Skip to main content

CAD-score-LT Python bindings via SWIG

Project description

CAD-score-LT Python bindings

The CAD-score-LT Python interface PyPI package is hosted at https://pypi.org/project/cadscorelt/.

Installation

Install with pip using this command:

pip install cadscorelt

Additionally, it is recommended to have the pandas library for data analysis available in the Python environment. This allows the CAD-score result tables to be converted to pandas data frames. The pandas library can also be installed using pip:

pip install pandas

CAD-score-LT also provides integration with some common libraries for reading macromolecular files - Biotite, Gemmi, Biopython, if those libraries are available in the Python environment. They can be installed via pip:

pip install biotite
pip install gemmi
pip install biopython

Usage examples

Basic example

Below is an example script that calculates CAD-scores for inter-chain residue-residue contact areas, produces a table of global scores, converts that table to pandas data frame, and preints the top rows of the data frame:

import cadscorelt

# init a CAD-score computation object
css = cadscorelt.CADScoreComputer.init(subselect_contacts="[-inter-chain]")

# add a target structure
css.add_target_structure_from_file("./input/data/protein_homodimer1/target.pdb")

# add a target structure
css.add_model_structure_from_file("./input/data/protein_homodimer1/model1.pdb")
css.add_model_structure_from_file("./input/data/protein_homodimer1/model2.pdb")

# get a list of global scores and convert it to pandas data frame
df_global_scores_residue_residue = css.get_all_cadscores_residue_residue_summarized_globally().to_pandas()

# print the first rows of the data frame
cadscorelt.print_head_of_pandas_data_frame(df_global_scores_residue_residue)

Below is an example of the printed output:

target_name model_name  CAD_score  F1_of_areas  target_area  model_area    TP_area    FP_area    FN_area renamed_chains
     target     model2   0.621922     0.774894  1047.807935  941.514533 784.870893 193.071031 262.937041              .
     target     model1   0.507319     0.639249  1047.807935  792.834440 648.098138 331.779276 399.709796              .

Basic example using different structure readers

Below is an example script that is similar to the previous example script, but it shows how to input structures from different sources:

import cadscorelt

# init a CAD-score computation object
csc = cadscorelt.CADScoreComputer.init(subselect_contacts="[-inter-chain]")

# add a target structure read by Biotite
import biotite.structure.io
structure_target = biotite.structure.io.load_structure("./input/data/protein_homodimer1/target.pdb")
csc.add_target_structure_from_biotite(structure_target, "target")

# add a model structure read by Gemmi 
import gemmi
structure_model1 = gemmi.read_structure("./input/data/protein_homodimer1/model1.pdb")
csc.add_model_structure_from_gemmi(structure_model1[0], "model1")

# add a model structure read by Biopython 
import Bio.PDB
parser = Bio.PDB.PDBParser(QUIET=True)
structure_model2 = parser.get_structure("id", "./input/data/protein_homodimer1/model2.pdb").get_atoms()
csc.add_model_structure_from_biopython(structure_model2, "model2")

# get a list of global scores and convert it to pandas data frame
df_global_scores_residue_residue = csc.get_all_cadscores_residue_residue_summarized_globally().to_pandas()

# print the first rows of the data frame
cadscorelt.print_head_of_pandas_data_frame(df_global_scores_residue_residue)

Below is an example of the printed output:

target_name model_name  CAD_score  F1_of_areas  target_area  model_area    TP_area    FP_area    FN_area renamed_chains
     target     model2   0.621922     0.774894  1047.808013  941.514579 784.870926 193.071041 262.937087              .
     target     model1   0.507319     0.639249  1047.808013  792.834440 648.098141 331.779274 399.709873              .

Advanced example

Below is an example script that that includes:

  • residue-residue contact scoring (enabled by default);
  • atom-atom contact scoring;
  • automatic chain remapping to maximize grobal similarity;
  • recording local scores.
import cadscorelt
from pathlib import Path

# to make comparison more strict, globally enable inclusion of residue names into atom and residue identifiers
cadscorelt.enable_considering_residue_names()

# init a CAD-score computation object, enable atom-atom contact scoring, enable automatic chain remapping to maximize grobal similarity, enable recording local scores
csc = cadscorelt.CADScoreComputer.init(subselect_contacts="[-inter-chain]", score_atom_atom_contacts=True, remap_chains=True, record_local_scores=True)

# set reference sequences and stoichiometry for automatic residue renumbering and chain namne assignment
csc.set_reference_sequences_from_file("./input/data/protein_heteromer1/sequences.fasta")
csc.set_reference_stoichiometry([2, 2, 2])

# input structures from all the files in a directory
input_directory = Path("./input/data/protein_heteromer1/structures")
for file_path in input_directory.iterdir():
    if file_path.is_file():
        csc.add_structure_from_file(str(file_path))

# get the table of structure decriptors and print its top rows
df_structure_descriptors = csc.get_all_structure_descriptors().to_pandas()
print("")
print(" # Table of structure decriptors:")
print("")
cadscorelt.print_head_of_pandas_data_frame(df_structure_descriptors)
print("")

# get the table of globals scores based on residue-residue contacts, print top rows
df_global_scores_residue_residue = csc.get_all_cadscores_residue_residue_summarized_globally().to_pandas()
print("")
print(" # Table of globals scores based on residue-residue contacts:")
print("")
cadscorelt.print_head_of_pandas_data_frame(df_global_scores_residue_residue)
print("")

# get the table of globals scores based on atom-atom contacts, print top rows
df_global_scores_atom_atom = csc.get_all_cadscores_atom_atom_summarized_globally().to_pandas()
print("")
print(" # Table of globals scores based on atom-atom contacts:")
print("")
cadscorelt.print_head_of_pandas_data_frame(df_global_scores_atom_atom)
print("")

# set placeholder variable for structure names
target_name="cf_woTemplates_model_3_multimer_v3_pred_47"
model_name="cf_woTemplates_model_2_multimer_v3_pred_26"

# get the table of per-residue scores based on residue-residue contacts, print top rows
df_local_scores_per_residue = csc.get_local_cadscores_residue_residue_summarized_per_residue(target_name, model_name).to_pandas()
print("")
print(" # Table of per-residue scores based on residue-residue contacts:")
print("")
cadscorelt.print_head_of_pandas_data_frame(df_local_scores_per_residue)
print("")

# get the table of scores for every residue-residue contact, print top rows
df_local_scores_residue_residue = csc.get_local_cadscores_residue_residue(target_name, model_name).to_pandas()
print("")
print(" # Table of scores for every residue-residue contact (CAD-score values of -1 idicate that the contact was not present in the target structure):")
print("")
cadscorelt.print_head_of_pandas_data_frame(df_local_scores_residue_residue)
print("")

# get the table of per-atom scores based on atom-atom contacts, print top rows
df_local_scores_per_atom = csc.get_local_cadscores_atom_atom_summarized_per_atom(target_name, model_name).to_pandas()
print("")
print(" # Table of per-atom scores based on atom-atom contacts (CAD-score values of -1 idicate that the atom had no relevant contacts in the target structure):")
print("")
cadscorelt.print_head_of_pandas_data_frame(df_local_scores_per_atom)
print("")

