A command-line tool that analyses the diversity and motifs of protein sequences

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for ShanW from gravatar.com ShanW

Unverified details

These details have not been verified by PyPI
Project links
Meta
Report project as malware

Project description

DiMA - Diversity Motif Analyser

Table of Contents

What is DiMA?

Protein sequence diversity is one of the major challenges in the design of diagnostic, prophylactic and therapeutic interventions against viruses. DiMA is a tool designed to facilitate the dissection of protein sequence diversity dynamics for viruses. DiMA provides a quantitative measure of sequence diversity by use of Shannon’s entropy, applied via a user-defined k-mer sliding window. Further, the entropy value is corrected for sample size bias by applying a statistical adjustment. Additionally, DiMA further interrogates the diversity by dissecting the entropy value at each k-mer position to various diversity motifs. The distinct k-mer sequences at each position are classified into the following motifs based on their incidence. Index is the predominant sequence, and all other distinct k-mers are referred to as total variants, sub-classified into major variant (the predominant variant), minor variants (k-mers with incidence in between major and unique motifs) and unique variants (seen once in the alignment). Moreover, the description line of the sequences in the alignment can be formatted for inclusion of meta-data that can be tagged to the diversity motifs. DiMA enables comparative diversity dynamics analysis, within and between proteins of a virus species, and proteomes of different viral species.

Installation

pip install dima-cli

Basic Usage

Shell Command

dima-cli -i aligned_sequences.afa -o results.json

Python

from dima import Dima
results = Dima(sequences="aligned_sequences.afa", sequences_source='file').run()

Results

{
   "sequence_count":203,
   "support_threshold":30,
   "low_support":false,
   "protein_name":"Unknown Protein",
   "kmer_length":9,
   "results":[
      {
         "position":1,
         "low_support":false,
         "entropy":0.8383740426713246,
         "support":124,
         "distinct_variants_count":4,
         "distinct_variants_incidence":3.2258062,
         "variants":[
            {
               "sequence":"MKTIIALSC",
               "count":2,
               "incidence":1.6129031,
               "motif_short":"Mi",
               "motif_long":"Minor",
               "metadata":null
            },
            {
               "sequence":"MKTIIALSH",
               "count":3,
               "incidence":2.4193547,
               "motif_short":"Mi",
               "motif_long":"Minor",
               "metadata":null
            },
            {
               "sequence":"METISLISM",
               "count":1,
               "incidence":0.80645156,
               "motif_short":"U",
               "motif_long":"Unique",
               "metadata":null
            },
            {
               "sequence":"MKNIIALSY",
               "count":13,
               "incidence":10.4838705,
               "motif_short":"Ma",
               "motif_long":"Major",
               "metadata":null
            },
            {
               "sequence":"MKTIIALSY",
               "count":105,
               "incidence":84.67742,
               "motif_short":"I",
               "motif_long":"Index",
               "metadata":null
            }
         ]
      }
   ]
}

Advance Usage

Shell Command

dima-cli -i aligned_sequences.afa -o results.json -f "accession|strain|country|date"

Python

from dima import Dima
results = Dima(sequences="aligned_sequences.afa", sequences_source='file', header_format="accession|strain|country|date").run()

