rerun dataset/profitability script 08032024

.gitattributes

@@ -58,3 +58,4 @@ delivers.csv filter=lfs diff=lfs merge=lfs -text
 requests.csv filter=lfs diff=lfs merge=lfs -text
 tools.csv filter=lfs diff=lfs merge=lfs -text
 all_trades_profitability.csv filter=lfs diff=lfs merge=lfs -text
+*.csv filter=lfs diff=lfs merge=lfs -text

.gitignore

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all_trades_profitability.csv

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delivers.csv

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fpmmTrades.csv

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summary_profitability.csv

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tools.csv

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 version https://git-lfs.github.com/spec/v1
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-size 253692243
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+size 750214066

tools.py

@@ -1,833 +0,0 @@
-#   -*- coding: utf-8 -*-
-#   ------------------------------------------------------------------------------
-#
-#     Copyright 2023 Valory AG
-#
-#     Licensed under the Apache License, Version 2.0 (the "License");
-#     you may not use this file except in compliance with the License.
-#     You may obtain a copy of the License at
-#
-#         http://www.apache.org/licenses/LICENSE-2.0
-#
-#     Unless required by applicable law or agreed to in writing, software
-#     distributed under the License is distributed on an "AS IS" BASIS,
-#     WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-#     See the License for the specific language governing permissions and
-#     limitations under the License.
-#
-#   ------------------------------------------------------------------------------
-
-import json
-import os.path
-import re
-import sys
-import time
-import random
-from dataclasses import dataclass
-from enum import Enum
-from io import StringIO
-from typing import (
-    Optional,
-    List,
-    Dict,
-    Any,
-    Union,
-    Callable,
-    Tuple,
-)
-
-import pandas as pd
-import requests
-from json.decoder import JSONDecodeError
-from eth_typing import ChecksumAddress
-from eth_utils import to_checksum_address
-from requests.adapters import HTTPAdapter
-from requests.exceptions import (
-    ReadTimeout as RequestsReadTimeoutError,
-    HTTPError as RequestsHTTPError,
-)
-from tqdm import tqdm
-from urllib3 import Retry
-from urllib3.exceptions import (
-    ReadTimeoutError as Urllib3ReadTimeoutError,
-    HTTPError as Urllib3HTTPError,
-)
-from web3 import Web3, HTTPProvider
-from web3.exceptions import MismatchedABI
-from web3.types import BlockParams
-from concurrent.futures import ThreadPoolExecutor, as_completed
-
-CONTRACTS_PATH = "contracts"
-MECH_TO_INFO = {
-    # this block number is when the creator had its first tx ever, and after this mech's creation
-    "0xff82123dfb52ab75c417195c5fdb87630145ae81": ("old_mech_abi.json", 28911547),
-    # this block number is when this mech was created
-    "0x77af31de935740567cf4ff1986d04b2c964a786a": ("new_mech_abi.json", 30776879),
-}
-# optionally set the latest block to stop searching for the delivered events
-LATEST_BLOCK: Optional[int] = None
-LATEST_BLOCK_NAME: BlockParams = "latest"
-BLOCK_DATA_NUMBER = "number"
-BLOCKS_CHUNK_SIZE = 10_000
-REDUCE_FACTOR = 0.25
-EVENT_ARGUMENTS = "args"
-DATA = "data"
-REQUEST_ID = "requestId"
-REQUEST_ID_FIELD = "request_id"
-REQUEST_SENDER = "sender"
-PROMPT_FIELD = "prompt"
-BLOCK_FIELD = "block"
-CID_PREFIX = "f01701220"
-HTTP = "http://"
-HTTPS = HTTP[:4] + "s" + HTTP[4:]
-IPFS_ADDRESS = f"{HTTPS}gateway.autonolas.tech/ipfs/"
-IPFS_LINKS_SERIES_NAME = "ipfs_links"
-BACKOFF_FACTOR = 1
-STATUS_FORCELIST = [404, 500, 502, 503, 504]
-DEFAULT_FILENAME = "tools.csv"
-RE_RPC_FILTER_ERROR = r"Filter with id: '\d+' does not exist."