# get the table of scores for every atom-atom contact, print top rows
df_local_scores_atom_atom = csc.get_local_cadscores_atom_atom(target_name, model_name).to_pandas()
print("")
print(" # Table of scores for every atom-atom contact (CAD-score values of -1 idicate that the contact was not present in the target structure):")
print("")
cadscorelt.print_head_of_pandas_data_frame(df_local_scores_atom_atom)
print("")

Below is an example of the printed output:


 # Table of structure decriptors:

                                                    name  is_target  is_model          renamed_chains reference_alignment
                   afm_basic_model_5_multimer_v1_pred_35       True      True B=A,C=D,D=B,E=E,F=C,G=F           available
            afm_dropout_full_model_1_multimer_v2_pred_42       True      True B=A,C=D,D=B,E=E,F=C,G=F           available
            afm_dropout_full_model_2_multimer_v1_pred_65       True      True B=A,C=D,D=B,E=E,F=C,G=F           available
            afm_dropout_full_model_3_multimer_v3_pred_64       True      True B=A,C=D,D=B,E=E,F=C,G=F           available
            afm_dropout_full_model_3_multimer_v3_pred_66       True      True B=A,C=D,D=B,E=E,F=C,G=F           available
 afm_dropout_full_woTemplates_model_3_multimer_v1_pred_4       True      True B=A,C=D,D=B,E=E,F=C,G=F           available
afm_dropout_full_woTemplates_model_3_multimer_v1_pred_45       True      True B=A,C=D,D=B,E=E,F=C,G=F           available
afm_dropout_full_woTemplates_model_4_multimer_v3_pred_50       True      True B=A,C=D,D=B,E=E,F=C,G=F           available
              cf_woTemplates_model_2_multimer_v3_pred_26       True      True A=A,B=D,C=B,D=E,E=C,F=F           available
              cf_woTemplates_model_3_multimer_v3_pred_47       True      True A=A,B=D,C=B,D=E,E=C,F=F           available


 # Table of globals scores based on residue-residue contacts:

                                 target_name                                               model_name  CAD_score  F1_of_areas  target_area  model_area     TP_area     FP_area     FN_area          renamed_chains
afm_dropout_full_model_1_multimer_v2_pred_42 afm_dropout_full_woTemplates_model_4_multimer_v3_pred_50   0.847662     0.701359  3970.007175 3836.593118 3582.890995 2664.103761  387.116180 A=A;B=B;C=F;D=D;E=E;F=C
  cf_woTemplates_model_3_multimer_v3_pred_47               cf_woTemplates_model_2_multimer_v3_pred_26   0.704688     0.780891  7483.973156 6871.838277 5912.094425 1745.848929 1571.878730 A=D;B=E;C=F;D=A;E=B;F=C
  cf_woTemplates_model_2_multimer_v3_pred_26               cf_woTemplates_model_3_multimer_v3_pred_47   0.699040     0.781187  7657.943354 6855.599895 5914.330867 1569.642289 1743.612487 A=A;B=B;C=C;D=D;E=E;F=F
afm_dropout_full_model_3_multimer_v3_pred_66             afm_dropout_full_model_3_multimer_v3_pred_64   0.657842     0.675283  7313.203511 5519.154809 5124.561234 2739.763621 2188.642277 A=A;B=B;C=C;D=D;E=E;F=F
afm_dropout_full_model_3_multimer_v3_pred_64             afm_dropout_full_model_3_multimer_v3_pred_66   0.620764     0.675283  7864.324855 5420.088717 5124.561234 2188.642277 2739.763621 A=A;B=B;C=C;D=D;E=E;F=F
afm_dropout_full_model_3_multimer_v3_pred_66               cf_woTemplates_model_2_multimer_v3_pred_26   0.575097     0.645935  7313.203511 5696.007986 4835.195167 2822.748187 2478.008344 A=A;B=E;C=C;D=D;E=B;F=F
  cf_woTemplates_model_2_multimer_v3_pred_26             afm_dropout_full_model_3_multimer_v3_pred_66   0.573808     0.645935  7657.943354 5446.078054 4835.195167 2478.008344 2822.748187 A=A;B=E;C=C;D=D;E=B;F=F
afm_dropout_full_model_3_multimer_v3_pred_66               cf_woTemplates_model_3_multimer_v3_pred_47   0.566239     0.627281  7313.203511 5493.415167 4640.996876 2842.976280 2672.206635 A=D;B=B;C=F;D=A;E=E;F=C
  cf_woTemplates_model_3_multimer_v3_pred_47             afm_dropout_full_model_3_multimer_v3_pred_66   0.561418     0.627332  7483.973156 5252.699687 4641.373085 2671.830426 2842.600071 A=A;B=E;C=C;D=D;E=B;F=F
  cf_woTemplates_model_2_multimer_v3_pred_26             afm_dropout_full_model_3_multimer_v3_pred_64   0.550970     0.603414  7657.943354 5255.694013 4683.177891 3181.146964 2974.765463 A=A;B=E;C=C;D=D;E=B;F=F


 # Table of globals scores based on atom-atom contacts:

                                 target_name                                               model_name  CAD_score  F1_of_areas  target_area  model_area     TP_area     FP_area     FN_area          renamed_chains
afm_dropout_full_model_1_multimer_v2_pred_42 afm_dropout_full_woTemplates_model_4_multimer_v3_pred_50   0.694870     0.612790  3970.007175 3631.663716 3130.437751 3116.557004  839.569423 A=A;B=B;C=F;D=D;E=E;F=C
afm_dropout_full_model_3_multimer_v3_pred_66             afm_dropout_full_model_3_multimer_v3_pred_64   0.600300     0.630986  7313.203511 5287.148112 4788.403033 3075.921822 2524.800478 A=A;B=B;C=C;D=D;E=E;F=F
afm_dropout_full_model_3_multimer_v3_pred_64             afm_dropout_full_model_3_multimer_v3_pred_66   0.566073     0.630986  7864.324855 5222.053418 4788.403033 2524.800478 3075.921822 A=A;B=B;C=C;D=D;E=E;F=F
  cf_woTemplates_model_3_multimer_v3_pred_47               cf_woTemplates_model_2_multimer_v3_pred_26   0.559002     0.635331  7483.973156 5931.794420 4810.063036 2847.880319 2673.910120 A=D;B=E;C=F;D=A;E=B;F=C
  cf_woTemplates_model_2_multimer_v3_pred_26               cf_woTemplates_model_3_multimer_v3_pred_47   0.550378     0.635281  7657.943354 5972.073003 4809.683681 2674.289475 2848.259673 A=A;B=B;C=C;D=D;E=E;F=F
afm_dropout_full_model_3_multimer_v3_pred_66               cf_woTemplates_model_2_multimer_v3_pred_26   0.455307     0.527325  7313.203511 5000.847832 3947.330056 3710.613299 3365.873455 A=A;B=E;C=C;D=D;E=B;F=F
  cf_woTemplates_model_2_multimer_v3_pred_26             afm_dropout_full_model_3_multimer_v3_pred_66   0.446372     0.527325  7657.943354 4761.917277 3947.330056 3365.873455 3710.613299 A=A;B=E;C=C;D=D;E=B;F=F
  cf_woTemplates_model_2_multimer_v3_pred_26             afm_dropout_full_model_3_multimer_v3_pred_64   0.445539     0.506868  7657.943354 4677.771912 3933.871243 3930.453612 3724.072111 A=A;B=E;C=C;D=D;E=B;F=F
  cf_woTemplates_model_3_multimer_v3_pred_47             afm_dropout_full_model_3_multimer_v3_pred_64   0.439929     0.489985  7483.973156 4453.132335 3760.215370 4104.109485 3723.757786 A=D;B=B;C=F;D=A;E=E;F=C
afm_dropout_full_model_3_multimer_v3_pred_66               cf_woTemplates_model_3_multimer_v3_pred_47   0.439601     0.499394  7313.203511 4526.494827 3694.810365 3789.162791 3618.393146 A=D;B=B;C=F;D=A;E=E;F=C


