php – How to merge selected queries into the wp_term column?

I return attribute values ​​from wp_term and that's one of my queries for an attribute, say color. And I have the same queries for other attributes. I'm looking for a way to merge them into query, because I could not make it work with multiple mysqli functions to display them. Is it possible to merge these queries:

$sql = "SELECT p.`ID` AS 'Product ID', 
        p.`post_title` AS 'Product Name', 
        t.`term_id` AS 'Attribute Value ID', 
        REPLACE(REPLACE(tt.`taxonomy`, 'pa_', ''), '-', ' ') AS 'Attribute Name', 
        t.`name` AS 'Carat' 
        FROM `wp_posts` AS p 
        INNER JOIN `wp_term_relationships` AS tr ON p.`ID` = tr.`object_id` 
        INNER JOIN `wp_term_taxonomy` AS tt ON tr.`term_taxonomy_id` = tt.`term_id` AND tt.`taxonomy` LIKE 'pa_carat%'
        INNER JOIN `wp_terms` AS t ON tr.`term_taxonomy_id` = t.`term_id` 
        WHERE p.`post_type` = 'product' 
        AND p.`post_status` = 'publish' ORDER BY p.`ID`";

$sql .= "
SELECT p.`ID` AS 'Product ID', 
       p.`post_title` AS 'Product Name', 
       t.`term_id` AS 'Attribute Value ID', 
       REPLACE(REPLACE(tt.`taxonomy`, 'pa_', ''), '-', ' ') AS 'Attribute Name', 
       t.`name` AS 'Color' 
       FROM `wp_posts` AS p 
       INNER JOIN `wp_term_relationships` AS tr ON p.`ID` = tr.`object_id` 
       INNER JOIN `wp_term_taxonomy` AS tt ON tr.`term_taxonomy_id` = tt.`term_id` AND tt.`taxonomy` LIKE 'pa_color%'
       INNER JOIN `wp_terms` AS t ON tr.`term_taxonomy_id` = t.`term_id` 
       WHERE p.`post_type` = 'product' 
       AND p.`post_status` = 'publish' ORDER BY p.`ID`";

Tiny Crash – Merge for app reviews: SCAM or LEGIT?

Download the application from:

How to play:

1. Buy characters and improve them with the gold coins of the game. Combine 2 characters of the same level, you will get the first level.
2. Then, let your characters fight the monster to collect coins.
3. Possibility also to upgrade cards, objects with game pieces.
4. When you reach level 5, put the code

3BHZY5EA flawless stay

win 100 diamonds. Click on …

Tiny Crash – Merge for app reviews: SCAM or LEGIT?

ecmascript 6 – How to make Javascript return a given result using For..OF to merge the values ​​of an array with a separator using Join?

I have some exercise in JAVASCRIPT I can not solve, the question is this.
Given the following object vector:

    var usuarios = [
 nome: "Diego",
 habilidades: ["Javascript", "ReactJS", "Redux"]
 nome: "Gabriel",
 habilidades: ["VueJS", "Ruby on Rails", "Elixir"]

Write a function that produces the following result:

Diego has the skills: Javascript, ReactJS, Redux.
Gabriel has the following skills: VueJS, Ruby on Rails, Elixir.

that is, I need Console.log to display what is shown above, but it is necessary that to go through the vector I use the syntax "For … from" and to join the values ​​of a table I use the Rejoin .

algorithms – Is there a name for the technique used in MergeSort's merge?

