py-spoo-url 0.0.6

Description:

pyspoourl 0.0.6

🚀 Simple URL shortening with advanced analytics, emoji aliases, and more using spoo.me


📖 Table of Contents

📦 Installing
📥 Importing
✂️ Shortening URL

For Non-emoji aliases
😎 For Emoji aliases


📊 URL Statistics

🔧 Initializing the class
👀 Viewing the Basic Statistics


Example Usage


📈 Generating Insightful Charts


Valid Data that can be passed to make the chart
Valid Chart types
Usage Example
👀 Heatmap Preview




📤 Exporting Stats Data
🧳 Dependencies
🚨 Error Codes
🤝 Support and Issues
🤗 Contributing
📜 Licence



📦 Installing
You can install this package using pip:
pip install py_spoo_url


📥 Importing
from py_spoo_url import Shorten, Statistics

✂️ Shortening URL
For Non-emoji aliases
shortener = Shortener()
long_url = "https://www.example.com"
short_url = shortener.shorten(long_url, password="SuperSecretPassword@444", max_clicks=100)
# for custom alias, put `alias=<your_choice>`

print(f"Shortened URL: {short_url}")

😎 For Emoji aliases
shortener = Shortener()
long_url = "https://www.example.com"
emoji_url = shorten.emojify(long_url) # pass password and max-clicks as shown above if you want
# for custom emoji alias, put `emoji_alias=<random_emoji_sequence>`

print(f"Emojified URL: {emoji_url}")

Note: The emoji sequence must contain actual emojies like 😆🤯...

📊 URL Statistics
The Statistics class enables you to retrieve detailed statistics for a given short code.
🔧 Initializing the class
from spoo_me import Statistics

# Initialize Statistics with a short code
stats = Statistics(short_code="ga") # replace with the shortcode you want
# if the shortUrl is password protected you have to pass the password too

👀 Viewing the Basic Statistics
print(f"Total Clicks: {stats.total_clicks}")
print(f"Total Unique Clicks: {stats.total_unique_clicks}")
print(f"Average Daily Clicks: {stats.average_daily_clicks}")
print(f"Clicks Analysis: {stats.clicks_analysis}")
print(f"Browser Analysis: {stats.browsers_analysis}")
# ... and more (details below)


List of the analytics you can access




Method/Attribute
Description




total_clicks
Total number of clicks on the short URL.


total_unique_clicks
Total number of unique clicks on the short URL.


average_daily_clicks
Average number of clicks per day.


average_monthly_clicks
Average number of clicks per month.


average_weekly_clicks
Average number of clicks per week.


last_click
Information about the last click on the short URL.


last_click_browser
Browser used for the last click.


last_click_platform
Operating system used for the last click.


created_at
Date when the short URL was created.


creation_time
Time of day when the short URL was created.


browsers_analysis
Analysis of browsers used for clicks.


platforms_analysis
Analysis of operating systems used for clicks.


country_analysis
Analysis of countries from which clicks originated.


referrers_analysis
Analysis of referrers (sources) of clicks.


clicks_analysis
Detailed analysis of daily clicks.


unique_browsers_analysis
Analysis of unique browsers used for clicks.


unique_platforms_analysis
Analysis of unique operating systems for clicks.


unique_country_analysis
Analysis of unique countries from which clicks originated.


unique_referrers_analysis
Analysis of unique referrers (sources) of clicks.


unique_clicks_analysis
Detailed analysis of daily unique clicks.


expired
Indicates if the short URL has expired.


password
Password associated with the short URL (if any).



Example Usage
print(f"Creation Time: {stats.creation_time}")


📈 Generating Insightful Charts
plt = stats.make_chart(data="browsers_analysis", chart_type="bar") # this returns an object of matplotlib
plt.show()

# ... and more (see below)

# generating countries heatmaps
plt = stats.make_countries_heatmap()
plt.savefig("heatmap.png", format="png", bbox_inches="tight", pad_inches=0.5, dpi=300,)

plt = stats.make_unique_countries_heatmap()
plt.savefig("unique_heatmap.png", format="png", bbox_inches="tight", pad_inches=0.5, dpi=300,)


List of Available Charts




Method
Description




make_chart
Create various types of charts based on the data provided.






Parameters
Description




data
Type of data to visualize (e.g., 'browsers_analysis', see below).


chart_type
Type of chart to create (e.g., "bar", "pie", "line", see below).


days
Number of days to consider for time-based analysis. (only for last_n_days_analysis and last_n_days_unique_analysis)



Valid Data that can be passed to make the chart

'browsers_analysis'
'platforms_analysis'
'country_analysis'
'referrers_analysis'
'clicks_analysis'
'unique_browsers_analysis'
'unique_platforms_analysis'
'unique_country_analysis'
'unique_referrers_analysis'
'unique_clicks_analysis'
'last_n_days_analysis'
'last_n_days_unique_analysis'

Valid Chart types

'bar'
'pie'
'line'
'scatter'
'hist'
'box'
'area'

Usage Example
plt = stats.make_chart('browsers_analysis', chart_type="bar")
plt.show()


👀 Heatmap Preview

📤 Exporting Stats Data
You can export the statistical data to various file formats, including Excel, CSV, and JSON:
# Export data to Excel
stats.export_data(filename="stats_export.xlsx", filetype="xlsx")

# Export data to CSV and compress into a ZIP file
stats.export_data(filename="stats_export", filetype="csv")

# Export data to Json
stats.export_data(filename="stats_export.json", filetypes="json")


🧳 Dependencies

matplotlib: For creating charts and visualizations.
requests: For making HTTP requests to the Spoo.me API.
pandas: For handling and manipulating data in tabular form. 🐼
geopandas: For creating geographical visualizations. 🌎

All of the dependencies are automatically installed while installing the package but in case of any errors, you can install all of the dependencies listed in the requirements.txt file.
🚨 Error Codes
To see the error codes returned by the API, please visit https://spoo.me/api
🤝 Support and Issues
If you encounter any issues or have questions about using the Spoo.me Python package, please open an issue on the GitHub repository.
🤗 Contributing
Contributions are welcome! If you have ideas for improvements or new features, feel free to fork the repository, make your changes, and submit a pull request
📜 Licence
This package is licensed under the MIT License - see the LICENSE file for details.










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