This small subclass of the Pandas sqlalchemy-based SQL support for reading/storing tables uses the Postgres-specific "COPY FROM" method to insert large amounts of data to the database. It is much faster that using INSERT. To acheive this, the table is created in the normal way using sqlalchemy but no data is inserted. Instead the data is saved to a temporary CSV file (using Pandas' mature CSV support) then read back to Postgres using Psychopg2 support for COPY FROM STDIN.
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import pytesseract | |
import os | |
import sys | |
def read_image(img_path, lang='eng'): | |
""" | |
Performs OCR on a single image | |
:img_path: str, path to the image file |
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#!/usr/bin/env python | |
import sys | |
import pandas as pd | |
import pymongo | |
import json | |
def import_content(filepath): | |
mng_client = pymongo.MongoClient('localhost', 27017) |
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"""Find Symmetric Differences between two Pandas DataFrames.""" | |
def dataframe_difference(df1, df2, which=None): | |
"""Find rows which are different.""" | |
comparison_df = df1.merge( | |
df2, | |
indicator=True, | |
how='outer' | |
) |
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{ | |
"1":{ | |
"name":"Bulbasaur", | |
"attack":49, | |
"defense":49, | |
"evolveLevel":16, | |
"evolveTo":"2", | |
"type":"grass", | |
"moves":[ | |
"tackle", |
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<!DOCTYPE HTML> | |
<html lang="en" ng-app="myApp"> | |
<head> | |
<meta charset="utf-8"> | |
<title>Dynamic Pagination w/ Filtering</title> | |
<meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
<meta name="description" content=""> | |
<meta name="author" content="Kim Maida"> | |
<!-- JS Libraries --> |
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# syntax=docker/dockerfile:1 | |
FROM python:3.8-slim-buster | |
WORKDIR /app | |
ENV ACCEPT_EULA=Y | |
RUN apt-get update -y && apt-get update \ | |
&& apt-get install -y --no-install-recommends curl gcc g++ gnupg unixodbc-dev |
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<div className='delete-button' onClick={() => { if (window.confirm('Are you sure you wish to delete this item?')) this.onCancel(item) } } /> |
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