python3脚本中使用的通用命令行工具。孟冠良，见https://github.com/linzhi2013/mglcmdtools。
mglcmdtools的Python项目详细描述
mglcmdtools
1简介
mglcmdtools是python3脚本中使用的一组常用的cmd工具。孟冠良，见https://github.com/linzhi2013/mglcmdtools。
2安装
pip install mglcmdtools
3用法
from mglcmdtools import rm_and_mkdir, runcmd, longStrings_not_match_shortStrings, read_fastaLike, read_fastaLike2, csv2dict, csv2tupe, split_fasta_to_equal_size
rm_and_mkdir('Newdirectory')
rm_and_mkdir('Newdirectory', force=True)
cmd = 'ls -lhtr /'
runcmd(cmd)
runcmd(cmd, verbose=True)
Long_strings = ['AABB', 'CCDD', 'EEFF']
Short_strings = ['AA', 'EE']
longStrings_not_match_shortStrings(Long_strings, Short_strings)
# ['CCDD']
seq.fa文件包含以下内容：
>scaffold512 Locus_1222_0 8.3 LINEAR length=1717 score=20.785
COX2 2 649 45 643 + 4
COX3 897 1691 18 784 + 4
>C7676 18.0 length=1633 score=19.113
DNA afd
COX1 34 1580 12 1530 - 4
>C7536 14.0 length=1185 score=13.529
CYTB 178 1185 25 1008 + 4
>scaffold619 Locus_1559_0 5.0 LINEAR length=803 score=3.515
ND4 27 764 515 1185 + 2
>scaffold367 Locus_808_0 4.6 LINEAR length=652 score=2.296
ATP6 1 306 324 620 - 4
AAA adfjkaj
然后阅读每条记录：
for rec in read_fastaLike('seq.fa'):
print('seqid line:', rec[0])
print('sequence line 1:', rec[1])
函数csv2dict(file=None, header=None, nrows=None, index_col=0, rm_self=True, **kwargs)：
targeted file: a csv file containing a matrix.
by default, assuming the csv file does not have header row, and the first column (index 0) is the row names.
you must specify how many rows to be read.
1. read data from a csv file into a pandas Dataframe;
2. change the up triangular and low triangular to dictionary 'triu_dict' and 'tril_dict', respectively.
Parameter:
rm_self: remove the pair of self-to-self, default True.
Return:
(triu_dict, tril_dict)
功能csv2tupe(file=None, header=None, nrows=None, index_col=0, rm_self=True, **kwargs)：
targeted file: a csv file containing a matrix.
by default, assuming the csv file does not have header row, and the first column (index 0) is the row names.
you must specify how many rows to be read.
1. read data from a csv file into a pandas Dataframe;
2. change the up triangular and low triangular to LIST of tupes 'triu' and 'tril', respectively.
Parameter:
rm_self: remove the pair of self-to-self, default True.
Return:
(triu, tril)
函数split_fasta_to_equal_size(fastafile=None, tot_file_num=10, outdir='./')：
Split a fasta file to `tot_file_num` subfiles, and all subfiles have
appropximately equal size.
Return:
A list of the subfiles' abspath
函数extend_ambiguous_dna(seq=None, get_a_random_seq=False, get_first_seq=False)：
return a `map` iterator of all possible sequences given an ambiguous
DNA input.
if `get_a_random_seq=True`, return a randomly chosen sequence. Beware, if the seq is too long, and there are too many ambiguous sites,this can take
a lot of memory. It is at your own risk to use `get_a_random_seq=True`. I
would suggest you use `get_first_seq=True` instead.
if `get_first_seq=True`, return only the first sequence of the `map`
iterator. the result should always be the same for one input DNA.
if `get_a_random_seq=True` and `get_first_seq=True` at the same time,
only `get_first_seq=True` will work.
cannot deal with 'U' in RNA sequences.
the lower case or upper case of each base will be the same with input DNA.
modified from:
https://stackoverflow.com/questions/27551921/how-to-extend-ambiguous-dna-sequence
函数extend_ambiguous_dna_randomly(seq=None)：
return one sequence by randomly extending the input ambiguous DNA.
the lower case or upper case of each base will be the same with input DNA.
cannot deal with 'U' in RNA sequences.
4作者
孟冠良
5条引文
目前我没有计划发布mglcmdtools。
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