I am struggling with a sanity check. I have a PostgreSQL database on dbeaver and a table named Album. I am trying to automate a sanity check. In the column ArtistId I have a small click-in window on the right, once I click on it I get a new window with ArtistId and Name. For every distinct ArtistId I wish to check whether the name is the corresponding ArtistId. So far I managed to get the table (Album) in a data-frame but I can not reach the sub-field. Thank you in advance for any help.
Problem 1: I need to access the sub-field (Database window picture).
Problem 2: I need to check for every row of the sub-field whether the artist name is 'Iron Maiden' or the corresponding artist name based on ArtistId that the user provided.
My code retrieves the entries in the database.
def get_entries(artistID):
artistID = int(input("Enter an artist_id from the available in postgresql :"))
df = pd.read_sql("SELECT * FROM Album WHERE ArtistId = %s",connection, params=(artistID,) )
return df
For problem 1) I found the following code SELECT x.* FROM Artist x WHERE x.ArtistId = 4 which can give me access to the sub-field.
Database Database window Database er diagram
The solution to the Problem 1 was a simple query:
SELECT *
FROM Album a
CROSS JOIN Artist b
Where a.ArtistId = b.ArtistId
AND a.ArtistId = 90
The solution to the Problem 2 was python line:
#This line returns the rows in my dataframe that are not same to the user_input
df.loc[df.ArtistId != artistID]
Related
I have a table containing full of movie genre, like this:
id | genre
---+----------------------------
1 | Drama, Romance, War
2 | Drama, Musical, Romance
3 | Adventure, Biography, Drama
Im looking for a way to get the most common word in the whole genre column and return it to a variable for further step in python.
I'm new to Python so I really don't know how to do it. Currently, I have these lines to connect to the database but don't know the way to get the most common word mentioned above.
conn = mysql.connect()
cursor = conn.cursor()
most_common_word = cursor.execute()
cursor.close()
conn.close()
First you need get list of words in each column. i.e create another table like
genre_words(genre_id bigint, word varchar(50))
For clues how to do that you may check this question:
SQL split values to multiple rows
You can do that as temporary table if you wish or use transaction and rollback. Which one to choose depend of your data size and PC on which DB running.
After that query will be really simple
select count(*) as c, word from genre_word group by word order by count(*) desc limit 1;
You also can do it using python, but if so it will not be a MySQL question at all. Need read table, create simple list of word+counter. If it new, add it, if exist - increase counter.
from collections import Counter
# Connect to database and get rows from table
rows = ...
# Create a list to hold all of the genres
genres = []
# Loop through each row and split the genre string by the comma character
# to create a list of individual genres
for row in rows:
genre_list = row['genre'].split(',')
genres.extend(genre_list)
# Use a Counter to count the number of occurrences of each genre
genre_counts = Counter(genres)
# Get the most common genre
most_common_genre = genre_counts.most_common(1)
# Print the most common genre
print(most_common_genre)
Okay so i have a table which has student id and the student id is used as identifier to edit the column but what if the same student lends a book twice then all the student value will b edited which i don't want....i want the last entered data of student id to b edited and using a Sl.No is not a solution here because its practically complicated.I am using python connector. Please help :) Thanks in advance
code i use right now :
con = mysql.connect(host='localhost', user='root',
password='monkey123', database='BOOK')
c = con.cursor()
c.execute(
f"UPDATE library set `status`='Returned',`date returned`='{str(cal.selection_get())}' WHERE `STUDENT ID`='{e_sch.get()}';")
c.execute('commit')
con.close()
messagebox.showinfo(
'Success', 'Book has been returned successfully')
If I followed you correctly, you want to update just one record that matches the where condition. For this to be done in a reliable manner, you need a column to define the ordering of the records. It could be a date, an incrementing id, or else. I assume that such column exists in your table and is called ordering_column.
A simple option is to use ORDER BY and LIMIT in the UPDATE statement, like so:
sql = """
UPDATE library
SET status = 'Returned', date returned = %s
WHERE student_id = %s
ORDER BY ordering_column DESC
LIMIT 1
"""
c = con.cursor()
c.execute(sql, (str(cal.selection_get()), e_sch.get(), )
Note that I modified your code so input values are given as parameters rather than concatenated into the query string. This is an important change, that makes your code safer and more efficient.
In a postgresql database:
class Persons(models.Model):
person_name = models.CharField(max_length=10, unique=True)
The persons.csv file, contains 1 million names.
$cat persons.csv
Name-1
Name-2
...
