tocase leverages the regex library to convert your strings into any case.
To install the package run the following command:
pip install tocaseOnce installed import the ToCase class.
from tocase.tocase import ToCaseIt is a naming convention where the first letter in compound words is capitalized, except for the first one.
# Example with simple string
Tocase("camel-case").camel() # ==> camelCase
Tocase("camel case").camel() # ==> camelCase
# Example with Pandas DataFrame and Iris DataFrame
list(df_with_original_column_names.columns) = ['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species']
df_with_modified_column_names = df.rename(columns=lambda x: ToCase(x).camel())
list(df_with_modified_column_names.columns) = ['sepalLength', 'sepalWidth', 'petalLength', 'petalWidth', 'species']It is a naming convention where all letters in compound words are capitalized. Words are joined with an underscore.
# Example with simple string
Tocase("Constant-case").constant() # ==> CONSTANT_CASE
Tocase("constant Case").constant() # ==> CONSTANT_CASE
# Example with Pandas DataFrame and Iris DataFrame
list(df_with_original_column_names.columns) = ['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species']
df_with_modified_column_names = df.rename(columns=lambda x: ToCase(x).constant())
list(df_with_modified_column_names.columns) = ['SEPAL_LENGTH', 'SEPAL_WIDTH', 'PETAL_LENGTH', 'PETAL_WIDTH', 'SPECIES']It is a naming convention where all letters in compound words are lowercased. Words are joined with a dot.
# Example with simple string
Tocase("Dot-case").dot() # ==> dot.case
Tocase("dot Case").dot() # ==> dot.case
# Example with Pandas DataFrame and Iris DataFrame
list(df_with_original_column_names.columns) = ['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species']
df_with_modified_column_names = df.rename(columns=lambda x: ToCase(x).dot())
list(df_with_modified_column_names.columns) = ['sepal.length', 'sepal.width', 'petal.length', 'petal.width', 'species']It is a naming convention where the first letter in compound words is capitalized. Words are joined by a dash.
# Example with simple string
Tocase("Header-case").header() # ==> Header-Case
Tocase("header Case").header() # ==> Header-Case
# Example with Pandas DataFrame and Iris DataFrame
list(df_with_original_column_names.columns) = ['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species']
df_with_modified_column_names = df.rename(columns=lambda x: ToCase(x).header())
list(df_with_modified_column_names.columns) = ['Sepal-Length', 'Sepal-Width', 'Petal-Length', 'Petal-Width', 'Species']It is a naming convention where all letters in compound words are lowercased. Words are joined by a dash.
# Example with simple string
Tocase("Kebab-case").kebab() # ==> kebab-case
Tocase("kebab Case").kebab() # ==> kebab-case
# Example with Pandas DataFrame and Iris DataFrame
list(df_with_original_column_names.columns) = ['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species']
df_with_modified_column_names = df.rename(columns=lambda x: ToCase(x).kebab())
list(df_with_modified_column_names.columns) = ['sepal-length', 'sepal-width', 'petal-length', 'petal-width', 'species']It is a naming convention where the first letter in compound words is capitalized.
# Example with simple string
Tocase("Pascal-case").pascal() # ==> PascalCase
Tocase("pascal Case").pascal() # ==> PascalCase
# Example with Pandas DataFrame and Iris DataFrame
list(df_with_original_column_names.columns) = ['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species']
df_with_modified_column_names = df.rename(columns=lambda x: ToCase(x).pascal())
list(df_with_modified_column_names.columns) = ['SepalLength', 'SepalWidth', 'PetalLength', 'PetalWidth', 'Species']It is a naming convention where all letters in compound words are lowercased. Words are joined by an underscore.
# Example with simple string
Tocase("Snake-case").snake() # ==> snake_case
Tocase("snake Case").snake() # ==> snake_case
# Example with Pandas DataFrame and Iris DataFrame
list(df_with_original_column_names.columns) = ['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species']
df_with_modified_column_names = df.rename(columns=lambda x: ToCase(x).snake())
list(df_with_modified_column_names.columns) = ['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species']It is a naming convention where the first letter in compound words is capitalized. Words are separated by a space.
# Example with simple string
Tocase("Title-case").title() # ==> "Title Case"
Tocase("title Case").title() # ==> "Title Case"
# Example with Pandas DataFrame and Iris DataFrame
list(df_with_original_column_names.columns) = ['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species']
df_with_modified_column_names = df.rename(columns=lambda x: ToCase(x).title())
list(df_with_modified_column_names.columns) = ['Sepal Length', 'Sepal Width', 'Petal Length', 'Petal Width', 'Species']Clone or download the repository on your machine. If you have poetry installed just run the following command to restore the working environment:
poetry installIf you don't have poetry you can use pip and the requirements.txt file:
pip install -r requirements.txtTo run tests, stay at the root of the directory and run:
pytest -vAll contributions are more than welcome. So feel free to to make a PR.
Faouzi Braza
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