The PDF to Text API provides a fast and reliable solution for converting PDF files into plain text or words. This API allows users to extract the text content from a PDF document, making it ideal for various use cases such as text analysis, data extraction, and document processing.
The API utilizes advanced technologies to accurately convert PDF files into text, preserving the format and structure of the original document. The resulting text can be easily manipulated and analyzed, providing users with valuable insights and information.
The API is simple to use and can be integrated into existing workflows, eliminating the need for manual data entry and saving time and resources. The API is designed to handle a wide range of PDF files, including those with complex layouts and formatting, making it a versatile tool for a variety of applications.
In addition to being fast and reliable, the PDF to Text API is also secure and protected, ensuring the privacy and security of user data. With this API, businesses and organizations can quickly and easily extract text from PDF files, streamlining their operations and gaining valuable insights.
Pass the publicly accessible PDF URL and receive the text recognized in it.
Text Analysis: The API can be used to extract text from PDFs and perform text analysis, such as sentiment analysis, keyword extraction, and topic modeling.
Data Extraction: The API allows users to extract data from PDFs, such as tables, lists, and forms, for use in spreadsheets and databases.
Document Processing: The API can be used to convert PDFs into editable text, making it easier to manipulate and process documents for various purposes.
E-book Conversion: The API can be used to convert PDFs into plain text, making it easier to create e-books and other digital content.
Language Translation: The API can extract text from PDFs written in different languages, making it easier to translate documents for global audiences.
Besides the number of API calls, there are no other limitations
Pass the PDF URL and receive the extracted text.
PDF to Text - Endpoint Features
Object | Description |
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Request Body |
[Required] Json |
{"pages_text_array":["Introduction to Big DataLearning ObjectivesAt the end of this text, you should present the following learnings: Define big data.Discuss the Vs of big data and implications.Point out the types of data related to big data.IntroductionSince the beginning, man has stored data for himself and for others, through drawings on the rocks and rock art. This record was made with the aim of making some decision or enabling access to knowledge. As societies became more complex, the volume of data storage This led to the construction of libraries and the later invention of printing by Johannes Gutenberg around 1450. The abacus itself, a mechanical instrument of Chinese origin created in the 5th century BC, stored information about numbers and helped with computing. Later, the emergence of the internet for information exchange, during World War II and the Cold War (1945\u01521991), made it even more necessary data storage for further analysis. Over time, various ways of storing this information were developed: mainframes, floppy disks, tapes, hard drives, NAS (Network -Attached Storage), cluster environment, pen drives, CDs, DVDs. In modern society, data began to be produced from different sources, whether in social networks (photos, videos, messages), in online purchases, in deli very applications, in distance education courses, in transactions with currencies and digital banks. In addition, there was the replacement of roles, such as physical agenda, medical records, request for exams, for the digital context. In this sense, companies realized the value of storing and processing strategic data. Thus, the new power race became clear: data started to be seen as the new oil. As a result, we can observe a gradual growth in the production and storage of data througho ut history, until we reach the context of big data. In this chapter, you will study the concept and characteristics inherent to big data. the main types of data that are related to context.1 The data society and what defines big dataModern culture started to produce and store more data. With a computer or a smartphone in our hands, we now have access to a greater volume of information. Thus, the massive growth of sending photos, videos, audio and text messages made the social relationship become digital. It was in this scenario that the concept of big data emerged. According to Mauro, Greco and Grimaldi (2015, online document, our translation), big data is defined as follows: \ufb01Big Data represents information assets characterized by high volume, speed and var iety, which require specific technologies and analysis methods to be transformed in value [...]\ufb02.From the growth of hundreds of Terabytes of data, the context of big data began to be systematized.The definition of this term is based on five principles: spe ed, volume, variety, veracity and value .You will see that such principles always go together in this context. Thus, big data is a broad term that deals with several areas and composes the various related studies. In the academic area, departments were cre ated focused on engineering and data science. , in order to compose the sets of knowledge and studies that the area demanded. Soon, several professions related to this area also emerged. The data engineer deals with acquisition, storage and disposal strate gies. level of data. The data scientist and the machine learning engineer (in English, machine learning) make up the context of exploratory analysis, pattern recognition and predictive analysis, as well as other related contexts. similar to software engine ering DevOps, but focused on the context of the data.Introduction to big data2 ","The exponential production of data with the internet of thingsThe internet of things has emerged with remarkable potential, causing the context of connected devices to exponen tially increase agricultural production produces voluminous data every second, with monitoring in the chicken coop, monitoring the temperature and ambient humidity, among others. As a result, a large volume of data