_id
stringlengths 2
7
| title
stringlengths 1
88
| partition
stringclasses 3
values | text
stringlengths 75
19.8k
| language
stringclasses 1
value | meta_information
dict |
|---|---|---|---|---|---|
q13500
|
NGSTk.merge_or_link
|
train
|
def merge_or_link(self, input_args, raw_folder, local_base="sample"):
"""
This function standardizes various input possibilities by converting
either .bam, .fastq, or .fastq.gz files into a local file; merging those
if multiple files given.
:param list input_args: This is a list of arguments, each one is a
class of inputs (which can in turn be a string or a list).
Typically, input_args is a list with 2 elements: first a list of
read1 files; second an (optional!) list of read2 files.
:param str raw_folder: Name/path of folder for the merge/link.
:param str local_base: Usually the sample name. This (plus file
extension) will be the name of the local file linked (or merged)
by this function.
"""
self.make_sure_path_exists(raw_folder)
if not isinstance(input_args, list):
raise Exception("Input must be a list")
if any(isinstance(i, list) for i in input_args):
# We have a list of lists. Process each individually.
local_input_files = list()
n_input_files = len(filter(bool, input_args))
print("Number of input file sets:\t\t" + str(n_input_files))
for input_i, input_arg in enumerate(input_args):
# Count how many non-null items there are in the list;
# we only append _R1 (etc.) if there are multiple input files.
if n_input_files > 1:
local_base_extended = local_base + "_R" + str(input_i + 1)
else:
local_base_extended = local_base
if input_arg:
out = self.merge_or_link(
input_arg, raw_folder, local_base_extended)
print("Local input file: '{}'".format(out))
# Make sure file exists:
if not os.path.isfile(out):
print("Not a file: '{}'".format(out))
local_input_files.append(out)
return local_input_files
else:
# We have a list of individual arguments. Merge them.
if len(input_args) == 1:
# Only one argument in this list. A single input file; we just link
# it, regardless of file type:
# Pull the value out of the list
input_arg = input_args[0]
input_ext = self.get_input_ext(input_arg)
# Convert to absolute path
if not os.path.isabs(input_arg):
input_arg = os.path.abspath(input_arg)
# Link it to into the raw folder
local_input_abs = os.path.join(raw_folder, local_base + input_ext)
self.pm.run(
"ln -sf " + input_arg + " " + local_input_abs,
target=local_input_abs,
shell=True)
# return the local (linked) filename absolute path
return local_input_abs
else:
# Otherwise, there are multiple inputs.
# If more than 1 input file is given, then these are to be merged
# if they are in bam format.
if all([self.get_input_ext(x) == ".bam" for x in input_args]):
sample_merged = local_base + ".merged.bam"
output_merge = os.path.join(raw_folder, sample_merged)
cmd = self.merge_bams(input_args, output_merge)
self.pm.run(cmd, output_merge)
cmd2 = self.validate_bam(output_merge)
self.pm.run(cmd, output_merge, nofail=True)
return output_merge
# if multiple fastq
if all([self.get_input_ext(x) == ".fastq.gz" for x in input_args]):
sample_merged_gz = local_base + ".merged.fastq.gz"
output_merge_gz = os.path.join(raw_folder, sample_merged_gz)
#cmd1 = self.ziptool + "-d -c " + " ".join(input_args) + " > " + output_merge
#cmd2 = self.ziptool + " " + output_merge
#self.pm.run([cmd1, cmd2], output_merge_gz)
# you can save yourself the decompression/recompression:
cmd = "cat " + " ".join(input_args) + " > " + output_merge_gz
self.pm.run(cmd, output_merge_gz)
return output_merge_gz
if all([self.get_input_ext(x) == ".fastq" for x in input_args]):
sample_merged = local_base + ".merged.fastq"
output_merge = os.path.join(raw_folder, sample_merged)
cmd = "cat " + " ".join(input_args) + " > " + output_merge
self.pm.run(cmd, output_merge)
return output_merge
# At this point, we don't recognize the input file types or they
# do not match.
raise NotImplementedError(
"Input files must be of the same type, and can only "
"merge bam or fastq.")
|
python
|
{
"resource": ""
}
|
q13501
|
NGSTk.input_to_fastq
|
train
|
def input_to_fastq(
self, input_file, sample_name,
paired_end, fastq_folder, output_file=None, multiclass=False):
"""
Builds a command to convert input file to fastq, for various inputs.
Takes either .bam, .fastq.gz, or .fastq input and returns
commands that will create the .fastq file, regardless of input type.
This is useful to made your pipeline easily accept any of these input
types seamlessly, standardizing you to the fastq which is still the
most common format for adapter trimmers, etc.
It will place the output fastq file in given `fastq_folder`.
:param str input_file: filename of input you want to convert to fastq
:return str: A command (to be run with PipelineManager) that will ensure
your fastq file exists.
"""
fastq_prefix = os.path.join(fastq_folder, sample_name)
self.make_sure_path_exists(fastq_folder)
# this expects a list; if it gets a string, convert it to a list.
if type(input_file) != list:
input_file = [input_file]
if len(input_file) > 1:
cmd = []
output_file = []
for in_i, in_arg in enumerate(input_file):
output = fastq_prefix + "_R" + str(in_i + 1) + ".fastq"
result_cmd, uf, result_file = \
self.input_to_fastq(in_arg, sample_name, paired_end,
fastq_folder, output, multiclass=True)
cmd.append(result_cmd)
output_file.append(result_file)
else:
# There was only 1 input class.
# Convert back into a string
input_file = input_file[0]
if not output_file:
output_file = fastq_prefix + "_R1.fastq"
input_ext = self.get_input_ext(input_file)
if input_ext == ".bam":
print("Found .bam file")
#cmd = self.bam_to_fastq(input_file, fastq_prefix, paired_end)
cmd, fq1, fq2 = self.bam_to_fastq_awk(input_file, fastq_prefix, paired_end)
# pm.run(cmd, output_file, follow=check_fastq)
elif input_ext == ".fastq.gz":
print("Found .fastq.gz file")
if paired_end and not multiclass:
# For paired-end reads in one fastq file, we must split the file into 2.
script_path = os.path.join(
self.tools.scripts_dir, "fastq_split.py")
cmd = self.tools.python + " -u " + script_path
cmd += " -i " + input_file
cmd += " -o " + fastq_prefix
# Must also return the set of output files
output_file = [fastq_prefix + "_R1.fastq", fastq_prefix + "_R2.fastq"]
else:
# For single-end reads, we just unzip the fastq.gz file.
# or, paired-end reads that were already split.
cmd = self.ziptool + " -d -c " + input_file + " > " + output_file
# a non-shell version
# cmd1 = "gunzip --force " + input_file
# cmd2 = "mv " + os.path.splitext(input_file)[0] + " " + output_file
# cmd = [cmd1, cmd2]
elif input_ext == ".fastq":
cmd = "ln -sf " + input_file + " " + output_file
print("Found .fastq file; no conversion necessary")
return [cmd, fastq_prefix, output_file]
|
python
|
{
"resource": ""
}
|
q13502
|
NGSTk.check_fastq
|
train
|
def check_fastq(self, input_files, output_files, paired_end):
"""
Returns a follow sanity-check function to be run after a fastq conversion.
Run following a command that will produce the fastq files.
This function will make sure any input files have the same number of reads as the
output files.
"""
# Define a temporary function which we will return, to be called by the
# pipeline.
# Must define default parameters here based on the parameters passed in. This locks
# these values in place, so that the variables will be defined when this function
# is called without parameters as a follow function by pm.run.
# This is AFTER merge, so if there are multiple files it means the
# files were split into read1/read2; therefore I must divide by number
# of files for final reads.
def temp_func(input_files=input_files, output_files=output_files,
paired_end=paired_end):
if type(input_files) != list:
input_files = [input_files]
if type(output_files) != list:
output_files = [output_files]
print(input_files)
print(output_files)
n_input_files = len(filter(bool, input_files))
total_reads = sum([int(self.count_reads(input_file, paired_end))
for input_file in input_files])
raw_reads = total_reads / n_input_files
self.pm.report_result("Raw_reads", str(raw_reads))
total_fastq_reads = sum(
[int(self.count_reads(output_file, paired_end))
for output_file in output_files])
fastq_reads = total_fastq_reads / n_input_files
self.pm.report_result("Fastq_reads", fastq_reads)
input_ext = self.get_input_ext(input_files[0])
# We can only assess pass filter reads in bam files with flags.
if input_ext == ".bam":
num_failed_filter = sum(
[int(self.count_fail_reads(f, paired_end))
for f in input_files])
pf_reads = int(raw_reads) - num_failed_filter
self.pm.report_result("PF_reads", str(pf_reads))
if fastq_reads != int(raw_reads):
raise Exception("Fastq conversion error? Number of reads "
"doesn't match unaligned bam")
return fastq_reads
return temp_func
|
python
|
{
"resource": ""
}
|
q13503
|
NGSTk.check_trim
|
train
|
def check_trim(self, trimmed_fastq, paired_end, trimmed_fastq_R2=None, fastqc_folder=None):
"""
Build function to evaluate read trimming, and optionally run fastqc.
This is useful to construct an argument for the 'follow' parameter of
a PipelineManager's 'run' method.
:param str trimmed_fastq: Path to trimmed reads file.
:param bool paired_end: Whether the processing is being done with
paired-end sequencing data.
:param str trimmed_fastq_R2: Path to read 2 file for the paired-end case.
:param str fastqc_folder: Path to folder within which to place fastqc
output files; if unspecified, fastqc will not be run.
:return callable: Function to evaluate read trimming and possibly run
fastqc.
