semvec/pypi-packages huggingface dataset:
PyMakTub 0.1.2
A Procedural Generation Python Lib
Requires Python: >=3.6

# PyMaktube
a Python Library for Procedural Pseudo Randon Generation

### Instalation from pip
```shel 
pip install PyMakTub
```

### Instalation from github

```shel 
pip install git+https://github.com/OUIsolutions/PyMaktube

```




### Quick Usage 
For making anything on Maktub , first you need to setup a seed, than you can generate
numbers, itens ,choices , etc

### Generating a Number
```py
from PyMaktube.MakTub import MakTub

r = MakTub("your seed here")
print(r.generate_num(0,100))

```

### Generating a Choice 

```py 
from PyMaktube.MakTub import MakTub

r = MakTub("your seed here")
names = ["Mateus","Samuel","Danilo"]
print(r.choice(names))

```
### Generating tokens 

```py
from PyMaktube.MakTub import MakTub
r = MakTub("your seed here")
size = 10
valid_chars = "ABCDEF"
print(r.generate_token(size,valid_chars))

```

### Probabilitys 
```py
from PyMaktube.MakTub import MakTub
r = MakTub("your seed here")
p = r.new_probability()
a = p.add_probability(0.33)
b = p.add_probability(0.33)
c = p.add_probability(0.33)
result = p.perform()
if a  == result:
    print("generated A")
if b == result:
    print("generated B")
if c == result:
    print("generated C")
```

### Multiple Generations 
you can generate any itens you want with the same seed 

```py 
from PyMaktube.MakTub import MakTub

r = MakTub("your seed here")

for i in range(0,100):
    print(r.generate_num(0,100))

```

### skping generation 
you also can skip genrations easly 

```py
from PyMaktube.MakTub import MakTub

r = MakTub("your seed here")
r.set_generation(5)# will skip the first 5
for i in range(0,100):
    print(r.generate_num(0,100))
print("generation ",r.get_generation())

```
### Modifiyng the Seed 
its possible to modify the seed , to test diferent results
```py 

from PyMaktube.MakTub import MakTub

r = MakTub("your seed here")
for i in range(0,10):
    r.set_seed(f'test {i}')
    print(r.generate_token())

```

### Making randon seed modifications 

```py


from PyMaktube.MakTub import MakTub
from PyMaktube.MakTubSeqs import MakTubSeqs
r = MakTub("your seed here")
for i in range(0,10):
    r.aply_seed_modification([0,1,2],MakTubSeqs.ALFHA_NUNS)#will modfiy the first 3 chars
    print(r.get_seed())

```
cdef-utils 2.8.0
Utility for converting CSV to Parquet files
Requires Python: >=3.8

# cdef-utils

cdef-utils is a Python package designed to convert CSV and Parquet files to a standardized Parquet format, specifically tailored for processing register data. It provides utilities for batch processing files, generating summaries, and handling various encoding issues.

## Features

- Convert CSV and Parquet files to a standardized Parquet format
- Automatic encoding detection for CSV files
- Batch processing of multiple files
- Generation of summary reports
- Progress tracking and resumable processing
- Rich console output with logging

## Installation

To install cdef-utils, you can use pip:

```
pip install cdef-utils
```

## Usage

You can use cdef-utils as a command-line tool:

```
python -m cdef_utils /path/to/input/directory --summary_file output_summary.json
```

### Arguments

- `input_directory`: Path to the directory containing CSV and Parquet files to process
- `--summary_file`: (Optional) Path to save the summary JSON file (default: "register_summary.json")

## Output

The script will:

1. Convert all CSV and Parquet files in the input directory to Parquet format
2. Save the converted files in a structured directory format under `/path/to/your/fixed/output/directory/registers`
3. Generate a summary JSON file with details about each processed register
4. Display a summary table in the console
5. Log processing details and any errors

## Requirements

- Python 3.7+
- polars
- rich

## Configuration

- The `OUTPUT_DIRECTORY` is set to `/path/to/your/fixed/output/directory` in the script. Modify this path as needed.
- Logging is configured to save logs in a `logs` directory in the current working directory.

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## License

This project is licensed under the MIT License.
zosedit 0.0.15
FTP-based MVS Dataset Editor
Keywords: editor, z/OS, MVS, dataset, FTP

# z/OS Edit

This GUI application provides a way to browse/edit datasets on z/OS as well as read job output from JES2.

## Installation

`pip install zosedit`

## Usage

Once installed with Pip, to run the application, simply type `zosedit` in your terminal.