pythonic-xray 0.8

No project description provided

Simple Python Code Analyzer. With no dependencies!

Contents:

• Installation
• How to Run
• Options for console run
• Examples for console run
• Options for python call of analyse_code
• Example Output (short version)

---

Installation

pip install pythonic-xray

---

How to Run

You can run it directly from your console:

python -m pythonic_xray

or:

pythonic-xray

Or in your python code:

from pythonic_xray import analyse_code

analysis_str = analyse_code(
                    path_to_file_or_dir=".", 
                    code_strs=None, 
                    name="My Awesome Project", 
                    save_path="./", 
                    should_print=True, 
                    should_save=True,
                    short_analysis=True
                )

---

Options for console run

Option	Type	Default	Description
--path	str	.	Path to a Python file or folder containing Python files to analyze.
--name	str	"My Awesome Project"	Name of your project (used in saved results).
--verbose	flag	False	If included, prints the analysis results in the console.
--save	flag	False	If included, saves the analysis results to a file.
--save_path	str	"./"	Folder path where analysis results will be saved.
--short	flag	False	If included, a shorter version will be created.

---

Examples for console run

1. Quick inspection of a local project (no files written)
   Use this when you just want a fast overview of the current repository.

   pythonic-xray --verbose
   

2. Analyze a full project and store the results for later review
   This is useful when analyzing larger repositories or when you want to share results.

   pythonic-xray --path ./src --save --save_path ./analysis_results
   

3. Analyze a single module you are actively working on
   Focus on one file while developing or debugging a specific component.

   pythonic-xray --path ./models/tsmixer.py --name "TSMixer Module" --verbose
   

4. Short summary for CI, reports, or quick comparisons
   Generate a compact analysis that is easy to scan or archive.

   pythonic-xray --path . --save --short
   

5. Full analysis with custom project name (recommended)
   Generate a compact analysis that is easy to scan or archive.

   pythonic-xray --path . --name "Recommendation System v2" --verbose --save --save_path ./
   

---

Options for python call of analyse_code

Parameters

Parameter	Type	Default	Description
path_to_file_or_dir	str	None	Path to a single file or folder containing Python files (.py) or notebooks (.ipynb).
code_strs	list[str]	None	List of Python code strings to analyze.
name	str	"My Awesome Project"	Name used in the output analysis.
save_path	str	"./"	Path where the analysis text file code_analysis.txt will be saved.
should_print	bool	True	If True, prints the analysis to the console.
should_save	bool	True	If True, saves the analysis to code_analysis.txt.
short_analysis	bool	True	If True, outputs a shorter summary of the analysis.

Returns
This function does return the analysis text as str. Results are printed and/or saved into a code_analysis.txt depending on should_print and should_save.

---

Example Output (short version)

_________________________________________
    >>> Analysis of My AI Guide <<<    

 Analysed 465 files (10 .py + 137 .ipynb)
 Failed to analyse 4 files because of errors.

 Analysed 0 given code strings.
 Failed to analyse 0 given code strings because of errors.


-------------------------------------
--------  Analysis of Calls  --------
-------------------------------------
There are 11276 calls.

820x print
416x len
223x range
125x np.random
99x plt.show
97x int
96x super
90x plt.subplots
87x np.arange
87x nlp
86x os.path
84x type
76x plt.figure
68x np.array
67x pd.DataFrame
66x enumerate
61x round
61x pd.read_csv
60x layers.LeakyReLU
58x dict
58x model
58x log
54x plt.scatter
52x nn.Conv2d
51x open
51x model.add
50x layers.BatchNormalization
48x layers.Conv2D
47x isinstance
43x scaler.fit_transform
42x list
42x torch.nn
42x loss.item
41x nn.Linear
40x ValueError
39x np.reshape
37x plt.title
36x layers.Conv2DTranspose
36x hook_func
35x os.makedirs
35x model.parameters
34x ax.plot
34x AgglomerativeClustering
33x torch.utils
33x dt.now
33x torch.tensor
31x plt.xlabel
31x plt.ylabel
31x loss.backward
30x Dense
29x torch.cuda
...

-------------------------------------
-------  Analysis of Imports  -------
-------------------------------------
- torchvision.models.detection.backbone_utils.resnet_fpn_backbone (1)
- h5py (1)
- importlib (1)
- tkinter (1)
- nni.retiarii.model_wrapper (1)
- diagrams.onprem.inmemory.Redis (1)
- torchvision.models.detection.faster_rcnn.TwoMLPHead (1)
- torchvision.models.detection.mask_rcnn.MaskRCNNHeads (1)
- tensorflow.keras.layers.Convolution2D (1)
- nltk.tag.brill_trainer (1)
- tensorflow.keras.Sequential (1)
- nni.retiarii.evaluator.FunctionalEvaluator (1)
- dask.distributed.LocalCluster (1)
- _api.WeightsEnum (1)
- cProfile (1)
- sklearn.neural_network.MLPClassifier (1)
- torchvision.models.detection.MaskRCNN (1)
- numba.float64 (1)
- mlxtend.frequent_patterns.apriori (1)
- sklearn.manifold.MDS (1)
- ast (1)
- nni.retiarii.nn.pytorch (1)
- math.cos (1)
- celluloid.Camera (1)
- typing.List (1)
- pprint (1)
- nltk.bigrams (1)
- sklearn.tree.export_text (1)
- ipywidgets.Layout (1)
- ray.tune (1)
- datetime.timezone (1)
- _utils._ovewrite_named_param (1)
- torch.nn.TransformerEncoder (1)
- helper.Helper (1)
- sklearn.base.TransformerMixin (1)
- folium.Marker (1)
- collections (1)
- sklearn.manifold.Isomap (1)
- hashlib.sha256 (1)
- torch_geometric.datasets.TUDataset (1)
- urllib (1)
- sklearn.linear_model.RidgeCV (1)
- folium.plugins.TimestampedGeoJson (1)
- sklearn.feature_extraction.text.CountVectorizer (1)
- diagrams.onprem.analytics.Spark (1)
- rl.core.Processor (1)
- dask_ml.model_selection.HyperbandSearchCV (1)
- sklearn.datasets.make_classification (1)
- mlxtend.preprocessing.TransactionEncoder (1)
- nni.retiarii.experiment.pytorch.RetiariiExeConfig (1)
- segmentation_models_pytorch (1)
- ...