Results

{
   "sequence_count":203,
   "support_threshold":30,
   "low_support":false,
   "protein_name":"Unknown Protein",
   "kmer_length":9,
   "results":[
      {
         "position":1,
         "low_support":false,
         "entropy":0.8361476856397749,
         "support":124,
         "distinct_variants_count":4,
         "distinct_variants_incidence":3.2258062,
         "variants":[
            {
               "sequence":"MKNIIALSY",
               "count":13,
               "incidence":10.4838705,
               "motif_short":"Ma",
               "motif_long":"Major",
               "metadata":{
                  "strain":[
                     "A/India/Pun_1922030/2019",
                     "A/India/Pun_1922292/2019",
                     "A/India/Pun_1921693/2019",
                     "A/India/Pun_1922218/2019",
                     "A/India/Pun_1922278/2019",
                     "A/India/Pun_1924667/2019",
                     "A/India/Pun_1923708/2019",
                     "A/India/Pun_1921994/2019",
                     "A/India/Pun_1922260/2019",
                     "A/India/Pun_1922016/2019",
                     "A/India/Pun_1923690/2019",
                     "A/India/Pun_1922295/2019",
                     "A/India/Pun_1923665/2019"
                  ],
                  "country":[
                     "India",
                     "India",
                     "India",
                     "India",
                     "India",
                     "India",
                     "India",
                     "India",
                     "India",
                     "India",
                     "India",
                     "India",
                     "India"
                  ],
                  "accession":[
                     "MN955496",
                     "MN955492",
                     "MN955499",
                     "MN955502",
                     "MN955493",
                     "MN955488",
                     "MN955487",
                     "MN955498",
                     "MN955494",
                     "MN955497",
                     "MN955489",
                     "MN955491",
                     "MN955490"
                  ],
                  "date":[
                     "08/04/2019",
                     "08/19/2019",
                     "07/17/2019",
                     "08/09/2019",
                     "08/18/2019",
                     "08/01/2019",
                     "09/07/2019",
                     "07/26/2019",
                     "08/16/2019",
                     "07/30/2019",
                     "08/31/2019",
                     "08/20/2019",
                     "09/01/2019"
                  ]
               }
            },
            {
               "sequence":"MKTIIALSY",
               "count":105,
               "incidence":84.67742,
               "motif_short":"I",
               "motif_long":"Index",
               "metadata":{
                  "date":[
                     "01/02/2019",
                     "02/17/2019",
                     "01/14/2019",
                     "02/17/2019",
                     "01/17/2019",
                     "03/14/2019",
                     "02/13/2019",
                     "01/02/2019",
                     "02/06/2019",
                     "01/18/2019",
                     "10/11/2019",
                     "11/15/2019",
                     "01/10/2019",
                     "01/17/2019",
                     "01/17/2019",
                     "01/24/2019",
                     "02/01/2019",
                     "02/01/2019",
                     "02/01/2019",
                     "02/14/2019",
                     "03/14/2019",
                     "07/25/2019",
                     "08/21/2019",
                     "09/05/2019",
                     "09/05/2019",
                     "03/2019",
                     "02/2019",
                     "01/28/2019",
                     "10/08/2019",
                     "03/27/2019",
                     "02/14/2019",
                     "03/14/2019",
                     "01/15/2019",
                     "01/19/2019",
                     "01/28/2019",
                     "01/18/2019",
                     "02/14/2019",
                     "01/04/2019",
                     "01/08/2019",
                     "01/07/2019",
                     "01/28/2019",
                     "01/2019",
                     "01/10/2019",
                     "01/11/2019",
                     "01/13/2019",
                     "01/24/2019",
                     "01/08/2019",
                     "01/09/2019",
                     "01/14/2019",
                     "01/10/2019",
                     "02/2019",
                     "01/2019",
                     "09/05/2019",
                     "01/19/2019",
                     "01/03/2019",
                     "01/23/2019",
                     "02/01/2019",
                     "02/21/2019",
                     "02/28/2019",
                     "02/05/2019",
                     "01/07/2019",
                     "01/08/2019",
                     "01/08/2019",
                     "01/28/2019",
                     "01/28/2019",
                     "01/29/2019",
                     "01/29/2019",
                     "01/29/2019",
                     "01/30/2019",
                     "01/30/2019",
                     "01/30/2019",
                     "01/31/2019",
                     "01/31/2019",
                     "01/31/2019",
                     "01/09/2019",
                     "02/27/2019",
                     "03/05/2019",
                     "03/05/2019",
                     "03/05/2019",
                     "03/05/2019",
                     "03/08/2019",
                     "03/08/2019",
                     "03/04/2019",
                     "03/12/2019",
                     "01/05/2019",
                     "01/28/2019",
                     "01/29/2019",
                     "01/31/2019",
                     "02/22/2019",
                     "03/05/2019",
                     "01/23/2019",
                     "02/19/2019",
                     "04/14/2019",
                     "01/17/2019",
                     "04/04/2019",
                     "02/01/2019",
                     "02/01/2019",
                     "03/21/2019",
                     "05/24/2019",
                     "08/13/2019",
                     "08/05/2019",
                     "01/08/2019",
                     "01/14/2019",
                     "01/21/2019",
                     "01/12/2019"
                  ],
                  "country":[
                     "Iran",
                     "Iran",
