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# CSV-UTILS DOCUMENTATION
# CSV-UTILITE DOCUMENTATION

csv-util is a Python package designed to facilitate working with CSV files in a more convenient and Pythonic manner compared to the built-in csv module. It provides a set of modules with classes and functions to perform various tasks related to CSV file handling.
csv-utilite is a Python package designed to facilitate working with CSV files in a more convenient and Pythonic manner compared to the built-in csv module. It provides a set of modules with classes and functions to perform various tasks related to CSV file handling.

## Installation

You can install csv-util via pip:
You can install csv-utilite via pip:

```pip install csv-utils ```
```pip install csv_utilite ```

## CORE MODULES

### Reader

This module contains the Reader class, which extends the functionality of csv.reader. It offers additional features such as automatic type casting, handling missing values, and support for different dialects.

``` from csv_util.reader import Reader ```
``` from csv_utilite import Reader ```

### Example usage
```python
from csv_utils.reader import Reader
from csv_utilite import Reader

with open('kano.csv', 'r') as file:
with open('myfile.csv', 'r') as file:
reader = Reader(file, dialect='excel', type_cast=True, na_values=['', 'NULL'])
for row in reader:
print(row)
Expand All @@ -32,11 +32,11 @@ with open('kano.csv', 'r') as file:

The writer.py module includes the Writer class, a subclass of csv.writer, enhanced with features like automatic type casting and support for different dialects.

``` from csv_util.writer import Writer ```
``` from csv_utilite import Writer ```

### Example usage
```python
from csv_utils.writer import Writer
from csv_utilite import Writer
with open('output.csv', 'w', newline='') as file:
writer = Writer(file, dialect='excel', na_rep='NA')
writer.writerow([1, 2.5, True, None, 'abc'])
Expand All @@ -50,19 +50,19 @@ with open('output.csv', 'w', newline='') as file:
This module provides functions for common operations on CSV data, such as filtering rows, sorting, merging multiple files, and handling headers.


``` from csv_util.manipulation import filter_rows, sort_rows ```
``` from csv_utilite import filter_rows, sort_rows ```

### Example usage
```python
from csv_utils.manipulation import filter_rows, sort_rows, merge_files
from csv_utilite import filter_rows, sort_rows, merge_files
# Filter rows
data = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
filtered_data = filter_rows(data, lambda row: sum(row) > 10)
print(filtered_data) # Output: [[7, 8, 9]]
print(filtered_data)

# Sort rows
sorted_data = sort_rows(data, key=lambda row: row[1], reverse=True)
print(sorted_data) # Output: [[7, 8, 9], [4, 5, 6], [1, 2, 3]]
print(sorted_data)

# Merge files
file_paths = ['file1.csv', 'file2.csv', 'file3.csv']
Expand All @@ -76,28 +76,28 @@ merge_files(file_paths, output_path, dialect='excel', has_header=True)
formatting.py includes functions for formatting CSV data, such as adding or removing quotes, handling newlines within fields, and customizing delimiters.


``` from csv_util.formatting import add_quotes, remove_quotes ```
``` from csv_utilite import add_quotes, remove_quotes ```

### Example usage

```python
import csv
from csv_utils.formating import quote_fields, remove_quotes, handle_newlines
from csv_utilite import quote_fields, remove_quotes, handle_newlines

# Quote fields
data = [['Name', 'Age', 'City'], ['John', 25, 'New York'], ['Jane', 30, 'London, UK']]
quoted_data = quote_fields(data, quoting=csv.QUOTE_NONNUMERIC)
print(quoted_data) # Output: [['Name', 'Age', '"London, UK"'], ['"John"', '25', '"New York"'], ['"Jane"', '30', '"London, UK"']]
print(quoted_data)

# Remove quotes
quoted_data = [['"Name"', '"Age"', '"City"'], ['"John"', '"25"', '"New York"'], ['"Jane"', '"30"', '"London, UK"']]
unquoted_data = remove_quotes(quoted_data)
print(unquoted_data) # Output: [['Name', 'Age', 'City'], ['John', '25', 'New York'], ['Jane', '30', 'London, UK']]
print(unquoted_data)

# Handle newlines
data = [['Name', 'Address'], ['John', '123 Main St.\nNew York, NY'], ['Jane', 'Flat 5\nLondon, UK']]
formatted_data = handle_newlines(data, replacement=' ')
print(formatted_data) # Output: [['Name', 'Address'], ['John', '123 Main St. New York, NY'], ['Jane', 'Flat 5 London, UK']]
print(formatted_data)

```

Expand All @@ -106,12 +106,12 @@ print(formatted_data) # Output: [['Name', 'Address'], ['John', '123 Main St. Ne

The validation.py module provides functions to validate CSV data against predefined rules or schemas, ensuring data integrity and consistency.