 # Table of per-residue scores based on residue-residue contacts:

ID_chain  ID_rnum ID_icode  CAD_score  F1_of_areas  target_area  model_area   TP_area   FP_area   FN_area
       A        4        .   0.000000     0.000000     5.723360    0.000000  0.000000 14.123374  5.723360
       A        6        .   0.000000     0.504191     7.178632   14.612032  7.160650 14.065207  0.017982
       A       15        .   0.000000     0.000000     1.346514    0.000000  0.000000  2.051384  1.346514
       A       17        .   0.175261     0.298250    25.529513    4.474315  4.474315  0.000000 21.055197
       A       18        .   0.378808     0.293841    26.519188   10.045678 10.045678 31.810069 16.473510
       A       19        .   0.715554     0.783253    69.951082   79.263636 63.086289 28.050569  6.864793
       A       20        .   0.228410     0.399188    97.824322   75.742435 35.484263 44.473835 62.340058
       A       21        .   0.892938     0.923627    55.431386   54.675708 52.086259  5.268696  3.345127
       A       22        .   0.000000     0.277170     0.401577    2.496120  0.401577  2.094543  0.000000
       A       23        .   0.406606     0.631095    34.355429   20.906229 17.437673  3.468556 16.917756


 # Table of scores for every residue-residue contact (CAD-score values of -1 idicate that the contact was not present in the target structure):

ID1_chain  ID1_rnum ID1_icode ID2_chain  ID2_rnum ID2_icode  CAD_score  F1_of_areas  target_area  model_area  TP_area   FP_area   FN_area
        A         4         .         D         6         .   0.000000     0.000000     0.043450    0.000000 0.000000  0.000000  0.043450
        A         4         .         D        61         .   0.000000     0.000000     5.679910    0.000000 0.000000  0.000000  5.679910
        A         4         .         D       206         .  -1.000000     0.000000     0.000000    0.000000 0.000000 14.123374  0.000000
        A         6         .         D         4         .   0.000000     0.000000     0.017982    0.000000 0.000000  0.000000  0.017982
        A         6         .         D        65         .   0.000000     0.657765     7.160650   14.612032 7.160650  7.451382  0.000000
        A         6         .         D       208         .  -1.000000     0.000000     0.000000    0.000000 0.000000  6.613825  0.000000
        A        15         .         C        31         .  -1.000000     0.000000     0.000000    0.000000 0.000000  2.051384  0.000000
        A        15         .         D       137         .   0.000000     0.000000     1.346514    0.000000 0.000000  0.000000  1.346514
        A        17         .         C        31         .   0.086301     0.158889    16.995494    1.466721 1.466721  0.000000 15.528773
        A        17         .         C        32         .   0.557286     0.715714     5.396860    3.007595 3.007595  0.000000  2.389265


 # Table of per-atom scores based on atom-atom contacts (CAD-score values of -1 idicate that the atom had no relevant contacts in the target structure):

ID_chain  ID_rnum ID_icode ID_atom_name  CAD_score  F1_of_areas  target_area  model_area  TP_area   FP_area   FN_area
       A        4        .           CD  -1.000000     0.000000     0.000000    0.000000 0.000000  0.589435  0.000000
       A        4        .           CE  -1.000000     0.000000     0.000000    0.000000 0.000000  6.218582  0.000000
       A        4        .           CG  -1.000000     0.000000     0.000000    0.000000 0.000000  0.040717  0.000000
       A        4        .           NZ   0.000000     0.000000     5.723360    0.000000 0.000000  7.274641  5.723360
       A        6        .           CB  -1.000000     0.000000     0.000000    0.000000 0.000000  0.005776  0.000000
       A        6        .          CG1  -1.000000     0.000000     0.000000    0.000000 0.000000 10.924598  0.000000
       A        6        .          CG2   0.315134     0.527725     7.178632    8.956361 4.610766  5.684717  2.567866
       A       15        .           CB  -1.000000     0.000000     0.000000    0.000000 0.000000  1.960049  0.000000
       A       15        .            O   0.000000     0.000000     1.346514    0.000000 0.000000  0.091335  1.346514
       A       17        .           CB   0.057452     0.097769    25.529513    1.466721 1.466721  3.007595 24.062792


 # Table of scores for every atom-atom contact (CAD-score values of -1 idicate that the contact was not present in the target structure):

ID1_chain  ID1_rnum ID1_icode ID1_atom_name ID2_chain  ID2_rnum ID2_icode ID2_atom_name  CAD_score  F1_of_areas  target_area  model_area  TP_area  FP_area  FN_area
        A         4         .            CD         D       206         .           OE1       -1.0          0.0     0.000000         0.0      0.0 0.589435 0.000000
        A         4         .            CE         D       206         .           NE2       -1.0          0.0     0.000000         0.0      0.0 1.398847 0.000000
        A         4         .            CE         D       206         .           OE1       -1.0          0.0     0.000000         0.0      0.0 4.819735 0.000000
        A         4         .            CG         D       206         .           OE1       -1.0          0.0     0.000000         0.0      0.0 0.040717 0.000000
        A         4         .            NZ         D         6         .           CG2        0.0          0.0     0.043450         0.0      0.0 0.000000 0.043450
        A         4         .            NZ         D        61         .            CZ        0.0          0.0     0.413695         0.0      0.0 0.000000 0.413695
        A         4         .            NZ         D        61         .            OH        0.0          0.0     5.266215         0.0      0.0 0.000000 5.266215
        A         4         .            NZ         D       206         .            CD       -1.0          0.0     0.000000         0.0      0.0 0.008074 0.000000
        A         4         .            NZ         D       206         .           NE2       -1.0          0.0     0.000000         0.0      0.0 5.372747 0.000000
        A         4         .            NZ         D       206         .           OE1       -1.0          0.0     0.000000         0.0      0.0 1.893820 0.000000

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cadscorelt-0.9.193.tar.gz (223.8 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

cadscorelt-0.9.193-cp313-cp313-win_amd64.whl (521.5 kB view details)

Uploaded CPython 3.13Windows x86-64

cadscorelt-0.9.193-cp313-cp313-win32.whl (406.6 kB view details)

Uploaded CPython 3.13Windows x86

cadscorelt-0.9.193-cp313-cp313-musllinux_1_2_x86_64.whl (8.1 MB view details)

Uploaded CPython 3.13musllinux: musl 1.2+ x86-64

cadscorelt-0.9.193-cp313-cp313-musllinux_1_2_i686.whl (8.0 MB view details)