MergeSort has two parts, "divide" and "merge" (it can be said that three if you include "recurse" as its own part in the middle). I am interested in the "fusion" part, which tends to look like this:

consider two priority queues list1, list2
initialize an empty sorted list
while neither list1 nor list2 is empty:
    find lowest element between peek(list1) and peek(list2)
    pop that element from its list and add it to the sorted list
add the rest of the non-empty list to the sorted list
return the sorted list

This paradigm of "splitting into several priority queues and continually managing the first elements" is also useful for problems that are definitely not related to the merge, such as executing operations on a dependency list. the priority element of another lower list. For example,

consider two priority queues list1, list2
initialize an empty destination list
while neither list1 nor list2 is empty:
    while peek(list1) < peek(list2):
        add f(peek(list1), peek(list2)) to destination list
        pop element from list1
    pop element from list2
return destination list

In these two examples, we use the same idea "to iterate simultaneously in several priority queues, doing something with the upper elements of each of them, but removing one at a time". This differs from matching two lists and enumeration by means of corresponding items.

Is there a specific name for this technique / paradigm? The MergeSort Wikipedia page does not answer the question at the time of writing and, in the context of MergeSort, I have never seen it described other than by "merge" (which is incorrect in my second example) or by "conquest". (which is too vague)

Merge Attach SSIS Error Despite Sorting and Matching Meta

I'm trying to merge Join two data sources. I made sure that the metadata matched and that the sort key was present in the metadata, but it still gives me the following error:

Both entries of the transformation must contain at least one sorted column and these metadata must have the corresponding metadata. "

All support articles and related forum questions all mention metadata and sorting. I even type the right dataset to match the one on the left … I do not know what to do here. The flow and the metadata are illustrated. The first is the left join, the second is the right join. The last entry is the column I want to join in both metadata tables.

Data flow
Input metadata1
Input2 metadata

nosql – How do you merge older data with a stream database only?

I read information about streaming databases that record all events as immutable entries in an add-only log. Then, the mapping / reduction tasks or something like a "materialized view" are built by reading the logs to get the current status.

However, my question is about interfacing with external systems. How are you supposed to add their data to the additions database only in order to avoid duplicates and order the data correctly?

Consider a night cron to extract XYZ and insert it into the current data stream.

pdf – Why Preview causes a color merge in these PNG images with pdflatex?

I have created the following image in PDF format (a figure for a scientific work):

color grid with distinct colors

On my linux machine, I opened this image in evince and okular and it looks like it's showing up pretty well here. It also appears this way on Google Drive.

However, when I open it with Preview on my Macbook, it looks like this:color grid with mixed colors

Why do colors blend in Preview and is there a way to prevent this from happening? (I'll need to send this figurine as part of a print work and I would like to guarantee that the figurine remains "whole" for printing.)

Join / Merge multiple files into one

How this option works "Join / Merge multiple files into one"
Can I need to do it?

Eliminate all empty cells by vertical merge: Google Sheets

I am working with a spreadsheet containing a set of "sections", for example when the "URL" column is set to "" in A1, and is left empty while many operations related to this URL are carried out in others. columns (let's say we extract all the

tags and list them). As all this applies to the same URL, it is not necessary to repeat it. The column of the URL thus remains empty until A7, when the URL becomes "".

I wanted to merge those cells with the cell containing the URL instead of leaving them empty, but I found myself repeating the same operation multiple times:

  • Find a cell containing text
  • Drag down to the next cell containing text
  • Merge vertically
  • Repeat.

As a result, I started to make a macro. For reference, this is my first-ever experience with Google Apps Script. Therefore, although I probably could have done things much more simply (tell me so!), I'm glad it was so long, because I learned a lot.

Whatever it is, here is my code. You simply select a range and the above process will be applied to all columns.