"""
def temp_func():
print("Evaluating read trimming")
if paired_end and not trimmed_fastq_R2:
print("WARNING: specified paired-end but no R2 file")
n_trim = float(self.count_reads(trimmed_fastq, paired_end))
self.pm.report_result("Trimmed_reads", int(n_trim))
try:
rr = float(self.pm.get_stat("Raw_reads"))
except:
print("Can't calculate trim loss rate without raw read result.")
else:
self.pm.report_result(
"Trim_loss_rate", round((rr - n_trim) * 100 / rr, 2))
# Also run a fastqc (if installed/requested)
if fastqc_folder:
if fastqc_folder and os.path.isabs(fastqc_folder):
self.make_sure_path_exists(fastqc_folder)
cmd = self.fastqc(trimmed_fastq, fastqc_folder)
self.pm.run(cmd, lock_name="trimmed_fastqc", nofail=True)
fname, ext = os.path.splitext(os.path.basename(trimmed_fastq))
fastqc_html = os.path.join(fastqc_folder, fname + "_fastqc.html")
self.pm.report_object("FastQC report r1", fastqc_html)
if paired_end and trimmed_fastq_R2:
cmd = self.fastqc(trimmed_fastq_R2, fastqc_folder)
self.pm.run(cmd, lock_name="trimmed_fastqc_R2", nofail=True)
fname, ext = os.path.splitext(os.path.basename(trimmed_fastq_R2))
fastqc_html = os.path.join(fastqc_folder, fname + "_fastqc.html")
self.pm.report_object("FastQC report r2", fastqc_html)
return temp_func
|
python
|
{
"resource": ""
}
|
q13504
|
NGSTk.validate_bam
|
train
|
def validate_bam(self, input_bam):
"""
Wrapper for Picard's ValidateSamFile.
:param str input_bam: Path to file to validate.
:return str: Command to run for the validation.
"""
cmd = self.tools.java + " -Xmx" + self.pm.javamem
cmd += " -jar " + self.tools.picard + " ValidateSamFile"
cmd += " INPUT=" + input_bam
return cmd
|
python
|
{
"resource": ""
}
|
q13505
|
NGSTk.merge_bams
|
train
|
def merge_bams(self, input_bams, merged_bam, in_sorted="TRUE", tmp_dir=None):
"""
Combine multiple files into one.
The tmp_dir parameter is important because on poorly configured
systems, the default can sometimes fill up.
:param Iterable[str] input_bams: Paths to files to combine
:param str merged_bam: Path to which to write combined result.
:param bool | str in_sorted: Whether the inputs are sorted
:param str tmp_dir: Path to temporary directory.
"""
if not len(input_bams) > 1:
print("No merge required")
return 0
outdir, _ = os.path.split(merged_bam)
if outdir and not os.path.exists(outdir):
print("Creating path to merge file's folder: '{}'".format(outdir))
os.makedirs(outdir)
# Handle more intuitive boolean argument.
if in_sorted in [False, True]:
in_sorted = "TRUE" if in_sorted else "FALSE"
input_string = " INPUT=" + " INPUT=".join(input_bams)
cmd = self.tools.java + " -Xmx" + self.pm.javamem
cmd += " -jar " + self.tools.picard + " MergeSamFiles"
cmd += input_string
cmd += " OUTPUT=" + merged_bam
cmd += " ASSUME_SORTED=" + str(in_sorted)
cmd += " CREATE_INDEX=TRUE"
cmd += " VALIDATION_STRINGENCY=SILENT"
if tmp_dir:
cmd += " TMP_DIR=" + tmp_dir
return cmd
|
python
|
{
"resource": ""
}
|
q13506
|
NGSTk.count_lines
|
train
|
def count_lines(self, file_name):
"""
Uses the command-line utility wc to count the number of lines in a file. For MacOS, must strip leading whitespace from wc.
:param str file_name: name of file whose lines are to be counted
"""
x = subprocess.check_output("wc -l " + file_name + " | sed -E 's/^[[:space:]]+//' | cut -f1 -d' '", shell=True)
return x.strip()
|
python
|
{
"resource": ""
}
|
q13507
|
NGSTk.get_chrs_from_bam
|
train
|
def get_chrs_from_bam(self, file_name):
"""
Uses samtools to grab the chromosomes from the header that are contained
in this bam file.
"""
x = subprocess.check_output(self.tools.samtools + " view -H " + file_name + " | grep '^@SQ' | cut -f2| sed s'/SN://'", shell=True)
# Chromosomes will be separated by newlines; split into list to return
return x.split()
|
python
|
{
"resource": ""
}
|
q13508
|
NGSTk.count_unique_mapped_reads
|
train
|
def count_unique_mapped_reads(self, file_name, paired_end):
"""
For a bam or sam file with paired or or single-end reads, returns the
number of mapped reads, counting each read only once, even if it appears
mapped at multiple locations.
:param str file_name: name of reads file
:param bool paired_end: True/False paired end data
:return int: Number of uniquely mapped reads.
"""
_, ext = os.path.splitext(file_name)
ext = ext.lower()
if ext == ".sam":
param = "-S -F4"
elif ext == "bam":
param = "-F4"
else:
raise ValueError("Not a SAM or BAM: '{}'".format(file_name))
if paired_end:
r1 = self.samtools_view(file_name, param=param + " -f64", postpend=" | cut -f1 | sort -k1,1 -u | wc -l | sed -E 's/^[[:space:]]+//'")
r2 = self.samtools_view(file_name, param=param + " -f128", postpend=" | cut -f1 | sort -k1,1 -u | wc -l | sed -E 's/^[[:space:]]+//'")
else:
r1 = self.samtools_view(file_name, param=param + "", postpend=" | cut -f1 | sort -k1,1 -u | wc -l | sed -E 's/^[[:space:]]+//'")
r2 = 0
return int(r1) + int(r2)
|
python
|
{
"resource": ""
}
|
q13509
|
NGSTk.count_flag_reads
|
train
|
def count_flag_reads(self, file_name, flag, paired_end):
"""
Counts the number of reads with the specified flag.
:param str file_name: name of reads file
:param str flag: sam flag value to be read
:param bool paired_end: This parameter is ignored; samtools automatically correctly responds depending
on the data in the bamfile. We leave the option here just for consistency, since all the other
counting functions require the parameter. This makes it easier to swap counting functions during
pipeline development.
"""
param = " -c -f" + str(flag)
if file_name.endswith("sam"):
param += " -S"
return self.samtools_view(file_name, param=param)
|
python
|
{
"resource": ""
}
|
q13510
|
NGSTk.count_uniquelymapping_reads
|
train
|
def count_uniquelymapping_reads(self, file_name, paired_end):
"""
Counts the number of reads that mapped to a unique position.
:param str file_name: name of reads file
:param bool paired_end: This parameter is ignored.
"""
param = " -c -F256"
if file_name.endswith("sam"):
param += " -S"
return self.samtools_view(file_name, param=param)
|
python
|
{
"resource": ""
}
|
q13511
|
NGSTk.samtools_view
|
train
|
def samtools_view(self, file_name, param, postpend=""):
"""
Run samtools view, with flexible parameters and post-processing.
This is used internally to implement the various count_reads functions.
:param str file_name: file_name
:param str param: String of parameters to pass to samtools view
:param str postpend: String to append to the samtools command;
useful to add cut, sort, wc operations to the samtools view output.
"""
cmd = "{} view {} {} {}".format(
self.tools.samtools, param, file_name, postpend)
return subprocess.check_output(cmd, shell=True)
|
python
|
{
"resource": ""
}
|
q13512
|
NGSTk.count_reads
|
train
|
def count_reads(self, file_name, paired_end):
"""
Count reads in a file.
Paired-end reads count as 2 in this function.
For paired-end reads, this function assumes that the reads are split
into 2 files, so it divides line count by 2 instead of 4.
This will thus give an incorrect result if your paired-end fastq files
are in only a single file (you must divide by 2 again).
:param str file_name: Name/path of file whose reads are to be counted.
:param bool paired_end: Whether the file contains paired-end reads.
"""
_, ext = os.path.splitext(file_name)
if not (is_sam_or_bam(file_name) or is_fastq(file_name)):
# TODO: make this an exception and force caller to handle that
# rather than relying on knowledge of possibility of negative value.
return -1
if is_sam_or_bam(file_name):
param_text = "-c" if ext == ".bam" else "-c -S"
return self.samtools_view(file_name, param=param_text)
else:
num_lines = self.count_lines_zip(file_name) \
if is_gzipped_fastq(file_name) \
else self.count_lines(file_name)
divisor = 2 if paired_end else 4
return int(num_lines) / divisor
|
python
|
{
"resource": ""
}
|
q13513
|
NGSTk.count_concordant
|
train
|
def count_concordant(self, aligned_bam):
"""
Count only reads that "aligned concordantly exactly 1 time."
:param str aligned_bam: File for which to count mapped reads.
"""
cmd = self.tools.samtools + " view " + aligned_bam + " | "
cmd += "grep 'YT:Z:CP'" + " | uniq -u | wc -l | sed -E 's/^[[:space:]]+//'"
return subprocess.check_output(cmd, shell=True)
|
python
|
{
"resource": ""
}
|
q13514
|
NGSTk.count_mapped_reads
|
train
|
def count_mapped_reads(self, file_name, paired_end):
"""
Mapped_reads are not in fastq format, so this one doesn't need to accommodate fastq,
and therefore, doesn't require a paired-end parameter because it only uses samtools view.
Therefore, it's ok that it has a default parameter, since this is discarded.
:param str file_name: File for which to count mapped reads.
:param bool paired_end: This parameter is ignored; samtools automatically correctly responds depending
on the data in the bamfile. We leave the option here just for consistency, since all the other
counting functions require the parameter. This makes it easier to swap counting functions during
pipeline development.
:return int: Either return code from samtools view command, or -1 to indicate an error state.
