mirror of
https://github.com/OpenBB-finance/OpenBB.git
synced 2026-10-28 21:12:16 +00:00
138 lines
3.9 KiB
Python
138 lines
3.9 KiB
Python
"""Finance Database view"""
|
|
__docformat__ = "numpy"
|
|
|
|
import logging
|
|
import os
|
|
|
|
import pandas as pd
|
|
|
|
from openbb_terminal.decorators import log_start_end
|
|
from openbb_terminal.etf import financedatabase_model
|
|
from openbb_terminal.helper_funcs import export_data, print_rich_table
|
|
from openbb_terminal.rich_config import console
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
@log_start_end(log=logger)
|
|
def display_etf_by_name(
|
|
name: str,
|
|
limit: int = 10,
|
|
export: str = "",
|
|
):
|
|
"""Display a selection of ETFs based on name filtered by total assets. [Source: Finance Database]
|
|
|
|
Parameters
|
|
----------
|
|
name: str
|
|
Search by name to find ETFs matching the criteria.
|
|
limit: int
|
|
Limit of ETFs to display
|
|
export: str
|
|
Type of format to export data
|
|
"""
|
|
data = financedatabase_model.get_etfs_by_name(name)
|
|
if not data:
|
|
console.print("No data was found with that name\n")
|
|
return
|
|
|
|
table_data = pd.DataFrame(data).T[
|
|
["long_name", "family", "category", "total_assets"]
|
|
]
|
|
table_data_sorted = table_data.sort_values(by="total_assets", ascending=False)
|
|
table_data_sorted["total_assets"] = table_data_sorted["total_assets"] / 1e6
|
|
|
|
print_rich_table(
|
|
table_data_sorted.iloc[:limit],
|
|
show_index=True,
|
|
headers=["Name", "Family", "Category", "Total Assets [M]"],
|
|
title="ETFs by Total Assets",
|
|
)
|
|
|
|
export_data(
|
|
export, os.path.dirname(os.path.abspath(__file__)), "ln_fd", table_data_sorted
|
|
)
|
|
|
|
|
|
@log_start_end(log=logger)
|
|
def display_etf_by_description(
|
|
description: str,
|
|
limit: int = 10,
|
|
export: str = "",
|
|
):
|
|
"""Display a selection of ETFs based on description filtered by total assets.
|
|
[Source: Finance Database]
|
|
|
|
Parameters
|
|
----------
|
|
description: str
|
|
Search by description to find ETFs matching the criteria.
|
|
limit: int
|
|
Limit of ETFs to display
|
|
export: str
|
|
Type of format to export data
|
|
"""
|
|
data = financedatabase_model.get_etfs_by_description(description)
|
|
if not data:
|
|
console.print("No data was found with that description\n")
|
|
return
|
|
|
|
table_data = pd.DataFrame(data).T[
|
|
["long_name", "family", "category", "total_assets"]
|
|
]
|
|
table_data_sorted = table_data.sort_values(by="total_assets", ascending=False)
|
|
table_data_sorted["total_assets"] = table_data_sorted["total_assets"] / 1e6
|
|
|
|
print_rich_table(
|
|
table_data_sorted.iloc[:limit],
|
|
show_index=True,
|
|
headers=["Name", "Family", "Category", "Total Assets [M]"],
|
|
title="ETFs by Total Assets",
|
|
)
|
|
|
|
export_data(export, os.path.dirname(os.path.abspath(__file__)), "ld", data)
|
|
|
|
|
|
@log_start_end(log=logger)
|
|
def display_etf_by_category(
|
|
category: str,
|
|
limit: int = 10,
|
|
export: str = "",
|
|
):
|
|
"""Display a selection of ETFs based on a category filtered by total assets.
|
|
[Source: Finance Database]
|
|
|
|
Parameters
|
|
----------
|
|
description: str
|
|
Search by description to find ETFs matching the criteria.
|
|
limit: int
|
|
Limit of ETFs to display
|
|
export: str
|
|
Type of format to export data
|
|
"""
|
|
data = financedatabase_model.get_etfs_by_category(category)
|
|
if not data:
|
|
console.print("No data was found on that category\n")
|
|
return
|
|
|
|
table_data = pd.DataFrame(data).T[
|
|
["long_name", "family", "category", "total_assets"]
|
|
]
|
|
table_data_sorted = table_data.sort_values(by="total_assets", ascending=False)
|
|
table_data_sorted["total_assets"] = table_data_sorted["total_assets"] / 1e6
|
|
|
|
print_rich_table(
|
|
table_data_sorted.iloc[:limit],
|
|
show_index=True,
|
|
headers=["Name", "Family", "Category", "Total Assets [M]"],
|
|
title="ETFs by Category and Total Assets",
|
|
)
|
|
|
|
export_data(
|
|
export,
|
|
os.path.join(os.path.dirname(os.path.abspath(__file__)), "screener"),
|
|
"sbc",
|
|
data,
|
|
)
|