textpy 0.1.21

Reads a python file/module and statically analyzes it.

textpy

Reads a python file/module and statically analyzes it. This works well with Jupyter extensions in VScode, and have better performance when the file/module is formatted with PEP-8.

Installation

$ pip install textpy

Requirements

lazyr>=0.0.11
pandas>=1.4.0 # A lower version is also acceptable, but some features will be invalid

Examples

Create a new file named myfile.py under ./examples/ (or any dir, just for an example):

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from typing import *


class MyClass:
    def __init__(self):
        """Write something."""
        self.var_1 = "hahaha"
        self.var_2 = "blabla"


def print_my_class(a: MyClass):
    """
    Print something.

    Parameters
    ----------
    a : ThisIsAClass
        An object.

    """
    print(a.var_1, a.var_2)

Run the following codes to find all the occurrences of the pattern "va" in myfile.py:

>>> from textpy import textpy
>>> res = textpy("./examples/myfile.py").findall("va", styler=False)
>>> res
examples/myfile.py:10: '        self.var_1 = "hahaha"'
examples/myfile.py:11: '        self.var_2 = "blabla"'
examples/myfile.py:24: '    print(a.var_1, a.var_2)'

Also, when using a Jupyter notebook in VScode, you can run a cell like this:

>>> from textpy import textpy
>>> textpy("./examples/myfile.py").findall("va")

and the output will be like:

source	match
myfile.MyClass.__init__:10	self.var_1 = "hahaha"
myfile.MyClass.__init__:11	self.var_2 = "blabla"
myfile.print_my_class:24	print(a.var_1, a.var_2)

Note that in the Jupyter notebook case, the matched substrings are **clickable**, linking to where the patterns were found.

Now suppose you've got a python module consists of a few files, for example, our textpy module itself, you can do almost the same thing:

>>> module_path = "textpy/" # you can type any path here
>>> pattern = "note.*k" # type any regular expression here

>>> res = textpy(module_path).findall("note.*k", styler=False, line_numbers=False)
>>> res
textpy/abc.py: '            in a Jupyter notebook, this only takes effect when'
textpy/abc.py: '        in a Jupyter notebook.'
textpy/__init__.py: 'Also, when using a Jupyter notebook in VScode, you can run a cell like this:'
textpy/__init__.py: 'Note that in the Jupyter notebook case, the matched substrings are **clickable**, linking to where'
textpy/__init__.py: '>>> pattern = "note.*k" # type any regular expression here'
textpy/__init__.py: '>>> res = textpy(module_path).findall("note.*k", styler=False, line_numbers=False)'

See Also

Github repository

• https://github.com/Chitaoji/textpy/

PyPI project

• https://pypi.org/project/textpy/

License

This project falls under the BSD 3-Clause License.

History

v0.1.21

• Various improvements.

v0.1.20

• Fixed issues:
  • Incorrectly displayed file paths in the output of TextPy.findall(styler=False);
  • Expired file links in the output of TextPy.findall(styler=True, line_numbers=False).

v0.1.19

• Various improvements.

v0.1.18

• Updated LICENSE.

v0.1.17

• Refactored README.

v0.1.16

• Lazily imported pandas to reduce the time cost for importing.

v0.1.12

• New optional parameters for TextPy.findall() :
  • whole_word : whether to match whole words only;
  • case_sensitive : specifies case sensitivity.

v0.1.10

• New optional parameter for textpy() :
  • encoding : specifies encoding.

v0.1.9

• Removing unnecessary dependencies.

v0.1.8

• Bugfix for Windows.

v0.1.5

• Compatible with pandas versions lower than 1.4.0.
• Updated textpy() :
  • Path objects are now acceptable as parameters.
  • New optional parameter home to specify the home path.
• More flexible presentation of output from TextPy.findall().

v0.1.4

• Fixed a display problem of README on PyPI.

v0.1.3

• Initial release.