-ABI_ERROR = "The event signature did not match the provided ABI"
-SLEEP = 0.5
-HTTP_TIMEOUT = 60
-N_IPFS_RETRIES = 2
-N_RPC_RETRIES = 100
-RPC_POLL_INTERVAL = 0.05
-IPFS_POLL_INTERVAL = 0.05
-FORMAT_UPDATE_BLOCK_NUMBER = 30411638
-IRRELEVANT_TOOLS = [
-    "openai-text-davinci-002",
-    "openai-text-davinci-003",
-    "openai-gpt-3.5-turbo",
-    "openai-gpt-4",
-    "stabilityai-stable-diffusion-v1-5",
-    "stabilityai-stable-diffusion-xl-beta-v2-2-2",
-    "stabilityai-stable-diffusion-512-v2-1",
-    "stabilityai-stable-diffusion-768-v2-1",
-    "deepmind-optimization-strong",
-    "deepmind-optimization",
-]
-# this is how frequently we will keep a snapshot of the progress so far in terms of blocks' batches
-# for example, the value 1 means that for every `BLOCKS_CHUNK_SIZE` blocks that we search, we also store the snapshot
-SNAPSHOT_RATE = 10
-NUM_WORKERS = 10
-GET_CONTENTS_BATCH_SIZE = 1000
-
-
-class MechEventName(Enum):
-    """The mech's event names."""
-
-    REQUEST = "Request"
-    DELIVER = "Deliver"
-
-
-@dataclass
-class MechEvent:
-    """A mech's on-chain event representation."""
-
-    for_block: int
-    requestId: int
-    data: bytes
-    sender: str
-
-    def _ipfs_link(self) -> Optional[str]:
-        """Get the ipfs link for the data."""
-        return f"{IPFS_ADDRESS}{CID_PREFIX}{self.data.hex()}"
-
-    @property
-    def ipfs_request_link(self) -> Optional[str]:
-        """Get the IPFS link for the request."""
-        return f"{self._ipfs_link()}/metadata.json"
-
-    @property
-    def ipfs_deliver_link(self) -> Optional[str]:
-        """Get the IPFS link for the deliver."""
-        if self.requestId is None:
-            return None
-        return f"{self._ipfs_link()}/{self.requestId}"
-
-    def ipfs_link(self, event_name: MechEventName) -> Optional[str]:
-        """Get the ipfs link based on the event."""
-        if event_name == MechEventName.REQUEST:
-            if self.for_block < FORMAT_UPDATE_BLOCK_NUMBER:
-                return self._ipfs_link()
-            return self.ipfs_request_link
-        if event_name == MechEventName.DELIVER:
-            return self.ipfs_deliver_link
-        return None
-
-
-@dataclass(init=False)
-class MechRequest:
-    """A structure for a request to a mech."""
-
-    request_id: Optional[int]
-    request_block: Optional[int]
-    prompt_request: Optional[str]
-    tool: Optional[str]
-    nonce: Optional[str]
-    trader_address: Optional[str]
-
-    def __init__(self, **kwargs: Any) -> None:
-        """Initialize the request ignoring extra keys."""
-        self.request_id = int(kwargs.pop(REQUEST_ID, 0))
-        self.request_block = int(kwargs.pop(BLOCK_FIELD, 0))
-        self.prompt_request = kwargs.pop(PROMPT_FIELD, None)
-        self.tool = kwargs.pop("tool", None)
-        self.nonce = kwargs.pop("nonce", None)
-        self.trader_address = kwargs.pop("sender", None)
-
-
-@dataclass(init=False)
-class PredictionResponse:
-    """A response of a prediction."""
-
-    p_yes: float
-    p_no: float
-    confidence: float
-    info_utility: float
-    vote: Optional[str]
-    win_probability: Optional[float]
-
-    def __init__(self, **kwargs: Any) -> None:
-        """Initialize the mech's prediction ignoring extra keys."""
