semvec/pypi-packages huggingface dataset:
garth 0.6.3
Garmin SSO auth + Connect client
License: MIT
Requires Python: >=3.10
Keywords: garmin, garmin api, garmin connect, garmin sso

# Garth

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Garmin SSO auth + Connect Python client

## Features

- OAuth1/OAuth2 authentication (OAuth1 token lasts ~1 year)
- MFA support with custom handlers
- Auto-refresh of OAuth2 token
- Auto-resume from `GARTH_HOME` or `GARTH_TOKEN` environment variables
- Works on Google Colab
- Pydantic dataclasses for validated data
- Full test coverage

## Installation

```bash
pip install garth
```

## Quick Start

### Authenticate and save session

```python
import garth
from getpass import getpass

garth.login(input("Email: "), getpass("Password: "))
garth.save("~/.garth")
```

### Resume session

```python
import garth
from garth.exc import GarthException

garth.resume("~/.garth")
try:
    garth.client.username
except GarthException:
    # Session is expired. You'll need to log in again
    pass
```

Or use environment variables for automatic session restoration:

```bash
export GARTH_HOME=~/.garth
# or
export GARTH_TOKEN="eyJvYXV0aF90b2tlbi..."  # from `uvx garth login`
```

```python
import garth
# Session is automatically loaded
garth.client.username
```

### Fetch data

```python
# Get daily stress
garth.DailyStress.list("2023-07-23", 7)

# Get sleep data
garth.SleepData.get("2023-07-20")

# Get weight
garth.WeightData.list("2025-06-01", 30)

# Direct API calls
garth.connectapi("/usersummary-service/stats/stress/weekly/2023-07-05/52")
```

## Documentation

Full documentation at **[garth.readthedocs.io](https://garth.readthedocs.io)**

## MCP Server

[`garth-mcp-server`](https://github.com/matin/garth-mcp-server) is in early development.

To generate your `GARTH_TOKEN`, use `uvx garth login`.

## Star History

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biblium 2.13.1
Comprehensive Python library for bibliometric analysis of scientific literature
License: MIT
Requires Python: >=3.9
Keywords: bibliometrics, scientometrics, citation analysis, scopus, web of science, openalex, pubmed, network analysis, topic modeling

\# Biblium



Comprehensive Python library for bibliometric analysis of scientific literature.



\## Installation

```

pip install biblium

```



\## Features



\- Multi-database support: Scopus, Web of Science, OpenAlex

\- Citation analysis, network analysis, visualization

\- Group analysis with statistical associations

\- GUI application for interactive analysis