semvec/pypi-packages huggingface dataset:
iLibrary 0.0.14
iLibrary - Tools for IBM i library
Requires Python: >=3.6

# iLibrary

A lightweight Python helper for working with IBM i (AS/400) libraries. It connects via ODBC (pyodbc) for DB2/SQL queries and uses Paramiko for SSH/SFTP to save and transfer library save files (SAVF).

[![PyPI Downloads](https://static.pepy.tech/personalized-badge/ilibrary?period=total&units=INTERNATIONAL_SYSTEM&left_color=BLACK&right_color=MAGENTA&left_text=downloads)](https://pepy.tech/projects/ilibrary)

Overview
- Query library metadata using QSYS2 services
- List objects in a library (and optionally source physical files)
- Create a save file (SAVF) for a library via SAVLIB and optionally download it
- Remove save files
- Simple context manager to handle DB connection lifecycle

Requirements
- Python 3.8+
- IBM i system access
- IBM i Access ODBC Driver (or compatible) installed locally
- Network access to the IBM i for ODBC and SSH/SFTP

Installation
- From PyPI: `pip install iLibrary`
- From source:
  - Clone the repo
  - Optionally create and activate a virtual environment
  - pip install -r requirements.txt
  - pip install -e .

Quickstart
```python
from os.path import join, dirname
import os
from dotenv import load_dotenv
from iLibrary import Library

# Load ENV file and get the connection settings
dotenv_path = join(dirname(__file__), '.env')
load_dotenv(dotenv_path)
DB_DRIVER = os.environ.get("DB_DRIVER")
DB_USER = os.environ.get("DB_USER")
DB_PASSWORD = os.environ.get("DB_PASSWORD")
DB_SYSTEM = os.environ.get("DB_SYSTEM")

with Library(DB_USER, DB_PASSWORD, DB_SYSTEM, DB_DRIVER) as lib:
    print(lib.getLibraryInfo('QGPL', wantJson=True))
    print(lib.getFileInfo('QGPL'))
```

Save a library to SAVF and optionally download it
```python
from os.path import dirname

with Library(DB_USER, DB_PASSWORD, DB_SYSTEM, DB_DRIVER) as lib:
    ok = lib.saveLibrary(
        library='MYLIB',
        saveFileName='MYLIBSAVE',
        description='Backup',
        localPath=dirname(__file__),
        remPath='/home/MYUSER/',
        getZip=True
    )
    print('Saved:', ok)
```

API overview
- Library(db_user, db_password, db_host, db_driver)
  - __enter__ / __exit__ for connection lifecycle
  - iclose(): manually close the connection
- getLibraryInfo(library: str, wantJson: bool = True) -> str | tuple
- getFileInfo(library: str, qFiles: bool = False) -> str
- saveLibrary(library: str, saveFileName: str, ..., getZip: bool = False, ...) -> bool
- removeFile(library: str, saveFileName: str) -> bool

Configuration
- Environment variables expected:
  - DB_DRIVER: e.g. {IBM i Access ODBC Driver}
  - DB_USER
  - DB_PASSWORD
  - DB_SYSTEM

Documentation
- Installation guide: [[docs/installation.md]]
- Usage examples: [[docs/usage.md]]
- Full API reference: [[docs/api.md]]
- Troubleshooting: [[docs/troubleshooting.md]]

Contributing
- Please run tests or the sample script before submitting changes.

License
- See the repository license file if present.
agentverse-client 0.1.12
A set of API clients to easily integrate to Featch AI services.
Requires Python: >=3.9

# List of available clients

| Name            | Description                                                                 | README                                                                                                             |
|-----------------|-----------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------|
| search (sync)   | Search engine that provides the agent that best fits your needs.            | [LINK](https://github.com/fetchai/api-clients/blob/main/agentverse-client/agentverse_client/search_README.md)      |
| search (async)  | Search engine that provides the agent that best fits your needs.            | [LINK](https://github.com/fetchai/api-clients/blob/main/agentverse-client/agentverse_client/aio_search_README.md)  |
| almanac (sync)  | The Almanac is a smart contract developed and deployed on the Fetch.ai blockchain | [LINK](https://github.com/fetchai/api-clients/blob/main/agentverse-client/agentverse_client/almanac_README.md)     |                                                                                        
| almanac (async) | The Almanac is a smart contract developed and deployed on the Fetch.ai blockchain | [LINK](https://github.com/fetchai/api-clients/blob/main/agentverse-client/agentverse_client/aio_almanac_README.md) |
chem-dcat-ap 0.1.0rc2
An extension of the DCAT Application Profile extended to provide chemistry specific specific metadata for datasets.
Requires Python: <4.0,>=3.9

# Chem-DCAT-AP

Extension of the DCAT Application Profile (DCAT-AP) tailored for chemistry-related data.  
It adds links to use-case specific context and enables describing:

- chemical datasets (e.g. spectra, chromatograms, assay results)
- related samples, substances and instruments
- provenance, experimental conditions and other domain-specific metadata

From the LinkML schemas in `src/chem_dcat_ap/schema/*.yaml`, two Python datamodel variants are generated:

- A variant based on Python `dataclasses`
- A variant based on Pydantic models

## Installation

```powershell
pip install chem-dcat-ap
```

Requires Python >= 3.9, < 4.0.

## Quick start

The package exposes the generated classes that correspond to the entities defined in the
`src/chem_dcat_ap/schema/*.yaml` LinkML schemas.

```python
import chem_dcat_ap
from chem_dcat_ap.datamodel.chem_dcat_ap import Dataset, DataGeneratingActivity

print(chem_dcat_ap.__version__)

dataset = Dataset(
    id="https://example.org/dataset/chem-001",
    title="Example chemical dataset",
    description="Minimal example dataset following the Chem-DCAT-AP schema.",
    was_generated_by=DataGeneratingActivity(
        id="https://example.org/activity/chem-001"
    ),
)

print(dataset)
```

For details about all available classes and fields, inspect the schema YAML files in
`src/chem_dcat_ap/schema/` and the generated module `chem_dcat_ap.datamodel.chem_dcat_ap`.

## Documentation

- Project docs and schema reference: <https://nfdi-de.github.io/dcat-ap-plus>
- Source code: <https://github.com/nfdi-de/chem-dcat-ap>

## License

MIT License. See the bundled `LICENSE` file for details.