"""
if file_name.endswith("bam"):
return self.samtools_view(file_name, param="-c -F4")
if file_name.endswith("sam"):
return self.samtools_view(file_name, param="-c -F4 -S")
return -1
|
python
|
{
"resource": ""
}
|
q13515
|
NGSTk.sam_conversions
|
train
|
def sam_conversions(self, sam_file, depth=True):
"""
Convert sam files to bam files, then sort and index them for later use.
:param bool depth: also calculate coverage over each position
"""
cmd = self.tools.samtools + " view -bS " + sam_file + " > " + sam_file.replace(".sam", ".bam") + "\n"
cmd += self.tools.samtools + " sort " + sam_file.replace(".sam", ".bam") + " -o " + sam_file.replace(".sam", "_sorted.bam") + "\n"
cmd += self.tools.samtools + " index " + sam_file.replace(".sam", "_sorted.bam") + "\n"
if depth:
cmd += self.tools.samtools + " depth " + sam_file.replace(".sam", "_sorted.bam") + " > " + sam_file.replace(".sam", "_sorted.depth") + "\n"
return cmd
|
python
|
{
"resource": ""
}
|
q13516
|
NGSTk.bam_conversions
|
train
|
def bam_conversions(self, bam_file, depth=True):
"""
Sort and index bam files for later use.
:param bool depth: also calculate coverage over each position
"""
cmd = self.tools.samtools + " view -h " + bam_file + " > " + bam_file.replace(".bam", ".sam") + "\n"
cmd += self.tools.samtools + " sort " + bam_file + " -o " + bam_file.replace(".bam", "_sorted.bam") + "\n"
cmd += self.tools.samtools + " index " + bam_file.replace(".bam", "_sorted.bam") + "\n"
if depth:
cmd += self.tools.samtools + " depth " + bam_file.replace(".bam", "_sorted.bam") + " > " + bam_file.replace(".bam", "_sorted.depth") + "\n"
return cmd
|
python
|
{
"resource": ""
}
|
q13517
|
NGSTk.fastqc
|
train
|
def fastqc(self, file, output_dir):
"""
Create command to run fastqc on a FASTQ file
:param str file: Path to file with sequencing reads
:param str output_dir: Path to folder in which to place output
:return str: Command with which to run fastqc
"""
# You can find the fastqc help with fastqc --help
try:
pm = self.pm
except AttributeError:
# Do nothing, this is just for path construction.
pass
else:
if not os.path.isabs(output_dir) and pm is not None:
output_dir = os.path.join(pm.outfolder, output_dir)
self.make_sure_path_exists(output_dir)
return "{} --noextract --outdir {} {}".\
format(self.tools.fastqc, output_dir, file)
|
python
|
{
"resource": ""
}
|
q13518
|
NGSTk.fastqc_rename
|
train
|
def fastqc_rename(self, input_bam, output_dir, sample_name):
"""
Create pair of commands to run fastqc and organize files.
The first command returned is the one that actually runs fastqc when
it's executed; the second moves the output files to the output
folder for the sample indicated.
:param str input_bam: Path to file for which to run fastqc.
:param str output_dir: Path to folder in which fastqc output will be
written, and within which the sample's output folder lives.
:param str sample_name: Sample name, which determines subfolder within
output_dir for the fastqc files.
:return list[str]: Pair of commands, to run fastqc and then move the files to
their intended destination based on sample name.
"""
cmds = list()
initial = os.path.splitext(os.path.basename(input_bam))[0]
cmd1 = self.fastqc(input_bam, output_dir)
cmds.append(cmd1)
cmd2 = "if [[ ! -s {1}_fastqc.html ]]; then mv {0}_fastqc.html {1}_fastqc.html; mv {0}_fastqc.zip {1}_fastqc.zip; fi".format(
os.path.join(output_dir, initial), os.path.join(output_dir, sample_name))
cmds.append(cmd2)
return cmds
|
python
|
{
"resource": ""
}
|
q13519
|
NGSTk.samtools_index
|
train
|
def samtools_index(self, bam_file):
"""Index a bam file."""
cmd = self.tools.samtools + " index {0}".format(bam_file)
return cmd
|
python
|
{
"resource": ""
}
|
q13520
|
NGSTk.skewer
|
train
|
def skewer(
self, input_fastq1, output_prefix, output_fastq1,
log, cpus, adapters, input_fastq2=None, output_fastq2=None):
"""
Create commands with which to run skewer.
:param str input_fastq1: Path to input (read 1) FASTQ file
:param str output_prefix: Prefix for output FASTQ file names
:param str output_fastq1: Path to (read 1) output FASTQ file
:param str log: Path to file to which to write logging information
:param int | str cpus: Number of processing cores to allow
:param str adapters: Path to file with sequencing adapters
:param str input_fastq2: Path to read 2 input FASTQ file
:param str output_fastq2: Path to read 2 output FASTQ file
:return list[str]: Sequence of commands to run to trim reads with
skewer and rename files as desired.
"""
pe = input_fastq2 is not None
mode = "pe" if pe else "any"
cmds = list()
cmd1 = self.tools.skewer + " --quiet"
cmd1 += " -f sanger"
cmd1 += " -t {0}".format(cpus)
cmd1 += " -m {0}".format(mode)
cmd1 += " -x {0}".format(adapters)
cmd1 += " -o {0}".format(output_prefix)
cmd1 += " {0}".format(input_fastq1)
if input_fastq2 is None:
cmds.append(cmd1)
else:
cmd1 += " {0}".format(input_fastq2)
cmds.append(cmd1)
if input_fastq2 is None:
cmd2 = "mv {0} {1}".format(output_prefix + "-trimmed.fastq", output_fastq1)
cmds.append(cmd2)
else:
cmd2 = "mv {0} {1}".format(output_prefix + "-trimmed-pair1.fastq", output_fastq1)
cmds.append(cmd2)
cmd3 = "mv {0} {1}".format(output_prefix + "-trimmed-pair2.fastq", output_fastq2)
cmds.append(cmd3)
cmd4 = "mv {0} {1}".format(output_prefix + "-trimmed.log", log)
cmds.append(cmd4)
return cmds
|
python
|
{
"resource": ""
}
|
q13521
|
NGSTk.filter_reads
|
train
|
def filter_reads(self, input_bam, output_bam, metrics_file, paired=False, cpus=16, Q=30):
"""
Remove duplicates, filter for >Q, remove multiple mapping reads.
For paired-end reads, keep only proper pairs.
"""
nodups = re.sub("\.bam$", "", output_bam) + ".nodups.nofilter.bam"
cmd1 = self.tools.sambamba + " markdup -t {0} -r --compression-level=0 {1} {2} 2> {3}".format(cpus, input_bam, nodups, metrics_file)
cmd2 = self.tools.sambamba + ' view -t {0} -f bam --valid'.format(cpus)
if paired:
cmd2 += ' -F "not (unmapped or mate_is_unmapped) and proper_pair'
else:
cmd2 += ' -F "not unmapped'
cmd2 += ' and not (secondary_alignment or supplementary) and mapping_quality >= {0}"'.format(Q)
cmd2 += ' {0} |'.format(nodups)
cmd2 += self.tools.sambamba + " sort -t {0} /dev/stdin -o {1}".format(cpus, output_bam)
cmd3 = "if [[ -s {0} ]]; then rm {0}; fi".format(nodups)
cmd4 = "if [[ -s {0} ]]; then rm {0}; fi".format(nodups + ".bai")
return [cmd1, cmd2, cmd3, cmd4]
|
python
|
{
"resource": ""
}
|
q13522
|
NGSTk.run_spp
|
train
|
def run_spp(self, input_bam, output, plot, cpus):
"""
Run the SPP read peak analysis tool.
:param str input_bam: Path to reads file
:param str output: Path to output file
:param str plot: Path to plot file
:param int cpus: Number of processors to use
:return str: Command with which to run SPP
"""
base = "{} {} -rf -savp".format(self.tools.Rscript, self.tools.spp)
cmd = base + " -savp={} -s=0:5:500 -c={} -out={} -p={}".format(
plot, input_bam, output, cpus)
return cmd
|
python
|
{
"resource": ""
}
|
q13523
|
NGSTk.calc_frip
|
train
|
def calc_frip(self, input_bam, input_bed, threads=4):
"""
Calculate fraction of reads in peaks.
A file of with a pool of sequencing reads and a file with peak call
regions define the operation that will be performed. Thread count
for samtools can be specified as well.
:param str input_bam: sequencing reads file
:param str input_bed: file with called peak regions
:param int threads: number of threads samtools may use
:return float: fraction of reads in peaks defined in given peaks file
"""
cmd = self.simple_frip(input_bam, input_bed, threads)
return subprocess.check_output(cmd.split(" "), shell=True)
|
python
|
{
"resource": ""
}
|
q13524
|
NGSTk.macs2_call_peaks
|
train
|
def macs2_call_peaks(
self, treatment_bams, output_dir, sample_name, genome,
control_bams=None, broad=False, paired=False,
pvalue=None, qvalue=None, include_significance=None):
"""
Use MACS2 to call peaks.
:param str | Iterable[str] treatment_bams: Paths to files with data to
regard as treatment.
:param str output_dir: Path to output folder.
:param str sample_name: Name for the sample involved.
:param str genome: Name of the genome assembly to use.
:param str | Iterable[str] control_bams: Paths to files with data to
regard as control
:param bool broad: Whether to do broad peak calling.
:param bool paired: Whether reads are paired-end
:param float | NoneType pvalue: Statistical significance measure to
pass as --pvalue to peak calling with MACS
:param float | NoneType qvalue: Statistical significance measure to
pass as --qvalue to peak calling with MACS
:param bool | NoneType include_significance: Whether to pass a
statistical significance argument to peak calling with MACS; if
omitted, this will be True if the peak calling is broad or if
either p-value or q-value is specified; default significance
specification is a p-value of 0.001 if a significance is to be
specified but no value is provided for p-value or q-value.
