This module includes different Python modules and scripts ubiquiously used on scripts in SomEnergia cooperative but with no entity by themselves to have their own repository.

• venv: script to run a command under a Python virtual enviroment
• sql2csv.py: script to run parametrized sql queries and get the result as (tab separated) csv.
• tsv: module for quick TSV serialization (csv with tabs as separators) of yamlns.namespace and dict like objects
  • tsvread: provides TSV rows as yamlns.namespaces (dict specialization)
  • tsvwrite: writes a TSV from a sequence of dicts
• dbutils.py: module with db related functions
  • runsql: runs a file with a sql and returns the objects as yamlns namespaces
  • runsql_cached: like runsql but cache the results in a tsv file to avoid second runs
  • fetchNs: a generator that wraps db cursors to fetch objects with attributes instead of psycopg arrays
  • nsList: uses the former to build a list of such object (slower but maybe convinient)
  • csvTable: [deprecated, use runsql] turns the results of a query into a tab separated table with proper header names
  • pgconfig_from_environ: constructs a db connection configuration dictionary from PG environment variables
• config: configuration utils
  • load_py_config load a python file as configuration file
• isodates: String to time/date/datetime objects with naive/timezoned handling
• sheetfetcher.py: convenience class to retrieve data from gdrive spreadshets
• trace: quickly enable and disable tracing function calling by decorating them with @trace
• testutils: module with common test utilities
  • testutils.enterContext: (Py<3.11 polyfill) enters a context handler from setUp() ensuring is exited on teardown
  • testutils.destructiveTest: decorator to avoid running destructive tests in production
  • testutils.temp_path: context manager that provides a selfdestructing temporary directory for tests
  • testutils.working_dir: context manager that changes the current working directory and restores it afterwards
  • testutils.sandbox_dir: context manager that combines temp_path and working_dir
• erptree: extracts an object and its children from the erp (erppeek, odoo) with controlled recursion

Simplifies running a Python script under a given virtual environtment. This is specially useful to run Python scripts from crontab lines.

usage: venv /PATH/TO/PYTHON/VIRTUALENV COMMAND [PARAM1 [PARAM2...]]

Runs an SQL file and outputs the result of the query as tabulator separated csv.a

A local config.py file is required, or you should provide it as -C file.py It should contain a dict named pyscopg with the keyword parameters to psycopg2.connect.

You can provide query parameters either as yamlfile or as commandline options.

 sql2csv.py <sqlfile> [<yamlfile>] [--<var1> <value1> [--<var2> <value2> ..] ]

Having a query in a file.

params = dict(
   param1='value',
   param2=[1,3,4,5], # Useful for the IN clause
)
for item in runsql('myquery.sql', **params):
   print(item.id, item.description) # id and description should be columns in the query

Like sql2csv there must exist a config.py file or provide it with the config keyword parameter

Parameters are inserted as specified in psycopg2 documentation

TODO: db and cursor parameters to reuse existing ones.

If you know the results will be always the same, you can use runsql_cached instead. It will generate a tsv file name like the sql file with the results, and will use it instead of the query for next executions.

The usage of runsql_cached is quite similar to runsql to be exchangeable. runsql_cached just adds a couple of keyword arguments.

• cachefile: to override the default cache file (a name, a path or a file like object)
• force: to force the query execution even if the cache exists

Convenient cursor wrappers to make the database access code more readable.

Example:

import psycopg2, dbutils
db = psycopg2.connect(**dbconfiguration)
with db.cursor() as cursor :
	cursor.execute("SELECT name, age FROM people")
	for person as dbutils.fetchNs(cursor):
		if person.age < 21: continue
		print("{name} is {age} years old".format(person))

Convenient wraper for gdrive.

from sheetfetcher import SheetFetcher

fetcher = SheetFetcher(
	documentName='My Document',
	credentialFilename='drive-certificate.json',
	)
table = fetcher.get_range("My Sheet", "A2:F12")
fulltable = fetcher.get_fullsheet("My Sheet")

• Document selectors can be either an uri or the title
• Sheet selectors can be either an index, a name or an id.
• Range selectors can be either a named range, index tuple or a "A2:F5" coordinates.
• You should Create a certificate and grant it access to the document

