I am having trouble passing a datetime.time variable into a SQLite database, I have some very basic code here to show what exactly the variable is.
import datetime as dt
time = dt.datetime.now().time()
time = time.strftime('%H:%M')
time = dt.datetime.strptime(time, '%H:%M').time()
print(time)
print(type(time))
time = dt.datetime.now().time() gets the current time in type datetime.time.
Output:
17:34:48.286215
<class 'datetime.time'>
time = time.strftime('%H:%M') is then retrieving just the hour and minute but is of type str
Output:
17:35
<class 'str'>
I then convert it back to a datetime.time with time = dt.datetime.strptime(time, '%H:%M').time() which gives the the output:
17:32:00
<class 'datetime.time'>
The column of type Time accepts the format of HH:SS as shown in the documentation (SQLite3 DateTime Documentation), so I am not sure why I am getting this error:
sqlite3.InterfaceError: Error binding parameter 11 - probably unsupported type.
From this INSERT statement:
cursor.execute("INSERT INTO booked_tickets VALUES (?,?,?,?,?,?,?,?,?,?,?,?)", (booking_ref, ticket_date, film, showing, ticket_type, num_tickets, cus_name, cus_phone, cus_email, ticket_price, booking_date, booking_time, ))
EDIT: As requested, here is a snippet of code to recreate the table with the broken columns:
import datetime as dt
import sqlite3
connection = sqlite3.connect("your_database.db")
cursor = connection.cursor()
# Get the current time
time = dt.datetime.now().time()
# Format the time as a string using the '%H:%M' format
time_str = time.strftime('%H:%M')
# Parse the string back to a time object using the '%H:%M' format
time = dt.datetime.strptime(time_str, '%H:%M').time()
# Create the table
cursor.execute("CREATE TABLE test (example_time Time)")
# Insert the time into the example_time column
cursor.execute("INSERT INTO test VALUES (?)", (time, ))
connection.commit()
connection.close()
There is no Date or Time data type in SQLite.
The documentation from the link that you have in your question clearly states that in SQLite you can store datetime in 3 ways: text in ISO-8601 format, integer unix epochs and float julian days.
If you chose the first way then you should pass strings:
booking_date = dt.datetime.now().date().strftime('%Y-%m-%d')
booking_time = dt.datetime.now().time().strftime('%H:%M:00')
sql = "INSERT INTO booked_tickets VALUES (?,?,?,?,?,?,?,?,?,?)"
cursor.execute(sql, (booking_ref, ticket_date, film, showing, ticket_type, num_tickets, cus_name, cus_phone, cus_email, ticket_price, booking_date, booking_time))
But, you could also let SQLite get the current date and/or time.
Assuming that in the columns booking_date and booking_time you want the current date and time, you can define these columns as:
booking_date TEXT NOT NULL DEFAULT CURRENT_DATE,
booking_time TEXT NOT NULL DEFAULT CURRENT_TIME
and then you don't need to pass anything for them in the INSERT statement:
sql = "INSERT INTO booked_tickets VALUES (?,?,?,?,?,?,?,?,?,?)"
cursor.execute(sql, (booking_ref, ticket_date, film, showing, ticket_type, num_tickets, cus_name, cus_phone, cus_email, ticket_price,))
Checkout the SQLite datatypes documentation
2.2. Date and Time Datatype
SQLite does not have a storage class set aside for storing dates
and/or times. Instead, the built-in Date And Time Functions of SQLite
are capable of storing dates and times as TEXT, REAL, or INTEGER
values:
TEXT as ISO8601 strings ("YYYY-MM-DD HH:MM:SS.SSS").
REAL as Julian day numbers, the number of days since noon in Greenwich on November 24, 4714 B.C. according to the proleptic
Gregorian calendar.
INTEGER as Unix Time, the number of seconds since 1970-01-01 00:00:00 UTC.
Applications can choose to store dates and times in any of these
formats and freely convert between formats using the built-in date and
time functions.
Store the dates as TEXT datatypes.
The documentation you refer to mostly discusses how to format column values that representing dates and times. That is, it discusses what you can do with dates and times that already exist in your database.
It does, however, give just enough information to help you here I think. It says:
Date and time values can be stored as
text in a subset of the ISO-8601 format,
numbers representing the Julian day, or
numbers representing the number of seconds since (or before) 1970-01-01 00:00:00 UTC (the unix timestamp).
So you want to define and supply your dates and times as either full ISO-8601 date strings or as numbers. When defining a table, you indicate which of these formats you wish to use by defining a column type as a STRING, REAL or INTEGER respectively.
Here's some documentation that discusses how to store dates and times in one of these formats: https://www.sqlitetutorial.net/sqlite-date/
I have a Datetime column and I am trying to filter that column by everything occurring on a Saturday.
I can filter Datetime by casting it to a date and comparing it to a date string like this:
session.query(SQL_table).filter(cast(SQL_table.datetime_column, Date) == '2020-7-1').all()
But how do I say I want that column to return everything that is on a certain day of the week? I tried this:
session.query(SQL_table).filter(cast(SQL_table.datetime_column, Date).strftime('%A') == 'Saturday').all()
This gives me the error:
AttributeError: Neither 'Cast' object nor 'Comparator' object has an attribute 'strftime'
So how do I cast the column to a weekday and filter it by a specific day then?
