semvec/pypi-packages huggingface dataset:
MinexPy 0.1.2
A python toolkit for geoscience researchers and students
License: MIT
Requires Python: >=3.8
Keywords: geoscience, geochemistry, geology, statistics, mining, exploration

# MinexPy

MinexPy is a practical toolkit for geoscience researchers and students who are learning how to solve real geoscientific problems with Python—or who want a deeper, more structured understanding of which Python tools fit which geoscience tasks.

Even though modern AI tools can help you prototype quickly, it’s still hard for beginners to answer questions like:

- Which library should I use for this exact problem?
- What’s the “standard” workflow in geoscience when using Python?
- How do I discover reliable tools without getting lost in hundreds of packages?

MinexPy aims to reduce that confusion by providing curated, beginner-friendly building blocks and sensible combinations of widely-used libraries, so you can focus more on the science and less on setup and guesswork.

---

## Installation

Install with pip:

```bash
pip install minexpy
```

---

## How to use

MinexPy provides both a Python API and a command-line interface.

### Python API

Like most Python packages, you install it and import what you need:

```python
import minexpy.stats as mstats
from minexpy import (
    StatisticalAnalyzer,
    describe,
    pearson_correlation,
    spearman_correlation,
    plot_histogram,
)
```

### Example: Correlation + Visualization

```python
import numpy as np
from minexpy.correlation import pearson_correlation, spearman_correlation
from minexpy.statviz import plot_histogram

zn = np.array([45.2, 52.3, 38.7, 61.2, 49.8, 55.1])
cu = np.array([12.5, 15.3, 11.2, 18.4, 14.1, 16.0])

print(pearson_correlation(zn, cu))
print(spearman_correlation(zn, cu))

fig, ax = plot_histogram(zn, bins=10, scale="linear", xlabel="Zn (ppm)")
```

### Command-Line Interface

After installation, use the `minexpy` command for quick access to documentation and examples:

```bash
# Show help and available functions
minexpy

# Show practical code examples you can copy
minexpy demo

# Open documentation in browser
minexpy docs

# Show package information
minexpy info
```

Documentation and examples will expand over time as modules are added.

---

## Roadmap / TODO

Want to contribute? Here are some high-impact areas to work on:

- Mapping module for geological, geochemical, and geophysical data

- Interpolation methods commonly used in geosciences (e.g., minimum curvature, triangulation, and others)

- AOI extraction from large satellite imagery (selecting/cropping a region of interest from big scenes)

---

## Contributing

Contributions are welcome—especially examples, notebooks/markdown tutorials, and new modules that follow the project’s goals:

- beginner-friendly

- practical workflows

- clear and detailed documentation using NumPy's docstrings guidelines
autogen-paylobster 0.1.0
AutoGen integration for PayLobster - AI agent payment escrow on Base
License: MIT
Requires Python: >=3.9
Keywords: ai-agents, autogen, crypto, escrow, paylobster, web3

# autogen-paylobster

AutoGen integration for PayLobster - AI agent payment escrow on Base.

## Installation

```bash
pip install autogen-paylobster
```

## Quick Start

```python
import autogen
from autogen_paylobster import get_function_map, get_function_specs

# Configure LLM
config_list = [{"model": "gpt-4", "api_key": "your-openai-key"}]

# Create an AutoGen agent with PayLobster functions
assistant = autogen.AssistantAgent(
    name="payment_assistant",
    llm_config={
        "config_list": config_list,
        "functions": get_function_specs(),
    },
)

# Create user proxy that can execute functions
user_proxy = autogen.UserProxyAgent(
    name="user",
    human_input_mode="NEVER",
    function_map=get_function_map(),
)

# Start conversation
user_proxy.initiate_chat(
    assistant,
    message="Check the reputation of agent 0x742d35Cc6634C0532925a3b844Bc9e7595f0bEb"
)
```

## Available Functions

### create_escrow
Create a payment escrow that locks USDC funds until work is completed.

### release_escrow
Release payment to the worker after work is completed.

### check_reputation
Check an agent's reputation score and task history.

### register_agent
Register your agent on the PayLobster identity system.

### get_balance
Check USDC balance of any address on Base.

## Helper Functions

### get_function_map()
Returns a dictionary mapping function names to their implementations. Pass this to AutoGen's `function_map` parameter.

### get_function_specs()
Returns OpenAI function specifications. Pass this to AutoGen's `llm_config["functions"]` parameter.

## Example: Negotiating Agents

See `examples/negotiating_agents.py` for a complete example with:
- Two agents negotiating payment terms
- Automatic reputation checking
- Escrow creation and release workflow
- Multi-agent conversation handling payments

## Contract Addresses (Base Mainnet)

- **Identity**: `0xA174ee274F870631B3c330a85EBCad74120BE662`
- **Reputation**: `0x02bb4132a86134684976E2a52E43D59D89E64b29`
- **Escrow**: `0x703B528C1b07cd27992af9Ae11DD67bE685E489e`
- **Credit**: `0x4c22B52eacAB9eD2Ce018d032739a93eC68eD27a`
- **USDC**: `0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913`

## Security

**⚠️ Never hardcode private keys in production!** Use environment variables:

```python
import os
private_key = os.environ.get("AGENT_PRIVATE_KEY")
```

## License

MIT
crewai-paylobster 0.1.0
CrewAI integration for PayLobster - AI agent payment escrow on Base
License: MIT
Requires Python: >=3.9
Keywords: ai-agents, crewai, crypto, escrow, paylobster, web3

# crewai-paylobster

CrewAI integration for PayLobster - AI agent payment escrow on Base.

