semvec/pypi-packages huggingface dataset:
libreria-senafim 0.0.1
Librería para cargar las funciones a utilizar para el análisis de alianzas y destinatarios
License: MIT

#			###### Libreria SENAFIM #######
# Esta librería contiene funciones que permitirán realizar los análisis correspondientes
# a las alianzas y destinatarios que se encuentran en la base de datos provenientes de
# las guías que emite SENAFIM. Tambien puede contener todas las funciones que se irán
# creando con el fin de ahorrar tiempo en los análisis.

# Para realizar la instalacióm de esta librería en nuestros notebooks se realizará el siguiente
# procedimiento:

#	1. Descargue el paquete
#	2. Descomprímalo si está comprimido
#	3. utilizando el comando 'cd' diríjase al directorio que contiene setup.py de la
#	   librería a instalar
#	4. Si hay instrucciones de instalación contenidas en la documentación aquí contenida,
# 	   lea y siga las instrucciones DE OTRA MANERA
#	5. Escriba python setup.py install
#	6. Llame la librería en el archivo como:
#		from libreria_senafim.Funciones import funcion_a_usar
#	7. Si queremos simplificarlo simplemente incluiremos en el fichero __init__.py las #	   siguientes líneas de código:
#		from .Funciones import leer_pdf
#	8. Luego se podrá llamar la librería como:
#		from libreria_senafim import funcion_a_usar
energyplus-diff-analysis 0.2
A tool used for plotting and comparing separate EnergyPlus output CSV files.
License: MIT

# CSV Compare

This is a very basic tool used for plotting and comparing csv data from two separate csv files.

## Usage

A version of the jupyter notebook is hosted at [mybinder.org](https://mybinder.org/v2/gh/mitchute/energyplus-diff-analysis/main)

*How is this used?*

1. Open the binder (https://mybinder.org/v2/gh/mitchute/energyplus-diff-analysis/main). This may take a few minutes to build and load the container images running behind the scenes. Once completed, mybinder.org will launch the jupyter dashboard in your web browser. This looks like a file explorer.
2. Launch the "Make_Plots.ipynb" jupyter notebook by clicking on it from the jupyter dashboard. This will launch a new tab in your browser with this notebook loaded and running.
3. Upload your data by clicking "upload" from the jupyter dashboard. For example, you could upload and name your baseline csv file "base.csv", and your modified version csv "mod.csv".
4. Back over on the "Make_Plots" jupyter notebook, update the names of your baseline and modified csv data files to match what you uploaded.
5. Select how you want your data plotted. See the examples section below for additional information.
6. To execute, you can select Cell >> Run All (or other available options). You can also run individual cells with the "shift+return" command."

## Examples

### Example 1 - Plotting all columns with diffs

As described, this plots all columns

```plot(baseline_path, mod_path, output_path)```

### Example 2 - Plot only one series

If you only want to plot a single column from the csv data, the column name can be passed explicitly to the ```cols``` field.

```plot(baseline_path, mod_path, output_path, cols="Col Name 1")```

### Example 3 - Plot a selected set of columns from the csv data

The ```cols``` field also accepts a list input for when you want to plot more than one column, but not all of them.

```plot(baseline_path, mod_path, output_path, cols=["Col Name 1", "Col Name 2"])```

### Example 4 - Plot one series for a specified number of rows

You may also specify the range of rows you want to plot.

```plot(baseline_path, mod_path, output_path, cols="Col Name 1", low_row_num=10, high_row_num=20)```

### Example 5 - Only plot files with diffs

To plot all files with including files without diffs, you can add the `plot_all_series` flag and set it to `True`.

```plot(baseline_path, mod_path, output_path, plot_all_series=True)```

### Example 6 - Zip plots

You can also zip your plots once plotting is complete for easier downloading.

```plot(baseline_path, mod_path, output_path, create_archive=True)```

## Command Line Interface

There's also a command line interface.

```bash
$ energyplus_diffs --help
Usage: eplus-diff [OPTIONS] BASELINE_CSV MODIFIED_CSV OUTPUT_DIR

Options:
  -p, --plot-all-series  Plot all series including series without diffs
  -a, --create-archive   Create archive of plots afterwards
  --help                 Show this message and exit.
```
wrapcord 0.1.3
Helpful tools for Discord.
License: MIT
Keywords: API,wrapper,discord,tools,wrapcord

# Wrapcord

Wrapcord is a Python package that provides a simple way to send messages to a Discord webhook.

## Installation

To install the `wrapcord` package, use the following command:

```
$ pip install wrapcord
```


## Usage

To use the `Wrapcord` package, you'll need a Discord webhook URL. If you don't already have a webhook URL, you can create one by following these steps:

1. Go to your Discord server settings
2. Click on "Integrations" and then "Webhooks"
3. Click "Create Webhook"
4. Enter a name for the webhook and choose a channel to post to
5. Click "Copy Webhook URL"

Once you have a webhook URL, you can use the `Wrapcord` package to send messages to it. Here's an example:

```python
from wrapcord import Wrapcord 

webhook = Wrapcord.Webhook("https://discord.com/api/webhooks/123456789012345678/abcdefg1234567")

webhook.send(content="Hello")
```


In the example above, we imported the Wrapcord class from the wrapcord package, initialized it with a Discord webhook URL, and sent a message to the webhook with the content "Hello".

You can also customize the message by specifying additional parameters


```python

webhook.send(
    content="Hello, world!",
    username="My Bot",
    avatar_url="img.png",
    tts=False,
    files=None,
    embeds=[{
        "title": "Example Embed",
        "description": "This is an example embed.",
        "color": 0x00ff00
    }],
    allowed_mentions=None
)

```
In the example above, we specified a custom username and avatar URL for the message, disabled text-to-speech, included an embed with a title, description, and color, and left the files and allowed_mentions parameters as their default values.

For more information on the available parameters, see the Discord webhook documentation.

## Contributing

If you have any suggestions, bug reports, or feature requests, please open an issue or submit a pull request on the GitHub repository.


## License
Wrapcord is released under the MIT License. See LICENSE for more information.