``` from csv_util.validation import validate_schema ```
``` from csv_utilite import validate_schema ```

### Example usage

```python
from csv_utils.validation import validate_rows, validate_headers
from csv_utilite import validate_rows, validate_headers
# Validate rows
data = [[1, 2, 3], [4, 'five', 6], [7, 8, 'nine']]
validators = {
Expand All @@ -120,13 +120,13 @@ validators = {
2: lambda x: isinstance(x, int) and x < 10
}
valid_data = validate_rows(data, validators)
print(valid_data) # Output: [[1, 2, 3], [7, 8, 'nine']]
print(valid_data)

# Validate headers
headers = ['Name', 'Age', 'City', 'Country']
required_headers = ['Name', 'Age', 'City']
is_valid = validate_headers(headers, required_headers)
print(is_valid) # Output: True
print(is_valid)

```

Expand All @@ -136,21 +136,22 @@ print(is_valid) # Output: True
This module contains functions to convert CSV data to and from other formats like JSON, Excel, SQL tables, etc.


``` from csv_util.conversion import csv_to_json, json_to_csv ```
``` from csv_utilite import csv_to_json, json_to_csv ```

### Example usage

```pyhton
from csv_utils.conversion import csv_to_json, json_to_csv
```python

from csv_utilite import csv_to_json, json_to_csv
# CSV to JSON
data = [['Name', 'Age', 'City'], ['John', 25, 'New York'], ['Jane', 30, 'London']]
json_data = csv_to_json(data[1:], headers=data[0], orient='records')
print(json_data) # Output: [{'Name': 'John', 'Age': 25, 'City': 'New York'}, {'Name': 'Jane', 'Age': 30, 'City': 'London'}]
print(json_data)

# JSON to CSV
json_data = [{'Name': 'John', 'Age': 25, 'City': 'New York'}, {'Name': 'Jane', 'Age': 30, 'City': 'London'}]
csv_data = json_to_csv(json_data, headers=['Name', 'Age', 'City'])
print(csv_data) # Output: [['Name', 'Age', 'City'], ['John', 25, 'New York'], ['Jane', 30, 'London']]
print(csv_data)

```

Expand All @@ -159,15 +160,15 @@ print(csv_data) # Output: [['Name', 'Age', 'City'], ['John', 25, 'New York'], [
The generation.py module includes functions to generate CSV files from various data sources, such as dictionaries, databases, or APIs.


from csv_util.generation import generate_from_dict
``` from csv_utilite import generate_from_dict ```

# Example usage

``` from csv_utils.generation import generate_from_db, generate_from_dict ```
``` from csv_utilite import generate_from_db, generate_from_dict ```

```python

from csv_utils.generation import generate_from_db, generate_from_dict
from csv_utilite import generate_from_db, generate_from_dict

# Generate CSV from a dictionary
data = {'Name': 'John', 'Age': 25, 'City': 'New York'}
Expand All @@ -187,6 +188,11 @@ output_path = 'output.csv'
generate_from_db(query, db_connection, output_path)

```
## Contributions

All meaningful contributions are welcome.

We appreciate any improvements, bug fixes, or new features you can contribute to this project. Feel free to fork this repository, make your changes, and submit a pull request.

# Conclusion
csv-util simplifies CSV file handling in Python by providing a comprehensive set of classes and functions for reading, writing, manipulating, formatting, validating, converting, and generating CSV data. With its intuitive API and enhanced features, csv-util is a valuable tool for data processing tasks involving CSV files.
csv-utilite simplifies CSV file handling in Python by providing a comprehensive set of classes and functions for reading, writing, manipulating, formatting, validating, converting, and generating CSV data. With its intuitive API and enhanced features, csv-utilite is a valuable tool for data processing tasks involving CSV files.

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