                     "Turkey",
                     "Iran",
                     "China",
                     "China",
                     "India",
                     "Iran",
                     "India",
                     "Japan",
                     "China",
                     "China",
                     "China",
                     "China",
                     "China",
                     "China",
                     "China",
                     "China",
                     "China",
                     "China",
                     "China",
                     "China",
                     "China",
                     "China",
                     "China",
                     "China",
                     "China",
                     "Japan",
                     "China",
                     "Japan",
                     "China",
                     "China",
                     "Japan",
                     "Japan",
                     "Japan",
                     "South_Korea",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "China",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "South_Korea",
                     "South_Korea",
                     "South_Korea",
                     "South_Korea",
                     "China",
                     "China",
                     "China",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "South_Korea",
                     "South_Korea",
                     "South_Korea",
                     "South_Korea",
                     "South_Korea",
                     "South_Korea",
                     "South_Korea",
                     "South_Korea",
                     "South_Korea",
                     "South_Korea",
                     "Japan",
                     "Japan",
                     "Japan",
                     "Japan",
                     "South_Korea",
                     "South_Korea",
                     "Japan",
                     "South_Korea",
                     "South_Korea",
                     "Japan",
                     "South_Korea",
                     "China",
                     "China",
                     "China",
                     "India",
                     "India",
                     "India",
                     "South_Korea",
                     "South_Korea",
                     "South_Korea",
                     "South_Korea"
                  ],
                  "accession":[
                     "MK592790",
                     "MK648247",
                     "MK840323",
                     "MK648248",
                     "MT102500",
                     "MT102510",
                     "MK592841",
                     "MK592791",
                     "MK592842",
                     "MK785815",
                     "MT102520",
                     "MT102521",
                     "MT102498",
                     "MT102499",
                     "MT102501",
                     "MT102502",
                     "MT102504",
                     "MT102506",
                     "MT102507",
                     "MT102508",
                     "MT102512",
                     "MT102514",
                     "MT102515",
                     "MT102516",
                     "MT102517",
                     "MN594842",
                     "MN594840",
                     "MK869211",
                     "MT102519",
                     "MN074410",
                     "MT102509",
                     "MT102511",
                     "MK785807",
                     "MK785831",
                     "MK633673",
                     "MK763864",
                     "MN873980",
                     "MK905306",
                     "MK633641",
                     "MK576906",
                     "MK633649",
                     "MN594838",
                     "MK743434",
                     "MK743442",
                     "MK743450",
                     "MK785847",
                     "MK763014",
                     "MK786319",
                     "MK869555",
                     "MK869563",
                     "MN594841",
                     "MN594839",
                     "MT102518",
                     "MK785823",
                     "MK576890",
                     "MK785839",
                     "MK869203",
                     "MK912758",
                     "MK912766",
                     "MK927223",
                     "MK633617",
                     "MK633625",
                     "MK633633",
                     "MK633657",
                     "MK633681",
                     "MK633689",
                     "MK633697",
                     "MK898645",
                     "MK633705",
                     "MK633713",
                     "MK633721",
                     "MK633729",
                     "MK633737",
                     "MK898652",
                     "MK868723",
                     "MK913110",
                     "MK913126",
                     "MK913134",
                     "MK913142",
                     "MK913158",
                     "MK913166",
                     "MK913174",
                     "MK913182",
                     "MN169149",
                     "MK576898",
                     "MK633665",
                     "MK898639",
                     "MK898657",
                     "MK913102",
                     "MK913150",
                     "MK762978",
                     "MK913118",
                     "MN081410",
                     "MK742954",
                     "MN074010",
                     "MT102503",
                     "MT102505",
                     "MT102513",
                     "MN955500",
                     "MN955495",
                     "MN955501",
                     "MK763848",
                     "MK763856",
                     "MK763872",
                     "MK869539"
                  ],
                  "strain":[
                     "A/Alborz/153084/2019",
                     "A/Iran/Clinical_Sample/2019",
                     "A/Turkey/8543/2019",
                     "A/Iran/Clinical_Sample/2019",
                     "A/Homo_sapien/China/LS320/2019",
                     "A/Homo_sapien/China/LS330/2019",
                     "A/India/Pun_19615/2019",
                     "A/Alborz/153427/2019",
                     "A/India/Pun_19533/2019",
                     "A/Japan/8262/2019",
                     "A/Homo_sapien/China/LS340/2019",
                     "A/Homo_sapien/China/LS341/2019",
                     "A/Homo_sapien/China/LS318/2019",
                     "A/Homo_sapien/China/LS319/2019",
                     "A/Homo_sapien/China/LS321/2019",
