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textextractor.html
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textextractor.html
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<main>
<article id="content">
<header>
<h1 class="title">Module <code>ktrain.text.textextractor</code></h1>
</header>
<section id="section-intro">
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">from .. import utils as U
from ..imports import *
from . import textutils as TU
try:
import textract
TEXTRACT_INSTALLED = True
except ImportError:
TEXTRACT_INSTALLED = False
JAVA_INSTALLED = U.checkjava()
class TextExtractor:
"""
```
Text Extractor: a wrapper to textract package
```
"""
def __init__(self, use_tika=True):
if use_tika:
try:
from tika import parser
except ImportError as e:
raise ValueError(
"If use_tika=True, then TextExtractor requires tika: pip install tika"
)
except PermissionError as e:
raise PermissionError(
f"There may already be a /tmp/tika.log file from another user - please delete it or change permissions: {e}"
)
if not use_tika and not TEXTRACT_INSTALLED:
raise ValueError(
"If use_tika=False, then TextExtractor requires textract: pip install textract"
)
self.use_tika = use_tika
def extract(
self, filename=None, text=None, return_format="document", lang=None, verbose=1
):
"""
```
Extracts text from document given file path to document.
filename(str): path to file, Mutually-exclusive with text.
text(str): string to tokenize. Mutually-exclusive with filename.
The extract method can also simply accept a string and return lists of sentences or paragraphs.
return_format(str): One of {'document', 'paragraphs', 'sentences'}
'document': returns text of document
'paragraphs': returns a list of paragraphs from document
'sentences': returns a list of sentences from document
lang(str): language code. If None, lang will be detected from extracted text
verbose(bool): verbosity
```
"""
if filename is None and text is None:
raise ValueError(
"Either the filename parameter or the text parameter must be supplied"
)
if filename is not None and text is not None:
raise ValueError("The filename and text parameters are mutually-exclusive.")
if return_format not in ["document", "paragraphs", "sentences"]:
raise ValueError(
'return_format must be one of {"document", "paragraphs", "sentences"}'
)
if filename is not None:
mtype = TU.get_mimetype(filename)
try:
if mtype and mtype.split("/")[0] == "text":
with open(filename, "r") as f:
text = f.read()
text = str.encode(text)
else:
text = self._extract(filename)
except Exception as e:
if verbose:
print("ERROR on %s:\n%s" % (filename, e))
try:
text = text.decode(errors="ignore")
except:
pass
if return_format == "sentences":
return TU.sent_tokenize(text, lang=lang)
elif return_format == "paragraphs":
return TU.paragraph_tokenize(text, join_sentences=True, lang=lang)
else:
return text
def _extract(self, filename):
if self.use_tika:
from tika import parser
if JAVA_INSTALLED:
parsed = parser.from_file(filename)
text = parsed["content"]
else:
raise Exception("Please install Java for TIKA text extraction")
else:
text = textract.process(filename)
return text.strip()</code></pre>
</details>
</section>
<section>
</section>
<section>
</section>
<section>
</section>
<section>
<h2 class="section-title" id="header-classes">Classes</h2>
<dl>
<dt id="ktrain.text.textextractor.TextExtractor"><code class="flex name class">
<span>class <span class="ident">TextExtractor</span></span>
<span>(</span><span>use_tika=True)</span>
</code></dt>
<dd>
<div class="desc"><pre><code>Text Extractor: a wrapper to textract package
</code></pre></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">class TextExtractor:
"""
```
Text Extractor: a wrapper to textract package
```
"""
def __init__(self, use_tika=True):
if use_tika:
try:
from tika import parser
except ImportError as e:
raise ValueError(
"If use_tika=True, then TextExtractor requires tika: pip install tika"
)
except PermissionError as e:
raise PermissionError(
f"There may already be a /tmp/tika.log file from another user - please delete it or change permissions: {e}"
)
if not use_tika and not TEXTRACT_INSTALLED:
raise ValueError(
"If use_tika=False, then TextExtractor requires textract: pip install textract"
)
self.use_tika = use_tika
def extract(
self, filename=None, text=None, return_format="document", lang=None, verbose=1
):
"""
```
Extracts text from document given file path to document.
filename(str): path to file, Mutually-exclusive with text.
text(str): string to tokenize. Mutually-exclusive with filename.