Uploaded CPython 3.13musllinux: musl 1.2+ i686

cadscorelt-0.9.193-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.3 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.17+ x86-64

cadscorelt-0.9.193-cp313-cp313-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl (6.9 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.12+ i686manylinux: glibc 2.17+ i686

cadscorelt-0.9.193-cp313-cp313-macosx_11_0_arm64.whl (581.1 kB view details)

Uploaded CPython 3.13macOS 11.0+ ARM64

cadscorelt-0.9.193-cp313-cp313-macosx_10_15_x86_64.whl (641.2 kB view details)

Uploaded CPython 3.13macOS 10.15+ x86-64

cadscorelt-0.9.193-cp313-cp313-macosx_10_15_universal2.whl (1.2 MB view details)

Uploaded CPython 3.13macOS 10.15+ universal2 (ARM64, x86-64)

cadscorelt-0.9.193-cp312-cp312-win_amd64.whl (521.4 kB view details)

Uploaded CPython 3.12Windows x86-64

cadscorelt-0.9.193-cp312-cp312-win32.whl (414.1 kB view details)

Uploaded CPython 3.12Windows x86

cadscorelt-0.9.193-cp312-cp312-musllinux_1_2_x86_64.whl (8.1 MB view details)

Uploaded CPython 3.12musllinux: musl 1.2+ x86-64

cadscorelt-0.9.193-cp312-cp312-musllinux_1_2_i686.whl (8.0 MB view details)

Uploaded CPython 3.12musllinux: musl 1.2+ i686

cadscorelt-0.9.193-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.3 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ x86-64

cadscorelt-0.9.193-cp312-cp312-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl (6.9 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.12+ i686manylinux: glibc 2.17+ i686

cadscorelt-0.9.193-cp312-cp312-macosx_11_0_arm64.whl (581.1 kB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

cadscorelt-0.9.193-cp312-cp312-macosx_10_15_x86_64.whl (641.2 kB view details)

Uploaded CPython 3.12macOS 10.15+ x86-64

cadscorelt-0.9.193-cp312-cp312-macosx_10_15_universal2.whl (1.2 MB view details)

Uploaded CPython 3.12macOS 10.15+ universal2 (ARM64, x86-64)

cadscorelt-0.9.193-cp311-cp311-win_amd64.whl (522.3 kB view details)

Uploaded CPython 3.11Windows x86-64

cadscorelt-0.9.193-cp311-cp311-win32.whl (413.4 kB view details)

Uploaded CPython 3.11Windows x86

cadscorelt-0.9.193-cp311-cp311-musllinux_1_2_x86_64.whl (8.1 MB view details)

Uploaded CPython 3.11musllinux: musl 1.2+ x86-64

cadscorelt-0.9.193-cp311-cp311-musllinux_1_2_i686.whl (7.9 MB view details)

Uploaded CPython 3.11musllinux: musl 1.2+ i686

cadscorelt-0.9.193-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.3 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ x86-64

cadscorelt-0.9.193-cp311-cp311-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl (6.9 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.12+ i686manylinux: glibc 2.17+ i686

cadscorelt-0.9.193-cp311-cp311-macosx_11_0_arm64.whl (580.5 kB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

cadscorelt-0.9.193-cp311-cp311-macosx_10_15_x86_64.whl (636.7 kB view details)

Uploaded CPython 3.11macOS 10.15+ x86-64

cadscorelt-0.9.193-cp311-cp311-macosx_10_15_universal2.whl (1.2 MB view details)

Uploaded CPython 3.11macOS 10.15+ universal2 (ARM64, x86-64)

cadscorelt-0.9.193-cp310-cp310-win_amd64.whl (522.3 kB view details)

Uploaded CPython 3.10Windows x86-64

cadscorelt-0.9.193-cp310-cp310-win32.whl (413.4 kB view details)

Uploaded CPython 3.10Windows x86

cadscorelt-0.9.193-cp310-cp310-musllinux_1_2_x86_64.whl (8.0 MB view details)

Uploaded CPython 3.10musllinux: musl 1.2+ x86-64

cadscorelt-0.9.193-cp310-cp310-musllinux_1_2_i686.whl (7.9 MB view details)

Uploaded CPython 3.10musllinux: musl 1.2+ i686

cadscorelt-0.9.193-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.3 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

cadscorelt-0.9.193-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl (6.9 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.12+ i686manylinux: glibc 2.17+ i686

cadscorelt-0.9.193-cp310-cp310-macosx_11_0_arm64.whl (580.5 kB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

cadscorelt-0.9.193-cp310-cp310-macosx_10_15_x86_64.whl (636.7 kB view details)

Uploaded CPython 3.10macOS 10.15+ x86-64

cadscorelt-0.9.193-cp310-cp310-macosx_10_15_universal2.whl (1.2 MB view details)

Uploaded CPython 3.10macOS 10.15+ universal2 (ARM64, x86-64)

cadscorelt-0.9.193-cp39-cp39-win_amd64.whl (522.2 kB view details)

Uploaded CPython 3.9Windows x86-64

cadscorelt-0.9.193-cp39-cp39-win32.whl (413.4 kB view details)

Uploaded CPython 3.9Windows x86

cadscorelt-0.9.193-cp39-cp39-musllinux_1_2_x86_64.whl (8.0 MB view details)

Uploaded CPython 3.9musllinux: musl 1.2+ x86-64

cadscorelt-0.9.193-cp39-cp39-musllinux_1_2_i686.whl (7.9 MB view details)

Uploaded CPython 3.9musllinux: musl 1.2+ i686

cadscorelt-0.9.193-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.3 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

cadscorelt-0.9.193-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl (6.9 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.12+ i686manylinux: glibc 2.17+ i686

cadscorelt-0.9.193-cp39-cp39-macosx_11_0_arm64.whl (580.6 kB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

cadscorelt-0.9.193-cp39-cp39-macosx_10_15_x86_64.whl (636.7 kB view details)

Uploaded CPython 3.9macOS 10.15+ x86-64

cadscorelt-0.9.193-cp39-cp39-macosx_10_15_universal2.whl (1.2 MB view details)

Uploaded CPython 3.9macOS 10.15+ universal2 (ARM64, x86-64)

cadscorelt-0.9.193-cp38-cp38-win_amd64.whl (522.2 kB view details)

Uploaded CPython 3.8Windows x86-64

cadscorelt-0.9.193-cp38-cp38-win32.whl (413.3 kB view details)

Uploaded CPython 3.8Windows x86

cadscorelt-0.9.193-cp38-cp38-musllinux_1_2_x86_64.whl (8.0 MB view details)

Uploaded CPython 3.8musllinux: musl 1.2+ x86-64

cadscorelt-0.9.193-cp38-cp38-musllinux_1_2_i686.whl (7.9 MB view details)

Uploaded CPython 3.8musllinux: musl 1.2+ i686

cadscorelt-0.9.193-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.3 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ x86-64

cadscorelt-0.9.193-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl (6.9 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ i686manylinux: glibc 2.17+ i686

cadscorelt-0.9.193-cp38-cp38-macosx_11_0_arm64.whl (580.3 kB view details)

Uploaded CPython 3.8macOS 11.0+ ARM64

cadscorelt-0.9.193-cp38-cp38-macosx_10_15_x86_64.whl (636.3 kB view details)

