PDFDataExtractor

https://pdfdataextractor.readthedocs.io/en/latest/
Admin
PDFDataExtractor is a toolkit for automatically extracting semantic information from PDF files of...
Tokens:1,606
Snippets:26
Trust Score:9.6
Update:5 months ago
Show doc for...
Tokens:
Raw
### Install PDFDataExtractor

Source: https://pdfdataextractor.readthedocs.io/en/latest/getting_started/installation.html

Run this command in the project directory to install the package.

```bash
python setup.py install
```

--------------------------------

### Install ChemDataExtractor Dependency

Source: https://pdfdataextractor.readthedocs.io/en/latest/getting_started/installation.html

Install ChemDataExtractor using pip if you need to extract chemistry-related information.

```bash
pip install chemdataextractor
```

--------------------------------

### Extract Pure Text using PDFDataExtractor

Source: https://pdfdataextractor.readthedocs.io/en/latest/perform_extraction/extraction.html

Use this snippet to extract plain text content from a PDF file. Ensure the PDFDataExtractor library is installed and specify the correct path to your PDF.

```python
# Import PDFDataExtractor
from pdfdataextractor import Reader

# Spefify the path to the PDF file
path = r'the path to the PDF file'

# Create an instance
file = Reader()

# Read the file
pdf = file.read_file(path)

# Get pure text
pdf.plaintext()
```

--------------------------------

### Pass a PDF File to Reader

Source: https://pdfdataextractor.readthedocs.io/en/latest/getting_started/running.html

Specify the path to your PDF file, create a Reader instance, read the file, and test the returned PDF object. Ensure the path variable points to an actual PDF file.

```python
# Spefify the path to the PDF file
path = r'the path to the PDF file'

# Create an instance
file = Reader()

# Read the file
pdf = file.read_file(path)

# Test if pdf is returned successfully
pdf.test()
```

--------------------------------

### Clone PDFDataExtractor Repository

Source: https://pdfdataextractor.readthedocs.io/en/latest/getting_started/installation.html

Use this command to download the PDFDataExtractor source code from GitHub.

```bash
git clone git@github.com:cat-lemonade/PDFDataExtractor.git
```

--------------------------------

### Import Reader Module

Source: https://pdfdataextractor.readthedocs.io/en/latest/getting_started/running.html

Import the Reader class from the pdfdataextractor library to begin.

```python
from pdfdataextractor import Reader
```

--------------------------------

### Extract Chemistry Information with ChemDataExtractor

Source: https://pdfdataextractor.readthedocs.io/en/latest/perform_extraction/extraction.html

Utilize this snippet to perform chemistry-related information extraction alongside metadata extraction by setting the 'chem' flag to True. This leverages ChemDataExtractor for specialized chemical data.

```python
# Path to the PDF file
file = r'path to the file'

# Create an instance
reader = Reader()

# Read the file
pdf = reader.read_file(file)

# Show extracted chemical information
r = pdf.abstract(chem=True)
r.records.serialize()
```

--------------------------------

### Access Specific Image from PDF

Source: https://pdfdataextractor.readthedocs.io/en/latest/perform_extraction/extraction.html

This snippet shows how to access individual images embedded within a PDF document. Note that this feature is temporarily unavailable.

```python
# Import PDFDataExtractor
from pdfdataextractor import Reader

# Spefify the path to the PDF file
path = r'the path to the PDF file'

# Create an instance
file = Reader()

# Read the file
pdf = file.read_file(path)

# To access a specific image
pdf.iamge()[0]
```

--------------------------------

### Extract Semantic Information using PDFDataExtractor

Source: https://pdfdataextractor.readthedocs.io/en/latest/perform_extraction/extraction.html

This snippet demonstrates how to extract various semantic elements from a PDF, such as captions, keywords, titles, DOIs, abstracts, and journal details. It allows for granular extraction of journal information by specifying fields like 'name', 'year', 'volume', and 'page'.

```python
# Import PDFDataExtractor
from pdfdataextractor import Reader

# Spefify the path to the PDF file
path = r'the path to the PDF file'

# Create an instance
file = Reader()

# Read the file
pdf = file.read_file(path)

# Get Caption
pdf.caption()

# Get Keywords
pdf.keywords()

# Get Title
pdf.title()

# Get DOI
pdf.doi()

# Get Abstract
pdf.abstract()

# Get Journal
pdf.journal()

# Get Journal Name
pdf.journal('name')

# Get Journal Year
pdf.journal('year')

# Get Journal Volume
pdf.journal('volume')

# Get Journal Page
pdf.journal('page')

# Get Section titles and corresponding text
pdf.section()

# Get References
pdf.reference()
```
Tokens:
Raw