# PyXatu
<img src="https://github.com/nerolation/pyxatu/blob/main/logo/pyxatu.png?raw=true" width="400">
Pyxatu is a Python package for querying data from the [Xatu](https://ethpandaops.io/data/xatu/schema/) database and was developed to make access to Ethereum data as easy as possible without sacrificing on a rich set of features.
---
**Pyxatu comes out of the box with:**
* High level access to Xatu (Ethereum EL + CL)
* Mevboost Data API Interface
* Validator label mapping
## Install
```console
pip install pyxatu
xatu setup
```
`xatu setup` copies the default configuration file to your HOME directory as `.pyxatu_config.json`. Update this file with your actual Xatu credentials. Alternatively, you can use environment variables.
If you don't have credentials yet, please get in contact with someone from [EthPandaOps](https://ethpandaops.io/).
## Example Usage
As a first step, we always want to initialize PyXatu.
```python
import pyxatu
xatu = pyxatu.PyXatu()
```
We use `xatu` to execute our first query: We want to get the *block number* and the *gas used* of a block in a certain slot:
```python
df = xatu.get_slots(
slot = [9000000, 9000010],
columns="slot, execution_payload_block_number, execution_payload_gas_used",
orderby="slot"
)
print(df)
```
| slot | execution_payload_block_number | execution_payload_gas_used |
|--------:|---------------------------------:|-----------------------------:|
| 9000000 | 19796604 | 18026681 |
| 9000001 | 19796605 | 13920219 |
| 9000002 | 19796606 | 12498513 |
| 9000003 | 19796607 | 2914192 |
| 9000004 | 19796608 | 29996743 |
| ... | ... | ... |
Second, let's say we want to know which validator attested correctly in a certain epoch:
```python
df = xatu.get_elaborated_attestations(slot = 9000000)
print(df.head().to_markdown(index=False))
```
| slot | validator | status | vote_type |
|--------:|------------:|:---------|:------------|
| 9000000 | 7 | correct | source |
| 9000000 | 1179655 | correct | source |
| 9000000 | 524305 | correct | source |
| 9000000 | 17 | correct | source |
| 9000000 | 1179681 | correct | source |
| ... | ... | ... | ... |
Next, we want to get all bids accross all mevboost relays for a specific slot:
```python
df = xatu.mevboost.get_bids(slot = 9096969)
print(df.groupby("relay")["value"].median().reset_index().to_markdown(index=False))
```
| relay | value |
|:-----------------------|------------:|
| aestus | 3.92872e+16 |
| bloxroute (max profit) | 3.89533e+16 |
| bloxroute (regulated) | 3.89042e+16 |
| eden | 3.07634e+16 |
| flashbots | 3.89779e+16 |
and the delivered mevboost payloads:
```python
df = xatu.mevboost.get_payloads(slot = 9814162)
print(df.groupby("relay")["value"].median().reset_index().to_markdown(index=False))
```
| relay | value |
|:-----------------------|------------:|
| bloxroute (max profit) | 1.39261e+16 |
| ultra sound | 1.39261e+16 |
What if we need a mappling from validator ids to labels:
```python
xatu.validators.mapping[["validator_id", "deposit_address", "label", "lido_node_operator"]]
```
| validator_id | deposit_address | label | lido_node_operator |
|---------------:|:-------------------------------------------|:--------|:---------------------|
| 1545106 | 0xfddf38947afb03c621c71b06c9c70bce73f12999 | lido | Develp GmbH |
| 1545105 | 0xfddf38947afb03c621c71b06c9c70bce73f12999 | lido | Develp GmbH |
| 1546068 | 0xd523794c879d9ec028960a231f866758e405be34 | everstake | |
| 1546067 | 0xe3cbd06d7dadb3f4e6557bab7edd924cd1489e8f | mantle | |
| 1546066 | 0xd4039ecc40aeda0582036437cf3ec02845da4c13 | kraken | |
| 1546065 | 0xd4039ecc40aeda0582036437cf3ec02845da4c13 | kraken | |
| 1545103 | 0xfddf38947afb03c621c71b06c9c70bce73f12999 | lido | Launchnodes |
| 1545102 | 0xfddf38947afb03c621c71b06c9c70bce73f12999 | lido | Launchnodes |
## Contribution Guidelines
Please follow these steps to contribute:
1. **Fork the Repository**: Start by forking the repository to your GitHub account.
2. **Create a New Branch**: Create a new branch for your feature or bugfix.
```
git checkout -b feature/new-feature
```
3. **Write Tests**: Ensure your code is well-tested and follows the project's coding standards.
4. **Submit a Pull Request**: Once you're ready, submit a pull request for review.
New contributions that help improve PyXatu are more than welcome!
---
For any additional questions or support, feel free to open an issue on the [GitHub repository](https://github.com/nerolation/pyxatu).