:return str: Command to run.
"""
sizes = {"hg38": 2.7e9, "hg19": 2.7e9, "mm10": 1.87e9, "dr7": 1.412e9, "mm9": 1.87e9}
# Whether to specify to MACS2 a value for statistical significance
# can be either directly indicated, but if not, it's determined by
# whether the mark is associated with broad peaks. By default, we
# specify a significance value to MACS2 for a mark associated with a
# broad peak.
if include_significance is None:
include_significance = broad
cmd = self.tools.macs2 + " callpeak -t {0}".format(treatment_bams if type(treatment_bams) is str else " ".join(treatment_bams))
if control_bams is not None:
cmd += " -c {0}".format(control_bams if type(control_bams) is str else " ".join(control_bams))
if paired:
cmd += " -f BAMPE "
# Additional settings based on whether the marks is associated with
# broad peaks
if broad:
cmd += " --broad --nomodel --extsize 73"
else:
cmd += " --fix-bimodal --extsize 180 --bw 200"
if include_significance:
# Allow significance specification via either p- or q-value,
# giving preference to q-value if both are provided but falling
# back on a default p-value if neither is provided but inclusion
# of statistical significance measure is desired.
if qvalue is not None:
cmd += " --qvalue {}".format(qvalue)
else:
cmd += " --pvalue {}".format(pvalue or 0.00001)
cmd += " -g {0} -n {1} --outdir {2}".format(sizes[genome], sample_name, output_dir)
return cmd
|
python
|
{
"resource": ""
}
|
q13525
|
NGSTk.spp_call_peaks
|
train
|
def spp_call_peaks(
self, treatment_bam, control_bam, treatment_name, control_name,
output_dir, broad, cpus, qvalue=None):
"""
Build command for R script to call peaks with SPP.
:param str treatment_bam: Path to file with data for treatment sample.
:param str control_bam: Path to file with data for control sample.
:param str treatment_name: Name for the treatment sample.
:param str control_name: Name for the control sample.
:param str output_dir: Path to folder for output.
:param str | bool broad: Whether to specify broad peak calling mode.
:param int cpus: Number of cores the script may use.
:param float qvalue: FDR, as decimal value
:return str: Command to run.
"""
broad = "TRUE" if broad else "FALSE"
cmd = self.tools.Rscript + " `which spp_peak_calling.R` {0} {1} {2} {3} {4} {5} {6}".format(
treatment_bam, control_bam, treatment_name, control_name, broad, cpus, output_dir
)
if qvalue is not None:
cmd += " {}".format(qvalue)
return cmd
|
python
|
{
"resource": ""
}
|
q13526
|
NGSTk.parse_duplicate_stats
|
train
|
def parse_duplicate_stats(self, stats_file):
"""
Parses sambamba markdup output, returns series with values.
:param str stats_file: sambamba output file with duplicate statistics.
"""
import pandas as pd
series = pd.Series()
try:
with open(stats_file) as handle:
content = handle.readlines() # list of strings per line
except:
return series
try:
line = [i for i in range(len(content)) if "single ends (among them " in content[i]][0]
series["single-ends"] = re.sub("\D", "", re.sub("\(.*", "", content[line]))
line = [i for i in range(len(content)) if " end pairs... done in " in content[i]][0]
series["paired-ends"] = re.sub("\D", "", re.sub("\.\.\..*", "", content[line]))
line = [i for i in range(len(content)) if " duplicates, sorting the list... done in " in content[i]][0]
series["duplicates"] = re.sub("\D", "", re.sub("\.\.\..*", "", content[line]))
except IndexError:
pass
return series
|
python
|
{
"resource": ""
}
|
q13527
|
NGSTk.get_peak_number
|
train
|
def get_peak_number(self, sample):
"""
Counts number of peaks from a sample's peak file.
:param pipelines.Sample sample: Sample object with "peaks" attribute.
"""
proc = subprocess.Popen(["wc", "-l", sample.peaks], stdout=subprocess.PIPE)
out, err = proc.communicate()
sample["peakNumber"] = re.sub("\D.*", "", out)
return sample
|
python
|
{
"resource": ""
}
|
q13528
|
NGSTk.get_frip
|
train
|
def get_frip(self, sample):
"""
Calculates the fraction of reads in peaks for a given sample.
:param pipelines.Sample sample: Sample object with "peaks" attribute.
"""
import pandas as pd
with open(sample.frip, "r") as handle:
content = handle.readlines()
reads_in_peaks = int(re.sub("\D", "", content[0]))
mapped_reads = sample["readCount"] - sample["unaligned"]
return pd.Series(reads_in_peaks / mapped_reads, index="FRiP")
|
python
|
{
"resource": ""
}
|
q13529
|
PipelineManager._set_status_flag
|
train
|
def _set_status_flag(self, status):
"""
Configure state and files on disk to match current processing status.
:param str status: Name of new status designation for pipeline.
"""
# Remove previous status flag file.
flag_file_path = self._flag_file_path()
try:
os.remove(flag_file_path)
except:
# Print message only if the failure to remove the status flag
# is unexpected; there's no flag for initialization, so we
# can't remove the file.
if self.status != "initializing":
print("Could not remove flag file: '{}'".format(flag_file_path))
pass
# Set new status.
prev_status = self.status
self.status = status
self._create_file(self._flag_file_path())
print("\nChanged status from {} to {}.".format(
prev_status, self.status))
|
python
|
{
"resource": ""
}
|
q13530
|
PipelineManager._flag_file_path
|
train
|
def _flag_file_path(self, status=None):
"""
Create path to flag file based on indicated or current status.
Internal variables used are the pipeline name and the designated
pipeline output folder path.
:param str status: flag file type to create, default to current status
:return str: path to flag file of indicated or current status.
"""
flag_file_name = "{}_{}".format(
self.name, flag_name(status or self.status))
return pipeline_filepath(self, filename=flag_file_name)
|
python
|
{
"resource": ""
}
|
q13531
|
PipelineManager._attend_process
|
train
|
def _attend_process(self, proc, sleeptime):
"""
Waits on a process for a given time to see if it finishes, returns True
if it's still running after the given time or False as soon as it
returns.
:param psutil.Popen proc: Process object opened by psutil.Popen()
:param float sleeptime: Time to wait
:return bool: True if process is still running; otherwise false
"""
# print("attend:{}".format(proc.pid))
try:
proc.wait(timeout=sleeptime)
except psutil.TimeoutExpired:
return True
return False
|
python
|
{
"resource": ""
}
|
q13532
|
PipelineManager._wait_for_process
|
train
|
def _wait_for_process(self, p, shell=False):
"""
Debug function used in unit tests.
:param p: A subprocess.Popen process.
:param bool shell: If command requires should be run in its own shell. Optional. Default: False.
"""
local_maxmem = -1
sleeptime = .5
while p.poll() is None:
if not shell:
local_maxmem = max(local_maxmem, self._memory_usage(p.pid) / 1e6)
# print("int.maxmem (pid:" + str(p.pid) + ") " + str(local_maxmem))
time.sleep(sleeptime)
sleeptime = min(sleeptime + 5, 60)
self.peak_memory = max(self.peak_memory, local_maxmem)
del self.procs[p.pid]
info = "Process " + str(p.pid) + " returned: (" + str(p.returncode) + ")."
if not shell:
info += " Peak memory: (Process: " + str(round(local_maxmem, 3)) + "GB;"
info += " Pipeline: " + str(round(self.peak_memory, 3)) + "GB)\n"
print(info + "\n")
if p.returncode != 0:
raise Exception("Process returned nonzero result.")
return [p.returncode, local_maxmem]
|
python
|
{
"resource": ""
}
|
q13533
|
PipelineManager._wait_for_lock
|
train
|
def _wait_for_lock(self, lock_file):
"""
Just sleep until the lock_file does not exist or a lock_file-related dynamic recovery flag is spotted
:param str lock_file: Lock file to wait upon.
"""
sleeptime = .5
first_message_flag = False
dot_count = 0
recover_file = self._recoverfile_from_lockfile(lock_file)
while os.path.isfile(lock_file):
if first_message_flag is False:
self.timestamp("Waiting for file lock: " + lock_file)
self._set_status_flag(WAIT_FLAG)
first_message_flag = True
else:
sys.stdout.write(".")
dot_count = dot_count + 1
if dot_count % 60 == 0:
print("") # linefeed
# prevents the issue of pypier waiting for the lock file to be gone infinitely
# in case the recovery flag is sticked by other pipeline when it's interrupted
if os.path.isfile(recover_file):
sys.stdout.write(" Dynamic recovery flag found")
break
time.sleep(sleeptime)
sleeptime = min(sleeptime + 2.5, 60)
if first_message_flag:
self.timestamp("File unlocked.")
self._set_status_flag(RUN_FLAG)
|
python
|
{
"resource": ""
}
|
q13534
|
PipelineManager.timestamp
|
train
|
def timestamp(self, message="", checkpoint=None,
finished=False, raise_error=True):
"""
Print message, time, and time elapsed, perhaps creating checkpoint.
This prints your given message, along with the current time, and time
elapsed since the previous timestamp() call. If you specify a
HEADING by beginning the message with "###", it surrounds the message
with newlines for easier readability in the log file. If a checkpoint
is designated, an empty file is created corresponding to the name
given. Depending on how this manager's been configured, the value of
the checkpoint, and whether this timestamp indicates initiation or
completion of a group of pipeline steps, this call may stop the
pipeline's execution.
:param str message: Message to timestamp.
:param str checkpoint: Name of checkpoint; this tends to be something
that reflects the processing logic about to be or having just been
completed. Provision of an argument to this parameter means that
a checkpoint file will be created, facilitating arbitrary starting
and stopping point for the pipeline as desired.