To solve your problem you can specify function which users use to extract day of week in your SQL dialect using function generator from sqlalchemy package. For example, Transact-SQL has format() function, Oracle SQL has to_char(date_column, 'D') function for day's of week extraction. Using this approach you can specify custom function that will be suitable for your SQL dialect.
from sqlalchemy import func
day_of_week_num = 6
day_of_week_str = 'Sunday'
# Example for Transact-SQL
session.query(SQL_table).filter(func.format(SQL_table.datetime_column, 'dddd') == day_of_week_str).all()
# Example for Oracle SQL
session.query(SQL_table).filter(func.to_char(SQL_table.datetime_column, 'D') == day_of_week_num).all()
Try using func.dayofweek
from sqlalchemy import func
...
# 1 = Sunday, 2 = Monday, ..., 7 = Saturday.
# Therefore, to get Saturday:
session.query(SQL_table).filter(func.dayofweek(
SQL_table.datetime_column) == 7).all()
I looked at that link
It's weird because the query im doing is hit and miss.
It can't show the dates if the difference is only a few days
SQLAlchemy: how to filter date field?
model:
class UserCallsModel(db.Model):
id = db.Column(db.Integer, primary_key = True)
date = db.Column(db.String(90))
username = db.Column(db.String(90))
event_name = db.Column(db.String(90))
query:
users = UserCallsModel.query.filter(UserCallsModel.date.between("2016-1-1", "2016-1-20")).order_by(UserCallsModel.date.desc())
I've got 2 dates that fall within this range but is not getting queried?
I'm not familiar with MySQL, but I imagine it is the same as PG which I've included output below.
When you use the "between" method, you end up using the "BETWEEN" operator, like so...
SELECT * FROM my_table WHERE date BETWEEN '2016-1-1' AND '2016-1-20'
The problem is that the "between" operator does something different for dates versus strings. For example, if the value that it is testing is a string, it will see the arguments (the '2016-1-1' AND '2016-1-20' part) as strings.
mhildreth=# select '2016-1-5' between '2016-1-1' AND '2016-1-10';
?column?
----------
f
(1 row)
Meanwhile, if the value that it is testing is a date object, then it will implicitly convert the strings to date objects, essentially doing the following...
mhildreth=# select '2016-1-5'::date between '2016-1-1'::date AND '2016-1-10'::date;
?column?
----------
t
(1 row)
Thus, my guess is that you want to convert your "date" column to be a date type. If you must leave it a string, then you need to ensure that you are using a date format that also works when doing string comparison. Thus, you'll need 2016-01-01 rather than 2016-1-1.
I was under the impression that a string will actually be queried correctly as long as it was of a certain format. but nope I'm afraid it ain't so.
a better way of doing this if you have strings formatted like this:
"2016-1-5" is to simply convert the string date to a datetime.date object
python 3
import datetime
splitted_date = [int(number) for number in "2016-1-5".split("-")]
formatted_date = datetime.date(*splitted_date)
I have a dataframe full of dates and I would like to select all dates where the month==12 and the day==25 and add replace the zero in the xmas column with a 1.
Anyway to do this? the second line of my code errors out.
df = DataFrame({'date':[datetime(2013,1,1).date() + timedelta(days=i) for i in range(0,365*2)], 'xmas':np.zeros(365*2)})
df[df['date'].month==12 and df['date'].day==25] = 1
Pandas Series with datetime now behaves differently. See .dt accessor.
This is how it should be done now:
df.loc[(df['date'].dt.day==25) & (cust_df['date'].dt.month==12), 'xmas'] = 1
Basically what you tried won't work as you need to use the & to compare arrays, additionally you need to use parentheses due to operator precedence. On top of this you should use loc to perform the indexing:
df.loc[(df['date'].month==12) & (df['date'].day==25), 'xmas'] = 1
An update was needed in reply to this question. As of today, there's a slight difference in how you extract months from datetime objects in a pd.Series.
So from the very start, incase you have a raw date column, first convert it to datetime objects by using a simple function:
import datetime as dt
def read_as_datetime(str_date):
# replace %Y-%m-%d with your own date format
return dt.datetime.strptime(str_date,'%Y-%m-%d')
then apply this function to your dates column and save results in a new column namely datetime:
df['datetime'] = df.dates.apply(read_as_datetime)
finally in order to extract dates by day and month, use the same piece of code that #Shayan RC explained, with this slight change; notice the dt.datetime after calling the datetime column:
df.loc[(df['datetime'].dt.datetime.month==12) &(df['datetime'].dt.datetime.day==25),'xmas'] =1
I have a input parameter dictionary as below -
InparamDict = {'DataInputDate':'2014-10-25'
}
Using the field InparamDict['DataInputDate'], I want to pull up data from 2013-10-01 till 2013-10-25. What would be the best way to arrive at the same using Pandas?
The sql equivalent is -
DATEFROMPARTS(DATEPART(year,GETDATE())-1,DATEPART(month,GETDATE()),'01')
You forgot to mention if you're trying to pull up data from a DataFrame, Series or what. If you just want to get the date parts, you just have to get the attribute you want from the Timestamp object.
from pandas import Timestamp
dt = Timestamp(InparamDict['DataInputDate'])
dt.year, dt.month, dt.day
If the dates are in a DataFrame (df) and you convert them to dates instead of strings. You can select the data by ranges as well, for instance
df[df['DataInputDate'] > datetime(2013,10,1)]