semvec/pypi-packages huggingface dataset:
yellowdog-python-examples 8.5.1
Python CLI commands using the YellowDog Python SDK
Requires Python: >=3.10

# Example Python CLI commands using the YellowDog Python SDK

## Overview

This is a set of Python CLI commands for interacting with the YellowDog Platform, providing examples of usage of the [YellowDog Python SDK](https://docs.yellowdog.ai/sdk/python/index.html).

The commands support:

- **Aborting** running Tasks with the **`yd-abort`** command
- **Boosting** Allowances with the **`yd-boost`** command
- **Cancelling** Work Requirements with the **`yd-cancel`** command
- **Comparing** whether worker pools are a match for task groups with the **`yd-compare`** command
- **Creating, Updating and Removing** Compute Source Templates, Compute Requirement Templates, Keyrings, Credentials, Storage Configurations, Image Families, Allowances, Configured Worker Pools, User Attributes, Namespace Policies, Groups, and Applications with the **`yd-create`** and **`yd-remove`** commands
- **Deleting** objects in the YellowDog Object Store with the **`yd-delete`** command
- **Downloading** Results from the YellowDog Object Store with the **`yd-download`** command
- **Finishing** Work Requirements with the **`yd-finish`** command
- **Following Event Streams** for Work Requirements, Worker Pools and Compute Requirements with the **`yd-follow`** command
- **Instantiating** Compute Requirements with the **`yd-instantiate`** command
- **Listing** YellowDog items using the **`yd-list`** command
- **Provisioning** Worker Pools with the **`yd-provision`** command
- **Resizing** Worker Pools and Compute Requirements with the **`yd-resize`** command
- **Showing** the details of any YellowDog entity using its YellowDog ID with the **`yd-show`** command
- **Showing** the details of the current Application with the **`yd-application`** command
- **Shutting Down** Worker Pools and Nodes with the **`yd-shutdown`** command
- **Starting** HELD Work Requirements and **Holding** (or pausing) RUNNING Work Requirements with the **`yd-start`** and **`yd-hold`** commands
- **Submitting** Work Requirements with the **`yd-submit`** command
- **Terminating** Compute Requirements with the **`yd-terminate`** command
- **Uploading** files to the YellowDog Object Store with the **`yd-upload`** command

Please see the documentation in the [GitHub repository](https://github.com/yellowdog/python-examples) for more details.
qcinput 0.1.0
Generate quantum chemistry input files from molecular structures
Requires Python: >=3.11
Keywords: cli, gaussian, orca, quantum-chemistry

# qcinput

`qcinput` is a CLI tool that reads an `xyz` geometry, loads task type and keywords
from TOML, and writes an ORCA or Gaussian input file.

## Install With pip

```bash
python -m pip install .
```

For development:

```bash
python -m pip install -e .
```

## Run With Nix

```bash
nix develop -c qcinput
```

Or run directly from the flake package:

```bash
nix run .
```

## Usage

```bash
qcinput generate <path/to/structure.xyz> [-c|--config <path/to/qcinput.toml>] [-o output.inp]
```

Compatibility shorthand (same behavior):

```bash
qcinput <path/to/structure.xyz> [-c|--config <path/to/qcinput.toml>] [-o output.inp]
```

First-time setup:

```bash
qcinput init-config
```

Default config path:

```text
./qcinput.toml
```

You can override this with:

```bash
QCINPUT_CONFIG=/path/to/config.toml qcinput water.xyz
```

Example:

```bash
qcinput water.xyz -c qcinput.toml -o water_opt.inp
```

When `qcinput.engine = "gaussian"`, default output suffix is `.gjf`.

## Config Format (TOML)

We use TOML because it is readable for humans, easy to version control, and strongly structured.

```toml
[qcinput]
engine = "orca" # or "gaussian"
kind = "int" # int | ts | sp

[molecule]
charge = 0
multiplicity = 1

[orca]
nprocs = 8
maxcore = 4000
base_keywords = ["r2scan-3c", "D4", "def2-mTZVPP"]

[orca.task.int]
keywords = ["Opt", "Freq"]

[orca.task.ts]
keywords = ["OptTS", "Freq"]

[orca.task.sp]
keywords = ["SP"]

[gaussian]
nprocshared = 8
mem = "8GB"
method_basis = "B3LYP/def2TZVP"

[gaussian.task.int]
route = ["Opt", "Freq"]

[gaussian.task.ts]
route = ["OptTS", "Freq"]

[gaussian.task.sp]
route = ["SP"]
```

## Output Snippet

```text
# Generated by qcinput from water.xyz
! Opt Freq r2scan-3c D4 def2-mTZVPP
%pal nprocs 8 end
%maxcore 4000
* xyz 0 1
O 0.000000 0.000000 0.000000
H 0.757000 0.586000 0.000000
H -0.757000 0.586000 0.000000
*
```