The Nuvolos python library for database connectivity, internal PyODBC-based version
Project description
Nuvolos connector for Python (PyODBC version, for internal use)
This package allows you to read table data from Nuvolos and upload Pandas dataframes as tables.
Loading data to Nuvolos
This package provides a to_sql
function, which bulk loads a Pandas DataFrame to Nuvolos.
This function is able to load large DataFrames quickly and efficiently, using the database engine's bulk data ingestion process.
It is based on the write_pandas
function of the snowflake-connector-python
package.
Note:
It is recommended to use lowercase DataFrame column and index names. Uppercase or mixed-case DataFrame column/index names will result in case-sensitive table name and column names, which can be queried with quoted identifiers.
Syntax:
def to_sql(
df,
name,
con,
database=None,
schema=None,
if_exists="fail",
index=True,
index_label=None,
nanoseconds=False,
):
"""
Load a DataFrame to the specified table in the database.
Creates the table if it doesn't yet exist, with TEXT/FLOAT/DATE/TIMESTAMP columns as required.
The name will be case sensitive (quoted) if it contains lowercase or special characters or is a reserved keyword.
Based on the write_pandas function of snowflake-connector-python:
https://docs.snowflake.com/en/user-guide/python-connector-api.html#write_pandas
:param df: The Pandas DataFrame to insert/stage as a table.
:param name: The name of the database table. It will only be quoted and case sensitive if it contains keywords or special chars.
:param con: The pre-opened database Connection to use.
:param database: The name of the database to which data will be inserted.
:param schema: The name of the schema to which data will be inserted.
:param if_exists: How to behave if the table already exists. {‘fail’, ‘replace’, ‘append’}, default ‘fail’
* fail: Raise a ValueError.
* replace: Drop the table before inserting new values.
* append: Insert new values to the existing table.
:param index: bool, default True: Write DataFrame index as a column. Uses index_label as the column name in the table.
:param index_label: Column label for index column(s). If None is given (default) and index is True, then the index names are used. A sequence should be given if the DataFrame uses MultiIndex.
:param nanoseconds: If True, nanosecond timestamps will be used to upload the data. Limits timestamp range from 1677-09-21 00:12:43.145224192 to 2262-04-11 23:47:16.854775807.
:return: Returns the COPY INTO command's results to verify ingestion in the form of a tuple of whether all chunks were
ingested correctly, # of chunks, # of ingested rows, and ingest's output.
"""
Usage example:
In this example, the DataFrame will be loaded to a table named "quotes_AND_index", which is a case-sensitive name.
from nuvolos import get_connection, to_sql
import pandas as pd
conn = get_connection()
to_sql(
df=df,
name="lowercase_is_best",
con=conn,
index=True,
index_label="seq_num",
if_exists="replace"
)
df_r = pd.read_sql('SELECT * FROM lowercase_is_best;', con=conn, index_col="seq_num")
df_c = df.compare(df_r) # Will be an empty DataFrame, as there are no differences.
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