## Installation

```bash
pip install crewai-paylobster
```

## Quick Start

```python
from crewai import Agent, Task, Crew
from crewai_paylobster import (
    create_escrow_tool,
    release_escrow_tool,
    check_reputation_tool,
    register_agent_tool,
    get_balance_tool,
)

# Create a Payment Agent with PayLobster tools
payment_agent = Agent(
    role="Payment Manager",
    goal="Handle secure escrow payments for AI agent work",
    backstory="""You are an expert at managing cryptocurrency payments.
    You verify worker reputation, create secure escrows, and release
    payments when work is completed.""",
    tools=[
        create_escrow_tool,
        release_escrow_tool,
        check_reputation_tool,
        get_balance_tool,
    ],
    verbose=True,
)

# Create a task
payment_task = Task(
    description="""Check the reputation of worker 0x742d35Cc6634C0532925a3b844Bc9e7595f0bEb.
    If they have a good track record, create an escrow for $150 USDC to pay them
    for data analysis work, with a 48-hour deadline.""",
    agent=payment_agent,
    expected_output="Confirmation that reputation was checked and escrow was created",
)

# Create crew and run
crew = Crew(agents=[payment_agent], tasks=[payment_task])
result = crew.kickoff()
print(result)
```

## Available Tools

### create_escrow_tool
Create a payment escrow that locks USDC funds until work is completed.

### release_escrow_tool
Release payment to the worker after work is completed.

### check_reputation_tool
Check an agent's reputation score and task history.

### register_agent_tool
Register your agent on the PayLobster identity system.

### get_balance_tool
Check USDC balance of any address on Base.

## Example: Payment Crew

See `examples/payment_crew.py` for a complete example with:
- A Payment Manager agent that handles all escrow operations
- A Negotiator agent that discusses terms with workers
- Coordination between agents for complete payment workflows

## Contract Addresses (Base Mainnet)

- **Identity**: `0xA174ee274F870631B3c330a85EBCad74120BE662`
- **Reputation**: `0x02bb4132a86134684976E2a52E43D59D89E64b29`
- **Escrow**: `0x703B528C1b07cd27992af9Ae11DD67bE685E489e`
- **Credit**: `0x4c22B52eacAB9eD2Ce018d032739a93eC68eD27a`
- **USDC**: `0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913`

## Security

**⚠️ Never hardcode private keys in production!** Use environment variables:

```python
import os
private_key = os.environ.get("AGENT_PRIVATE_KEY")
```

## License

MIT
langchain-paylobster 0.1.0
LangChain integration for PayLobster - AI agent payment escrow on Base
License: MIT
Requires Python: >=3.9
Keywords: ai-agents, crypto, escrow, langchain, paylobster, web3

# langchain-paylobster

LangChain integration for PayLobster - AI agent payment escrow on Base.

## Installation

```bash
pip install langchain-paylobster
```

## Quick Start

```python
from langchain_paylobster import (
    PayLobsterCreateEscrow,
    PayLobsterReleaseEscrow,
    PayLobsterCheckReputation,
    PayLobsterRegisterAgent,
    PayLobsterGetBalance,
)
from langchain.agents import initialize_agent, AgentType
from langchain_openai import ChatOpenAI

# Initialize tools
tools = [
    PayLobsterCreateEscrow(),
    PayLobsterReleaseEscrow(),
    PayLobsterCheckReputation(),
    PayLobsterRegisterAgent(),
    PayLobsterGetBalance(),
]

# Create agent
llm = ChatOpenAI(temperature=0, model="gpt-4")
agent = initialize_agent(
    tools, 
    llm, 
    agent=AgentType.OPENAI_FUNCTIONS, 
    verbose=True
)

# Use the agent
response = agent.run(
    "Check the reputation of agent 0x742d35Cc6634C0532925a3b844Bc9e7595f0bEb"
)
print(response)
```

## Available Tools

### PayLobsterCreateEscrow
Create a payment escrow that locks USDC funds until work is completed.

**Parameters:**
- `worker_address`: Ethereum address of the worker
- `amount_usdc`: Amount in USDC (e.g., 100.50)
- `deadline_hours`: Hours until deadline (default: 24)
- `description`: Description of the work
- `private_key`: Your private key (client)

### PayLobsterReleaseEscrow
Release payment to the worker after work is completed.

**Parameters:**
- `escrow_id`: ID of the escrow to release
- `private_key`: Your private key (must be the client)

### PayLobsterCheckReputation
Check an agent's reputation score and task history.

**Parameters:**
- `agent_address`: Ethereum address of the agent

### PayLobsterRegisterAgent
Register your agent on the PayLobster identity system.

**Parameters:**
- `metadata`: JSON string with agent info (capabilities, contact, etc.)
- `private_key`: Your agent's private key

### PayLobsterGetBalance
Check USDC balance of any address on Base.

**Parameters:**
- `address`: Ethereum address to check

## Example: Negotiating Agent

See `examples/negotiating_agent.py` for a complete example of an agent that can:
- Negotiate work terms
- Create escrow for agreed payment
- Track reputation of potential workers
- Release payment upon completion

## Contract Addresses (Base Mainnet)

- **Identity**: `0xA174ee274F870631B3c330a85EBCad74120BE662`
- **Reputation**: `0x02bb4132a86134684976E2a52E43D59D89E64b29`
- **Escrow**: `0x703B528C1b07cd27992af9Ae11DD67bE685E489e`
- **Credit**: `0x4c22B52eacAB9eD2Ce018d032739a93eC68eD27a`
- **USDC**: `0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913`

## Security

**⚠️ Never hardcode private keys in production!** Use environment variables or secure key management:

```python
import os
private_key = os.environ.get("AGENT_PRIVATE_KEY")
```

## License

MIT