                     "A/Homo_sapien/China/LS322/2019",
                     "A/Homo_sapien/China/LS324/2019",
                     "A/Homo_sapien/China/LS326/2019",
                     "A/Homo_sapien/China/LS327/2019",
                     "A/Homo_sapien/China/LS328/2019",
                     "A/Homo_sapien/China/LS332/2019",
                     "A/Homo_sapien/China/LS334/2019",
                     "A/Homo_sapien/China/LS335/2019",
                     "A/Homo_sapien/China/LS336/2019",
                     "A/Homo_sapien/China/LS337/2019",
                     "A/Wuhan/11193/2019",
                     "A/Wuhan/1120/2019",
                     "A/Japan/8604/2019",
                     "A/Homo_sapien/China/LS339/2019",
                     "A/Japan/9505/2019",
                     "A/Homo_sapien/China/LS329/2019",
                     "A/Homo_sapien/China/LS331/2019",
                     "A/Japan/8261/2019",
                     "A/Japan/8264/2019",
                     "A/Japan/NHRC_OID_FDX70576/2019",
                     "A/South_Korea/8207/2019",
                     "A/Yokosuka/NHRC_OID_FDX70622/2019",
                     "A/Japan/NHRC_OID_FDX70557/2019",
                     "A/Japan/NHRC_OID_FDX70566/2019",
                     "A/Japan/7848/2019",
                     "A/Japan/NHRC_OID_FDX70571/2019",
                     "A/Wuhan/345/2019",
                     "A/Japan/8000/2019",
                     "A/Japan/8001/2019",
                     "A/Japan/8002/2019",
                     "A/Japan/8266/2019",
                     "A/South_Korea/8203/2019",
                     "A/South_Korea/8352/2019",
                     "A/South_Korea/8671/2019",
                     "A/South_Korea/8674/2019",
                     "A/Wuhan/5413/2019",
                     "A/Wuhan/877/2019",
                     "A/Homo_sapien/China/LS338/2019",
                     "A/Japan/8263/2019",
                     "A/Japan/7846/2019",
                     "A/Japan/8265/2019",
                     "A/Japan/8603/2019",
                     "A/Japan/8768/2019",
                     "A/Japan/8769/2019",
                     "A/Japan/8957/2019",
                     "A/Japan/NHRC_OID_FDX70561/2019",
                     "A/Japan/NHRC_OID_FDX70563/2019",
                     "A/Japan/NHRC_OID_FDX70564/2019",
                     "A/Japan/NHRC_OID_FDX70572/2019",
                     "A/Japan/NHRC_OID_FDX70577/2019",
                     "A/Japan/NHRC_OID_FDX70579/2019",
                     "A/Japan/NHRC_OID_FDX70583/2019",
                     "A/Japan/NHRC_OID_FDX70584/2019",
                     "A/Japan/NHRC_OID_FDX70586/2019",
                     "A/Japan/NHRC_OID_FDX70587/2019",
                     "A/Japan/NHRC_OID_FDX70589/2019",
                     "A/Japan/NHRC_OID_FDX70590/2019",
                     "A/Japan/NHRC_OID_FDX70591/2019",
                     "A/Japan/NHRC_OID_FDX70592/2019",
                     "A/South_Korea/8667/2019",
                     "A/South_Korea/8823/2019",
                     "A/South_Korea/8825/2019",
                     "A/South_Korea/8826/2019",
                     "A/South_Korea/8827/2019",
                     "A/South_Korea/8829/2019",
                     "A/South_Korea/8830/2019",
                     "A/South_Korea/8831/2019",
                     "A/South_Korea/8832/2019",
                     "A/South_Korea/9116/2019",
                     "A/Japan/7847/2019",
                     "A/Japan/NHRC_OID_FDX70574/2019",
                     "A/Japan/NHRC_OID_FDX70581/2019",
                     "A/Japan/NHRC_OID_FDX70593/2019",
                     "A/South_Korea/8822/2019",
                     "A/South_Korea/8828/2019",
                     "A/Japan/8142/2019",
                     "A/South_Korea/8824/2019",
                     "A/South_Korea/9704/2019",
                     "A/Japan/8003/2019",
                     "A/South_Korea/9578/2019",
                     "A/Homo_sapien/China/LS323/2019",
                     "A/Homo_sapien/China/LS325/2019",
                     "A/Homo_sapien/China/LS333/2019",
                     "A/India/Pun_1920970/2019",
                     "A/India/Pun_1922253/2019",
                     "A/India/Pun_1922052/2019",
                     "A/South_Korea/8204/2019",
                     "A/South_Korea/8206/2019",
                     "A/South_Korea/8208/2019",
                     "A/South_Korea/8668/2019"
                  ]
               }
            },
            {
               "sequence":"MKTIIALSC",
               "count":2,
               "incidence":1.6129031,
               "motif_short":"Mi",
               "motif_long":"Minor",
               "metadata":{
                  "accession":[
                     "MN169648",
                     "MN873990"
                  ],
                  "country":[
                     "Japan",
                     "Japan"
                  ],
                  "strain":[
                     "A/Japan/9070/2019",
                     "A/Yokosuka/NHRC_OID_FDX70722/2019"
                  ],
                  "date":[
                     "03/12/2019",
                     "04/17/2019"
                  ]
               }
            },
            {
               "sequence":"METISLISM",
               "count":1,
               "incidence":0.80645156,
               "motif_short":"U",
               "motif_long":"Unique",
               "metadata":{
                  "accession":[
                     "MN853423"
                  ],
                  "country":[
                     "China"
                  ],
                  "strain":[
                     "A/Beijing/16/2019"
                  ],
                  "date":[
                     "01/2019"
                  ]
               }
            },
            {
               "sequence":"MKTIIALSH",
               "count":3,
               "incidence":2.4193547,
               "motif_short":"Mi",
               "motif_long":"Minor",
               "metadata":{
                  "country":[
                     "South_Korea",
                     "South_Korea",
                     "South_Korea"
                  ],
                  "date":[
                     "04/05/2019",
                     "04/10/2019",
                     "04/11/2019"
                  ],
                  "strain":[
                     "A/South_Korea/9579/2019",
                     "A/South_Korea/9645/2019",
                     "A/South_Korea/9646/2019"
                  ],
                  "accession":[
                     "MN074938",
                     "MN078683",
                     "MN078691"
                  ]
               }
            }
         ]
      }
   ]
}

