superzadeh

Methodologies

Event storming

• An introduction to event storming: The easy way to achieve domain-driven design
• Introducing Event Storming
• Facilitating Event Storming

Meetups

ghandic

import boto3
import pandas as pd
from io import StringIO

class S3DataFrame(pd.DataFrame):
    
	"""
	# Make a dataframe and upload it as csv
	s3df = S3DataFrame({'h1':[1], 'h2':[2]})
	s3df.to_s3(Bucket='bucket-name', 

zeyneloz

// HTTPError implements ClientError interface.
type HTTPError struct {
	Cause  error  `json:"-"`
	Detail string `json:"detail"`
	Status int    `json:"-"`
}

func (e *HTTPError) Error() string {
	if e.Cause == nil {
		return e.Detail

farhadmpr

class ReportFormat(object):
    PDF = 0
    TEXT = 1


class Report(object):
    def __init__(self, format_):
        self.title = 'title'
        self.format_ = format_

philippegirard

import logging
from fastapi import FastAPI
from uicheckapp.services import EchoService

logging.config.fileConfig('logging.conf', disable_existing_loggers=False)

logger = logging.getLogger(__name__)

app = FastAPI()

lisakim0

import streamlit as st
from langchain_community.document_loaders import PDFPlumberLoader
from langchain_experimental.text_splitter import SemanticChunker
from langchain_community.embeddings import HuggingFaceEmbeddings
from langchain_community.vectorstores import FAISS
from langchain_community.llms import Ollama
from langchain.prompts import PromptTemplate
from langchain.chains.llm import LLMChain
from langchain.chains.combine_documents.stuff import StuffDocumentsChain
from langchain.chains import RetrievalQA