c-l-nguyen

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# append all DataFrames into one before writing to single table in Hyper
final_df = df1.append(df2).append(df3).reset_index(drop=True)
pantab.frames_to_hyper({"pokemon": final_df}, "hyper/all_pokemon_in_one.hyper")

# this produces the same result as above
pantab.frame_to_hyper(df1, "hyper/all_pokemon_append.hyper", table = "pokemon")
pantab.frame_to_hyper(df2, "hyper/all_pokemon_append.hyper", table = "pokemon", table_mode = "a")
pantab.frame_to_hyper(df3, "hyper/all_pokemon_append.hyper", table = "pokemon", table_mode = "a")

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df1 = pd.read_csv("data/starter_pokemon_grass.csv")
df2 = pd.read_csv("data/starter_pokemon_fire.csv")
df3 = pd.read_csv("data/starter_pokemon_water.csv")

dict_df = {"grass": df1, "fire": df2, "water": df3}

pantab.frames_to_hyper(dict_df, "hyper/all_pokemon_separate.hyper")

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import csv
from tableauhyperapi import HyperProcess, Telemetry, Connection, CreateMode, NOT_NULLABLE, NULLABLE, SqlType, \
TableDefinition, Inserter, escape_name, escape_string_literal, HyperException, TableName

with HyperProcess(telemetry=Telemetry.DO_NOT_SEND_USAGE_DATA_TO_TABLEAU) as hyper:
    print("starting up Hyper Process")
    with Connection(hyper.endpoint, 'hyper/pokemon_hyper_api.hyper', CreateMode.CREATE_AND_REPLACE) as connection:
        print("creating or replacing pokemon_hyper_api.hyper")
        
        poke_table = TableDefinition(TableName('public','pokemon'), [

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# these two are equivalent
pantab.frame_from_hyper("hyper/pokemon_public.hyper", table = "pokemon")
pantab.frame_from_hyper("hyper/pokemon_public.hyper", table = TableName("public", "pokemon"))

c-l-nguyen

# this errors out with message "HyperException: Specified table does not exist: pokemon."
pantab.frame_from_hyper("hyper/pokemon_extract.hyper", table = "pokemon")

# need to specify schema to read table from
pantab.frame_from_hyper("hyper/pokemon_extract.hyper", table = TableName("Extract", "pokemon"))

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print(pantab.frames_from_hyper("hyper/pokemon_public.hyper").keys())
# dict_keys([TableName('public', 'pokemon')])

print(pantab.frames_from_hyper("hyper/pokemon_extract.hyper").keys())
# dict_keys([TableName('Extract', 'pokemon')])

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import pandas as pd
import pantab
from tableauhyperapi import TableName

df = pd.read_csv("data/starter_pokemon_grass.csv")

# save DataFrame output to .hyper file
pantab.frame_to_hyper(df, "hyper/pokemon_public.hyper", table = "pokemon")

# save to schema other than public

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1. Download basic instant client (and maybe the SQL*Plus package) at
https://www.oracle.com/database/technologies/instant-client/macos-intel-x86-downloads.html#ic_osx_inst
2. Unzip downloads
3. Mostly follow this tutorial: https://www.talkapex.com/2013/03/oracle-instant-client-on-mac-os-x/
	a. But create an /oracle folder in /usr/local folder instead
	b. Move the unzipped folders to /usr/local/oracle
	c. Put lines in .zshrc file if on macOS Catalina and set zsh as default shell
4. Get the tnsnames.ora file (and maybe the sqlnet.ora file) and move to
/usr/local/oracle/instantclient_19_3/network/admin
5. Go into Datagrip and set up an Oracle connection

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#### macOS startup chime
# 1. Enter macOS Recovery
# 2. Launch Terminal
# 3. Copy paste this command and press ENTER: nvram StartupMute=%00
# 4. Reboot
# Note that you must unmute your Mac in macOS to hear the chime.

#### To fix Messages not staying open
defaults write -g NSDisableAutomaticTermination -bool yes