Command-Line Arguments

Argument Type Required Default Example Description
-h N/A False N/A dima-cli -h Prints a summary of all available command-line arguments.
-v N/A False N/A dima-cli -v Prints the version of dima-cli that is currently installed.
-n String False Unknown Protein dima-cli -n "Coronavirus Surface Protein" -i sequences.afa The name of the protein that will appear on the results.
-i String True N/A dima-cli -i sequences.afa The path to the FASTA Multiple Sequence Alignment file.
-o String False STDOUT (Prints the results) dima-cli -i sequences.afa -o results,json The location where the results shall be saved.
-l Integer False 9 dima-cli -i sequences.afa -l 12 The length of the kmers generated.
-f String False N/A dima-cli -i sequences.afa -f "accession|strain|country" The format of the FASTA header. Labels where each variant of a kmer position originated from.
-s Integer False 30 dima-cli -i sequences.afa -l 12 -s 40 The minimum required support for each kmer position.

Module Parameters

Parameter Type Required Default Description
sequences String True N/A The path to a FASTA Multiple Sequence Alignment file (MSA), or a string containing FASTA MSA.
sequences_source String True N/A The source of the sequences (ie: "file" or "string")
kmer_length Integer False 9 The length of the kmers generated.
json Boolean False False Whether the result is a JSON string, or a Python object.
header_format String False N/A The format of the FASTA header. Labels where each variant of a kmer position originated from.
support_threshold Integer False 30 The minimum required support for each kmer position.
protein_name String False Unknown Protein The name of the protein that will appear on the results.
json_save_path String False STDOUT (prints to console) The location where the results shall be saved (only required when python json = True).

