SQLAlchemy ORM conversion to pandas DataFrame

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Is there a solution converting a SQLAlchemy <Query object> to a pandas DataFrame?

Pandas has the capability to use pandas.read_sql but this requires use of raw SQL. I have two reasons for wanting to avoid it:

  1. I already have everything using the ORM (a good reason in and of itself) and
  2. I"m using python lists as part of the query, e.g.:

db.session.query(Item).filter(Item.symbol.in_(add_symbols) where Item is my model class and add_symbols is a list). This is the equivalent of SQL SELECT ... from ... WHERE ... IN.

Is anything possible?

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SQLAlchemy ORM conversion to pandas DataFrame __del__: Questions

How can I make a time delay in Python?

5 answers

I would like to know how to put a time delay in a Python script.

2973

Answer #1

import time
time.sleep(5)   # Delays for 5 seconds. You can also use a float value.

Here is another example where something is run approximately once a minute:

import time
while True:
    print("This prints once a minute.")
    time.sleep(60) # Delay for 1 minute (60 seconds).

2973

Answer #2

You can use the sleep() function in the time module. It can take a float argument for sub-second resolution.

from time import sleep
sleep(0.1) # Time in seconds

SQLAlchemy ORM conversion to pandas DataFrame __del__: Questions

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Answer #1


Path objects from the Python 3.4+ pathlib module also expose these instance methods:

We hope this article has helped you to resolve the problem. Apart from SQLAlchemy ORM conversion to pandas DataFrame, check other __del__-related topics.

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Boris Wu

Boston | 2023-04-01

Maybe there are another answers? What SQLAlchemy ORM conversion to pandas DataFrame exactly means?. Will use it in my bachelor thesis

Schneider Jackson

Warsaw | 2023-04-01

io Python module is always a bit confusing 😭 SQLAlchemy ORM conversion to pandas DataFrame is not the only problem I encountered. I am just not quite sure it is the best method

Frank OConnell

Prague | 2023-04-01

Maybe there are another answers? What SQLAlchemy ORM conversion to pandas DataFrame exactly means?. I am just not quite sure it is the best method

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