Uploaded CPython 3.8macOS 10.15+ x86-64

cadscorelt-0.9.193-cp38-cp38-macosx_10_15_universal2.whl (1.2 MB view details)

Uploaded CPython 3.8macOS 10.15+ universal2 (ARM64, x86-64)

cadscorelt-0.9.193-cp37-cp37m-win_amd64.whl (519.9 kB view details)

Uploaded CPython 3.7mWindows x86-64

cadscorelt-0.9.193-cp37-cp37m-win32.whl (413.0 kB view details)

Uploaded CPython 3.7mWindows x86

cadscorelt-0.9.193-cp37-cp37m-musllinux_1_2_x86_64.whl (8.1 MB view details)

Uploaded CPython 3.7mmusllinux: musl 1.2+ x86-64

cadscorelt-0.9.193-cp37-cp37m-musllinux_1_2_i686.whl (8.0 MB view details)

Uploaded CPython 3.7mmusllinux: musl 1.2+ i686

cadscorelt-0.9.193-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.3 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.17+ x86-64

cadscorelt-0.9.193-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl (7.0 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ i686manylinux: glibc 2.17+ i686

cadscorelt-0.9.193-cp37-cp37m-macosx_10_15_x86_64.whl (635.5 kB view details)

Uploaded CPython 3.7mmacOS 10.15+ x86-64

cadscorelt-0.9.193-cp36-cp36m-win_amd64.whl (519.9 kB view details)

Uploaded CPython 3.6mWindows x86-64

cadscorelt-0.9.193-cp36-cp36m-win32.whl (413.0 kB view details)

Uploaded CPython 3.6mWindows x86

cadscorelt-0.9.193-cp36-cp36m-musllinux_1_2_x86_64.whl (8.1 MB view details)

Uploaded CPython 3.6mmusllinux: musl 1.2+ x86-64

cadscorelt-0.9.193-cp36-cp36m-musllinux_1_2_i686.whl (8.0 MB view details)

Uploaded CPython 3.6mmusllinux: musl 1.2+ i686

cadscorelt-0.9.193-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.3 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.17+ x86-64

cadscorelt-0.9.193-cp36-cp36m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl (7.0 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ i686manylinux: glibc 2.17+ i686

cadscorelt-0.9.193-cp36-cp36m-macosx_10_15_x86_64.whl (635.3 kB view details)

Uploaded CPython 3.6mmacOS 10.15+ x86-64

File details

Details for the file cadscorelt-0.9.193.tar.gz.

File metadata

  • Download URL: cadscorelt-0.9.193.tar.gz
  • Upload date:
  • Size: 223.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.12.3

File hashes

Hashes for cadscorelt-0.9.193.tar.gz
Algorithm Hash digest
SHA256 aba142613257092d9e91aefac827702f0d93aad326b01a8a6778c2c051ebff8b
MD5 063b891ec1511635c5595f713923d57b
BLAKE2b-256 ad24850fd213ffd393a719025100cc5120ea5c1e5521ba490beb11115f351101

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp313-cp313-win_amd64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 05e2b76fad4802dbf41de2342594b4444c5b0ea4ccd628c3d55a5d1ae11ace3f
MD5 1516257f1c63c45b061f748690fb488c
BLAKE2b-256 d5f2fcbc40c41a4fa8bcbe98341891a431d4b3e418347848a2decd5a9554dd98

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp313-cp313-win32.whl.

File metadata

  • Download URL: cadscorelt-0.9.193-cp313-cp313-win32.whl
  • Upload date:
  • Size: 406.6 kB
  • Tags: CPython 3.13, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.12.3

File hashes

Hashes for cadscorelt-0.9.193-cp313-cp313-win32.whl
Algorithm Hash digest
SHA256 e80224d068f48f71a988ea64f35bc35e89840df7789bf582f3874c2dd981d695
MD5 0d5d15cf90dde8defe1fad73a6bcd8c6
BLAKE2b-256 db5845ad2f1c74a6e06e033e06b2dec9de36db8d08754a1502b27bcd24f52575

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp313-cp313-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp313-cp313-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 3e6f0de2eb69ac5533a72562379c2f66a90ac6d8afc0ce2c8e1141b08634c61a
MD5 7b7c181ee03102a4c07a9b2de52e94e5
BLAKE2b-256 aa6745ed9d1e43bf8fd9aa2fc6da1ff26732edac53e51a0b626d673a093115ff

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp313-cp313-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp313-cp313-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 3eaf23fa1fbc77bf87216d16541f0711678e926da999fc7905f6710d8908f0df
MD5 6f770ebf111fc970268dc6d03f0631a0
BLAKE2b-256 31419b79f2266cac59d7057a88fff619cf57ccab3e081a7a5ae3f3781bb2dcc8

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f3aeec954e07e773b2a3523f69ab4f02d7a81e22d32a74b2ff0d640420593078
MD5 2a8c7b9ffa59e79192bc6b9f686719c5
BLAKE2b-256 116086d09d47c059efbe9157b421fbd9515e2d6622aed5c82ec37eeada793945

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp313-cp313-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp313-cp313-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 bdacc778a5909768605e3abf4abde8efc8b29552b41d3d993c103017525d3b79
MD5 f36d93d50a6c9e58e516544865c1e0f5
BLAKE2b-256 3234f49e1ee9eb6c81a606480b3144aa61224df72193181ae4a75549bd19ffff

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp313-cp313-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 929cd906331ca5f1dcdc77baa6d7aa04c1974d6ec258948ed611539058b861b9
MD5 87e0b10e792b7ea323d0ac8f1003c4ce
BLAKE2b-256 6cd671612902d584ff080bf1b7332e287317ad15bcc2c97d60eeb500f49dd073

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp313-cp313-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp313-cp313-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 b09807566ed4b6742add6dcad6653d9265cef8098965fed0611eefa95b3248b5
MD5 3c4eeb8f276c08dd9f2e12f3f4194454
BLAKE2b-256 d7154d89b83fb433bd7d0825fc89d924b5783843b272ef5face2a77d474508f9

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp313-cp313-macosx_10_15_universal2.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp313-cp313-macosx_10_15_universal2.whl
Algorithm Hash digest
SHA256 14b970cc9a0ad9a66ce09dc67dd3e78a4ebb8f969575fbe20b4b90214ee13c6b
MD5 ec2d7236dec5525823df7fd6b0eed45a
BLAKE2b-256 c18c2b6087ee9dc13c5929359f3bc9e2d717fe38bd44355fe486661c76578b05

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 d2bda84dbae73bd18f047b91c0a73abd4e3d2a72564ae29e27c0f702a52c50af
MD5 c1b4937ff11fc32f5cbbd05bdfd5011e
BLAKE2b-256 a4ab3db7c5eedd38552516126b9342cc26798017e29089a35ee7a7ba013221ed

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp312-cp312-win32.whl.