:param bool finished: Whether this call represents the completion of a
conceptual unit of a pipeline's processing
:param raise_error: Whether to raise exception if
checkpoint or current state indicates that a halt should occur.
"""
# Halt if the manager's state has been set such that this call
# should halt the pipeline.
if self.halt_on_next:
self.halt(checkpoint, finished, raise_error=raise_error)
# Determine action to take with respect to halting if needed.
if checkpoint:
if finished:
# Write the file.
self._checkpoint(checkpoint)
self.prev_checkpoint = checkpoint
self.curr_checkpoint = None
else:
self.prev_checkpoint = self.curr_checkpoint
self.curr_checkpoint = checkpoint
self._checkpoint(self.prev_checkpoint)
# Handle the two halting conditions.
if (finished and checkpoint == self.stop_after) or (not finished and checkpoint == self.stop_before):
self.halt(checkpoint, finished, raise_error=raise_error)
# Determine if we've started executing.
elif checkpoint == self.start_point:
self._active = True
# If this is a prospective checkpoint, set the current checkpoint
# accordingly and whether we should halt the pipeline on the
# next timestamp call.
if not finished and checkpoint == self.stop_after:
self.halt_on_next = True
elapsed = self.time_elapsed(self.last_timestamp)
t = time.strftime("%m-%d %H:%M:%S")
if checkpoint is None:
msg = "{m} ({t}) elapsed: {delta_t} _TIME_".\
format(m=message, t=t, delta_t=elapsed)
else:
msg = "{m} ({t}) ({status} {stage}) elapsed: {delta_t} _TIME_".\
format(m=message, t=t,
status="finished" if finished else "starting",
stage=checkpoint, delta_t=elapsed)
if re.match("^###", message):
msg = "\n{}\n".format(msg)
print(msg)
self.last_timestamp = time.time()
|
python
|
{
"resource": ""
}
|
q13535
|
PipelineManager._report_profile
|
train
|
def _report_profile(self, command, lock_name, elapsed_time, memory):
"""
Writes a string to self.pipeline_profile_file.
"""
message_raw = str(command) + "\t " + \
str(lock_name) + "\t" + \
str(datetime.timedelta(seconds = round(elapsed_time, 2))) + "\t " + \
str(memory)
with open(self.pipeline_profile_file, "a") as myfile:
myfile.write(message_raw + "\n")
|
python
|
{
"resource": ""
}
|
q13536
|
PipelineManager.report_object
|
train
|
def report_object(self, key, filename, anchor_text=None, anchor_image=None,
annotation=None):
"""
Writes a string to self.pipeline_objects_file. Used to report figures and others.
:param str key: name (key) of the object
:param str filename: relative path to the file (relative to parent output dir)
:param str anchor_text: text used as the link anchor test or caption to
refer to the object. If not provided, defaults to the key.
:param str anchor_image: a path to an HTML-displayable image thumbnail (so,
.png or .jpg, for example). If a path, the path should be relative
to the parent output dir.
:param str annotation: By default, the figures will be annotated with the
pipeline name, so you can tell which pipeline records which figures.
If you want, you can change this.
"""
# Default annotation is current pipeline name.
annotation = str(annotation or self.name)
# In case the value is passed with trailing whitespace.
filename = str(filename).strip()
if anchor_text:
anchor_text = str(anchor_text).strip()
else:
anchor_text = str(key).strip()
# better to use a relative path in this file
# convert any absolute paths into relative paths
relative_filename = os.path.relpath(filename, self.outfolder) \
if os.path.isabs(filename) else filename
if anchor_image:
relative_anchor_image = os.path.relpath(anchor_image, self.outfolder) \
if os.path.isabs(anchor_image) else anchor_image
else:
relative_anchor_image = "None"
message_raw = "{key}\t{filename}\t{anchor_text}\t{anchor_image}\t{annotation}".format(
key=key, filename=relative_filename, anchor_text=anchor_text,
anchor_image=relative_anchor_image, annotation=annotation)
message_markdown = "> `{key}`\t{filename}\t{anchor_text}\t{anchor_image}\t{annotation}\t_OBJ_".format(
key=key, filename=relative_filename, anchor_text=anchor_text,
anchor_image=relative_anchor_image,annotation=annotation)
print(message_markdown)
self._safe_write_to_file(self.pipeline_objects_file, message_raw)
|
python
|
{
"resource": ""
}
|
q13537
|
PipelineManager._create_file_racefree
|
train
|
def _create_file_racefree(self, file):
"""
Creates a file, but fails if the file already exists.
This function will thus only succeed if this process actually creates
the file; if the file already exists, it will cause an OSError,
solving race conditions.
:param str file: File to create.
"""
write_lock_flags = os.O_CREAT | os.O_EXCL | os.O_WRONLY
os.open(file, write_lock_flags)
|
python
|
{
"resource": ""
}
|
q13538
|
PipelineManager.make_sure_path_exists
|
train
|
def make_sure_path_exists(self, path):
"""
Creates all directories in a path if it does not exist.
:param str path: Path to create.
:raises Exception: if the path creation attempt hits an error with
a code indicating a cause other than pre-existence.
"""
try:
os.makedirs(path)
except OSError as exception:
if exception.errno != errno.EEXIST:
raise
|
python
|
{
"resource": ""
}
|
q13539
|
PipelineManager._refresh_stats
|
train
|
def _refresh_stats(self):
"""
Loads up the stats sheet created for this pipeline run and reads
those stats into memory
"""
# regex identifies all possible stats files.
#regex = self.outfolder + "*_stats.tsv"
#stats_files = glob.glob(regex)
#stats_files.insert(self.pipeline_stats_file) # last one is the current pipeline
#for stats_file in stats_files:
stats_file = self.pipeline_stats_file
if os.path.isfile(self.pipeline_stats_file):
with open(stats_file, 'r') as stat_file:
for line in stat_file:
try:
# Someone may have put something that's not 3 columns in the stats file
# if so, shame on him, but we can just ignore it.
key, value, annotation = line.split('\t')
except ValueError:
print("WARNING: Each row in a stats file is expected to have 3 columns")
if annotation.rstrip() == self.name or annotation.rstrip() == "shared":
self.stats_dict[key] = value.strip()
|
python
|
{
"resource": ""
}
|
q13540
|
PipelineManager._checkpoint
|
train
|
def _checkpoint(self, stage):
"""
Decide whether to stop processing of a pipeline. This is the hook
A pipeline can report various "checkpoints" as sort of status markers
that designate the logical processing phase that's just been completed.
The initiation of a pipeline can preordain one of those as a "stopping
point" that when reached, should stop the pipeline's execution.
:param pypiper.Stage | str stage: Pipeline processing stage/phase just completed.
:return bool: Whether a checkpoint was created (i.e., whether it didn't
already exist)
:raise ValueError: If the stage is specified as an absolute filepath,
and that path indicates a location that's not immediately within
the main output folder, raise a ValueError.
"""
# For null stage, short-circuit and indicate no file write.
# This handles case in which we're timestamping prospectively and
# previously weren't in a stage.
if stage is None:
return False
try:
is_checkpoint = stage.checkpoint
except AttributeError:
# Maybe we have a raw function, not a stage.
if hasattr(stage, "__call__"):
stage = stage.__name__
else:
# Maybe we have a stage name not a Stage.
# In that case, we can proceed as-is, with downstream
# processing handling Stage vs. stage name disambiguation.
# Here, though, warn about inputs that appear filename/path-like.
# We can't rely on raw text being a filepath or filename,
# because that would ruin the ability to pass stage name rather
# than actual stage. We can issue a warning message based on the
# improbability of a stage name containing the '.' that would
# be expected to characterize the extension of a file name/path.
base, ext = os.path.splitext(stage)
if ext and "." not in base:
print("WARNING: '{}' looks like it may be the name or path of "
"a file; for such a checkpoint, use touch_checkpoint.".
format(stage))
else:
if not is_checkpoint:
print("Not a checkpoint: {}".format(stage))
return False
stage = stage.name
print("Checkpointing: '{}'".format(stage))
if os.path.isabs(stage):
check_fpath = stage
else:
check_fpath = checkpoint_filepath(stage, pm=self)
return self._touch_checkpoint(check_fpath)
|
python
|
{
"resource": ""
}
|
q13541
|
PipelineManager._touch_checkpoint
|
train
|
def _touch_checkpoint(self, check_file):
"""
Alternative way for a pipeline to designate a checkpoint.
:param str check_file: Name or path of file to use as checkpoint.
:return bool: Whether a file was written (equivalent to whether the
checkpoint file already existed).
:raise ValueError: Raise a ValueError if the argument provided as the
checkpoint file is an absolute path and that doesn't correspond
to a location within the main output folder.
"""
if os.path.isabs(check_file):
folder, _ = os.path.split(check_file)
# For raw string comparison, ensure that each path
# bears the final path separator.
other_folder = os.path.join(folder, "")
this_folder = os.path.join(self.outfolder, "")
if other_folder != this_folder:
errmsg = "Path provided as checkpoint file isn't in pipeline " \
"output folder. '{}' is not in '{}'".format(
check_file, self.outfolder)
raise ValueError(errmsg)
fpath = check_file
else:
fpath = pipeline_filepath(self, filename=check_file)
# Create/update timestamp for checkpoint, but base return value on
# whether the action was a simple update or a novel creation.
already_exists = os.path.isfile(fpath)
open(fpath, 'w').close()
action = "Updated" if already_exists else "Created"
print("{} checkpoint file: '{}'".format(action, fpath))
return already_exists
|
python
|
{
"resource": ""
}
|
q13542
|
PipelineManager.fail_pipeline
|
train
|
def fail_pipeline(self, e, dynamic_recover=False):
"""
If the pipeline does not complete, this function will stop the pipeline gracefully.
