Your daily Python utility
Project description
Using this library
Installation
pip install utill
Usage syntax
from utill.__MODULE__ import __OBJECT__
Example
# Using the string module
from utill.my_string import generate_random_string
print(generate_random_string(16))
Initial set up
This package contains CLI command
utill conf init
Additional extensions
Syntax
pip install utill[__EXTENSION_NAME__]
Extension list:
- google-cloud
- postgresql
Per module usages
my_bq
Executing a query
from utill.my_bq import BQ
# Initialize BigQuery client
bq = BQ()
# Execute a query, returns iterable QueryJob
job = bq.execute_query('...')
# Convert into list for quick data conversion
results = list(job)
# Iterate the results
for row in job:
# Do anything with the row
Uploading CSV file into BigQuery table
from utill.my_bq import BQ, Dtype, LoadStrategy
# Initialize BigQuery client
bq = BQ()
# Load the data
filename = '/path/to/file.csv' # Your local CSV file location
bq_table_fqn = 'project.dataset.table' # An FQN (fully qualified name) of a BigQuery table to export
columns = {
'col1': Dtype.INT64,
'col2': Dtype.STRING,
'col3': Dtype.DATE,
...
}
partition_col = 'col3' # Optional, for performance and cost optimization
cluster_cols = ['col1'] # Optional, for performance and cost optimization
load_strategy = LoadStrategy.APPEND # Optional, default to APPEND
bq.upload_csv(filename, bq_table_fqn, columns, partition_col, cluster_cols, load_strategy)
Exporting query into CSV
from utill.my_bq import BQ
# Initialize BigQuery client
bq = BQ()
query = 'SELECT * FROM `project.dataset.table`' # The query to export
filename = '/path/to/file.csv' # Destination CSV file location
bq.download_csv(query, filename)
Exporting table into XLSX
from utill.my_bq import BQ
# Initialize BigQuery client
bq = BQ()
bq_table_fqn = 'project.dataset.table' # An FQN (fully qualified name) of a BigQuery table to export
filename = '/path/to/file.xlsx' # Destination XLSX file location
bq.download_xlsx(src_table_fqn, dst_filename)
Project details
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