semvec/pypi-packages huggingface dataset:
solarchive 0.0.1
Python SDK for accessing Solana blockchain data from solarchive.org - free Parquet datasets of transactions, accounts, and tokens
Requires Python: >=3.11
Keywords: archive, blockchain, crypto, data, parquet, solana, web3

# solarchive

Python SDK for accessing Solana blockchain data from [solarchive.org](https://solarchive.org).

**solarchive** is a project to archive Solana's public transaction data and make it freely accessible in ergonomic formats (Apache Parquet) for developers, researchers, and the entire Solana community.

## Features

- Download Solana transaction, account, and token data in Parquet format
- Access historical data from 2020 to present
- No API keys or rate limits - direct HTTP access to data files
- Query data with DuckDB, pandas, Spark, or any Parquet-compatible tool
- Browse available datasets via index files
- Licensed under CC-BY-4.0

## Installation

```bash
pip install solarchive
```

## Usage

```python
from solarchive import SolArchive

# Initialize the client
client = SolArchive()

# List available transaction dates
dates = client.list_transaction_dates()
print(f"Available dates: {dates[:5]}...")

# Get index for a specific date
index = client.get_transaction_index("2025-11-01")
print(f"Files available: {len(index['files'])}")

# Download transaction data for a date
# Downloads all Parquet files for that date
client.download_transactions("2025-11-01", output_dir="./data/txs")

# Get account snapshots for a month
client.download_accounts("2025-12", output_dir="./data/accounts")

# Get token snapshots for a month
client.download_tokens("2024-09", output_dir="./data/tokens")
```

## Data Schema

The archive contains three main datasets:

1. **Transactions** - All non-vote transactions with signatures, fees, account changes, and token balances
   - Schema: `https://data.solarchive.org/schemas/solana/transactions.json`
   - Partitioned by day: `txs/YYYY-MM-DD/*.parquet`

2. **Accounts** - Periodic snapshots of account states including balances and program data
   - Schema: `https://data.solarchive.org/schemas/solana/accounts.json`
   - Partitioned by month: `accounts/YYYY-MM/*.parquet`

3. **Tokens** - Metadata snapshots for fungible and non-fungible tokens
   - Schema: `https://data.solarchive.org/schemas/solana/tokens.json`
   - Partitioned by month: `tokens/YYYY-MM/*.parquet`

## Development

This package requires Python 3.11 or higher.

```bash
# Install dependencies
pip install -e .

# Run the example
python main.py
```

## About solarchive.org

Visit [solarchive.org](https://solarchive.org) to explore the data directly in your browser using DuckDB-WASM, or to support the project. Hosting hundreds of terabytes costs nearly $10,000/year!

## License

MIT
collabnet 0.1.0
Build collaboration networks from publication records.
Requires Python: >=3.12

# CollabNet

[![Documentation Status](https://readthedocs.org/projects/collabnet/badge/?version=latest)](https://collabnet.readthedocs.io/en/latest/?badge=latest)

This Python package allows to generate co-authorship and co-country networks.
The source data (currently from OpenAlex) can be works for the same journal,
institution or topic. The data is transformed into a suitable format to facilitate
the network creation. Networks are generated and saved as GRAPHML files.

In addition the app allows to calculate the Adjusted International Collaboration Index,
as defined in Lalli 2025.

![Gephi Lite plot of Co-authorship network for 1980 with interval 3](docs/_static/gephi_lite_coauthors-1980-interval-3.png)

[Gephi Lite](https://lite.gephi.org) plot of Co-authorship network for 1980 with interval 3 with 738 nodes and 2402 edges.
Layout in ForceAtlas2 design, colors related to Louvain modularity class. Node size by degree. The selected node with label has
degree 16.

Documentation is available on [ReadTheDocs](https://collabnet.readthedocs.io).

## Installation

tl;dr Use pip

~~~bash
pip install collabnet
~~~

Consider using a clean virtual environment to keep your main packages separated.
Create a new virtual environment and install the package

~~~bash
python3 -m venv env
source env/bin/activate
pip install collabnet
~~~

## Example

You can find an example Jupyter Notebook showing the use of package by demonstrating a query for data, transforming the data, and generate networks in the [examples folder](../example/collab_pipeline.ipynb).

## Testing

Tests can be run by running

~~~bash
uv run pytest --cov-report=term-missing --cov=src/collabnet
~~~
which installs the `test` dependency group and runs the files. Coverage of testing is shown.

## Building documentation

The documentation is build using _sphinx_. Install of the _doc_ dependency group is automated with `uv`:

~~~bash
uv run sphinx-build -c docs -b html docs docs/_build/html
~~~

## Funding information

This work is part of a collaboration between the department for
Structural Changes of the Technosphere, Max Planck Institute of Geoanthropology, Jena, Germany and
DIMEAS - Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Torino, Italy.