def create_nb_proj(project: str = 'project',
description: str = 'notebook project',
relative_to: str = '.',
sub_folders: bool = True):
''' Create notebook project.
This function uses the default configuration file ('config.json') to
create a default jupyter project folder.
Examples
--------
.. code-block::
create_nb_proj('eoin_dev')
Parameters:
-----------
project
project folder name.
description
project description.
relative_to
relative path to current folder (default '.')
Returns:
--------
None
'''
project_path = Path(relative_to).absolute().parent / project
# Check whether project folder exists
if project_path.exists():
raise FileExistsError(f'project: {project_path} already exists!')
# create project directory
try:
project_path.mkdir(parents=True, exist_ok=False)
except FileExistsError as e:
logger.info(e)
# Copy package default config.json and adjust as needed.
config_file = 'config.json'
config = get_config(config_file, info=False)
config['project'] = description
config['meta']['project'] = description
logger.debug(config)
# Write to the project default folder
new_config = project_path / config_file
with open(new_config, "w") as f:
json.dump(config, f)
if sub_folders:
create_nb_folders(project=project,
relative_to=relative_to)
logger.info(f'{project} folder created.')
def connections(file_name=None, return_type='dataframe'):
''' get all available defined database environments
Parameters
----------
file_name
json formatted connections file (similar to tnsnames.ora)
if None (default) uses ../src/config.json
return type
return object type: 'dataframe'(default) 'dictionary'
Returns
-------
dictionary or dataframe
Examples
--------
.. code-block::
df = connections(return_type='dataframe')
dict_config = connections(return_type='dictionary')
'''
if file_name == None:
default_config = get_config('config.json')
file_name = default_config['connections']['location']
config = get_config(file_name, info=False)
logger.debug(config)
if return_type == 'dictionary':
return config
if return_type == 'dataframe':
df = (pd.DataFrame(config).T).fillna('')
if 'pw' in df.columns:
df = df.drop(columns=['pw'])
lowercase_cols = ['schema', 'sid', 'user']
for col in lowercase_cols:
if col in df.columns:
df[col] = df[col].str.lower()
return df
def get_styles(self, file_name=None):
''' Retrieve dictionary of styles allowing easy access to styles by name. '''
if file_name is None:
config = get_config('config.json')
else:
config = get_config(file_name)
styles_dict = get_config(config['excel']['formats'])
base_fmt = {'font_name': 'Calibri', 'font_size': 11}
def set_format(v):
v.update(deepcopy(base_fmt))
return self.wb.add_format(v)
styles = {k: set_format(v) for k, v in styles_dict.items()}
default = {'sheet_default': set_format(base_fmt)}
styles = {**styles, **default}
return styles
def get_metadata(self, meta_file=None):
''' Get XL metadata
Parameters
----------
meta_file
If None defaults to 'config.json'
Returns
-------
Dictionary of xl meta information.
'''
if meta_file is None:
config = get_config('config.json', info=False)
else:
xl_meta = get_config(meta_file, info=False)
xl_meta = get_config(config['excel']['meta'], info=False)
return xl_meta
def test_get_config_valid_with_info(get_complete_config):
file_name = 'piper/temp/test_config.json'
# Convert dictionary to json format, write to test temp config file
json_data = json.dumps(get_complete_config)
with open(file_name, 'w') as f:
f.write(json_data)
# Read the data back and load to dict object
with open(file_name, 'r') as f:
expected = json.load(f)
actual = get_config(file_name, info=True)
assert expected == actual
def test_get_config_file_name_invalid_returns_NONE():
assert get_config(file_name='invalid', info=False) is None