semvec/pypi-packages huggingface dataset:
azdatalake 1.1.1
A package to implement a singleton for azure data storage gen2
Requires Python: >=3.8

---

# AZ Data Lake

## Instalación

```bash
pip3 install azdatalake
```

## Manual de uso
1. **Variables de Entorno**

| Variable | Tipo de dato |
|:-|-:|
|AZ_DATA_LAKE_STRING_CONNECTION|string|
|AZ_CONTAINNER_CLI|string|

2. **Funciones**:
   - **`upload_file(blob_name, data)`**: Este método permite subir un archivo a azure data storage gen2.
   - **`upsert_data_to_table(table_name, data)`**: Este método permite subir datos a una tabla de azure data storage gen2.
   - **`send_data_to_queue(queue_name, data)`**: Este método permite subir datos a una cola de azure data storage gen2.
   - **`get_messages_from_queue(queue_name, max_messages)`**: Este método permite obtener datos de una cola de azure data storage gen2.
   - **`get_table_data(table_name, partition_key, row_key)`**: Este método permite obtener datos de una tabla de azure data storage gen2.
   - **`get_all_table_data(table_name, partition_key, row_key)`**: Este método permite obtener una tabla de azure data storage gen2.
   - **`get_data_by_partition(table_name, partition_key, row_key)`**: Este método permite obtener los datos de una particion de una tabla de azure data storage gen2.
   - **`get_csv(blob_name)`**: Este método permite obtener datos de un csv de azure data storage gen2 y retorna un dataframe.

3. **Ejemplos de Uso**
```py
from azdatalake.singleton import AzDataLakeSingleton

# Crear instancia del singleton
az = AzDataLakeSingleton()

# Consultar datos de un csv
content = az.get_csv(blob_name="mis_datos.csv")
print(content)

# Subir un archivo
az.upload_file("local.csv", az.read_file_as_bytes("local.csv"))

# Consulta datos de una tabla
data = az.get_table_data("unitest3", "480217418839", 23)
print(data)

# actualizar datos de una tabla
az.upsert_data_to_table(table_name="unitest3", data=data)

# obtener tabla completa
data = az.get_all_table_data("alarmassolis")
print("tabla obtenidos: ")
print(data)


# obtener particion de tabla
data = az.get_data_by_partition("alarmassolis", "1298491919449258694_2025_01")
print("tabla obtenidos: ")
print(data)



```

---

By: Alan Medina ⚙️
hackatari 0.0.6
Extended Atari Learning Environments

# HackAtari

This repository relies on OCAtari, a fork of the OpenAI Gym Atari environment. 
The OCAtari repository can be found [here](https://github.com/k4ntz/OC_Atari).


## Installation
To install the OCAtari environment, please follow the instructions in the OCAtari repository,
or simply run the following command:
```bash
pip install ocatari
```
To install the hackatari environment, run 
```bash
pip install hackatari
```

or clone this repository and run the following command:
```bash
git clone https://github.com/k4ntz/HackAtari
cd HackAtari
pip install -e .
```

## Usage
To use the HackAtari environment, simply import it as you would any other OpenAI Gym environment:
You can run the `run.py` file to start the original game or any of the modified versions.
E.g.:
```python
python run.py -g Freeway # Starts normal Freeway (random agent)
python run.py -g Freeway -hu # Starts Freeway with the cars being invisible (interactive/human playing mode)
python run.py -g Freeway -m color8 # Starts Freeway with the cars of color #8 being (i.e. invisible) (random agent)
python run.py -g Freeway -m stop3 # Starts Freeway with stopping mode #3 (i.e. static cars) (random agent)
python run.py -g Seaquest -m oxygen disable_enemies gravity # Starts Seaquest with infinite oxygen, no enemy, gravity (random agent)
python run.py -g Kangaroo -m random_init disable_monkeys # Starts Kangaroo with random initial floor and no monkeys (random agent)
```

See [the documentation](https://hackatari.readthedocs.io/en/latest/)
or [this markdown file](modification_list.md) for more information on the available modifications.

## Cite our work
```bibtex
@article{delfosse2024hackatari,
  title={HackAtari: Atari Learning Environments for Robust and Continual Reinforcement Learning},
  author={Delfosse, Quentin and Bl{\"u}ml, Jannis and Gregori, Bjarne and Kersting, Kristian},
  journal={arXiv preprint arXiv:2406.03997},
  year={2024}
}
```