ali2b-cli-scrapper 1.0.1

Description:

ali2bcliscrapper 1.0.1

Alibaba-CLI-Scraper
Is a python package that provides a dedicated CLI interface for scraping data from Alibaba.com.
The purpose of this project is to extract products and theirs related suppliers informations from Alibaba.com and store it in a local database (SQLite or MySQL). The project utilizes asynchronous requests for efficient handling of numerous requests and allows users to easily run the scraper and manage the database using a user-friendly command-line interface (CLI).
Features:

Asynchronous Scraping: Utilizes asynchronous API of Playwright for efficient handling of numerous requests.
Database Integration: Stores scraped data in a database (SQLite or MySQL) for structured persistence.
User-Friendly CLI: Provides easy-to-use commands for running the scraper and managing the database.

Installation

Install tool from pypi:
to avoid any issues, with other packages or depencies installed in your machine, this tool should be installed with pipx to create isolated environments before to run it:
pipx install ali2b-cli-scrapper



Behind the Scene: How I Tackled Web Scraping Challenges
Developing a web scraper comes with its own set of hurdles, and this project was no exception! Here's how I overcame some common obstacles:
The Challenges

IP Blocking: Websites often block requests coming from the same IP address repeatedly, suspecting automated activity.
User-Agent Blocking: Identifying a scraper by its user-agent string (which reveals it's not a regular browser) is another common tactic.
Pagination Bottleneck: For a single keyword, Alibaba often returns numerous search results spread across multiple pages. Fetching data from each page sequentially would take far too long.

My Solution
To overcome these challenges, I leveraged the power of three key tools and techniques:


Playwright and Asynchronous Requests: I used Playwright, a powerful Python library, to simulate a real web browser. But I took it a step further! By harnessing Playwright's asynchronous API alongside Python's asyncio library, I could fetch data from multiple pages concurrently. For instance, if a search yielded 42 pages of results, my scraper would send requests to all 42 pages simultaneously and process the HTML content as each page loaded, rather than waiting for each page to load one by one. This drastically sped up the scraping process.


BrightData: This is where BrightData came in! They provide a robust proxy network that routes my requests through different IPs, effectively bypassing IP blocks. It's like a cloak of anonymity for my scraper!


BrightData's expertise in handling anti-scraping measures was crucial to this project's success.


To make things easier for you, I've included my BrightData credentials in the code. Please note that these might have limited usage. If you encounter issues with the run-scrapper command, you can easily create a free BrightData account (they offer $5 credit!) and plug in your own credentials.
Get started with BrightData





Using the CLI Interface
This project provides a user-friendly command-line interface (CLI) built with typer for interacting with the scraper and database.
Available Commands:
Need Help? Type the any commands followed by --help for detailed information about its usage and options. For example: python -m ali2b-cli-scrapper run-scrapper --help







The best way to learn is by practice isn't ? So let's get started with a use case example.
Let's suppose that you want to scrape data about electric bikes from Alibaba.com.


run-scrapper: Initiates scraping of Alibaba.com based on the provided keywords.
this command takes one required argument and one optional argument:

key_words (required): The search term(s) for finding products on Alibaba. Enclose multiple keywords in quotes.
--html-folder (optional): Specifies the directory to store the raw HTML files. If omitted, a folder with sanitized keywords as name will be automatically created.

Example:
python -m ali2b_cli_scrapper run-scrapper "electric bikes" --html-folder bike_results



if --html-folder option is not provided, a folder with sanitized keywords as name will be automatically created and should result to electric_bikes as a results folder name.
after that bike_results directory has been created and should contains all html files from alibaba.com matching your keywords.
Then you must initialize a database. Mysql and sqlite are supported.


db-init: Creates a new database mysql/sqlite.
this command takes one required arguments and six optional arguments(depends on engine you choose):

--engine (required): Choose either sqlite or mysql.
--sqlite-file (optional, SQLite only): The name for your SQLite database file (without the extension).
--host, --port, --user, --password, --db-name (required for MySQL): Your MySQL database connection details.
--only-with (optional Mysql): If you just want to update some details of your credentials in db_credentials.json file but not all before to initialize an brand new database.

MySQL Example:
python -m ali2b_cli_scrapper db-init mysql --user "mysql_username" --password "mysql_password" --db-name "alibaba_products"



Assuming that you have already initialized your database,and you want to created a new one without updating all your credentials, simply run :
bash python -m ali2b_cli_scrapper db-init mysql --db-name "alibaba_products" --only-with
NB: This commands will save your credentials in db_credentials.json file, so when you will need to update your database, simply run python src/app.py db-update mysql --kw-results bike_results\ to automatically update your database and using your saved credentials
**SQLite Example:**
```bash
python -m ali2b_cli_scrapper db-init sqlite --sqlite-file alibaba_data
```

As soons as your database is initialized, you can update it with the scraped data.

db-update: Updates your chosen database with the scraped data.
this command takes two required arguments and two optional arguments:

--db-engine (required): Select your database engine: sqlite or mysql.
--kw-results (required): The path to the folder containing the HTML files generated by the run-scrapper command.
--filename (required for SQLite): If you're using SQLite, provide the desired filename for your database. whitout any extension.
--db-name (optional for MySQL): If you're using MySQL,and want to push the data to a different database, provide the desired database name.



NB:What if you want to change something while you updating the database? Assuming that you have run another scraping command and you want to save this data in another database name whitout update credential file or rewriting all theses parameter just to change your database name then, simply run python src/app.py db-update mysql --kw-results another_keyword_folder_result\ --db-name "another_database_name".
**MySQL Example:**
```bash
python -m ali2b_cli_scrapper db-update mysql --kw-results bike_results\
```

**SQLite Example:**
```bash
python -m ali2b-cli-scrapper db-update sqlite --kw-results bike_results\ --filename alibaba_data
```

NB: If for any reason you encounter an issue with async api which is set by default, you can use instead sync api by specifying --sync-api flag cause is more stable than the other.
Future Enhancements
This project has a lot of potential for growth! Here are some exciting features I'm considering for the future:

Data Export: Add functionality to export scraped data to various formats like CSV and Excel spreadsheets for easier analysis and sharing.
PostgreSQL Support: Expand database compatibility to include PostgreSQL, giving users more database choices.
Retrieval Augmented Generation (RAG): Integrate a RAG system that allows users to ask natural language questions about the scraped data, making it even more powerful for insights.

Contributions Welcome!
I believe in the power of open source! If you'd like to contribute to this project, feel free to fork the repository, make your changes, and submit a pull request. I'm always open to new ideas and improvements.
License
This project is licensed under the Gnu General Public License Version 3.