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import openai
import tiktoken
from scipy import spatial 
import pandas as pd

df=pd.read_csv('./data/oscars.csv')
print(df.head())

df=df.loc[df['year_ceremony'] == 2023]
df=df.dropna(subset=['film'])

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Python Zeep SOAP Client

First, we'll look at the SOAP URL and see what Prefixes, Global Elements, Global Types, Bindings, and Services are provided by the SOAP Service.

You can do this by running zeep as a CLI tool.

export WSDL_URL="http://www.dneonline.com/calculator.asmx?WSDL"
python -m zeep $WSDL_URL

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• Aeroporto
• Alameda
• Área
• Avenida
• Campo
• Chácara
• Colônia
• Condomínio
• Conjunto
• Distrito

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PSQL

Magic words:

psql -U postgres

Some interesting flags (to see all, use -h or --help depending on your psql version):

• -E: will describe the underlaying queries of the \ commands (cool for learning!)
• -l: psql will list all databases and then exit (useful if the user you connect with doesn't has a default database, like at AWS RDS)

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DROP TABLE IF EXISTS matrices;
CREATE TABLE matrices (
  matrix_id int NOT NULL, -- unique identifier for each matrix
  i int NOT NULL,         -- row number
  j int NOT NULL,         -- column number
  val decimal NOT NULL,   -- the value in this cell
  PRIMARY KEY (matrix_id, i, j)
);

-- insert sparse representation of

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-- show running queries (pre 9.2)
SELECT procpid, age(clock_timestamp(), query_start), usename, current_query 
FROM pg_stat_activity 
WHERE current_query != '<IDLE>' AND current_query NOT ILIKE '%pg_stat_activity%' 
ORDER BY query_start desc;

-- show running queries (9.2)
SELECT pid, age(clock_timestamp(), query_start), usename, query 
FROM pg_stat_activity 
WHERE query != '<IDLE>' AND query NOT ILIKE '%pg_stat_activity%' 

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Importing/Indexing database (MySQL or SQL Server) in Solr using Data Import Handler

Install Solr

download and install Solr from http://lucene.apache.org/solr/.

you can access Solr admin from your browser: http://localhost:8983/solr/

use the port number used in installation.

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### Libraries
library(shiny)
library(dplyr)
library(DT)

### Data
input_data <- data.frame(Brand = c("Brand1", "Brand2","Brand3"),
                         ratio = c (.5, .5, .5),
                         cost = c(2000, 3000, 4000),
                         stringsAsFactors = FALSE) %>% 

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## Versão do ubuntu

`lsb_release -a`

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library(shiny)

# WARNING: This sketch does not make proper use of the "state" parameter.
# Doing so usually involves using cookies, which can be done with the
# Rook package but I have not done that here. If you choose to use this
# approach in production, please check the state parameter properly!

APP_URL <- if (interactive()) {
  # This might be useful for local development. If not, just hardcode APP_URL
  # to the deployed URL that you'll provide a few lines below.