The extract method can also simply accept a string and return lists of sentences or paragraphs.
return_format(str): One of {'document', 'paragraphs', 'sentences'}
'document': returns text of document
'paragraphs': returns a list of paragraphs from document
'sentences': returns a list of sentences from document
lang(str): language code. If None, lang will be detected from extracted text
verbose(bool): verbosity
```
"""
if filename is None and text is None:
raise ValueError(
"Either the filename parameter or the text parameter must be supplied"
)
if filename is not None and text is not None:
raise ValueError("The filename and text parameters are mutually-exclusive.")
if return_format not in ["document", "paragraphs", "sentences"]:
raise ValueError(
'return_format must be one of {"document", "paragraphs", "sentences"}'
)
if filename is not None:
mtype = TU.get_mimetype(filename)
try:
if mtype and mtype.split("/")[0] == "text":
with open(filename, "r") as f:
text = f.read()
text = str.encode(text)
else:
text = self._extract(filename)
except Exception as e:
if verbose:
print("ERROR on %s:\n%s" % (filename, e))
try:
text = text.decode(errors="ignore")
except:
pass
if return_format == "sentences":
return TU.sent_tokenize(text, lang=lang)
elif return_format == "paragraphs":
return TU.paragraph_tokenize(text, join_sentences=True, lang=lang)
else:
return text
def _extract(self, filename):
if self.use_tika:
from tika import parser
if JAVA_INSTALLED:
parsed = parser.from_file(filename)
text = parsed["content"]
else:
raise Exception("Please install Java for TIKA text extraction")
else:
text = textract.process(filename)
return text.strip()</code></pre>
</details>
<h3>Methods</h3>
<dl>
<dt id="ktrain.text.textextractor.TextExtractor.extract"><code class="name flex">
<span>def <span class="ident">extract</span></span>(<span>self, filename=None, text=None, return_format='document', lang=None, verbose=1)</span>
</code></dt>
<dd>
<div class="desc"><pre><code>Extracts text from document given file path to document.
filename(str): path to file, Mutually-exclusive with text.
text(str): string to tokenize. Mutually-exclusive with filename.
The extract method can also simply accept a string and return lists of sentences or paragraphs.
return_format(str): One of {'document', 'paragraphs', 'sentences'}
'document': returns text of document
'paragraphs': returns a list of paragraphs from document
'sentences': returns a list of sentences from document
lang(str): language code. If None, lang will be detected from extracted text
verbose(bool): verbosity
</code></pre></div>
<details class="source">
<summary>
<span>Expand source code</span>
</summary>
<pre><code class="python">def extract(
self, filename=None, text=None, return_format="document", lang=None, verbose=1
):
"""
```
Extracts text from document given file path to document.
filename(str): path to file, Mutually-exclusive with text.
text(str): string to tokenize. Mutually-exclusive with filename.
The extract method can also simply accept a string and return lists of sentences or paragraphs.
return_format(str): One of {'document', 'paragraphs', 'sentences'}
'document': returns text of document
'paragraphs': returns a list of paragraphs from document
'sentences': returns a list of sentences from document
lang(str): language code. If None, lang will be detected from extracted text
verbose(bool): verbosity
```
"""
if filename is None and text is None:
raise ValueError(
"Either the filename parameter or the text parameter must be supplied"
)
if filename is not None and text is not None:
raise ValueError("The filename and text parameters are mutually-exclusive.")
if return_format not in ["document", "paragraphs", "sentences"]:
raise ValueError(
'return_format must be one of {"document", "paragraphs", "sentences"}'
)
if filename is not None:
mtype = TU.get_mimetype(filename)
try:
if mtype and mtype.split("/")[0] == "text":
with open(filename, "r") as f:
text = f.read()
text = str.encode(text)
else:
text = self._extract(filename)
except Exception as e:
if verbose:
print("ERROR on %s:\n%s" % (filename, e))
try:
text = text.decode(errors="ignore")
except:
pass
if return_format == "sentences":
return TU.sent_tokenize(text, lang=lang)
elif return_format == "paragraphs":
return TU.paragraph_tokenize(text, join_sentences=True, lang=lang)
else:
return text</code></pre>
</details>
</dd>
</dl>
</dd>
</dl>
</section>
</article>
<nav id="sidebar">
<h1>Index</h1>
<div class="toc">
<ul></ul>
</div>
<ul id="index">
<li><h3>Super-module</h3>
<ul>
<li><code><a title="ktrain.text" href="index.html">ktrain.text</a></code></li>
</ul>
</li>
<li><h3><a href="#header-classes">Classes</a></h3>
<ul>
<li>
<h4><code><a title="ktrain.text.textextractor.TextExtractor" href="#ktrain.text.textextractor.TextExtractor">TextExtractor</a></code></h4>
<ul class="">
<li><code><a title="ktrain.text.textextractor.TextExtractor.extract" href="#ktrain.text.textextractor.TextExtractor.extract">extract</a></code></li>
</ul>
</li>
</ul>
</li>
</ul>
</nav>
</main>
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