File metadata

  • Download URL: cadscorelt-0.9.193-cp312-cp312-win32.whl
  • Upload date:
  • Size: 414.1 kB
  • Tags: CPython 3.12, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.12.3

File hashes

Hashes for cadscorelt-0.9.193-cp312-cp312-win32.whl
Algorithm Hash digest
SHA256 32aa49a8969598996b1bc95fb40c743e04f875a80095772ed8117328a0ea8c93
MD5 90978ca265cfdfe18bf5dae9a4a4d30e
BLAKE2b-256 e1b3853b79ef5174db5b1fb37de374cee2c92e71cfa2877811e2d162e0c1b4f1

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp312-cp312-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp312-cp312-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 414ea9ffc3392bf43bbdd6c678e5710a9ab7ed27f5276bb07a2b9f0c7ad3090c
MD5 d3a6cd878dfeffb8c6ee04cd06aa770c
BLAKE2b-256 64a8ecbfaab29de7af599a8c763744df50d3de07129e2c9512add18355796b55

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp312-cp312-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp312-cp312-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 7c4d346d0f68d4c5b3fd92dcbbecc9a261f1c48d191867ef7ebe8664c1270303
MD5 8a575c1af14dc058819c17387ef26bc2
BLAKE2b-256 d93877dbc946ef41b69f33130fd217a46061954494a9d5405d361557000d1067

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 ca76a0c6f7b9f7b032b206112340b4686c4e14e2047c51d34d5cba983ab2c206
MD5 eeddca830909d4a73300dab4879bb659
BLAKE2b-256 984566169d8e5ae0d8f762b710f50c035ed4cd9150d434a509c91cd546fbeffc

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp312-cp312-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp312-cp312-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 33ad70127846e19df812d4d662e991d40f1bc5335bc7bd18db12953a591d319b
MD5 9205142fb06118cb150b37a9de06d7f2
BLAKE2b-256 4e6097390e5cb8dce0342f030a68277cace3694f8005ba8d8791ae26117139e4

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 c71eb86c0452c4e8270ef332bbc50a9307607af2d1f0ae44fe64e5234a950958
MD5 95b600f00df974568eae7973f7c2f27c
BLAKE2b-256 71ad5aac39c8de3c5e098d934cc00c28c2e3ae60600b466c1a32ba7f89d6c3d2

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp312-cp312-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp312-cp312-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 84276f0b0bfa982fc9386a8cd876e5e7eaf0e153e2a9b1395cb2ebb38ee3af88
MD5 9ac351614ccd31e039fad9cdf126dc62
BLAKE2b-256 b212564ab683f1d58148bd3a3c2bb2d6f3139d67f944110b83be3e6c68221745

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp312-cp312-macosx_10_15_universal2.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp312-cp312-macosx_10_15_universal2.whl
Algorithm Hash digest
SHA256 79e3147cdad982164996699f7e268581fe75c8b04670c7501d41abe4988263cd
MD5 61da39dfe79a45ca8d9d94394c9ae5c1
BLAKE2b-256 da00024f127d80d3492106175f9c8a2bff48ce5acab2da766c9fc04584522c1d

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 40f24a5f1bb84043258e98200283ff525d1a04499bbd926948b071d4e6b810ab
MD5 c1239dec76b0888054b3b99e9e04c76b
BLAKE2b-256 86e8325bf441d39ded03230816a0cba6e80cb351c55d4f3952752d236f96affa

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp311-cp311-win32.whl.

File metadata

  • Download URL: cadscorelt-0.9.193-cp311-cp311-win32.whl
  • Upload date:
  • Size: 413.4 kB
  • Tags: CPython 3.11, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.12.3

File hashes

Hashes for cadscorelt-0.9.193-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 357b9fe4c249d01e566944cd141849cc1a60a25db855baa3390323755e8bdfcf
MD5 a51ea29ff8295873d65025be2b3de209
BLAKE2b-256 b91a8b866aa7539afd38689df57645778bc5cf401e9b1d8fae31fc75d427ff9e

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp311-cp311-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp311-cp311-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 989aa59d7963dc2bec720dff96c5a21726a22d6641f616b328a9e565f085d19a
MD5 0a267fe39df643cda1c6dc9aa4a64260
BLAKE2b-256 e1f0d1b0e791f160627cb8d9ff5aad7f81c87d17ceeca978a1fb2d757154665d

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp311-cp311-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp311-cp311-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 63c8868ea9949d47cce41e88a5781b943595ff614dfe69f5da5d01ea22025356
MD5 d71ab0ca67625a9e181e0805c8308552
BLAKE2b-256 b0f69582bd1204ced1f526ce1f5e344a2bf2c9cfbd7b8ee6feabe4189eaeb571

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b174b19366a71be2cc289a5e22a9c073b309a42a581a7aed747ddb58c16591df
MD5 f2b2878ea5762661b55c0f1319995f83
BLAKE2b-256 287dc1d6a597d5e5d274f8d3133b231b291b956f622d33b120864c86b42bf4ab

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp311-cp311-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp311-cp311-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 f4e0759b16a0d0ece6671c2670afa6ff17e2e27f9e1dc2482605c1e99f9afbd5
MD5 95c91c471297d8015fa11f6deaf610fa
BLAKE2b-256 39dcf978cbbee7b8f9993d88bcbb0f54b999b08f28fd09c78d2ddaec0b976d43

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 a44ce832e3f983986c169b27f9e4fec8cdd973522aabd22eddb572cb5879dc16
MD5 2ef401fe860e0ebde0018617c296f873
BLAKE2b-256 f00981fbf01d28c26b5e8f0d7418271a60136cc86cd16577659cba02b44293c4

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp311-cp311-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp311-cp311-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 103b0c084dc5bce66e0b380c6e0352257c4c4840350492ab99e84e69e96de282
MD5 6ad9461f8908bb7a2a5800448bef8bae
BLAKE2b-256 26b6d5ac14ab46499faaf716dcaaa83acbdc0e36d54120f3dcc22ae8f8fafb98

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp311-cp311-macosx_10_15_universal2.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp311-cp311-macosx_10_15_universal2.whl
Algorithm Hash digest
SHA256 0e02053ce110ce5c73d53557c6d81f32ff2797e1bdaa65698c48c48178e5986b
MD5 b9509ff64fb0a3e90b61f97d29033d7e
BLAKE2b-256 cd23871d2ac047ce88403c5aae57488d67751d598b4d1c52b959ea3d1dcd3e77

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 c4598f01f264d42ba58a2be03a85a5406d35ece891fa57cba997874dbfd81510
MD5 dcb457d0ef6bcf6d8b49e5e3986d1047
BLAKE2b-256 ba514ad35fc3e4fc07608f6eda508705d857d2c2cdec9ce1973965768a31cb87

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp310-cp310-win32.whl.

