kmatt

# Alternative to_sql() *method* for mssql+pyodbc or mssql+pymssql
#
# adapted from https://pandas.pydata.org/docs/user_guide/io.html#io-sql-method
import json

import pandas as pd
import sqlalchemy as sa


def mssql_insert_json(table, conn, keys, data_iter):

kmatt

# version 1.2 - 2022-11-01
import pandas as pd
import sqlalchemy as sa


def df_upsert(data_frame, table_name, engine, schema=None, match_columns=None):
    """
    Perform an "upsert" on a SQL Server table from a DataFrame.

    Constructs a T-SQL MERGE statement, uploads the DataFrame to a

kmatt

Create a file:
$ vim /Users/Shared/logoutHook.sh

File content:
#!/bin/bash
say 'Hasta la vista baby!'

Set execution permission:
$ sudo chmod +x /Users/Shared/logoutHook.sh

kmatt

# brew install unixodbc

export CPPFLAGS="-I/opt/homebrew/Cellar/unixodbc/2.3.9_1/include"
export LDFLAGS="-L/opt/homebrew/Cellar/unixodbc/2.3.9_1/lib -liodbc -liodbcinst"
export PKG_CONFIG_PATH="/opt/homebrew/Cellar/unixodbc/2.3.9_1/lib/pkgconfig $PKG_CONFIG_PATH"
pip install --no-binary pyodbc pyodbc

kmatt

# ========= PROMPT =========
# Version control information
autoload -Uz vcs_info
precmd() { vcs_info }
# Format the vcs_info_msg_0_ variable
zstyle ':vcs_info:git:*' formats ' %b '

# Render the prompt
setopt PROMPT_SUBST

kmatt

" Maintainer:	Lars Nielsen (dengmao@gmail.com)
" Last Change:	January 22 2007
" https://dengmao.wordpress.com/2007/01/22/vim-color-scheme-wombat/

set background=dark

hi clear

if exists("syntax_on")
  syntax reset

kmatt

/*
ClickHouse client version 1.1.53996.
Connecting to localhost:9000.
Connected to ClickHouse server version 1.1.53996.
*/

:) CREATE TABLE IF NOT EXISTS `employee` (
:-]   `empid` Int32,
:-]   `deptid` Int32,
:-]   `salary` Int64

kmatt

Learn Go in ~5mins

This is inspired by A half-hour to learn Rust and Zig in 30 minutes.

Basics

Your first Go program as a classical "Hello World" is pretty simple:

First we create a workspace for our project:

kmatt

import pandas as pd
import visidata as vd
df=pd.read_csv('file.csv')
vd.view_pandas(df)

kmatt

create or replace function create_jsonb_flat_view
    (table_name text, regular_columns text, json_column text)
    returns text language plpgsql as $$
declare
    cols text;
begin
    execute format ($ex$
        select string_agg(format('%2$s->>%%1$L "%%1$s"', key), ', ')
        from (
            select distinct key