semvec/pypi-packages huggingface dataset:
faust-avro-model-codegen 0.1.8
Generate Faust Avro Models from Avro Schema files.
License: MIT
Requires Python: >=3.10

# Faust Avro Code Generator

This is a Python library that generates Faust models from Avro schemas.

## Installation

You can install the library using pip:

```bash
pip install faust_avro_code_gen
```

## Configuration

You can configure the library for your application using either `pyproject.toml` or a standalone configuration file.

### Using `pyproject.toml`

Add the following section to your `pyproject.toml`:

```toml
[tool.faust_avro_code_gen]
schema_dir = "path/to/your/schemas"
outfile = "path/to/your/models.py"
schema_registry_url = "http://localhost:8081"
faust_app_models_module = "models"
```

### Using a standalone configuration file

Create a `faust_avro_code_gen.toml` file in your project root with the following content:

```toml
schema_dir = "path/to/your/schemas"
outfile = "path/to/your/models.py"
schema_registry_url = "http://localhost:8081"
faust_app_models_module = "models"
```

## Usage

You can use the library from the command line as follows:

```bash
python -m faust_avro_code_gen 
```

If you have already registered your schemas with a Schema Registry, you can also verify that the schemas are correctly rendered by running the following command:

```bash
python -m faust_avro_code_gen --verify
```

This will generate Faust models from the Avro schemas in the directory specified in your configuration.
opinionated 0.0.3.0
opinionated provides simple, clean stylesheets for plotting with matplotlib and seaborn.
License: MIT

Opinionated
===========

``opinionated`` provides simple, clean stylesheets for plotting with
``matplotlib`` and ``seaborn``.

It’s modeled and named after hrbrthemes in R, by hrbrmstr, which are
“Opinionated, typographic-centric ggplot2 themes”. It’s not meant to be
an exact clone though, I have made a few different choices.

The main application I had in mind was to increase the quality of plots
in colab-environments, where there is a very small range of preinstalled
fonts. The package therefore automatically downloads fonts from
GoogleFonts. But I think everything should also work on your local
machine. Be aware though, that it’s not super well-tested, and might e.
g. fail with facets.

Installation
------------

::

   pip install opinionated

Usage
-----

The package is very simple to use, you just import it and set the style
you want:

::

   import opinionated
   plt.style.use("opinionated_rc")

Then you do your plotting:

::

   f, ax = plt.subplots(figsize=(10, 7))
   sns.scatterplot(x="bill_length_mm", y="flipper_length_mm", hue='species', data=penguins, s=100, alpha=0.9)

And finally, you can slap on some additional information, using some
convenience functions with reasonable defaults. Of course, the usual
ways of setting titles, legends, etc. still work.

::

   opinionated.add_legend(title='Species')
   opinionated.add_attribution('by Maximilian Noichl')
   opinionated.set_title_and_suptitle('Penguins!','They are an excellent type of bird!')

Here’s the result:

.. figure:: https://raw.githubusercontent.com/MNoichl/opinionated/master/img/opinionated_rc_example.png
   :alt: img



This certainly does look better than what the defaults would give you,
right? –

.. figure:: https://raw.githubusercontent.com/MNoichl/opinionated/master/img/outofthebox_penguins.png
   :alt: img

You can find more options, stylesheets, etc. in the github-repository!