-        try:
-            self.p_yes = float(kwargs.pop("p_yes"))
-            self.p_no = float(kwargs.pop("p_no"))
-            self.confidence = float(kwargs.pop("confidence"))
-            self.info_utility = float(kwargs.pop("info_utility"))
-            self.win_probability = 0
-
-            # Validate probabilities
-            probabilities = {
-                "p_yes": self.p_yes,
-                "p_no": self.p_no,
-                "confidence": self.confidence,
-                "info_utility": self.info_utility,
-            }
-
-            for name, prob in probabilities.items():
-                if not 0 <= prob <= 1:
-                    raise ValueError(f"{name} probability is out of bounds: {prob}")
-
-            if self.p_yes + self.p_no != 1:
-                raise ValueError(
-                    f"Sum of p_yes and p_no is not 1: {self.p_yes} + {self.p_no}"
-                )
-
-            self.vote = self.get_vote()
-            self.win_probability = self.get_win_probability()
-
-        except KeyError as e:
-            raise KeyError(f"Missing key in PredictionResponse: {e}")
-        except ValueError as e:
-            raise ValueError(f"Invalid value in PredictionResponse: {e}")
-
-    def get_vote(self) -> Optional[str]:
-        """Return the vote."""
-        if self.p_no == self.p_yes:
-            return None
-        if self.p_no > self.p_yes:
-            return "No"
-        return "Yes"
-
-    def get_win_probability(self) -> Optional[float]:
-        """Return the probability estimation for winning with vote."""
-        return max(self.p_no, self.p_yes)
-
-
-@dataclass(init=False)
-class MechResponse:
-    """A structure for the response of a mech."""
-
-    request_id: int
-    deliver_block: Optional[int]
-    result: Optional[PredictionResponse]
-    error: Optional[str]
-    error_message: Optional[str]
-    prompt_response: Optional[str]
-    mech_address: Optional[str]
-
-    def __init__(self, **kwargs: Any) -> None:
-        """Initialize the mech's response ignoring extra keys."""
-        self.error = kwargs.get("error", None)
-        self.request_id = int(kwargs.get(REQUEST_ID, 0))
-        self.deliver_block = int(kwargs.get(BLOCK_FIELD, 0))
-        self.result = kwargs.get("result", None)
-        self.prompt_response = kwargs.get(PROMPT_FIELD, None)
-        self.mech_address = kwargs.get("sender", None)
-
-        if self.result != "Invalid response":
-            self.error_message = kwargs.get("error_message", None)
-
-            try:
-                if isinstance(self.result, str):
-                    kwargs = json.loads(self.result)
-                    self.result = PredictionResponse(**kwargs)
-                    self.error = str(False)
-
-            except JSONDecodeError:
-                self.error_message = "Response parsing error"
-                self.error = str(True)
-
-            except Exception as e:
-                self.error_message = str(e)
-                self.error = str(True)
-
-        else:
-            self.error_message = "Invalid response from tool"
-            self.error = str(True)
-            self.result = None
-
-
-EVENT_TO_MECH_STRUCT = {
-    MechEventName.REQUEST: MechRequest,
-    MechEventName.DELIVER: MechResponse,
-}
-
-
-def parse_args() -> str:
-    """Parse the arguments and return the RPC."""
-    if len(sys.argv) != 2:
-        raise ValueError("Expected the RPC as a positional argument.")
-    return sys.argv[1]
-
-
-def read_abi(abi_path: str) -> str:
-    """Read and return the wxDAI contract's ABI."""
-    with open(abi_path) as abi_file:
-        return abi_file.read()
-
-
-def reduce_window(contract_instance, event, from_block, batch_size, latest_block):
-    """Dynamically reduce the batch size window."""
-    keep_fraction = 1 - REDUCE_FACTOR
-    events_filter = contract_instance.events[event].build_filter()
-    events_filter.fromBlock = from_block
-    batch_size = int(batch_size * keep_fraction)
-    events_filter.toBlock = min(from_block + batch_size, latest_block)
-    tqdm.write(f"RPC timed out! Resizing batch size to {batch_size}.")
-    time.sleep(SLEEP)
-    return events_filter, batch_size
-
-
-def get_events(
-    w3: Web3,
-    event: str,
-    mech_address: ChecksumAddress,
-    mech_abi_path: str,
-    earliest_block: int,
-    latest_block: int,
-) -> List:
-    """Get the delivered events."""
