PyPI 官网下载 | readpaf-0.0.5.tar.gz

readpaf ======= [](https://github.com/alexomics/read-paf/actions/workflows/main.yml) [](https://pypi.org/p/readpaf) readpaf is a fast parser for [minimap2](https://github.com/lh3/minimap2) PAF (**P**airwise m**A**pping **F**ormat) files. It is pure python with no dependencies (unless you want a DataFrame). Installation === ```bash pip install readpaf ``` <details> <summary>Other install methods</summary> ### Install with pandas: This is only needed if you want to manipulate the PAF file as a `pandas.DataFrame` ```bash pip install readpaf[pandas] ``` ### Direct download: using cURL ```bash curl -O https://raw.githubusercontent.com/alexomics/read-paf/main/readpaf.py ``` or wget ```bash wget https://raw.githubusercontent.com/alexomics/read-paf/main/readpaf.py ``` </details> Usage === readpaf only has one user function, `parse_paf` that accepts of file-like object; this is any object in python that has a file-oriented API (`sys.stdin`, `stdout` from subprocess, `io.StringIO`, open files from `gzip` or `open`). The following script demonstrates how minimap2 output can be piped into read-paf ```python from readpaf import parse_paf from sys import stdin for record in parse_paf(stdin): print(record.query_name, record.target_name) ``` read-paf can also generate a pandas DataFrame: ```python from readpaf import parse_paf with open("test.paf", "r") as handle: df = parse_paf(handle, dataframe=True) ``` Functions === read-paf has a single user function parse_paf --- ```python parse_paf(file_like=file_handle, fields=list, dataframe=bool) ``` Parameters: - **file_like:** A file like object, such as `sys.stdin`, a file handle from open or io.StringIO objects - **fields:** A list of 13 field names to use for the PAF file, default: ```python "query_name", "query_length", "query_start", "query_end", "strand", "target_name", "target_length", "target_start", "target_end", "residue_matches", "alignment_block_length", "mapping_quality", "tags" ``` These are based on the [PAF specification](https://github.com/lh3/miniasm/blob/master/PAF.md). - **dataframe:** bool, if True, return a pandas.DataFrame with the tags expanded into separate Series If used as an iterator, then each object returned is a named tuple representing a single line in the PAF file. Each named tuple has field names as specified by the `fields` parameter. The SAM-like tags are converted into their correct types and stored in a dictionary. When `print` or `str` are called on `PAF` record (named tuple) a formated PAF string is returned, which is useful for writing records to a file. The `PAF` record also has a method `blast_identity` which calculates the [blast identity](https://lh3.github.io/2018/11/25/on-the-definition-of-sequence-identity) for that record. If used to generate a pandas DataFrame, then each row represents a line in the PAF file and the SAM-like tags are expanded into individual series.