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for ShanW from gravatar.com ShanW

Unverified details

These details have not been verified by PyPI
Project links
Meta

Release history Release notifications | RSS feed

5.0.9

5.0.6

5.0.0

4.1.3

4.1.1

4.1.0

4.0.0

3.2.2

3.2.1

3.2.0

3.0.0

3.0.0_beta.1 pre-release

2.1.3

2.1.3_beta.19 pre-release

2.1.3_beta.18 pre-release

2.1.3_beta.16 pre-release

2.1.3_beta.15 pre-release

2.1.3_beta pre-release

2.1.0

2.0.5

2.0.4

2.0.3

2.0.2

2.0.1

This version

2.0.0

2.0.0_alpha.25 pre-release

2.0.0_alpha.24 pre-release

2.0.0_alpha.23 pre-release

2.0.0_alpha.22 pre-release

2.0.0_alpha.21 pre-release

2.0.0_alpha.20 pre-release

2.0.0_alpha.19 pre-release

2.0.0_alpha.18 pre-release

2.0.0_alpha.17 pre-release

2.0.0_alpha.16 pre-release

2.0.0_alpha.15 pre-release

2.0.0_alpha.14 pre-release

2.0.0_alpha.13 pre-release

2.0.0_alpha.12 pre-release

2.0.0_alpha.11 pre-release

2.0.0_alpha.10 pre-release

2.0.0_alpha.9 pre-release

2.0.0_alpha.8 pre-release

2.0.0_alpha.7 pre-release

2.0.0_alpha.6 pre-release

2.0.0_alpha.5 pre-release

2.0.0_alpha.4 pre-release

2.0.0_alpha.3 pre-release

2.0.0_alpha.2 pre-release

2.0.0_alpha.1 pre-release

1.0.0

Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

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

dima_cli-2.0.0-cp38-none-win_amd64.whl (275.3 kB view details)

Uploaded CPython 3.8Windows x86-64

dima_cli-2.0.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl (336.2 kB view details)

Uploaded CPython 3.8manylinux: glibc 2.5+ x86-64

dima_cli-2.0.0-cp38-cp38-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl (589.4 kB view details)

Uploaded CPython 3.8macOS 10.9+ universal2 (ARM64, x86-64)macOS 10.9+ x86-64macOS 11.0+ ARM64

dima_cli-2.0.0-cp37-none-win_amd64.whl (275.4 kB view details)

Uploaded CPython 3.7Windows x86-64

dima_cli-2.0.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl (336.4 kB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.5+ x86-64

dima_cli-2.0.0-cp37-cp37m-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl (589.4 kB view details)

Uploaded CPython 3.7mmacOS 10.9+ universal2 (ARM64, x86-64)macOS 10.9+ x86-64macOS 11.0+ ARM64

dima_cli-2.0.0-cp36-none-win_amd64.whl (275.2 kB view details)

Uploaded CPython 3.6Windows x86-64

dima_cli-2.0.0-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.whl (335.9 kB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.5+ x86-64

dima_cli-2.0.0-cp36-cp36m-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl (589.4 kB view details)

Uploaded CPython 3.6mmacOS 10.9+ universal2 (ARM64, x86-64)macOS 10.9+ x86-64macOS 11.0+ ARM64

File details

Details for the file dima_cli-2.0.0-cp38-none-win_amd64.whl.

File metadata

  • Download URL: dima_cli-2.0.0-cp38-none-win_amd64.whl
  • Upload date:
  • Size: 275.3 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: maturin/0.11.3

File hashes

Hashes for dima_cli-2.0.0-cp38-none-win_amd64.whl
Algorithm Hash digest
SHA256 3d27f49cbe5a44e924b368e2f68c4dfe50cd1e54dfb20fd569b70765495434ee
MD5 565f2bcc6477d9ad68dcb494e67a2628
BLAKE2b-256 d3a28be6518c69a9713f7ea01890b1a15bb56881b41b3332fa113ffdda71c712

See more details on using hashes here.