-    abi = read_abi(mech_abi_path)
-    contract_instance = w3.eth.contract(address=mech_address, abi=abi)
-
-    events = []
-    from_block = earliest_block
-    batch_size = BLOCKS_CHUNK_SIZE
-    with tqdm(
-        total=latest_block - from_block,
-        desc=f"Searching {event} events for mech {mech_address}",
-        unit="blocks",
-    ) as pbar:
-        while from_block < latest_block:
-            events_filter = contract_instance.events[event].build_filter()
-            events_filter.fromBlock = from_block
-            events_filter.toBlock = min(from_block + batch_size, latest_block)
-
-            entries = None
-            retries = 0
-            while entries is None:
-                try:
-                    entries = events_filter.deploy(w3).get_all_entries()
-                    retries = 0
-                except (RequestsHTTPError, Urllib3HTTPError) as exc:
-                    if "Request Entity Too Large" in exc.args[0]:
-                        events_filter, batch_size = reduce_window(
-                            contract_instance,
-                            event,
-                            from_block,
-                            batch_size,
-                            latest_block,
-                        )
-                except (Urllib3ReadTimeoutError, RequestsReadTimeoutError):
-                    events_filter, batch_size = reduce_window(
-                        contract_instance, event, from_block, batch_size, latest_block
-                    )
-                except Exception as exc:
-                    retries += 1
-                    if retries == N_RPC_RETRIES:
-                        tqdm.write(
-                            f"Skipping events for blocks {events_filter.fromBlock} - {events_filter.toBlock} "
-                            f"as the retries have been exceeded."
-                        )
-                        break
-                    sleep = SLEEP * retries
-                    if (
-                        (
-                            isinstance(exc, ValueError)
-                            and re.match(
-                                RE_RPC_FILTER_ERROR, exc.args[0].get("message", "")
-                            )
-                            is None
-                        )
-                        and not isinstance(exc, ValueError)
-                        and not isinstance(exc, MismatchedABI)
-                    ):
-                        tqdm.write(
-                            f"An error was raised from the RPC: {exc}\n Retrying in {sleep} seconds."
-                        )
-                    time.sleep(sleep)
-
-            from_block += batch_size
-            pbar.update(batch_size)
-
-            if entries is None:
-                continue
-
-            chunk = list(entries)
-            events.extend(chunk)
-            time.sleep(RPC_POLL_INTERVAL)
-
-    return events
-
-
-def parse_events(raw_events: List) -> List[MechEvent]:
-    """Parse all the specified MechEvents."""
-    parsed_events = []
-    for event in raw_events:
-        for_block = event.get("blockNumber", 0)
-        args = event.get(EVENT_ARGUMENTS, {})
-        request_id = args.get(REQUEST_ID, 0)
-        data = args.get(DATA, b"")
-        sender = args.get(REQUEST_SENDER, "")
-        parsed_event = MechEvent(for_block, request_id, data, sender)
-        parsed_events.append(parsed_event)
-
-    return parsed_events
-
-
-def create_session() -> requests.Session:
-    """Create a session with a retry strategy."""
-    session = requests.Session()
-    retry_strategy = Retry(
-        total=N_IPFS_RETRIES + 1,
-        backoff_factor=BACKOFF_FACTOR,
-        status_forcelist=STATUS_FORCELIST,
-    )
-    adapter = HTTPAdapter(max_retries=retry_strategy)
-    for protocol in (HTTP, HTTPS):
-        session.mount(protocol, adapter)
-
-    return session
-
-
-def request(
-    session: requests.Session, url: str, timeout: int = HTTP_TIMEOUT
-) -> Optional[requests.Response]:
-    """Perform a request with a session."""
-    try:
-        response = session.get(url, timeout=timeout)
-        response.raise_for_status()
-    except requests.exceptions.HTTPError as exc:
-        tqdm.write(f"HTTP error occurred: {exc}.")
-    except Exception as exc:
-        tqdm.write(f"Unexpected error occurred: {exc}.")
-    else:
-        return response
-    return None
-
-
-def limit_text(text: str, limit: int = 200) -> str:
-    """Limit the given text"""
-    if len(text) > limit:
-        return f"{text[:limit]}..."
-    return text
-
-
-def parse_ipfs_response(
-    session: requests.Session,
-    url: str,
-    event: MechEvent,
-    event_name: MechEventName,
-    response: requests.Response,
-) -> Optional[Dict[str, str]]:
-    """Parse a response from IPFS."""
-    try:
-        return response.json()
-    except requests.exceptions.JSONDecodeError:
-        # this is a workaround because the `metadata.json` file was introduced and removed multiple times
-        if event_name == MechEventName.REQUEST and url != event.ipfs_request_link:
-            url = event.ipfs_request_link
-            response = request(session, url)
-            if response is None:
-                tqdm.write(f"Skipping {event=}.")
