semvec/pypi-packages huggingface dataset:
pastes 1.5.1.post1
Minimalistic Python client for pastes.dev
Requires Python: >=3.8
Keywords: paste, pastes, pastes.dev, code, pastebin, client, share, send

![pasters](https://raw.githubusercontent.com/RimMirK/pastes/main/.github/logo+name_pypi.png)

[![PyPI](https://img.shields.io/pypi/v/pastes?color=blue&label=PyPI)](https://pypi.org/project/pastes/)
[![Python](https://img.shields.io/pypi/pyversions/pastes.svg?logo=python&logoColor=yellow)](https://pypi.org/project/pastes/)
[![License](https://img.shields.io/github/license/RimMirK/pastes?color=green)](LICENSE)
[![StandWithUkraine](https://raw.githubusercontent.com/vshymanskyy/StandWithUkraine/main/badges/StandWithUkraine.svg)](https://github.com/vshymanskyy/StandWithUkraine/blob/main/docs/README.md)

Minimalistic Python client for [pastes.dev](https://pastes.dev/)
Share your code in seconds with a simple function call.  

---

## ✨ Features
- 🌀 Both **sync** and **async** APIs  
- ⚡ One-liner usage  
- 📤 Returns instant paste URL  
- 🐍 Pure Python, only requests and httpx are required

---

## 📦 Installation
```sh
pip install pastes
```

---

## ⚡ Usage

### 🔹 Sync

```py
from pastes import paste, get_paste, _set_api_url, _set_user_agent

# set custom API endpoint (optional)
_set_api_url("https://my-api.example.com")

# set custom user agent (optional)
_set_user_agent("My project/1.0.0")

code = """
def fib(n):
    a, b = 0, 1
    while a < n:
        print(a, end=' ')
        a, b = b, a+b
    print()
fib(1000)
"""

# create paste
url = paste(code)
print(url)  # https://pastes.dev/UUHlliP7SF

# fetch paste
print(get_paste(url))  # def fib(n): ...
```

### 🔹 Async

```py
from pastes import apaste, aget_paste, _set_api_url, _set_user_agent
import asyncio

# set custom API endpoint (optional)
_set_api_url("https://my-api.example.com")

# set custom user agent (optional)
_set_user_agent("My project/1.0.0")

code = """
def fib(n):
    a, b = 0, 1
    while a < n:
        print(a, end=' ')
        a, b = b, a+b
    print()
fib(1000)
"""

async def main():
    # create paste
    url = await apaste(code)
    print(url)  # https://pastes.dev/UUHlliP7SF

    # fetch paste
    text = await aget_paste(url)
    print(text) # def fib(n): ...

asyncio.run(main())
```

## 👨‍💻 Author

Made with ❤️ by [@RimMirK](https://t.me/RimMirK)
pytest-grader 0.1.4
Pytest extension for scoring programming assignments.
Requires Python: >=3.10

# pytest-grader

A pytest plugin for testing and scoring programming assignments.

## Features

- **Assignment Scoring**
  - Add point values to test functions using the `@points(n)` decorator
  - Show a score summary when running `pytest --score`
- **Test Locking** as described in Basu et al., *Automated Problem Clarification at Scale* ([abstract](https://dl.acm.org/doi/10.1145/2724660.2724679), [pdf](http://denero.org/content/pubs/las15_basu_unlocking.pdf))
  - Lock doctests using the `# LOCK` comment before the function.
  - `python3 pytest-grader --lock [src] [dest]` will generate a copy of src with doctests locked.
  - `pytest --unlock` provides an interactive interface for unlocking locked doctests.
- **Progress Logging**
  - Snapshots of assignment files, test case results, and unlocking attempts are stored in a `grader.sqlite`.
  - This file is designed to be submitted along with the assignment as a record of how the assignment was completed.

## Usage

Include a `conftest.py` file in the distribution of your assignment that contains `pytest_plugins = ["pytest_grader"]`.

See the `examples` directory for more usage info.

## License

A permissive license will be chosen shortly...

## Updating versions

- Change version in `pyproject.toml`
- `python -m build`
- `python -m twine upload dist/*`
topasio 1.1.2
Automation of (Open)TOPAS scripts, allowing for type inference and better access to parameters
Requires Python: >=3.10

This is a python wrapper around [OpenTOPAS](https://github.com/OpenTOPAS/OpenTOPAS), which is a tool for radiation transport simulation that itself wraps around [Geant4](https://geant4.web.cern.ch/).

The goal of this library is extend the Topas functionalities without forcing the user to rely on Geant. For example, this library implements python for-loops, conditionals, and all operations. It also extends functionalities by reducing the number of repeated code, implementing printing, and allowing interaction with the full python scientific computing suite. For example, one might have a single file that both launches a simulation and analyses its results, or even launches multiple simulations sequentially. 

For more details, see the wiki at https://gchristille.github.io/topasio
arches-orm 0.4.2
Representation of Arches graphs for client and server side manipulation
Requires Python: >=3.9

# (Unofficial) Arches ORM [EXPERIMENTAL]

This provides simple (server-side) access to Arches resources from Python
as Python objects. It makes no guarantees about efficiency or type-accuracy
but such issues raised will be addressed as far as possible.

## Installation

Basic installation can then happen as follows, _without_ Arches backend support:

```
pip install .
```

To run tests, make sure you have `libsqlite3-mod-spatialite`, or your distribution's equivalent
package for enabling Spatialite in Python. Instead of using a real Arches PostgreSQL database, we spin
a fresh test database up in memory.

**WARNING:** The mock DB behaviour for Python testing is not identical to a
real Arches database, but is adequately close for now, is fast and has no server dependency.

There are several sets of optional dependencies.

### GraphQL

Turns Arches ORM into an API server for Arches.

```
pip install .[graphql]
```

### Arches

Allows Arches ORM to directly manipulate the Arches database.

```
pip install .[arches]
```

### Test

Runs tests across the various backends.

```
pip install .[tests]
```

## Well-known Resource Models

To provide a partial boundary, this package expects a settings object called
`WELL_KNOWN_RESOURCE_MODELS` to list, at least, the models that should be
wrapped by this system.

It should be a list:

    WELL_KNOWN_RESOURCE_MODELS = [
        {
            "model_name": "Person",
            "graphid": "4110f743-1a44-11e9-9a37-000d3ab1e500",
            "nodes": {}, # optional additional configuration
            "to_string": lambda wkrm: str(wkrm) # optional callback for stringifying
        }
    ]

You must _not_ take this list as an exclusive boundary of data that can be accessed.

## Hooks

This package also contains experimental functionality for hooking tile saves,
so that client code can use the `MyModel.post_save` signal to get well-known
resource model events. To avoid any unintended overhead, it does not load
unless explicitly turned on with `arches_orm.add_hooks()`.

## Tests

Note that the tests require `spatialite` and so a Python that allows Sqlite3
extension loading:

    PYTHON_CONFIGURE_OPTS="--enable-loadable-sqlite-extensions" pyenv install 3.10.10

## Documentation

Documentation is available on [https://flaxandteal.github.io/arches-orm/](https://flaxandteal.github.io/arches-orm/).

## Thanks

Particular thanks to the funders of this work, and to the Arches community for
their work on which this builds. Particular thanks to Historic England's team
for the underlying resource models used in the test-cases.