File details

Details for the file dima_cli-2.0.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for dima_cli-2.0.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 0a78b3981b58cf89f14fa80e909accb75d520e853b0e42b6fca5b0c1f9c95eb7
MD5 ffb649e6b41bd1a6e14dd28780a0ff28
BLAKE2b-256 09ec4dca044e6ab1152da34879cf5404b763660cea2e869b85a1694cc975bf7a

See more details on using hashes here.

File details

Details for the file dima_cli-2.0.0-cp38-cp38-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for dima_cli-2.0.0-cp38-cp38-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 83fc2fead843d1c7b8801db5378e1ed5b660c72b676bc0a456e12fc123e2e0b0
MD5 438a783624cfcc4d77db6fa9c247555f
BLAKE2b-256 a8957c8db7cfe26f2bb26691bef1cf0bf7be41d0ecc0045339f7076266b91e02

See more details on using hashes here.

File details

Details for the file dima_cli-2.0.0-cp37-none-win_amd64.whl.

File metadata

  • Download URL: dima_cli-2.0.0-cp37-none-win_amd64.whl
  • Upload date:
  • Size: 275.4 kB
  • Tags: CPython 3.7, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: maturin/0.11.3

File hashes

Hashes for dima_cli-2.0.0-cp37-none-win_amd64.whl
Algorithm Hash digest
SHA256 b43e121c55d295115c739a01f1ca005ddcf8312cbd8c9e7a0287fa283179790a
MD5 b454ad168ddce9ecd8a8fb9824d5cd02
BLAKE2b-256 35cb701d4bf3c028512a02f8c1d738c74e8b09699ba366174bd88771fb6b8664

See more details on using hashes here.

File details

Details for the file dima_cli-2.0.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for dima_cli-2.0.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 542e9970046957dbc76d4dd9785f950c8709a3c43e8ddd898b82ab9e18386d72
MD5 d06b3c852ea4bd2cf6340abcf24ea7ce
BLAKE2b-256 4f37ade255c411d0ccc69cead1f4a767e8b73ce084b73e96c57d7f54938271e9

See more details on using hashes here.

File details

Details for the file dima_cli-2.0.0-cp37-cp37m-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for dima_cli-2.0.0-cp37-cp37m-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 dfa6dada8e1e82697aedecf29764ff5652e71c296cd3295bfa5fe19d39b90dce
MD5 727c4a58a94518b9017962e3ef3d6727
BLAKE2b-256 7c94c592a11315053a9ec3043e5143c54324919fe9f801281e7d23c5a809d23c

See more details on using hashes here.

File details

Details for the file dima_cli-2.0.0-cp36-none-win_amd64.whl.

File metadata

  • Download URL: dima_cli-2.0.0-cp36-none-win_amd64.whl
  • Upload date:
  • Size: 275.2 kB
  • Tags: CPython 3.6, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: maturin/0.11.3

File hashes

Hashes for dima_cli-2.0.0-cp36-none-win_amd64.whl
Algorithm Hash digest
SHA256 ffb3c60d972119698a4bba6824c6accc4d9d4e8ba0eb508c84ce768ddc56716e
MD5 24dccf60c1530d6e1fc08f48932970df
BLAKE2b-256 3e0e9d3fd619ef673c3c84bae2c88f74e7e8b148ffd9e59c91de6969942e5cf2

See more details on using hashes here.

File details

Details for the file dima_cli-2.0.0-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for dima_cli-2.0.0-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 8d8c35aa165572a28564ce7cb7f03cf671addd1d624ac747b10b2123de6b8b22
MD5 201eb8b86df0bd16f7af24d313fb2d32
BLAKE2b-256 0c58d28bb6fe75b00d599e44d2fedc14da674142681a23a3ff0541d9d312b400

See more details on using hashes here.

File details

Details for the file dima_cli-2.0.0-cp36-cp36m-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for dima_cli-2.0.0-cp36-cp36m-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 b1c8383cc179b763765da4d2bbae6918d344e1edf54370f65e6700290463fc5b
MD5 5dddd19142fb8d4cf6f100bafe3648e3
BLAKE2b-256 bfd2b60cb181ca23bf18e6fc7508a6d84d03844c8a749ded1a24bc5d00b47bdd

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