-                return None
-
-            try:
-                return response.json()
-            except requests.exceptions.JSONDecodeError:
-                pass
-
-    tqdm.write(f"Failed to parse response into json for {url=}.")
-    return None
-
-
-def parse_ipfs_tools_content(
-    raw_content: Dict[str, str], event: MechEvent, event_name: MechEventName
-) -> Optional[Union[MechRequest, MechResponse]]:
-    """Parse tools content from IPFS."""
-    struct = EVENT_TO_MECH_STRUCT.get(event_name)
-    raw_content[REQUEST_ID] = str(event.requestId)
-    raw_content[BLOCK_FIELD] = str(event.for_block)
-    raw_content["sender"] = str(event.sender)
-
-    try:
-        mech_response = struct(**raw_content)
-    except (ValueError, TypeError, KeyError):
-        tqdm.write(f"Could not parse {limit_text(str(raw_content))}")
-        return None
-
-    if event_name == MechEventName.REQUEST and mech_response.tool in IRRELEVANT_TOOLS:
-        return None
-
-    return mech_response
-
-
-def get_contents(
-    session: requests.Session, events: List[MechEvent], event_name: MechEventName
-) -> pd.DataFrame:
-    """Fetch the tools' responses."""
-    contents = []
-    for event in tqdm(events, desc=f"Tools' results", unit="results"):
-        url = event.ipfs_link(event_name)
-        response = request(session, url)
-        if response is None:
-            tqdm.write(f"Skipping {event=}.")
-            continue
-
-        raw_content = parse_ipfs_response(session, url, event, event_name, response)
-        if raw_content is None:
-            continue
-
-        mech_response = parse_ipfs_tools_content(raw_content, event, event_name)
-        if mech_response is None:
-            continue
-        contents.append(mech_response)
-        time.sleep(IPFS_POLL_INTERVAL)
-
-    return pd.DataFrame(contents)
-
-
-def clean(df: pd.DataFrame) -> pd.DataFrame:
-    """Clean the dataframe."""
-    cleaned = df.drop_duplicates()
-    cleaned[REQUEST_ID_FIELD] = cleaned[REQUEST_ID_FIELD].astype("str")
-    return cleaned
-
-
-def transform_request(contents: pd.DataFrame) -> pd.DataFrame:
-    """Transform the requests dataframe."""
-    return clean(contents)
-
-
-def transform_deliver(contents: pd.DataFrame, full_contents=False) -> pd.DataFrame:
-    """Transform the delivers dataframe."""
-    unpacked_result = pd.json_normalize(contents.result)
-    # # drop result column if it exists
-    if "result" in unpacked_result.columns:
-        unpacked_result.drop(columns=["result"], inplace=True)
-
-    # drop prompt column if it exists
-    if "prompt" in unpacked_result.columns:
-        unpacked_result.drop(columns=["prompt"], inplace=True)
-
-    # rename prompt column to prompt_deliver
-    unpacked_result.rename(columns={"prompt": "prompt_deliver"}, inplace=True)
-    contents = pd.concat((contents, unpacked_result), axis=1)
-
-    if "result" in contents.columns:
-        contents.drop(columns=["result"], inplace=True)
-
-    if "prompt" in contents.columns:
-        contents.drop(columns=["prompt"], inplace=True)
-
-    return clean(contents)
-
-
-def gen_event_filename(event_name: MechEventName) -> str:
-    """Generate the filename of an event."""
-    return f"{event_name.value.lower()}s.csv"
-
-
-def read_n_last_lines(filename: str, n: int = 1) -> str:
-    """Return the `n` last lines' content of a file."""
-    num_newlines = 0
-    with open(filename, "rb") as f:
-        try:
-            f.seek(-2, os.SEEK_END)
-            while num_newlines < n:
-                f.seek(-2, os.SEEK_CUR)
-                if f.read(1) == b"\n":
-                    num_newlines += 1
-        except OSError:
-            f.seek(0)
-        last_line = f.readline().decode()
-    return last_line
-
-
-def get_earliest_block(event_name: MechEventName) -> int:
-    """Get the earliest block number to use when filtering for events."""