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"description": "# PyXatu\n\n<img src=\"https://github.com/nerolation/pyxatu/blob/main/logo/pyxatu.png?raw=true\" width=\"400\">\n\n\n\nPyxatu is a Python package for querying data from the [Xatu](https://ethpandaops.io/data/xatu/schema/) database and was developed to make access to Ethereum data as easy as possible without sacrificing on a rich set of features.\n\n---\n\n**Pyxatu comes out of the box with:**\n* High level access to Xatu (Ethereum EL + CL)\n* Mevboost Data API Interface\n* Validator label mapping\n\n ## Install\n\n ```console\n pip install pyxatu\n xatu setup\n ```\n\n\n`xatu setup` copies the default configuration file to your HOME directory as `.pyxatu_config.json`. Update this file with your actual Xatu credentials. Alternatively, you can use environment variables.\nIf you don't have credentials yet, please get in contact with someone from [EthPandaOps](https://ethpandaops.io/).\n\n## Example Usage\n\n\nAs a first step, we always want to initialize PyXatu. \n ```python\n import pyxatu\n\n xatu = pyxatu.PyXatu()\n ```\n\nWe use `xatu` to execute our first query: We want to get the *block number* and the *gas used* of a block in a certain slot:\n\n ```python\n df = xatu.get_slots(\n slot = [9000000, 9000010],\n columns=\"slot, execution_payload_block_number, execution_payload_gas_used\",\n orderby=\"slot\"\n )\n\n print(df)\n ```\n\n| slot | execution_payload_block_number | execution_payload_gas_used |\n|--------:|---------------------------------:|-----------------------------:|\n| 9000000 | 19796604 | 18026681 |\n| 9000001 | 19796605 | 13920219 |\n| 9000002 | 19796606 | 12498513 |\n| 9000003 | 19796607 | 2914192 |\n| 9000004 | 19796608 | 29996743 |\n| ... | ... | ... |\n\n\n\nSecond, let's say we want to know which validator attested correctly in a certain epoch:\n\n ```python\n df = xatu.get_elaborated_attestations(slot = 9000000)\n\n print(df.head().to_markdown(index=False))\n ```\n\n\n| slot | validator | status | vote_type |\n|--------:|------------:|:---------|:------------|\n| 9000000 | 7 | correct | source |\n| 9000000 | 1179655 | correct | source |\n| 9000000 | 524305 | correct | source |\n| 9000000 | 17 | correct | source |\n| 9000000 | 1179681 | correct | source |\n| ... | ... | ... | ... |\n\n\nNext, we want to get all bids accross all mevboost relays for a specific slot:\n\n\n```python\ndf = xatu.mevboost.get_bids(slot = 9096969)\n\nprint(df.groupby(\"relay\")[\"value\"].median().reset_index().to_markdown(index=False))\n```\n\n\n| relay | value |\n|:-----------------------|------------:|\n| aestus | 3.92872e+16 |\n| bloxroute (max profit) | 3.89533e+16 |\n| bloxroute (regulated) | 3.89042e+16 |\n| eden | 3.07634e+16 |\n| flashbots | 3.89779e+16 |\n\n\nand the delivered mevboost payloads:\n\n```python\ndf = xatu.mevboost.get_payloads(slot = 9814162)\n\nprint(df.groupby(\"relay\")[\"value\"].median().reset_index().to_markdown(index=False))\n```\n\n| relay | value |\n|:-----------------------|------------:|\n| bloxroute (max profit) | 1.39261e+16 |\n| ultra sound | 1.39261e+16 |\n\n\nWhat if we need a mappling from validator ids to labels:\n\n```python\nxatu.validators.mapping[[\"validator_id\", \"deposit_address\", \"label\", \"lido_node_operator\"]]\n```\n\n| validator_id | deposit_address | label | lido_node_operator |\n|---------------:|:-------------------------------------------|:--------|:---------------------|\n| 1545106 | 0xfddf38947afb03c621c71b06c9c70bce73f12999 | lido | Develp GmbH |\n| 1545105 | 0xfddf38947afb03c621c71b06c9c70bce73f12999 | lido | Develp GmbH |\n| 1546068 | 0xd523794c879d9ec028960a231f866758e405be34 | everstake | |\n| 1546067 | 0xe3cbd06d7dadb3f4e6557bab7edd924cd1489e8f | mantle | |\n| 1546066 | 0xd4039ecc40aeda0582036437cf3ec02845da4c13 | kraken | |\n| 1546065 | 0xd4039ecc40aeda0582036437cf3ec02845da4c13 | kraken | |\n| 1545103 | 0xfddf38947afb03c621c71b06c9c70bce73f12999 | lido | Launchnodes |\n| 1545102 | 0xfddf38947afb03c621c71b06c9c70bce73f12999 | lido | Launchnodes |\n\n\n## Contribution Guidelines\n\nPlease follow these steps to contribute:\n\n1. **Fork the Repository**: Start by forking the repository to your GitHub account.\n2. **Create a New Branch**: Create a new branch for your feature or bugfix.\n ```\n git checkout -b feature/new-feature\n ```\n3. **Write Tests**: Ensure your code is well-tested and follows the project's coding standards.\n4. **Submit a Pull Request**: Once you're ready, submit a pull request for review.\n\n\nNew contributions that help improve PyXatu are more than welcome!\n\n---\n\nFor any additional questions or support, feel free to open an issue on the [GitHub repository](https://github.com/nerolation/pyxatu).\n",
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