semvec/pypi-packages huggingface dataset:
toposkg 0.3.2
A Python interface to the ToposKG knowledge graph generation pipeline.
License: MIT
Requires Python: >=3.10

<div align="center">
  <h1>toposkg-lib</h1>
</div>

<div align="center">
  A Python library for Knowledge Graph customization and expansion.
</div>

## Overview
toposkg-lib is a Python library developed as part of the Topos framework. It provides easy access to powerful functionality for customizing and extending ToposKG but is also compatible with arbitrary source files.

## Highlights
- **Powerful features.** Customize and expand ToposKG using powerful tools for geospatial interlinking, toponym translation and entity linking.
- **Ease of use.** toposkg-lib is designed around a simple builder pattern, simplifying the process of generating your Knowledge Graph.
- **Natural Language Interface.** toposkg-lib can be used with a textual interface, powered by LLM function calling.
- **Active development.** toposkg-lib will keep getting updates as we work on our projects.

## Repository contents
- `examples/`: Additional data, used in examples.
- `notebooks/`: Jupyter Notebooks that showcase the functionality of the library.
- `toposkg/`: The source code. Some files contain `main` functions that also include examples of use.

## Getting Started

### pip

We recommend using toposkg-lib through [pip](https://pypi.org/project/toposkg/).

```sh
pip install toposkg
```

If you want to include the translation functionality.

```sh
pip install toposkg[tl]
```

If you want to include the function calling functionality.

```sh
pip install toposkg[fc]
```

We recommend that you install this custom version of RDF-lib before using toposkg-lib.

```sh
pip install git+https://github.com/SKefalidis/rdflib-speed@main
```

Otherwise you can use the original rdflib.

### Simple example

```python
from toposkg.toposkg_lib_core import KnowledgeGraphBlueprintBuilder, KnowledgeGraphSourcesManager

# Create a KnowledgeGraphSourcesManager object to load the available data sources and their metadata
sources_manager = KnowledgeGraphSourcesManager(['PATH_TO_YOUR_SOURCES'])

# See the available data sources
sources_manager.print_available_data_sources()

# Create a KnowledgeGraphBlueprintBuilder object to build the knowledge graph blueprint
builder = KnowledgeGraphBlueprintBuilder()

builder.set_name("ToposKG.nt")
builder.set_output_dir("/home/example/")

builder.add_source_path("PATH_TO_KG_SOURCE_1") # relative or absolute path
builder.add_source_path("PATH_TO_KG_SOURCE_2")

# Use the blueprint to construct the knowledge graph
blueprint = builder.build()
blueprint.construct()
```

### Advanced Examples

Explore advanced functionality with our interactive Google Colab notebooks:

- 🚀 **[Quickstart Notebook](https://colab.research.google.com/drive/1mv0YYDcd_zWzl1IC7jgxHERwdiHo6I-4?usp=sharing)**  

A fast introduction to the capabilities of toposkg-lib.

- 🤖 **[Chatbot Notebook](https://colab.research.google.com/drive/1A1F23tJUbGlIsLPEXaNi8lK9Y5zYOS0F?usp=sharing)**

Our LLM-based chatbot that utilizes toposkg-lib, in action.
bitquery-corecast-proto 1.0.3
gRPC protobuf definitions and generated Python code for Bitquery CoreCast Solana gRPC
License: MIT
Requires Python: >=3.8

# bitquery-corecast-proto

A Python package containing gRPC protobuf definitions and generated Python code for Bitquery CoreCast Solana gRPC.

## Installation

```bash
pip install bitquery-corecast-proto
```

## Quick Start

```python
import grpc
from bitquery_corecast_proto import corecast_pb2, corecast_pb2_grpc
from bitquery_corecast_proto import stream_message_pb2

# Import Solana protobuf definitions
from solana import token_block_message_pb2, dex_block_message_pb2

# Create gRPC channel and stub
channel = grpc.insecure_channel('localhost:50051')
stub = corecast_pb2_grpc.CoreCastStub(channel)

# Make gRPC calls
request = corecast_pb2.StreamRequest()
response = stub.StreamMessages(request)
```

## Available Modules

- `bitquery_corecast_proto.corecast_pb2` - Core request/response messages
- `bitquery_corecast_proto.corecast_pb2_grpc` - gRPC service stubs
- `bitquery_corecast_proto.stream_message_pb2` - Stream message definitions
- `bitquery_corecast_proto.request_pb2` - Request message definitions

## Solana Dependencies

This package automatically installs `bitquery-pb2-kafka-package` which provides:
- `solana.token_block_message_pb2` - Token block messages
- `solana.dex_block_message_pb2` - DEX block messages
- `solana.parsed_idl_block_message_pb2` - Parsed IDL block messages
- `solana.block_message_pb2` - Block messages

## Requirements

- Python 3.8+
- grpcio>=1.60.0
- grpcio-tools>=1.60.0
- protobuf>=6.30.0,<7.0.0
- bitquery-pb2-kafka-package

## License

MIT License - see LICENSE file for details.
redis-namespace-client 0.1.2
A simple Redis client for Python with support for: namespacing and JSON serialization/deserialization, designed for middleware applications.
License: MIT
Requires Python: >=3.7

# redis-namespace-client

A simple Redis client for Python with support for:

- Namespacing
- JSON serialization
- Expiry (TTL)
- Logging
- `.env` support via `python-dotenv`

## Installation

```bash
pip install redis-namespace-client
````

## Usage

```python
from redis_namespace_client import redis_set, redis_get

# Set a key
redis_set("mykey", {"foo": "bar"}, ex=3600)

# Get the key
value = redis_get("mykey")
print(value)
```

## Environment Variables

Create a `.env` file or export these:

```env
REDIS_ERP_HOST=localhost
REDIS_ERP_PORT=6379
REDIS_ERP_DB=3
REDIS_ERP_NAMESPACE=my_namespace
```

````

Enjoy
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