-    filename = gen_event_filename(event_name)
-    if not os.path.exists(filename):
-        return 0
-
-    cols = pd.read_csv(filename, index_col=0, nrows=0).columns.tolist()
-    last_line_buff = StringIO(read_n_last_lines(filename))
-    last_line_series = pd.read_csv(last_line_buff, names=cols)
-    block_field = f"{event_name.value.lower()}_{BLOCK_FIELD}"
-    return int(last_line_series[block_field].values[0])
-
-
-def pipeline_step(
-    w3: Web3,
-    session: requests.Session,
-    event_to_contents: Dict[MechEventName, pd.DataFrame],
-    event_to_transformer: Dict[MechEventName, Callable],
-    mech_to_info: Dict[ChecksumAddress, Tuple[str, int]],
-    stop_block: Optional[int] = None,
-    start_block: Optional[int] = None,
-    full_contents: bool = False,
-):
-    """Perform a step of the pipeline, from start block (or default earliest) to stop block."""
-    for event_name, transformer in event_to_transformer.items():
-        events = []
-        for address, (abi, earliest_block) in mech_to_info.items():
-            if start_block is None:
-                start_block = max(earliest_block, get_earliest_block(event_name))
-                stop_block = start_block + SNAPSHOT_RATE * BLOCKS_CHUNK_SIZE
-
-            # Parallelize the fetching of events
-            with ThreadPoolExecutor(max_workers=NUM_WORKERS) as executor:
-                futures = []
-                for i in range(start_block, stop_block, BLOCKS_CHUNK_SIZE):
-                    futures.append(
-                        executor.submit(
-                            get_events,
-                            w3,
-                            event_name.value,
-                            address,
-                            abi,
-                            i,
-                            min(i + BLOCKS_CHUNK_SIZE, stop_block),
-                        )
-                    )
-
-                for future in tqdm(
-                    as_completed(futures),
-                    total=len(futures),
-                    desc=f"Fetching {event_name.value} Events",
-                ):
-                    current_mech_events = future.result()
-                    events.extend(current_mech_events)
-
-        parsed = parse_events(events)
-
-        # Parallelize the fetching of contents; use tqdm to show progress
-        contents = []
-        with ThreadPoolExecutor(max_workers=NUM_WORKERS) as executor:
-            futures = []
-            for i in range(0, len(parsed), 1000):
-                futures.append(
-                    executor.submit(
-                        get_contents, session, parsed[i : i + 1000], event_name
-                    )
-                )
-
-            for future in tqdm(
-                as_completed(futures),
-                total=len(futures),
-                desc=f"Fetching {event_name.value} Contents",
-            ):
-                current_mech_contents = future.result()
-                contents.append(current_mech_contents)
-
-        contents = pd.concat(contents, ignore_index=True)
-
-        if event_name == MechEventName.REQUEST:
-            transformed = transformer(contents)
-        elif event_name == MechEventName.DELIVER:
-            transformed = transformer(contents, full_contents=full_contents)
-
-        events_filename = gen_event_filename(event_name)
-        if os.path.exists(events_filename):
-            old = pd.read_csv(events_filename)
-
-            # Reset index to avoid index conflicts
-            old.reset_index(drop=True, inplace=True)
-            transformed.reset_index(drop=True, inplace=True)
-
-            # Concatenate DataFrames
-            transformed = pd.concat([old, transformed], ignore_index=True)
-
-            # Drop duplicates if necessary
-            transformed.drop_duplicates(inplace=True)
-
-        event_to_contents[event_name] = transformed.copy()
-
-    return stop_block
-
-
-def store_progress(
-    filename: str,
-    event_to_contents: Dict[MechEventName, pd.DataFrame],
-    tools: pd.DataFrame,
-) -> None:
-    """Store the given progress."""
-    if filename:
-        for event_name, content in event_to_contents.items():
-            event_filename = gen_event_filename(event_name)
-            if "error" in content.columns:
-                content.drop(columns=["error"], inplace=True)
-
-            if "result" in content.columns:
-                content.drop(columns=["result"], inplace=True)
-
-            content.to_csv(event_filename, index=False, escapechar="\\")
-
-        # drop result and error columns
-        if "result" in tools.columns:
-            tools.drop(columns=["result"], inplace=True)
-
-        tools.to_csv(filename, index=False, escapechar="\\")
-
-
-def etl(
-    rpcs: List[str], filename: Optional[str] = None, full_contents: bool = True
-) -> pd.DataFrame:
-    """Fetch from on-chain events, process, store and return the tools' results on all the questions as a Dataframe."""