-------------------------------------
-----  Analysis of Definitions  -----
-------------------------------------
- Defined Functions (596):
    - PlusX (1)
    - __getitem__ (9)
    - add5 (1)
    - analyse_calls (1)
    - analyze_python_code (1)
    - axpy (1)
    - build_optimizer (1)
    - calculate_train_duration (2)
    - collate_fn (1)
    - compile (2)
    - compute_next_q_value (1)
    - configure_optimizers (1)
    - cross_validate (1)
    - cv2_to_pil (1)
    - dist_sim_revert (1)
    - encode_cat (1)
    - enrich_result (1)
    - filter_labels (1)
    - func_fit (1)
    - generate (1)
    - get_all_indexes_of_cluster (1)
    - get_depth (2)
    - get_peaks (1)
    - get_used_depth (2)
    - handle_nulls (1)
    - has_down_peak (1)
    - isLarger10 (1)
    - job_description_sum_similarity (1)
    - load_kaggle_dataset (2)
    - merge_analysis_results (1)
    - metrics (3)
    - monte_carlo_pi (2)
    - monte_carlo_pi_parallel (1)
    - objective_umap (1)
    - pad_masks (1)
    - preprocessing (3)
    - process_observation (1)
    - request_gpt3 (1)
    - resnet101 (1)
    - run_local (1)
    - setup (1)
    - top (1)
    - training (1)
    - update_size (1)
    - valid (1)
    - visualize_results (1)
    - visualize_stack_plot (1)
    - warm_up_and_cool_down_lr (1)
    - wide_resnet101_2 (1)
    - wide_resnet50_2 (1)
    - ...

- Defined Classes (90):
    - CharCount (1)
    - analyse_code (1)
    - analyse_definitions (1)
    - axpy (1)
    - build_network (1)
    - calc_accuracy (1)
    - calc_pixel_accuracy (1)
    - change_bit_depth_with_scaling (2)
    - collate_without_mask_fn (1)
    - compile (2)
    - create_bins (1)
    - draw_dendrogram (1)
    - dropdown_c2_eventhandler (1)
    - evaluation (1)
    - extract_width_height (1)
    - f (2)
    - filter_labels (1)
    - forward (41)
    - generate_fibonacci_distributed (1)
    - generate_square_subsequent_mask (1)
    - get_and_clear_messages (1)
    - get_cur_date_time_as_str (3)
    - get_dataset (1)
    - get_frequency (1)
    - get_informations (1)
    - get_mean (1)
    - get_model (1)
    - get_newest_file (1)
    - get_random_elem (1)
    - get_season (1)
    - get_similar_job_posts_experiment (1)
    - initializeData (1)
    - job_description_similarity_counter (1)
    - kMap (1)
    - main (2)
    - merge_analysis_results (1)
    - plotTimeSeriesResultsInOne (1)
    - proposal_console (1)
    - regular_function (1)
    - save_as_pickle (1)
    - select (4)
    - smoothing_2 (1)
    - stocks_data (1)
    - sum_array (1)
    - test_loop_fn (2)
    - update_cat (1)
    - update_size (1)
    - verify_data (1)
    - visualize_results (1)
    - warm_up_and_cool_down_lr (1)
    - ...

- Lambda Functions: 155

- Returns: 480

- Yields: 6

- `global` Keywords: 7

- `nonlocal` Keywords: 0

-------------------------------------
-----  Analysis of Structures  ------
-------------------------------------
- Defined loops (555):
    - For-Loops: 525
    - While-Loops: 30

- Break's: 49

- Continue's: 22

- If-Statements: 1119

- Try-Blocks: 45

- With-Blocks: 127

-------------------------------------
-----  Analysis of Operations  ------
-------------------------------------
- Operations (1639):
    - Add's: 1081
    - Sub's: 263
    - Mult's: 497
    - Div's: 222
    - Mod's: 56
    - Floor Div's: 66
    - Pow's: 84

- Bool Operations (1474):
    - And's: 154
    - Or's: 64
    - Equals's: 546
    - Not Equals's: 95
    - Is's: 33
    - Is not's: 39
    - In's: 128
    - Not In's: 16

         >>> END of Analysis <<<
_________________________________________