is produced. The production of refrigerat ors, air conditioners, fans, electric pans and other connected devices made daily life permeated by the internet of things .Thus, with so much data produced, it is necessary to organize a storage and processing structure for decision making. The term \ufb01inte rnet of things\ufb02 refers to the interconnection of intelligent devices, which produce, consume and transmit data. make up the context, in addition to several boards and embedded systems.The production of data by peopleThe biggest producers of given Away s in the world are human beings themselves. Previously, each could only create small notes for themselves or within a small group. Now, we have a massive online file sharing environment at our disposal. As we walk, we produce data through of our GPS positions, which are transmitted in real time via applications. Our speech produces data that is analyzed by virtual assistants. If we are hospitalized, our breathing will produce data, through sensors, for the medical record. the use of social networks is increasing , generating immense amounts of data. The sending of daily e -mails with advertisements and for closing deals, the allocation of photos of travel in the cloud and several other situations of our daily life generate data, in tremendous volume and speed.So, i n the age of big data, to live is to produce data.3Introduction to big data The production of public data by governmentsGovernments also produce a tremendous range of data, on the most diverse fronts: health, infrastructure, transport, education, tourism , economy, bids, contracts, among others. Federal Government website and are commonly consumed by entities that In addition, the market seeks to carry out, from this data, various predictive analyses. On the other hand, governments also use each other's da ta, 2 The Vs of big data and its impact on technologies and society Big data has changed the way companies see their data. Currently, each piece of information about their own business and customer has become crucial in decision making. In the academic con text, more and more processing and data analysis. In this sense, the characteristics of big data and its five Vs showed the systematization of the context, offering a vision of how studies and technological solutions should be. those proposed for the area. See below for more information on each of these aspects.Volume The reference to the size of the data produced and the need to store it encompasses the volume of big data. Currently, we are not talking about Terabytes, but about Zettabytes or of Brotonbyte s.Speed The speed in data production can be seen, for example, from the perspective of social networks, where we have millions of messages exchanged per minute.Imagine that a million people sent 10 messages only in the morning, that is, in the first six hours of your day. In that case, we would already have Introduction to big data4 ","10 million pieces of data to be stored. The reality, however, is much greater. The production of data is fast, whether in monitoring, through sensors, or in the data that pe ople themselves produce. VarietyThe multiplicity of file types within of big data is, in fact, a punctual characteristic. When we started to produce, mostly, digital data, we transformed physical tasks into online data. This data can be agendas, purchase o rders and deliveries, sending text messages , audio, video and image. This variety can be composed and stored, for example, in the HDFS file structure of Apache Hadoop, and managed by its various services, such as Hive, Hbase, Spark, among others. Veracity The composition of the veracity of the data in big data is a characteristic part of data quality and continuous improvement. We cannot use data that do not represent the problem or that have a bias. In this context, data science deals with cleaning and org anizing the data, in order to increase the framework for the context of data quality comes from The Dama guide to the data management body of knowledge that help in data governance.ValorThe first step that occurred in big data was the need to store the dat a, for only later see what to do with them. This was because it was realized that, with the rise of predictive analytics, having a lot of data about a given context could be invaluable. .The use of data for companies was already used in business intelligen ce, which became known for the theories of the data warehouse and the respective specificities, with techniques to create data structures and enter the dashboards. However, predictive analysis has gained immense importance , since everyone wants to predict the future based on several variables in a context.5Introduction to big data Other VsAccording to Taleb, Serhani and Dssouli (2019), there are still other Vs involved. Some of them are variability, which consists of the constant change of security issue s. Data ingestion and storage in Apache HadoopData can take different forms. structured as spreadsheets, in ERP systems, they can be semi -structured or unstructured, like data from social networks, or they can come from a network of wireless sensors that p roduce information such as temperature, humidity or pressure (Figure 1).Figure 1.The various data types of "],"pdf_complete_text":"Introduction to Big DataLearning ObjectivesAt the end of this text, you should present the following learnings: Define big data.Discuss the Vs of big data and implications.Point out the types of data related to big data.IntroductionSince the beginning, man has stored data for himself and for others, through drawings on the rocks and rock art. This record was made with the aim of making some decision or enabling access to knowledge. As societies became more ...
curl --location --request POST 'https://zylalabs.com/api/1341/pdf+text+extractor+api/1122/pdf+to+text' --header 'Authorization: Bearer YOUR_API_KEY'
--data-raw '{
"url_pdf": "https://halo-pro.com/pdfingles.pdf"
}'
Header | Description |
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Authorization
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[Required] Should be Bearer access_key . See "Your API Access Key" above when you are subscribed. |
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