Disclaimer: All the code is mine except the columnToLetter function that I has stolen borrowed from AdamL's answer on this question

function mergeAtText() {
  var spreadsheet = SpreadsheetApp.getActive();
  var range = spreadsheet.getActiveRange().getA1Notation();
  var toMerge = ();

  var toCheck = ();
  var axis = range.split(":");

  var cols = ();
  var rows = ()
  for (var i=0;i 0){
      temp = (column - 1) % 26;
      letter = String.fromCharCode(temp + 65) + letter;
      column = (column - temp - 1) / 26;
    return letter;

  cols = cols.sort();
  var colList = ();
  for (var i=getColNum(cols(0));i

All comments on code quality, conciseness, etc. are welcome.

python – Merge, add and concatenate geocoded data images

I am new to python programming and are looking for a code optimization that calls 2 functions (1 google and 1 python github) and processes records of more than 300 KB

My code can be summarized with the algorithm

  1. Reading from Multiple CSV Files from a Local Computer Folder Containing Lat and Long Columns in Dataframe – It takes a lot less time
  2. Delete Duplicate Data Frame: The distinct number of Lat and Lon combinations is 313,540
  3. Send each lat and long to google reverse geocoding and get the zip code, state, country and load it as columns in Dataframe created in step 2
  4. Send each Lat and Lon combination to the python library "uszipcode" to retrieve the 10 rows of closest postal code, median household income, dwelling units, population density, and load in a data block.
  5. Merge the two data sets created in steps 3 and 4 and continue adding the results to a result_data frame.
  6. Display the result in a CSV tab-delimited format


  1. I have Free Google KEY API that have limit of 5000 requests for 500ms and unlimited requests in a day
  2. Most time consuming steps are 3, 4 and 5 For 500 records One step 3 took ~ 4 minutes One step 4 took ~ 10 minutes One step 5 took ~ 10 minutes

I'm worried if I open my code to all the records, this is going to be a long process and I'm not sure, even though the data block may contain the values ​​to be put completely in the file at the end aka l & rsquo; Step 6.

import os
import glob
import pandas as pd
import numpy as np
from uszipcode import SearchEngine
import googlemaps
from datetime import datetime

#setting directory where all the csv files are present
os.chdir("Directory where i have all my csv files")
extension = 'csv'
all_filenames = (i for i in glob.glob('*.{}'.format(extension)))
combined_csv = pd.concat((pd.read_csv(f) for f in all_filenames ))
#removing where BEGIN_LAT and BEGIN_LON is 'Null' or NaN
#removing duplicates 
#adding row_number to the dataframe
#redirecting the lat, long and id to a new dataframe
#checking type of input_lat_long, len
print(input_lat_lon)  #gives 313513records
#to check a sample of dataframe processed: input_lat_lon.head()

search = SearchEngine(simple_zipcode=True)

print("dataframe to be sent for google is computed")
#looping through all the values in the input_lat_long dataframe
#googlemaps key
gmaps = googlemaps.Client(key='MyGoogleKey')
print("About to send requests to google with start time of :",
for x in range(5):
    mykeys = ('formatted_address')
     #retreving zipcode from googlemaps and getting the formatted_address for the sent lat and lon combination
    newList={k:gmaps.reverse_geocode((test_df.iloc(x,1),test_df.iloc(x,2)))(0)(k) for k in mykeys if k in gmaps.reverse_geocode((test_df.iloc(x,1),test_df.iloc(x,2)))(0)}
    #assigning the zipcode retrieved from google to the lat_lon combination

print("Google Requests are processed :",
print('Duration: {}'.format(end_time - start_time))

print("to get nearest zip start time:",start_time)
for x in range(len(test_df)):      

    nearest_result=search.by_coordinates(test_df.iloc(x,1),test_df.iloc(x,2), radius=30,returns=5)
    nzip=(res.zipcode for res in nearest_result)
    pop_den=(res.population_density for res in nearest_result)
    occ_hou_unt=(res.occupied_housing_units for res in nearest_result)
    median_hou_inc=(res.median_household_income for res in nearest_result)  

    return_list = pd.DataFrame(
     'NEAREST_ZIP': nzip,
     'POPULATION_DENSITY': pop_den,
print("to get nearest zip start time:",end_time)
print("duration for nearestzip:",format(end_time - start_time))
export_csv = result_df.to_csv (r'foldersample.csv', index = None, header=True,sep='|')

Sample output when I ran for less lat and long combinations