dotools_py.utility.create_report#
- dotools_py.utility.create_report(log_file)[source]#
Create a report file.
This function takes a log_file that should have been set at the beginning of the session with
dotools_py.settings.set.set_kernel_loggerand add information regarding the session such as the machine characteristics and the version of the packages.- Parameters:
- Return type:
- Returns:
Returns None. The log file is updated with session information.
Examples
>>> import dotools_py as do >>> do.settings.set_kernel_logger('./History.log', overwrite=True) >>> adata = do.dt.example_10x_processed() >>> adata >>> do.utility.create_report("./History.log") >>> print(open("History.log").read()) [CODE 2026-01-22 13:59:28.904757] >>> adata = do.dt.example_10x_processed() [CODE 2026-01-22 13:59:29.617186] >>> adata [OUTPUT 2026-01-22 13:59:29.619246] AnnData object with n_obs × n_vars = 700 × 1851 obs: 'batch', 'condition', 'n_genes_by_counts', 'log1p_n_genes_by_counts', 'total_counts', 'log1p_total_counts', 'total_counts_mt', 'log1p_total_counts_mt', 'pct_counts_mt', 'total_counts_ribo', 'log1p_total_counts_ribo', 'pct_counts_ribo', 'n_genes', 'n_counts', 'doublet_class', 'doublet_score', 'leiden', 'cell_type', 'autoAnnot', 'celltypist_conf_score', 'annotation', 'annotation_recluster' var: 'mean', 'std', 'highly_variable', 'means', 'dispersions', 'dispersions_norm', 'highly_variable_nbatches', 'highly_variable_intersection' uns: 'annotation_colors', 'annotation_recluster_colors', 'batch_colors', 'hvg', 'leiden', 'leiden_colors', 'log1p', 'neighbors', 'pca', 'umap' obsm: 'X_CCA', 'X_pca', 'X_umap' varm: 'PCs' layers: 'counts', 'logcounts' obsp: 'connectivities', 'distances' ==================== Session Information ==================== OS:macOS-26.2-arm64-arm-64bit Machine: arm64 Processor: arm CPU cores (physical): 10 CPU cores (logical): 10 Total RAM (GB): 16.0 Python version: 3.11.13 ----- anndata 0.11.4 dotools_py 0.0.1 pandas 2.3.2 platform 1.0.8 ----- Cython 3.1.4 IPython 9.5.0 PIL 11.3.0 adjustText 1.3.0 altair 6.0.0 argparse 1.1 arrow 1.3.0 attr 25.3.0 attrs 25.3.0 beartype 0.22.8 charset_normalizer 3.4.3 cloudpickle 3.1.1 comm 0.2.3 coverage 7.11.0 csv 1.0 ctypes 1.1.0 cycler 0.12.1 cython 3.1.4 dask 2024.11.2 dateutil 2.9.0.post0 decimal 1.70 decorator 5.2.1 defusedxml 0.7.1 deprecated 1.2.18 executing 2.2.1 h5py 3.14.0 idna 3.10 igraph 0.11.9 ipaddress 1.0 ipywidgets 8.1.7 jedi 0.19.2 jinja2 3.1.6 joblib 1.5.2 json 2.0.9 jsonpointer 3.0.0 jsonschema 4.25.1 kiwisolver 1.4.9 lark 1.2.2 leidenalg 0.10.2 llvmlite 0.45.0 logging 0.5.1.2 markupsafe 3.0.2 marshal 4 matplotlib 3.10.6 msgpack 1.1.2 narwhals 2.5.0 natsort 8.4.0 numba 0.62.0 numcodecs 0.15.1 numpy 2.3.3 packaging 25.0 parso 0.8.5 patsy 1.0.1 polars 1.33.1 prompt_toolkit 3.0.52 psutil 7.1.0 pure_eval 0.2.3 pyarrow 21.0.0 pydot 4.0.1 pygments 2.19.2 pyparsing 3.2.4 pytz 2025.2 re 2.2.1 rfc3339_validator 0.1.4 rfc3986_validator 0.1.1 scanpy 1.11.4 scipy 1.15.3 seaborn 0.13.2 session_info v1.0.1 six 1.17.0 sklearn 1.7.2 socketserver 0.4 sparse 0.17.0 sqlite3 2.6.0 stack_data 0.6.3 statsmodels 0.14.5 stdlib_list 0.11.1 sys 3.11.13 (main, Jun 5 2025, 08:21:08) [Clang 14.0.6 ] tarfile 0.9.0 texttable 1.7.0 threadpoolctl 3.6.0 tlz 1.0.0 toolz 1.0.0 torch 2.8.0 tqdm 4.67.1 traitlets 5.14.3 wcwidth 0.2.13 wrapt 1.17.3 yaml 6.0.2 zarr 2.18.7 zlib 1.0 ----- Python 3.11.13 (main, Jun 5 2025, 08:21:08) [Clang 14.0.6 ] macOS-26.2-arm64-arm-64bit 10 logical CPU cores, arm ----- Session information updated at 2026-01-22 13:59 =============================================================