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from struct import calcsize
import polars as pl

def scid_parse_trades(filepath: str) -> pl.DataFrame:
    """Sierrachart's SCID format. Must be configured to record single trade ticks."""
    intraday_record_struct = np.dtype(
        [
            ("timestamp", "<q"),
            ("open", "<f"),
            ("ask_price", "<f"),

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{
  "results": [
    {
      "id": 1,
      "type": "exchange",
      "asset_class": "stocks",
      "locale": "us",
      "name": "NYSE American, LLC",
      "acronym": "AMEX",
      "mic": "XASE",

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from nautilus_trader.backtest.data.wranglers import BarDataWrangler
from nautilus_trader.persistence.external.readers import ParquetReader
from nautilus_trader.persistence.catalog import DataCatalog
from functools import partial
from nautilus_trader.core.datetime import dt_to_unix_nanos
from nautilus_trader.model.c_enums.bar_aggregation import BarAggregation
from nautilus_trader.model.data.bar import Bar, BarType, BarSpecification
from nautilus_trader.model.enums import AggregationSource, PriceType
from nautilus_trader.persistence.external.core import process_files, write_objects

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import streamlit.ReportThread as ReportThread
from streamlit.ScriptRequestQueue import RerunData
from streamlit.ScriptRunner import RerunException
from streamlit.server.Server import Server


def rerun():
    """Rerun a Streamlit app from the top!"""
    widget_states = _get_widget_states()
    raise RerunException(RerunData(widget_states))

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{
  "smarts": "[#9,#17,#35,#53]-[*:1]",
  "limit": 10,
  "offset": 0,
  "search_conditions": [
    {
      "condition": "and_",
      "filters": [
        {
          "kind": "location",

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from scipy.sparse import csr_matrix
from rdkit import Chem
from rdkit.Chem.rdFingerprintGenerator import GetRDKitFPGenerator

smiles = 'CC1=C(C=C(C=C1)NC(=O)C2=CC=C(C=C2)CN3CCN(CC3)C)NC4=NC=CC(=N4)C5=CN=CC=C5'
molobj = Chem.MolFromSmiles(smiles)

for max_path in [2,3,4,5,6,7]:
    rdk_gen = GetRDKitFPGenerator(maxPath=max_path)
    fp = rdk_gen.GetSparseCountFingerprint(molobj)

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from typing import List
import pandas as pd


def explode_multi_column(
    df: pd.DataFrame, index_cols: List[str], sep: str
):
    """

    In [13]: