semvec/pypi-packages huggingface dataset:
markdown_code_exec 0.3.0
Executes Python code in Markdown files and captures the output
Requires Python: >=3.5

# markdown_code_exec

*Execute Python code in Markdown files and captures the output*

Copyright 2022 Sebastiaan Mathôt

## Command-line usage

usage: markdown_code_exec.py [-h] [-i INPUT] [-o OUTPUT]

optional arguments:
  -h, --help            show this help message and exit
  -i INPUT, --input INPUT
                        input markdown file
  -o OUTPUT, --output OUTPUT
                        output markdown file


## Function reference

**<span style="color:purple">markdown&#95;code&#95;exec.parse&#95;text</span>_(md)_**


Takes a `str` containing markdown text, finds code blocks in the
markdown, executes these code blocks and captures the output, and then
embeds the captured output in the markdown.


#### Parameters
* md: str :  The input markdown string

#### Returns
<b><i>str</i></b>  The compiled markdown string



**<span style="color:purple">markdown&#95;code&#95;exec.parse&#95;file</span>_(src, dst)_**


Takes a markdown input file, executes code blocks while capturing output
and writes the result to a new output file.


src: str
    The full path to the input file
dst: str
    The full path to the output file

## License

GNU General Public License 3
iron-worker 1.3.8
The Python client for IronWorker, a cloud service for background processing.
Keywords: iron,ironio,iron.io,iron-io,ironworker,iron-worker,iron_worker,worker,cloud,task queue,background processing

IronWorker Python Library
-------------------------

This package offers a client interface to the Iron.io IronWorker service. It 
offers a full, native interface to the IronWorker API, including creating 
and uploading code package, queuing and scheduling tasks, viewing task logs, 
and more.

IronWorker is a background processing and task queuing system that lets your 
applications use the cloud to do their heavy lifting. Find out more at 
http://www.iron.io/products/worker.
env-fields 0.2.0
Awesome env_fields created by dvvolynkin

---
# env_fields

[![codecov](https://codecov.io/gh/dvvolynkin/env-fields/branch/main/graph/badge.svg?token=env-fields_token_here)](https://codecov.io/gh/dvvolynkin/env-fields)
[![CI](https://github.com/dvvolynkin/env-fields/actions/workflows/main.yml/badge.svg)](https://github.com/dvvolynkin/env-fields/actions/workflows/main.yml)

Dataclass fields with getting values from environment by default

## Install it from PyPI

```bash
pip install env_fields
```

## Usage

```python
import os
from dataclasses import field, dataclass
from env_fields import (
    env_field_int,
    env_field_str,
    env_field,
)


@dataclass
class SomeClass:
    attribute_1: int = field()
    attribute_2: int = env_field_int('SOME_INT_ENVIRONMENT_VARIABLE')
    attribute_3: str = env_field_str('SOME_STR_ENVIRONMENT_VARIABLE')
    attribute_4: str = env_field_str(
        'SOME_STR_ENVIRONMENT_VARIABLE_THAT_NOT_SET',
        default="hello, world"
    )
    attribute_5: int = env_field("SOME_CUSTOM_TYPE_ENV_VARIABLE", float, init=False)

```
Let's create some dataclass!
```python
>>> os.environ['SOME_INT_ENVIRONMENT_VARIABLE'] = "1234"
>>> os.environ['SOME_STR_ENVIRONMENT_VARIABLE'] = "hello, world 1"
>>> os.environ['SOME_CUSTOM_TYPE_ENV_VARIABLE'] = "2.59"
>>> SomeClass(12)
SomeClass(
    attribute_1=12,
    attribute_2=1234,
    attribute_3='hello, world 1',
    attribute_4='hello, world',
    attribute_5=2.59,
)
```


## Development

Read the [CONTRIBUTING.md](CONTRIBUTING.md) file.
pyUsmap 1.1.3
.usmap file reader

# pyUsmap
.usmap reader

[![pypi](https://img.shields.io/pypi/v/pyusmap.svg)](https://pypi.python.org/pypi/pyusmap/)
[![Downloads](https://pepy.tech/badge/pyusmap)](https://pepy.tech/project/pyusmap)

# Installation
`pip install pyUsmap`

# Usages
```py
from Usmap import Usmap
import json

with open("xyz.usmap", "rb") as f:
    data = Usmap(f).read()

# from bytes or byte array
import io

data = Usmap(io.BytesIO(b'')).read()

# writing to json
jsondict = data.GetValue() # get json serializable dict
with open("Mappings.json", "w") as f:
    json.dump(jsondict, f, indent=4)


```
# Requirements

* Python 3
* Brotli