

Run migrations & copy static files

```bash
python manage.py migrate
python manage.py collectstatic --noinput
```

Restart your supervisor services for Auth.

### Step 5 - Load data

You can load data using 2 commands depending on the area you want to cover.
Commands can take some time to execute so avoid loading an entire region if you only need a few systems.

#### Region:

```shell
python manage.py skyhook_intel_create_region [[region_id]]
```

#### Constellation:

```shell
python manage.py skyhook_intel_create_constellation [[constellation_id]]
```

Once the data is loaded you can add skyhooks owners using in the admin panel.

## Settings

| Name                               | Description                                                                           | Default value |
|------------------------------------|---------------------------------------------------------------------------------------|---------------|
| SKYHOOK_INTEL_POPULATE_TIMERBOARDS | If the application should try to find known timerboards and populate them with timers | True          |
mcstools 0.1.0
Read, load, and process Mars Climate Sounder data
Requires Python: >=3.10

# mcstools
Tools to read and process Mars Climate Sounder data.

#### Setup
Setup a virtual environment with `python3[>3.10] -m venv env`.

Then, either pip install: `pip install mcstools`

Or download or clone the repo:
```bash
$ git clone https://github.com/cloudspotting-on-mars/mcstools
```
and install with `pip install -e .`

#### Download data
See https://pds-atmospheres.nmsu.edu/data_and_services/atmospheres_data/MARS/atmosphere_temp_prof.html

#### Read a single file
To read in an L1B file as a DataFrame:
```python
from mcstools import L1BReader
reader = L1BReader()
reader.read(path_to_file)
```

#### Load Data from PDS
To load data from PDS:
```python
from mcstools import L1BLoader
loader = L1BLoader(pds=True)
loader.load_date_range("2016-01-01", "2016-01-02")
```

#### Find and load subset of L2 profiles
```python
from mcstools import L2Loader
loader = L2Loader(pds=True)
ddr1_df = loader.load_date_range("2018-04-18", "2018-04-19", "DDR1")
ddr1_subset = ddr1[ddr1["Profile_lat"].between(-10, 10)]
ddr2 = loader.load("DDR2", profiles=ddr1_subset["Profile_identifier"])
```

#### Plot L1B radiances
To view the radiances for a single 4-hour L1B file, run
```bash
python mcstools/plotting/l1b_panel.py
```

That should bring up a dashboard in a browser allowing you to choose a 4-hour file at the top
(enter the date in `YYMMDDHH0000` format).
You can switch between channels using the tabs.
The slider on the right allows you to set the colorbar limits (radiance units).
There are also tools to zoom in and out, pan, etc.

#### Preprocess data
To preprocess L1B data and reduce to standard in-track limb views:
```python
from mcstools.preprocess.l1b import L1BStandardInTrack
preprocesser = L1BStandardInTrack()
df = preprocesser.process(df)
```