-    w3s = [Web3(HTTPProvider(r)) for r in rpcs]
-    session = create_session()
-    event_to_transformer = {
-        MechEventName.REQUEST: transform_request,
-        MechEventName.DELIVER: transform_deliver,
-    }
-    mech_to_info = {
-        to_checksum_address(address): (
-            os.path.join(CONTRACTS_PATH, filename),
-            earliest_block,
-        )
-        for address, (filename, earliest_block) in MECH_TO_INFO.items()
-    }
-    event_to_contents = {}
-
-    latest_block = LATEST_BLOCK
-    if latest_block is None:
-        latest_block = w3s[0].eth.get_block(LATEST_BLOCK_NAME)[BLOCK_DATA_NUMBER]
-
-    next_start_block = None
-
-    # Loop through events in event_to_transformer
-    for event_name, transformer in event_to_transformer.items():
-        if next_start_block is None:
-            next_start_block_base = get_earliest_block(event_name)
-
-        # Loop through mech addresses in mech_to_info
-        events = []
-        for address, (abi, earliest_block) in mech_to_info.items():
-            if next_start_block_base == 0:
-                next_start_block = earliest_block
-            else:
-                next_start_block = next_start_block_base
-
-            print(
-                f"Searching for {event_name.value} events for mech {address} from block {next_start_block} to {latest_block}."
-            )
-
-            # parallelize the fetching of events
-            with ThreadPoolExecutor(max_workers=NUM_WORKERS) as executor:
-                futures = []
-                for i in range(
-                    next_start_block, latest_block, BLOCKS_CHUNK_SIZE * SNAPSHOT_RATE
-                ):
-                    futures.append(
-                        executor.submit(
-                            get_events,
-                            random.choice(w3s),
-                            event_name.value,
-                            address,
-                            abi,
-                            i,
-                            min(i + BLOCKS_CHUNK_SIZE * SNAPSHOT_RATE, latest_block),
-                        )
-                    )
-
-                for future in tqdm(
-                    as_completed(futures),
-                    total=len(futures),
-                    desc=f"Fetching {event_name.value} Events",
-                ):
-                    current_mech_events = future.result()
-                    events.extend(current_mech_events)
-
-        parsed = parse_events(events)
-
-        contents = []
-        with ThreadPoolExecutor(max_workers=NUM_WORKERS) as executor:
-            futures = []
-            for i in range(0, len(parsed), GET_CONTENTS_BATCH_SIZE):
-                futures.append(
-                    executor.submit(
-                        get_contents,
-                        session,
-                        parsed[i : i + GET_CONTENTS_BATCH_SIZE],
-                        event_name,
-                    )
-                )
-
-            for future in tqdm(
-                as_completed(futures),
-                total=len(futures),
-                desc=f"Fetching {event_name.value} Contents",
-            ):
-                current_mech_contents = future.result()
-                contents.append(current_mech_contents)
-
-        contents = pd.concat(contents, ignore_index=True)
-
-        full_contents = True
-        if event_name == MechEventName.REQUEST:
-            transformed = transformer(contents)
-        elif event_name == MechEventName.DELIVER:
-            transformed = transformer(contents, full_contents=full_contents)
-
-        events_filename = gen_event_filename(event_name)
-
-        if os.path.exists(events_filename):
-            old = pd.read_csv(events_filename)
-
-            # Reset index to avoid index conflicts
-            old.reset_index(drop=True, inplace=True)
-            transformed.reset_index(drop=True, inplace=True)
-
-            # Concatenate DataFrames
-            transformed = pd.concat([old, transformed], ignore_index=True)
-
-            # Drop duplicates if necessary
-            transformed.drop_duplicates(inplace=True)
-
-        event_to_contents[event_name] = transformed.copy()
-
-    # Store progress
-    tools = pd.merge(*event_to_contents.values(), on=REQUEST_ID_FIELD)
-    store_progress(filename, event_to_contents, tools)
-
-    return tools
-
-
-if __name__ == "__main__":
-    RPCs = [
-        "https://lb.nodies.app/v1/406d8dcc043f4cb3959ed7d6673d311a",
-    ]
-
-    tools = etl(rpcs=RPCs, filename=DEFAULT_FILENAME, full_contents=True)