It sets the status flag to failed and skips the normal success completion procedure.
:param Exception e: Exception to raise.
:param bool dynamic_recover: Whether to recover e.g. for job termination.
"""
# Take care of any active running subprocess
sys.stdout.flush()
self._terminate_running_subprocesses()
if dynamic_recover:
# job was terminated, not failed due to a bad process.
# flag this run as recoverable.
if len(self.locks) < 1:
# If there is no process locked, then recovery will be automatic.
print("No locked process. Dynamic recovery will be automatic.")
# make a copy of self.locks to iterate over since we'll be clearing them as we go
# set a recovery flag for each lock.
for lock_file in self.locks[:]:
recover_file = self._recoverfile_from_lockfile(lock_file)
print("Setting dynamic recover file: {}".format(recover_file))
self._create_file(recover_file)
self.locks.remove(lock_file)
# Produce cleanup script
self._cleanup(dry_run=True)
# Finally, set the status to failed and close out with a timestamp
if not self._failed: # and not self._completed:
self.timestamp("### Pipeline failed at: ")
total_time = datetime.timedelta(seconds=self.time_elapsed(self.starttime))
print("Total time: " + str(total_time))
self._set_status_flag(FAIL_FLAG)
raise e
|
python
|
{
"resource": ""
}
|
q13543
|
PipelineManager.halt
|
train
|
def halt(self, checkpoint=None, finished=False, raise_error=True):
"""
Stop the pipeline before completion point.
:param str checkpoint: Name of stage just reached or just completed.
:param bool finished: Whether the indicated stage was just finished
(True), or just reached (False)
:param bool raise_error: Whether to raise an exception to truly
halt execution.
"""
self.stop_pipeline(PAUSE_FLAG)
self._active = False
if raise_error:
raise PipelineHalt(checkpoint, finished)
|
python
|
{
"resource": ""
}
|
q13544
|
PipelineManager.stop_pipeline
|
train
|
def stop_pipeline(self, status=COMPLETE_FLAG):
"""
Terminate the pipeline.
This is the "healthy" pipeline completion function.
The normal pipeline completion function, to be run by the pipeline
at the end of the script. It sets status flag to completed and records
some time and memory statistics to the log file.
"""
self._set_status_flag(status)
self._cleanup()
self.report_result("Time", str(datetime.timedelta(seconds=self.time_elapsed(self.starttime))))
self.report_result("Success", time.strftime("%m-%d-%H:%M:%S"))
print("\n##### [Epilogue:]")
print("* " + "Total elapsed time".rjust(20) + ": " + str(datetime.timedelta(seconds=self.time_elapsed(self.starttime))))
# print("Peak memory used: " + str(memory_usage()["peak"]) + "kb")
print("* " + "Peak memory used".rjust(20) + ": " + str(round(self.peak_memory, 2)) + " GB")
if self.halted:
return
self.timestamp("* Pipeline completed at: ".rjust(20))
|
python
|
{
"resource": ""
}
|
q13545
|
PipelineManager._generic_signal_handler
|
train
|
def _generic_signal_handler(self, signal_type):
"""
Function for handling both SIGTERM and SIGINT
"""
print("</pre>")
message = "Got " + signal_type + ". Failing gracefully..."
self.timestamp(message)
self.fail_pipeline(KeyboardInterrupt(signal_type), dynamic_recover=True)
sys.exit(1)
|
python
|
{
"resource": ""
}
|
q13546
|
PipelineManager._exit_handler
|
train
|
def _exit_handler(self):
"""
This function I register with atexit to run whenever the script is completing.
A catch-all for uncaught exceptions, setting status flag file to failed.
"""
# TODO: consider handling sys.stderr/sys.stdout exceptions related to
# TODO (cont.): order of interpreter vs. subprocess shutdown signal receipt.
# TODO (cont.): see https://bugs.python.org/issue11380
# Make the cleanup file executable if it exists
if os.path.isfile(self.cleanup_file):
# Make the cleanup file self destruct.
with open(self.cleanup_file, "a") as myfile:
myfile.write("rm " + self.cleanup_file + "\n")
os.chmod(self.cleanup_file, 0o755)
# If the pipeline hasn't completed successfully, or already been marked
# as failed, then mark it as failed now.
if not self._has_exit_status:
print("Pipeline status: {}".format(self.status))
self.fail_pipeline(Exception("Pipeline failure. See details above."))
if self.tee:
self.tee.kill()
|
python
|
{
"resource": ""
}
|
q13547
|
PipelineManager._kill_child_process
|
train
|
def _kill_child_process(self, child_pid, proc_name=None):
"""
Pypiper spawns subprocesses. We need to kill them to exit gracefully,
in the event of a pipeline termination or interrupt signal.
By default, child processes are not automatically killed when python
terminates, so Pypiper must clean these up manually.
Given a process ID, this function just kills it.
:param int child_pid: Child process id.
"""
# When we kill process, it turns into a zombie, and we have to reap it.
# So we can't just kill it and then let it go; we call wait
def pskill(proc_pid, sig=signal.SIGINT):
parent_process = psutil.Process(proc_pid)
for child_proc in parent_process.children(recursive=True):
child_proc.send_signal(sig)
parent_process.send_signal(sig)
if child_pid is None:
return
if proc_name:
proc_string = " ({proc_name})".format(proc_name=proc_name)
# First a gentle kill
sys.stdout.flush()
still_running = self._attend_process(psutil.Process(child_pid), 0)
sleeptime = .25
time_waiting = 0
while still_running and time_waiting < 3:
try:
if time_waiting > 2:
pskill(child_pid, signal.SIGKILL)
# print("pskill("+str(child_pid)+", signal.SIGKILL)")
elif time_waiting > 1:
pskill(child_pid, signal.SIGTERM)
# print("pskill("+str(child_pid)+", signal.SIGTERM)")
else:
pskill(child_pid, signal.SIGINT)
# print("pskill("+str(child_pid)+", signal.SIGINT)")
except OSError:
# This would happen if the child process ended between the check
# and the next kill step
still_running = False
time_waiting = time_waiting + sleeptime
# Now see if it's still running
time_waiting = time_waiting + sleeptime
if not self._attend_process(psutil.Process(child_pid), sleeptime):
still_running = False
if still_running:
# still running!?
print("Child process {child_pid}{proc_string} never responded"
"I just can't take it anymore. I don't know what to do...".format(child_pid=child_pid,
proc_string=proc_string))
else:
if time_waiting > 0:
note = "terminated after {time} sec".format(time=int(time_waiting))
else:
note = "was already terminated"
msg = "Child process {child_pid}{proc_string} {note}.".format(
child_pid=child_pid, proc_string=proc_string, note=note)
print(msg)
|
python
|
{
"resource": ""
}
|
q13548
|
PipelineManager._memory_usage
|
train
|
def _memory_usage(self, pid='self', category="hwm", container=None):
"""
Memory usage of the process in kilobytes.
:param str pid: Process ID of process to check
:param str category: Memory type to check. 'hwm' for high water mark.
"""
if container:
# TODO: Put some debug output here with switch to Logger
# since this is relatively untested.
cmd = "docker stats " + container + " --format '{{.MemUsage}}' --no-stream"
mem_use_str = subprocess.check_output(cmd, shell=True)
mem_use = mem_use_str.split("/")[0].split()
mem_num = re.findall('[\d\.]+', mem_use_str.split("/")[0])[0]
mem_scale = re.findall('[A-Za-z]+', mem_use_str.split("/")[0])[0]
#print(mem_use_str, mem_num, mem_scale)
mem_num = float(mem_num)
if mem_scale == "GiB":
return mem_num * 1e6
elif mem_scale == "MiB":
return mem_num * 1e3
elif mem_scale == "KiB":
return mem_num
else:
# What type is this?
return 0
# Thanks Martin Geisler:
status = None
result = {'peak': 0, 'rss': 0, 'hwm': 0}
try:
# This will only work on systems with a /proc file system
# (like Linux).
# status = open('/proc/self/status')
proc_spot = '/proc/%s/status' % pid
status = open(proc_spot)
for line in status:
parts = line.split()
key = parts[0][2:-1].lower()
if key in result:
result[key] = int(parts[1])
except:
return 0
finally:
if status is not None:
status.close()
# print(result[category])
return result[category]
|
python
|
{
"resource": ""
}
|
q13549
|
PipelineManager._triage_error
|
train
|
def _triage_error(self, e, nofail):
""" Print a message and decide what to do about an error. """
if not nofail:
self.fail_pipeline(e)
elif self._failed:
print("This is a nofail process, but the pipeline was terminated for other reasons, so we fail.")
raise e
else:
print(e)
print("ERROR: Subprocess returned nonzero result, but pipeline is continuing because nofail=True")
|
python
|
{
"resource": ""
}
|
q13550
|
read_reqs_file
|
train
|
def read_reqs_file(reqs_name):
""" Read requirements file for given requirements group. """
path_reqs_file = os.path.join(
"requirements", "reqs-{}.txt".format(reqs_name))
with open(path_reqs_file, 'r') as reqs_file:
return [pkg.rstrip() for pkg in reqs_file.readlines()
if not pkg.startswith("#")]
|
python
|
{
"resource": ""
}
|
q13551
|
_is_unordered
|
train
|
def _is_unordered(collection):
"""
Determine whether a collection appears to be unordered.
This is a conservative implementation, allowing for the possibility that
someone's implemented Mapping or Set, for example, and provided an
__iter__ implementation that defines a consistent ordering of the
collection's elements.
:param object collection: Object to check as an unordered collection.
:return bool: Whether the given object appears to be unordered
:raises TypeError: If the given "collection" is non-iterable, it's
illogical to investigate whether it's ordered.