File metadata

  • Download URL: cadscorelt-0.9.193-cp310-cp310-win32.whl
  • Upload date:
  • Size: 413.4 kB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.12.3

File hashes

Hashes for cadscorelt-0.9.193-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 2b94535fdf8ace6a3b6e0bdd8e9c758820b2e872c2bdaef3767625c72062a982
MD5 39294cbbb0f3b3c0cc25fdc3555e9f3b
BLAKE2b-256 e1efff64481047d689d4d575b15b67dc51aa7ac54392318b02c90bc4a0e425d2

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp310-cp310-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp310-cp310-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 f3cbf091584889b6f88e95d4768320d56e2ebda3c7a760d870ab3cfa9aa5d8c6
MD5 c3dfea29e8a5f5f9c843dfa2ca9a2a0f
BLAKE2b-256 99e99f26e5ae88be7d34e97b1154dd93e6e03960322b8dcfce860131c613f1ad

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp310-cp310-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp310-cp310-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 154937295cc6375e89c415bf297a61b99888074c5c0e08ac1972644d51103a23
MD5 f660cff3d8af900afed8a05222cb7e97
BLAKE2b-256 ee936be7111b412e29acf2559bab34da4c15a46995283493650d5a615e4ecacd

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 cd458924158a377932d823038efba95715837dfa78fabd27d2754ab22f979656
MD5 9027d5ad94f865576462cd9d7f853ed0
BLAKE2b-256 0dfbf5a5a984ac40f6206038bd0ae43722a0bd1a9d7863639b5fcaafb36c7fdc

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 c800346a9580cc7d310a651ae8001410dcc263f0c0cab604224270550642696f
MD5 78915e889b5a91eb9e915df0f4941d63
BLAKE2b-256 386f239e788b2c25c33d4cb437ce658ccafa96911806c4ab5d5b8fbda4f73d79

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 6ff9f56d5f9c67ed3637e172eedecaca6674b5ad932f8941b00f9036f5dc9d91
MD5 722aea8357e7527e64e682c3dd2cfc02
BLAKE2b-256 0aa06b53b9135f9208aeb433d269def127c7f2646ec3106da185b317343e7b91

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp310-cp310-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp310-cp310-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 9e5a26eba901981fbebb019b72fd503c6fb73708f476a221a71ce5335b5a85a9
MD5 a0b8701f116c2de471dd62ba299e3c45
BLAKE2b-256 c1a8812f0c2120de6c1fae06aa4f0d7901eec9808acb7e02fba4fead18a0b950

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp310-cp310-macosx_10_15_universal2.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp310-cp310-macosx_10_15_universal2.whl
Algorithm Hash digest
SHA256 9d4b5f8cd9d96951010f9ef9160f6459f6215c2b02c1c4655115ea69ee3509ba
MD5 d1e3a770637e5c615825f204bee09c49
BLAKE2b-256 9486dcaecc2089d591f5b4b2981047209e62cc79bf5380e1387517a9368f4d54

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: cadscorelt-0.9.193-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 522.2 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.12.3

File hashes

Hashes for cadscorelt-0.9.193-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 647905f548d685d9c1cea0381490d2c1ae717de453c80775d52dba7ff9a4ff50
MD5 5fdf26d2c34df99ae513143343245748
BLAKE2b-256 75b07600f5b3d6b5362cc6efcfea7b4d947b1ba899c3d45544ec0ba396b3c59b

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp39-cp39-win32.whl.

File metadata

  • Download URL: cadscorelt-0.9.193-cp39-cp39-win32.whl
  • Upload date:
  • Size: 413.4 kB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.12.3

File hashes

Hashes for cadscorelt-0.9.193-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 b08ab3acef48d294598f5db4f53dfc8c02077727590489ecc1fa73ed5db10c2e
MD5 0dd16ee8e366f99cdb6e79e0b1640a2b
BLAKE2b-256 9f864e9bd53de4e2b529325a0ab91416c51faee49c2220b47742035f1a5520f8

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp39-cp39-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp39-cp39-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 43eee4bd059db60287b739f8d02966079c89eab562cddcb89715375d74b55541
MD5 99f4f85a10f1bff402a3bfc7d9e6ad6a
BLAKE2b-256 10e63f06fbbf39dc6fcd8aa6f3731acc6c1f5f533100730babd213f07a5e3032

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp39-cp39-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp39-cp39-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 d6d8e0365238d600ad3c22d12aced70732928833d6be81299e33014adcd416f6
MD5 e116e80327e492deb6bee487e60bdf90
BLAKE2b-256 a63e132cd07f3d10e6d6c9648a4c3332bd14c59b57a09a34ca17bfbbda5d3d82

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 492a202dd78f23f1941b3a1b05f365b530262028099ada37711fb429593ed7bd
MD5 cd2dc4f044a6236faaf010761a26ef29
BLAKE2b-256 bcd0e72924cf77ccc198dbddbb0385fce2ef4152d9abc9b27af5a2a094f736bc

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp39-cp39-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 c671d3397b506237da1697876a0898d8b0629538551351a1ba62ba599d687ea8
MD5 0c6bd8b36636868e613f179216cfef4d
BLAKE2b-256 24d3d196c541272c5c3babf267143870187cea11b02598eed829fe61c5454e8e

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 3fb38a7c281297b5ef26d001405a0b6fc2408edee9b5eb56acc900ff4a4693e2
MD5 bbf7e4910d623d730a48907367a6cc3d
BLAKE2b-256 e7402b0e1a678ed3637d33fc469189e75a7989266b9e5cad11c7f163f807ac7e

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp39-cp39-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp39-cp39-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 e95cd2dc65c1586a0d466c0235547a323b84676175a89a4ed6073049bd76c847
MD5 a682c7192031aa344cd282dfd5e001a6
BLAKE2b-256 cff288452a8e171e983e376f7fa5aed9fb504bf7dd442e4f1a992f169e27cef5

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp39-cp39-macosx_10_15_universal2.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp39-cp39-macosx_10_15_universal2.whl
Algorithm Hash digest
SHA256 35a39b496cd757d20bc8319b505253b51e77d1a7bcfa65387cfb6870900ce9b7
MD5 e5841ebfb3bba3559f3f90f6151419ac
BLAKE2b-256 7e2cde335068bd4c237b66653640d5a86122a472c7863201cadd398ce2a3ecf5

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: cadscorelt-0.9.193-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 522.2 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.12.3

File hashes

Hashes for cadscorelt-0.9.193-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 562107470786b9d9df22a261708158cdc91823256a290015168a3baaa4a050f1
MD5 2db7ba3ec3dc50a6036b9a1b4b7678e8
BLAKE2b-256 b93194d9631e11162e870296914ada91242a5d78237856bf1edff0b11078a27d

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp38-cp38-win32.whl.

File metadata

  • Download URL: cadscorelt-0.9.193-cp38-cp38-win32.whl
  • Upload date:
  • Size: 413.3 kB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.12.3

File hashes

Hashes for cadscorelt-0.9.193-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 41b186aeb5d7cfbf50397434ff2ef77d62da34bf16b3f755df3b49befd180a38
MD5 1ea78692564d48cf498360bb7560f04f
BLAKE2b-256 6c58cf966419a6ae13ee6908c6e6ff210e9d2de423e3646f3f9143f9b2e82359

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp38-cp38-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp38-cp38-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 d2aebe327cc079e349269f3271a4aa5ec24e3503ef08c1459352443bb7b81a98
MD5 7e766ed78104fb950cd495a12e6b4d1f
BLAKE2b-256 1257cb93c53264883a5c323918e912e951c16ef7d441a5b55a15ae1833bbb6fe

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp38-cp38-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp38-cp38-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 6d0cb4c4f7e2f0e4594d7741667addd3f4b0a36fb873757a4f56d1bee93043f8
MD5 27d2f170aae2e23420dee66ba2d530b1
BLAKE2b-256 a97a80bc3af4e2033a6b9bd9c8963ca2d78a2d49714bc2efd61b9036882da66e