This decorator is a fast helper to trace calls to functions and methods. It will show the name of the functions the values of the parameters and the returned values.

from trace import trace

@trace
def factorial(n):
    if n<1: return 1
    return n*factorial(n-1)

factorial(6)

('> factorial', (6,))
('> factorial', (5,))
('> factorial', (4,))
('> factorial', (3,))
('> factorial', (2,))
('> factorial', (1,))
('> factorial', (0,))
('< factorial', (0,), '->', 1)
('< factorial', (1,), '->', 1)
('< factorial', (2,), '->', 2)
('< factorial', (3,), '->', 6)
('< factorial', (4,), '->', 24)
('< factorial', (5,), '->', 120)
('< factorial', (6,), '->', 720)

These assertion has been moved to yamlns.testutils and yamlns.pytestutils. To maintain compatibility those imports cna also found in somutils.testutils.

assertNsEqual allows to assert equality on json/yaml like structures combining dicts, lists, numbers, strings, dates...

After normalizing the structure (sorting dict keys), the comparision is done on the YAML output so that differences are spoted as text diffs. yamlns.testutils also provides assertNsContains which ignores additional keys in the second parameter.

yamlns.pytestutils provides the equivalents for pytest

• assert_ns_equal
• assert_ns_contains

Also those pytest fixtures:

• test_name fixture
• text_snapshot fixture
• yaml_snapshot fixture

Context handler that creates a temporary directory and ensures it is deleted after exiting the context.

with testutils.temp_path() as tmp:
    # The folder will exist while you are in the context
    # You can use tmp as path
    with (tmp/"myfile").open() as f:
        f.write("yep")
# No trace of the folder after the context

Allows to open context handlers in setUp that get properly closed on teardown. This allows using context handlers as quick selfdestroying fixtures.

It is a polyfill of the homonimous method introduced in Python 3.11.

Usage:

from somutils.testutils import enterContext
class MyTest(unittest.TestCase):
	if not hasattr(unittest.TestCase, 'enterContext'):
		enterContext = enterContext

	def setUp(self):
		self.file = self.enterContext(open('myfile'))
		# on teardown, the file is closed

Changes the working dir while the context is active, and recovers the former working dir afterwards.

with testutils.working_dir("this/other/folder"):
    print(os.get_cwd()) # here we are in this/other/folder
print(os.get_cwd()) # here we are back to our previous working dir

Combines the former two context handlers to create a temporary directory, set it as current working dir and after the context ends, restore the working dir and clean up the temporary folder.

with testutils.sandbox_dir() as sandbox:
    # There you use tmp folder as path
    with Path("myfile").open() as f:
        f.write("yep")
# No trace of the folder after the context

An utility to avoid running destrutive tests in a production OpenERP. It is a decorator that checks wheter the erp configured in dbconfig has the testing flag and skips the test if it doesn't.

The script enable_destructive_test.py is also provided to set/unset that testing flag which is not defined by default.

Module for simplified isodate parsing and timezone handling.

Interprets strings like the ones the standard Print Dialog uses to specify pages to be printed. ie. "2,4,6-9,13" means "2, 4, from 6 to 9 and 13"

>>> [x for x in sequence("2,4,6-9,13")]
[2, 4, 6, 7, 8, 9, 13]

Creates an structure from ERP objects that you can navigate or dump as yaml. You can select fields to expand, taking just the name or the id, anonymize or removing. You can use dot notation to specify fields in related objects. For multiple relations, a subfield refers to the subfield in all related objects.

from somutils.erptree import erptree

O = Client(....)

partner = erptree(
	partnerAddress_id,
	O.ResPartnerAddress,
	expand = {
		# Will expand those attributes
		'partner_id': O.ResPartner,
		'partner_id.company': O.ResPartner,
	},
	pickName = [
		# For those fk pick the name instead of the default id,name tuple
		# pickId parameter does the analog with id
		'partner_id.state_id',
		'partner_id.country_id',
	],
	anonymize = [
		# Will tamper the value
		'email',
	],
	remove = [
		# Means clear this field
		'superfluous_field',
	],
	only = [
		# Means: just retrieve name and code from partner_id.company
		'partner_id.company.name',
		'partner_id.company.code',
	],
)