"""
if not isinstance(collection, Iterable):
raise TypeError("Non-iterable alleged collection: {}".
format(type(collection)))
return isinstance(collection, set) or \
(isinstance(collection, dict) and
not isinstance(collection, OrderedDict))
|
python
|
{
"resource": ""
}
|
q13552
|
_parse_stage_spec
|
train
|
def _parse_stage_spec(stage_spec):
"""
Handle alternate Stage specifications, returning name and Stage.
Isolate this parsing logic from any iteration. TypeError as single
exception type funnel also provides a more uniform way for callers to
handle specification errors (e.g., skip a stage, warn, re-raise, etc.)
:param (str, pypiper.Stage) | callable stage_spec: name and Stage
:return (name, pypiper.Stage): Pair of name and Stage instance from parsing
input specification
:raise TypeError: if the specification of the stage is not a supported type
"""
# The logic used here, a message to a user about how to specify Stage.
req_msg = "Stage specification must be either a {0} itself, a " \
"(<name>, {0}) pair, or a callable with a __name__ attribute " \
"(e.g., a non-anonymous function)".format(Stage.__name__)
# Simplest case is stage itself.
if isinstance(stage_spec, Stage):
return stage_spec.name, stage_spec
# Handle alternate forms of specification.
try:
# Unpack pair of name and stage, requiring name first.
name, stage = stage_spec
except (TypeError, ValueError):
# Normally, this sort of unpacking issue create a ValueError. Here,
# though, we also need to catch TypeError since that's what arises
# if an attempt is made to unpack a single function.
# Attempt to parse stage_spec as a single named callable.
try:
name = stage_spec.__name__
except AttributeError:
raise TypeError(req_msg)
else:
# Control flow here indicates an anonymous function that was not
# paired with a name. Prohibit that.
if name == (lambda: None).__name__:
raise TypeError(req_msg)
stage = stage_spec
# Ensure that the stage is callable.
if not hasattr(stage, "__call__"):
raise TypeError(req_msg)
return name, Stage(stage, name=name)
|
python
|
{
"resource": ""
}
|
q13553
|
Pipeline.checkpoint
|
train
|
def checkpoint(self, stage, msg=""):
"""
Touch checkpoint file for given stage and provide timestamp message.
:param pypiper.Stage stage: Stage for which to mark checkpoint
:param str msg: Message to embed in timestamp.
:return bool: Whether a checkpoint file was written.
"""
# Canonical usage model for Pipeline checkpointing through
# implementations of this class is by automatically creating a
# checkpoint when a conceptual unit or group of operations of a
# pipeline completes, so fix the 'finished' parameter to the manager's
# timestamp method to be True.
return self.manager.timestamp(
message=msg, checkpoint=stage.checkpoint_name, finished=True)
|
python
|
{
"resource": ""
}
|
q13554
|
Pipeline.completed_stage
|
train
|
def completed_stage(self, stage):
"""
Determine whether the pipeline's completed the stage indicated.
:param pypiper.Stage stage: Stage to check for completion status.
:return bool: Whether this pipeline's completed the indicated stage.
:raises UnknownStageException: If the stage name given is undefined
for the pipeline, a ValueError arises.
"""
check_path = checkpoint_filepath(stage, self.manager)
return os.path.exists(check_path)
|
python
|
{
"resource": ""
}
|
q13555
|
Pipeline.list_flags
|
train
|
def list_flags(self, only_name=False):
"""
Determine the flag files associated with this pipeline.
:param bool only_name: Whether to return only flag file name(s) (True),
or full flag file paths (False); default False (paths)
:return list[str]: flag files associated with this pipeline.
"""
paths = glob.glob(os.path.join(self.outfolder, flag_name("*")))
if only_name:
return [os.path.split(p)[1] for p in paths]
else:
return paths
|
python
|
{
"resource": ""
}
|
q13556
|
Pipeline._start_index
|
train
|
def _start_index(self, start=None):
""" Seek to the first stage to run. """
if start is None:
return 0
start_stage = translate_stage_name(start)
internal_names = [translate_stage_name(s.name) for s in self._stages]
try:
return internal_names.index(start_stage)
except ValueError:
raise UnknownPipelineStageError(start, self)
|
python
|
{
"resource": ""
}
|
q13557
|
to_ufo_font_attributes
|
train
|
def to_ufo_font_attributes(self, family_name):
"""Generate a list of UFOs with metadata loaded from .glyphs data.
Modifies the list of UFOs in the UFOBuilder (self) in-place.
"""
font = self.font
# "date" can be missing; Glyphs.app removes it on saving if it's empty:
# https://github.com/googlei18n/glyphsLib/issues/134
date_created = getattr(font, "date", None)
if date_created is not None:
date_created = to_ufo_time(date_created)
units_per_em = font.upm
version_major = font.versionMajor
version_minor = font.versionMinor
copyright = font.copyright
designer = font.designer
designer_url = font.designerURL
manufacturer = font.manufacturer
manufacturer_url = font.manufacturerURL
# XXX note is unused?
# note = font.note
glyph_order = list(glyph.name for glyph in font.glyphs)
for index, master in enumerate(font.masters):
source = self._designspace.newSourceDescriptor()
ufo = self.ufo_module.Font()
source.font = ufo
ufo.lib[APP_VERSION_LIB_KEY] = font.appVersion
ufo.lib[KEYBOARD_INCREMENT_KEY] = font.keyboardIncrement
if date_created is not None:
ufo.info.openTypeHeadCreated = date_created
ufo.info.unitsPerEm = units_per_em
ufo.info.versionMajor = version_major
ufo.info.versionMinor = version_minor
if copyright:
ufo.info.copyright = copyright
if designer:
ufo.info.openTypeNameDesigner = designer
if designer_url:
ufo.info.openTypeNameDesignerURL = designer_url
if manufacturer:
ufo.info.openTypeNameManufacturer = manufacturer
if manufacturer_url:
ufo.info.openTypeNameManufacturerURL = manufacturer_url
ufo.glyphOrder = glyph_order
self.to_ufo_names(ufo, master, family_name)
self.to_ufo_family_user_data(ufo)
self.to_ufo_custom_params(ufo, font)
self.to_ufo_master_attributes(source, master)
ufo.lib[MASTER_ORDER_LIB_KEY] = index
# FIXME: (jany) in the future, yield this UFO (for memory, lazy iter)
self._designspace.addSource(source)
self._sources[master.id] = source
|
python
|
{
"resource": ""
}
|
q13558
|
to_glyphs_font_attributes
|
train
|
def to_glyphs_font_attributes(self, source, master, is_initial):
"""
Copy font attributes from `ufo` either to `self.font` or to `master`.
Arguments:
self -- The UFOBuilder
ufo -- The current UFO being read
master -- The current master being written
is_initial -- True iff this the first UFO that we process
"""
if is_initial:
_set_glyphs_font_attributes(self, source)
else:
_compare_and_merge_glyphs_font_attributes(self, source)
|
python
|
{
"resource": ""
}
|
q13559
|
to_ufo_glyph_background
|
train
|
def to_ufo_glyph_background(self, glyph, layer):
"""Set glyph background."""
if not layer.hasBackground:
return
background = layer.background
ufo_layer = self.to_ufo_background_layer(glyph)
new_glyph = ufo_layer.newGlyph(glyph.name)
width = background.userData[BACKGROUND_WIDTH_KEY]
if width is not None:
new_glyph.width = width
self.to_ufo_background_image(new_glyph, background)
self.to_ufo_paths(new_glyph, background)
self.to_ufo_components(new_glyph, background)
self.to_ufo_glyph_anchors(new_glyph, background.anchors)
self.to_ufo_guidelines(new_glyph, background)
|
python
|
{
"resource": ""
}
|
q13560
|
to_designspace_instances
|
train
|
def to_designspace_instances(self):
"""Write instance data from self.font to self.designspace."""
for instance in self.font.instances:
if self.minimize_glyphs_diffs or (
is_instance_active(instance)
and _is_instance_included_in_family(self, instance)
):
_to_designspace_instance(self, instance)
|
python
|
{
"resource": ""
}
|
q13561
|
apply_instance_data
|
train
|
def apply_instance_data(designspace, include_filenames=None, Font=defcon.Font):
"""Open UFO instances referenced by designspace, apply Glyphs instance
data if present, re-save UFOs and return updated UFO Font objects.
Args:
designspace: DesignSpaceDocument object or path (str or PathLike) to
a designspace file.
include_filenames: optional set of instance filenames (relative to
the designspace path) to be included. By default all instaces are
processed.
Font: the class used to load the UFO (default: defcon.Font).
Returns:
List of opened and updated instance UFOs.
"""
from fontTools.designspaceLib import DesignSpaceDocument
from os.path import normcase, normpath
if hasattr(designspace, "__fspath__"):
designspace = designspace.__fspath__()
if isinstance(designspace, basestring):
designspace = DesignSpaceDocument.fromfile(designspace)
basedir = os.path.dirname(designspace.path)
instance_ufos = []
if include_filenames is not None:
include_filenames = {normcase(normpath(p)) for p in include_filenames}
for designspace_instance in designspace.instances:
fname = designspace_instance.filename
assert fname is not None, "instance %r missing required filename" % getattr(
designspace_instance, "name", designspace_instance
)
if include_filenames is not None:
fname = normcase(normpath(fname))
if fname not in include_filenames:
continue
logger.debug("Applying instance data to %s", fname)
# fontmake <= 1.4.0 compares the ufo paths returned from this function
# to the keys of a dict of designspace locations that have been passed
# through normpath (but not normcase). We do the same.
ufo = Font(normpath(os.path.join(basedir, fname)))
set_weight_class(ufo, designspace, designspace_instance)
set_width_class(ufo, designspace, designspace_instance)
glyphs_instance = InstanceDescriptorAsGSInstance(designspace_instance)
to_ufo_custom_params(None, ufo, glyphs_instance)
ufo.save()
instance_ufos.append(ufo)
return instance_ufos
|
python
|
{
"resource": ""
}
|
q13562
|
_to_ufo_features
|
train
|
def _to_ufo_features(self, master, ufo):
"""Write an UFO's OpenType feature file."""