Name-1000000
I want to:
Create the names that do not already exist
Query the database and fetch the id for each name contained in the csv file.
My approach:
Use the COPY command or the django-postgres-copy application that implements it.
Also take advantage of the new Postgresql-9.5+ upsert feature.
Now, all the names in the csv file, are also in the database.
I need to get their ids -from the database- either in memory or in another csv file with an efficient way:
Use Q objects
list_of_million_q = <iterate csv and append Qs>
million_names = Names.objects.filter(list_of_million_q)
or
Use __in to filter based on a list of names:
list_of_million_names = <iterate csv and append strings>
million_names = Names.objects.filter(
person_name__in=[list_of_million_names]
)
or
?
I do not feel that any of the above approaches for fetching the ids is efficient.
Update
There is a third option, along the lines of this post that should be a great solution which combines all the above.
Something like:
SELECT * FROM persons;
make a name: id dictionary out of the names recieved from the database:
db_dict = {'Harry': 1, 'Bob': 2, ...}
Query the dictionary:
ids = []
for name in list_of_million_names:
if name in db_dict:
ids.append(db_dict[name])
This way you're using the quick dictionary indexing as opposed to the slower if x in list approach.
But the only way to really know for sure is to benchmark these 3 approaches.
This post describes how to use RETURNING with ON CONFLICT so while inserting into the database the contents of the csv file, the ids will be saved in another table either when an insertion was successful, or when -due to unique constraints- the insertion was omitted.
I have tested it in sqlfiddle where I used a set up that resembles the one used for the COPY command which inserts to the database straight from a csv file, respecting the unique constraints.
The schema:
CREATE TABLE IF NOT EXISTS label (
id serial PRIMARY KEY,
label_name varchar(200) NOT NULL UNIQUE
);
INSERT INTO label (label_name) VALUES
('Name-1'),
('Name-2');
CREATE TABLE IF NOT EXISTS ids (
id serial PRIMARY KEY,
label_ids varchar(12) NOT NULL
);
The script:
CREATE TEMP TABLE tmp_table
(LIKE label INCLUDING DEFAULTS)
ON COMMIT DROP;
INSERT INTO tmp_table (label_name) VALUES
('Name-2'),
('Name-3');
WITH ins AS(
INSERT INTO label
SELECT *
FROM tmp_table
ON CONFLICT (label_name) DO NOTHING
RETURNING id
)
INSERT INTO ids (label_ids)
SELECT
id FROM ins
UNION ALL
SELECT
l.id FROM tmp_table
JOIN label l USING(label_name);
The output:
SELECT * FROM ids;
SELECT * FROM label;
I am trying to create an new unique id field in an access table. I already have one field called SITE_ID_FD, but it is historical. The format of the unique value in that field isn't what our current format is, so I am creating a new field with the new format.
Old Format = M001, M002, K003, K004, S005, M006, etc
New format = 12001, 12002, 12003, 12004, 12005, 12006, etc
I wrote the following script:
fc = r"Z:\test.gdb\testfc"
x = 12001
cursor = arcpy.UpdateCursor(fc)
for row in cursor:
row.setValue("SITE_ID", x)
cursor.updateRow(row)
x+= 1
This works fine, but it populates the new id field based on the default sorting of objectID. I need to sort 2 fields first and then populate the new id field based on that sorting (I want to sort by a field called SITE and then by the old id field SITE_ID_FD)
I tried manually sorting the 2 fields in hopes that Python would honor the sort, but it doesn't. I'm not sure how to do this in Python. Can anyone suggest a method?
A possible solution is when you are creating your update cursor. you can specify to the cursor the fields by which you wish it to be sorted (sorry for my english..), they explain this in the documentation: http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#//000v0000003m000000
so it goes like this:
UpdateCursor(dataset, {where_clause}, {spatial_reference}, {fields}, {sort_fields})
and you are intrested only in the sort_fields so assuming that your code will work well on a sorted table and that you want the table ordered asscending the second part of your code should look like this:
fc = r"Z:\test.gdb\testfc"
x = 12001
cursor = arcpy.UpdateCursor(fc,"","","","SITE A, SITE_ID_FD A")
#if you want to sort it descending you need to write it with a D
#>> cursor = arcpy.UpdateCursor(fc,"","","","SITE D, SITE_ID_FD D")
for row in cursor:
row.setValue("SITE_ID", x)
cursor.updateRow(row)
x+= 1
i hope this helps
Added a link to the arcpy docs in a comment, but from what I can tell, this will create a new, sorted dataset--
import arcpy
from arcpy import env
env.workspace = r"z:\test.gdb"
arcpy.Sort_management("testfc", "testfc_sort", [["SITE", "ASCENDING"],
["SITE_IF_FD", "ASCENDING]])
And this will, on the sorted dataset, do what you want:
fc = r"Z:\test.gdb\testfc_sort"
x = 12001
cursor = arcpy.UpdateCursor(fc)
for row in cursor:
row.setValue("SITE_ID", x)
cursor.updateRow(row)
x+= 1
I'm assuming there's some way to just copy the sorted/modified dataset back over the original, so it's all good?
