Extra 5 Python trends for automated data collection in 2024
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In the capacity of a trusted proxy website, the Dexodata team takes understandable interest in the domain of data harvesting solutions. It comes as no surprise that we like to explore the potential of Python in terms of web scraping tools. As a popular object-oriented language, it is used by numerous users who buy residential IP addresses. We have published an overview of major Python trends earlier. Today we continue this journey and add 5 extra aspects to consider in 2024. These hints might help you build even better solutions to grab datasets, preferably, with our ethical and KYC-compliant IPs, including proxies for social networks.
To begin, why is Python in great demand among the members of the web scraping professional community? It is simple to master and speedy in terms of code execution. Managing its syntax is no rocket science. As a language, it is compatible with external packages and offers enough ready-to-go solutions.
Today, Dexodata invites readers to dive deeper.
Python in 2024: Top 5 trends to know and apply
Presenting the most crucial updates of the latest Python 3.12 version, we have emphasized five of trends to be aware of.
1. Asynchronous web scraping and asyncio
Why bother to deal with asynchronous programming for web scrapers? A typical app supposes a mix of tasks in the following two states while being executed. Task can be processed or wait for its turn to be “activated”. The state of processing means accessing and manipulating data. The state of waiting means the task is standing by until a file input is read in, a response to a query is sent by the server, and so forth.
If the process runs step by step, that is, your next task is processed only after the preceding one is accomplished, it will take time. In our case, only a single scraping request at a time can be handled. Speeding by this process is what asynchronous programming does. The idea here is to switch the execution process from a task that is currently waiting to a new one, dynamically and concurrently.
In the context of web scraping, the asynchronous approach will give a user an opportunity to initiate a potentially time-consuming task and still have an opportunity to react to other events, instead of waiting for the first lengthy task to get accomplished. As an outcome, a team becomes able to scrape multiple URL addresses and get these numerous things done quickly.
Dexodata, as a credible and trusted proxy website recommends you to try the asyncio library to build an asynchronous app for data harvesting. Asynchronous scraping practices will be particular helpful in case you intend to apply our proxies for social networks and grab a lot of info on social media. It is a promising Python trend in 2024.
2. Type annotating
The main consequence of type hints with Python, which is quite widespread, is that the latter advances code readability and mitigates the risks of runtime errors. Type annotations enable coders to “inform” Python concerning what one anticipates to be assigned to names at certain points in our programs. Hence, one can apply such annotations to verify that the program is, actually, performing what we expect.
As a trusted proxy website, we believe the main advantages of type hinting are as follows:
- It simplifies working with and comprehending our own code, as our useful variable names are followed by descriptions of the kind of data we intend them to be related to;
- Majority of up-to-date editors are capable of making the most of one's annotations to present actionable hints while a person activates functions;
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It is possible to apply such tools as mypy to verify that our type annotations are being observed, assisting ourselves with detecting and eliminating bugs caused by passing around incorrect types.
3. Jupyter Notebook used for interactive computing
As long as web scraping is about data, sometimes massive volumes of it, Dexodata has to mention Jupyter Notebook. Operating as an ethical infrastructure for raising online intelligence that provides proxies for social media, we know how elaborate and complex data harvesting and processing tools might be. Advanced projects in this field mandate collaboration between several developers and parties involved. This is exactly what Jupyter is for, as a Python trend of 2024.
It serves as an original web-based tool for generating, sharing, and jointly working on computational docs. In this capacity, it offers an intuitive, streamlined, document-centered engineering experience. Thus, in case you intend to build a web scraper of great proportions and functionalities, there can be no better environment for joint efforts.
4. Serverless web scraping with Python and trusted proxy websites
Serverless approaches have gotten popular recently, it is a real buzzword. And Python, due to its simplicity and adaptability, is an option in demand for it. The Dexodata team cannot omit this point on the list of Python trends of 2024.
What does “serveless” mean? It stands for a cloud-native engineering pattern enabling developers to craft and run their programs with no need for servers and related management activities. Servers do not disappear, but servers are not a factor to care about a lot during coding. All routine work of providing, handling, and scaling the needed server infrastructure is entrusted to cloud providers. As an outcome, developers can easily deploy their products in containers.
We are a trusted proxy website one can buy residential IPs from. That is the reason we take interest in serverless approaches to web scraping. In this role, serverless and cloud-based approaches are productive and effective for a range of reasons:
- Automated data harvesting is by default an input/output thing. The biggest share of time is reserved for waiting for HTTP responses sent. Hence, upscale CPU servers get irrelevant;
- Cloud functions are cost-effective and not a big thing to get rolling;
- Clouds serve as a perfect match for parallel scraping, which is a positive factor when it comes to ambitious scraping initiatives.
Expectedly, the best option Dexodata could recommend for “placing” a serverless web scraper created via Python, is provided by Amazon. It is an event-fueled computing service Lambda, enabling users to execute their code lines, and S3 for storing their objects. In our experience, for tech-savvy individuals, that will suffice even for complicated projects that might require our proxies for social networks and other advanced scenarios.
5. Scrapy
Our final point on the agenda is Scrapy. It is not new, but a lot has been posted about it recently. Dexodata has to address this issue.
As we believe, an open source framework Scrapy is amazing for the Python community that needs workable leverage for web scraping. To name a short list of its advantages, Scrapy offers such capabilities as:
- Multithreading
- “Travelling” from one link to another, aka web crawling
- Grabbing the data
- Validating the info collected
- Saving that info as files of different formats and datasets of associated with various bases, etc.
An opinionated framework, it mandates special knowledge concerning its guidelines and principles. One has to invest both time and effort into mastering Scrapy. However, once this steep learning curve is left behind, one is in the right position to elegantly address the most prevalent and specific web scraping challengers.
No matter on what Python-based web scraping trend our readers intend to capitalize, one is recommended to buy residential IP addresses, mobile or datacenter ones in 2024. Dexodata, a top-ranked and trusted proxy website, is ready to serve as a one-stop-shop for needs of this sort. Ethically maintained servers in 100+ countries, including proxies for social media, are available. Newcomers are entitled to request a proxy free trial.