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 9b757ad7237976037f9ddc26c662f1b442b185ee767749517e0ce42d9973612d
MD5 fdbca8b10bcbdce88720f5b908cd4924
BLAKE2b-256 ba5bb9861cc62b90c27f3ae08f5ffeb675d2693bccaaa2fdc9e7551dcaa94f2b

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 39fccda9f7d83072a4cf6027445c682d47ea50e4aeb467b4fcadaf3ec34621cc
MD5 7c766e8ba930c0387559b0e9755e42bf
BLAKE2b-256 43ca7af2cf9c76566c5b4296dbc79db1ef0d5cf43dc0da33b6de5eab0b01c74d

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 5c32cd6ade948365acac2bc42826d7e34d5da299a54a37e9c835a0c3fa3e7738
MD5 839226004dd938a7c9574a57a16cb7b9
BLAKE2b-256 fd70565a3026ed335294cfc28fd719e1dd986b738e97042b432dd41c16b235aa

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp38-cp38-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp38-cp38-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 523346cd0df4c45c5122e0a07936a3d236a5b5905646070642d3add96a204211
MD5 2d50b4c674a2c504deccf547282a1e67
BLAKE2b-256 992b2406745bacdca309e2f84379ef0be5527837388c6fcf6562f814fe7daa4f

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp38-cp38-macosx_10_15_universal2.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp38-cp38-macosx_10_15_universal2.whl
Algorithm Hash digest
SHA256 e6b1a907f4aa22101790c0ff101f13a9b0ebbaee4a0590e34207339f8d627a96
MD5 3b5c075a908fe2b72d87f2b3da2b3fcb
BLAKE2b-256 1bcf5c61af6bf629b6a7cfd23824d809af9ff9f78be2c7ca738089333facf099

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 eeb6b74dca2dd210f56697ebd68e1827f3471d2f4d945e96e5962282b2bc074b
MD5 fce5262e6905dd4ebb926865748b12eb
BLAKE2b-256 ae6170d8a2c4053eecc38e404e1839f642baaacb1ecebba8d1d5125ddb0607a6

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp37-cp37m-win32.whl.

File metadata

  • Download URL: cadscorelt-0.9.193-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 413.0 kB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.12.3

File hashes

Hashes for cadscorelt-0.9.193-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 1c6979c2b1f15fa7fe97a57cd65b994953c42034060d6cb1531fe4430cfa5cdd
MD5 bef9cfc076fa469da6ab99746881302b
BLAKE2b-256 a31ca548d03acad58b93cdbb0d7acb19128140d7b70c2b9fc0411afb9a83da48

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp37-cp37m-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp37-cp37m-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 7eee4af50fcd14524845c8dc9df5cfdeaa877edfd7b15fb2dabf2a2c91489152
MD5 6c4e2996af3087a594f7fe8d0b209a45
BLAKE2b-256 ef770011db5b948a18a40a0700f5e9e226306dc85450264138821bd6ab711052

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp37-cp37m-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp37-cp37m-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 ad26627c209c8b9868a17f338ac5630b12c52b4fcb3d0caae3a9e8dc5cc0c15d
MD5 68dd8faa23835ea032f2444e7632eb84
BLAKE2b-256 2aeda1ff33ceddf673523d2dcfeb13791eea227c0867488000806b3c50142a16

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 999a40521219c357f63a8498f4fb5bfb4b6508eeb841c2689c747178c2851a9a
MD5 07df1c55e9ae9c237e8b62d29e3be8dd
BLAKE2b-256 d41397ac067986b53376c517155118f85c772b8cce9e6b56cae8b866666b4565

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 075afe41e0b6fd6e2becd011f7d3bf1bfa570db0e005a4d0149147f7b358b553
MD5 31c99b0971de9931f2b2027d268e949f
BLAKE2b-256 af4cbb620f9ad8268a885fc8d25b93783490110733b60bc8e1bc9d87b43593ec

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp37-cp37m-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp37-cp37m-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 c3dc389b89c6b02a740d82fee5ff1e0a44bdb484b414c3821d1303d6b033b32d
MD5 b7830d55a040d31ca64031c616644539
BLAKE2b-256 afc50fc08c42a6ab5fa5d77727d1f50784a16a11bd22898af89d5705e1742b99

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp36-cp36m-win_amd64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 6bc0ca380820ec5af54ae8d1e9bb37b51f0cb117428edb36b8ee80a0ef4954ee
MD5 86edd9cd0b47ac5079e948b58407533d
BLAKE2b-256 8e5fe9693a70c2d1228c62b2bd02f34e1fb3a4a4f18f1f29e24aa616e30db45e

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp36-cp36m-win32.whl.

File metadata

  • Download URL: cadscorelt-0.9.193-cp36-cp36m-win32.whl
  • Upload date:
  • Size: 413.0 kB
  • Tags: CPython 3.6m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.12.3

File hashes

Hashes for cadscorelt-0.9.193-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 ce9d1aec09c86394eeeeeb674e9547df827532eb867e7eb489dc6a4b84cfbd00
MD5 fd3998fa732b4da5334fd6cff74b7e80
BLAKE2b-256 5772ee2caa96b2a27c24007c9bca9dca99dcdc6dc2034bcece7fc39ad32e86cf

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp36-cp36m-musllinux_1_2_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp36-cp36m-musllinux_1_2_x86_64.whl
Algorithm Hash digest
SHA256 0f89f571845872295727c3422a11754ccad28471f6484ecf697534a43893db7c
MD5 2f49b135e8ff14a3c246c32d734898c3
BLAKE2b-256 4468543e78e2b308cdd778df2eba4e60bda72574c7a58219d3cfdc4301f9d408

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp36-cp36m-musllinux_1_2_i686.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp36-cp36m-musllinux_1_2_i686.whl
Algorithm Hash digest
SHA256 35dd2dbce1da53ce61f909b54bdddb12c8c682020d87ff9163b7ef375ca55a8a
MD5 8f8c649aa90fd87bf43dc667772b7b9c
BLAKE2b-256 cd2b18e11caeee751527f8298a199e046cbc83073ba6eadb0eb72ef45ea454ce

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1124b70ca562561ecabc3b2c0ed7bb43857ae0759999f1859c2516e93ea098e0
MD5 492b9a08f537e66037525adf3e4c1502
BLAKE2b-256 e6f35bf055bc4b61e9dd28b113708795d14aaf0cbc67854440eee6535e1c8c2a

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp36-cp36m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp36-cp36m-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 0179e2b3ee8e27b4b2570a1fbca1016fdd12cc7c7cce500e695d193a308d18d4
MD5 453435dc655420ee5b10ed0466eb2805
BLAKE2b-256 a477b6e3f5c31f2f4b9fc826b8785ad46e069c96886a02bd7a7a848a26cef4d3

See more details on using hashes here.

File details

Details for the file cadscorelt-0.9.193-cp36-cp36m-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for cadscorelt-0.9.193-cp36-cp36m-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 d46901a36237d9c893caa92f5523e70fcdc55f602fd316464d15a82ae3f08a09
MD5 f9c958b05756b7b85734a5b3f224c43c
BLAKE2b-256 6140b9492bb0ce8c2a187d963a96259dcfef8fb7460cb74c04273dc9d671955e

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page