I'll admit, I don't use arcpy, and the docs could be a lot more explicit.
I am trying to scrape form field IDs using Beautiful Soup like this
for link in BeautifulSoup(content, parseOnlyThese=SoupStrainer('input')):
if link.has_key('id'):
print link['id']
Lets us assume that it returns something like
username
email
password
passwordagain
terms
button_register
I would like to write this into Sqlite3 DB.
What I will be doing down the line in my application is... Use these form fields' IDs and try to do a POST may be. The problem is.. there are plenty of sites like this whose form field IDs I have scraped. So the relation is like this...
Domain1 - First list of Form Fields for this Domain1
Domain2 - Second list of Form Fields for this Domain2
.. and so on
What I am unsure here is... How should I design my column for this kind of purpose? Will it be OK if I just create a table with two columns - say
COL 1 - Domain URL (as TEXT)
COL 2 - List of Form Field IDs (as TEXT)
One thing to be remembered is... Down the line in my application I will need to do something like this...
Pseudocode
If Domain is "http://somedomain.com":
For ever item in the COL2 (which is a list of form field ids):
Assign some set of values to each of the form fields & then make a POST request
Can any one guide, please?
EDITed on 22/07/2011 - Is My Below Database Design Correct?
I have decided to have a solution like this. What do you guys think?
I will be having three tables like below
Table 1
Key Column (Auto Generated Integer) - Primary Key
Domain as TEXT
Sample Data would be something like:
1 http://url1.com
2 http://url2.com
3 http://url3.com
Table 2
Domain (Here I will be using the Key Number from Table 1)
RegLink - This will have the registeration link (as TEXT)
Form Fields (as Text)
Sample Data would be something like:
1 http://url1.com/register field1
1 http://url1.com/register field2
1 http://url1.com/register field3
2 http://url2.com/register field1
2 http://url2.com/register field2
2 http://url2.com/register field3
3 http://url3.com/register field1
3 http://url3.com/register field2
3 http://url3.com/register field3
Table 3
Domain (Here I will be using the Key Number from Table 1)
Status (as TEXT)
User (as TEXT)
Pass (as TEXT)
Sample Data would be something like:
1 Pass user1 pass1
2 Fail user2 pass2
3 Pass user3 pass3
Do you think this table design is good? Or are there any improvements that can be made?
There is a normalization problem in your table.
Using 2 tables with
TABLE domains
int id primary key
text name
TABLE field_ids
int id primary key
int domain_id foreign key ref domains
text value
is a better solution.
Proper database design would suggest you have a table of URLs, and a table of fields, each referenced to a URL record. But depending on what you want to do with them, you could pack lists into a single column. See the docs for how to go about that.
Is sqlite a requirement? It might not be the best way to store the data. E.g. if you need random-access lookups by URL, the shelve module might be a better bet. If you just need to record them and iterate over the sites, it might be simpler to store as CSV.
Try this to get the ids:
ids = (link['id'] for link in
BeautifulSoup(content, parseOnlyThese=SoupStrainer('input'))
if link.has_key('id'))
And this should show you how to save them, load them, and do something to each. This uses a single table and just inserts one row for each field for each domain. It's the simplest solution, and perfectly adequate for a relatively small number of rows of data.
from itertools import izip, repeat
import sqlite3
conn = sqlite3.connect(':memory:')
c = conn.cursor()
c.execute('''create table domains
(domain text, linkid text)''')
domain_to_insert = 'domain_name'
ids = ['id1', 'id2']
c.executemany("""insert into domains
values (?, ?)""", izip(repeat(domain_to_insert), ids))
conn.commit()
domain_to_select = 'domain_name'
c.execute("""select * from domains where domain=?""", (domain_to_select,))
# this is just an example
def some_function_of_row(row):
return row[1] + ' value'
fields = dict((row[1], some_function_of_row(row)) for row in c)
print fields
c.close()