# Recover the original feature code if it was stored in the user data
original = master.userData[ORIGINAL_FEATURE_CODE_KEY]
if original is not None:
ufo.features.text = original
return
prefixes = []
for prefix in self.font.featurePrefixes:
strings = []
if prefix.name != ANONYMOUS_FEATURE_PREFIX_NAME:
strings.append("# Prefix: %s\n" % prefix.name)
strings.append(autostr(prefix.automatic))
strings.append(prefix.code)
prefixes.append("".join(strings))
prefix_str = "\n\n".join(prefixes)
class_defs = []
for class_ in self.font.classes:
prefix = "@" if not class_.name.startswith("@") else ""
name = prefix + class_.name
class_defs.append(
"{}{} = [ {} ];".format(autostr(class_.automatic), name, class_.code)
)
class_str = "\n\n".join(class_defs)
feature_defs = []
for feature in self.font.features:
code = feature.code
lines = ["feature %s {" % feature.name]
if feature.notes:
lines.append("# notes:")
lines.extend("# " + line for line in feature.notes.splitlines())
if feature.automatic:
lines.append("# automatic")
if feature.disabled:
lines.append("# disabled")
lines.extend("#" + line for line in code.splitlines())
else:
lines.append(code)
lines.append("} %s;" % feature.name)
feature_defs.append("\n".join(lines))
fea_str = "\n\n".join(feature_defs)
# Don't add a GDEF table when planning to round-trip. To get Glyphs.app-like
# results, we would need anchor propagation or user intervention. Glyphs.app
# only generates it on generating binaries.
gdef_str = None
if self.generate_GDEF:
if re.search(r"^\s*table\s+GDEF\s+{", prefix_str, flags=re.MULTILINE):
raise ValueError(
"The features already contain a `table GDEF {...}` statement. "
"Either delete it or set generate_GDEF to False."
)
gdef_str = _build_gdef(
ufo, self._designspace.lib.get("public.skipExportGlyphs")
)
# make sure feature text is a unicode string, for defcon
full_text = (
"\n\n".join(filter(None, [class_str, prefix_str, fea_str, gdef_str])) + "\n"
)
ufo.features.text = full_text if full_text.strip() else ""
|
python
|
{
"resource": ""
}
|
q13563
|
FeatureFileProcessor._pop_comment
|
train
|
def _pop_comment(self, statements, comment_re):
"""Look for the comment that matches the given regex.
If it matches, return the regex match object and list of statements
without the special one.
"""
res = []
match = None
for st in statements:
if match or not isinstance(st, ast.Comment):
res.append(st)
continue
match = comment_re.match(st.text)
if not match:
res.append(st)
return match, res
|
python
|
{
"resource": ""
}
|
q13564
|
FeatureFileProcessor._pop_comment_block
|
train
|
def _pop_comment_block(self, statements, header_re):
"""Look for a series of comments that start with one that matches the
regex. If the first comment is found, all subsequent comments are
popped from statements, concatenated and dedented and returned.
"""
res = []
comments = []
match = None
st_iter = iter(statements)
# Look for the header
for st in st_iter:
if isinstance(st, ast.Comment):
match = header_re.match(st.text)
if match:
# Drop this comment an move on to consuming the block
break
else:
res.append(st)
else:
res.append(st)
# Consume consecutive comments
for st in st_iter:
if isinstance(st, ast.Comment):
comments.append(st)
else:
# The block is over, keep the rest of the statements
res.append(st)
break
# Keep the rest of the statements
res.extend(list(st_iter))
# Inside the comment block, drop the pound sign and any common indent
return match, dedent("".join(c.text[1:] + "\n" for c in comments)), res
|
python
|
{
"resource": ""
}
|
q13565
|
ApiViewDeclaration.get_marshmallow_schema_name
|
train
|
def get_marshmallow_schema_name(self, plugin, schema):
"""Get the schema name.
If the schema doesn't exist, create it.
"""
try:
return plugin.openapi.refs[schema]
except KeyError:
plugin.spec.definition(schema.__name__, schema=schema)
return schema.__name__
|
python
|
{
"resource": ""
}
|
q13566
|
to_ufo_components
|
train
|
def to_ufo_components(self, ufo_glyph, layer):
"""Draw .glyphs components onto a pen, adding them to the parent glyph."""
pen = ufo_glyph.getPointPen()
for index, component in enumerate(layer.components):
pen.addComponent(component.name, component.transform)
if component.anchor:
if COMPONENT_INFO_KEY not in ufo_glyph.lib:
ufo_glyph.lib[COMPONENT_INFO_KEY] = []
ufo_glyph.lib[COMPONENT_INFO_KEY].append(
{"name": component.name, "index": index, "anchor": component.anchor}
)
# data related to components stored in lists of booleans
# each list's elements correspond to the components in order
for key in ["alignment", "locked", "smartComponentValues"]:
values = [getattr(c, key) for c in layer.components]
if any(values):
ufo_glyph.lib[_lib_key(key)] = values
|
python
|
{
"resource": ""
}
|
q13567
|
ApiView.request_args
|
train
|
def request_args(self):
"""Use args_schema to parse request query arguments."""
args = flask.request.args
data_raw = {}
for field_name, field in self.args_schema.fields.items():
alternate_field_name = field.load_from if MA2 else field.data_key
if alternate_field_name and alternate_field_name in args:
field_name = alternate_field_name
elif field_name not in args:
# getlist will return an empty list instead of raising a
# KeyError for args that aren't present.
continue
value = args.getlist(field_name)
if not self.is_list_field(field) and len(value) == 1:
value = value[0]
data_raw[field_name] = value
return self.deserialize_args(data_raw)
|
python
|
{
"resource": ""
}
|
q13568
|
ModelView.query
|
train
|
def query(self):
"""The SQLAlchemy query for the view.
Override this to customize the query to fetch items in this view.
By default, this applies the filter from the view's `authorization` and
the query options from `base_query_options` and `query_options`.
"""
query = self.query_raw
query = self.authorization.filter_query(query, self)
query = query.options(
*itertools.chain(self.base_query_options, self.query_options)
)
return query
|
python
|
{
"resource": ""
}
|
q13569
|
ModelView.query_options
|
train
|
def query_options(self):
"""Options to apply to the query for the view.
Set this to configure relationship and column loading.
By default, this calls the ``get_query_options`` method on the
serializer with a `Load` object bound to the model, if that serializer
method exists.
"""
if not hasattr(self.serializer, 'get_query_options'):
return ()
return self.serializer.get_query_options(Load(self.model))
|
python
|
{
"resource": ""
}
|
q13570
|
to_ufo_paths
|
train
|
def to_ufo_paths(self, ufo_glyph, layer):
"""Draw .glyphs paths onto a pen."""
pen = ufo_glyph.getPointPen()
for path in layer.paths:
# the list is changed below, otherwise you can't draw more than once
# per session.
nodes = list(path.nodes)
for node in nodes:
self.to_ufo_node_user_data(ufo_glyph, node)
pen.beginPath()
if not nodes:
pen.endPath()
continue
if not path.closed:
node = nodes.pop(0)
assert node.type == "line", "Open path starts with off-curve points"
pen.addPoint(tuple(node.position), segmentType="move")
else:
# In Glyphs.app, the starting node of a closed contour is always
# stored at the end of the nodes list.
nodes.insert(0, nodes.pop())
for node in nodes:
node_type = _to_ufo_node_type(node.type)
pen.addPoint(
tuple(node.position), segmentType=node_type, smooth=node.smooth
)
pen.endPath()
|
python
|
{
"resource": ""
}
|
q13571
|
request_cached_property
|
train
|
def request_cached_property(func):
"""Make the given method a per-request cached property.
This caches the value on the request context rather than on the object
itself, preventing problems if the object gets reused across multiple
requests.
"""
@property
@functools.wraps(func)
def wrapped(self):
cached_value = context.get_for_view(self, func.__name__, UNDEFINED)
if cached_value is not UNDEFINED:
return cached_value
value = func(self)
context.set_for_view(self, func.__name__, value)
return value
return wrapped
|
python
|
{
"resource": ""
}
|
q13572
|
_ufo_logging_ref
|
train
|
def _ufo_logging_ref(ufo):
"""Return a string that can identify this UFO in logs."""
if ufo.path:
return os.path.basename(ufo.path)
return ufo.info.styleName
|
python
|
{
"resource": ""
}
|
q13573
|
parse_datetime
|
train
|
def parse_datetime(src=None):
"""Parse a datetime object from a string."""
if src is None:
return None
string = src.replace('"', "")
# parse timezone ourselves, since %z is not always supported
# see: http://bugs.python.org/issue6641
m = UTC_OFFSET_RE.match(string)
if m:
sign = 1 if m.group("sign") == "+" else -1
tz_hours = sign * int(m.group("hours"))
tz_minutes = sign * int(m.group("minutes"))
offset = datetime.timedelta(hours=tz_hours, minutes=tz_minutes)
string = string[:-6]
else:
# no explicit timezone
offset = datetime.timedelta(0)
if "AM" in string or "PM" in string:
datetime_obj = datetime.datetime.strptime(string, "%Y-%m-%d %I:%M:%S %p")
else:
datetime_obj = datetime.datetime.strptime(string, "%Y-%m-%d %H:%M:%S")
return datetime_obj + offset
|
python
|
{
"resource": ""
}
|
q13574
|
parse_color
|
train
|
def parse_color(src=None):
# type: (Optional[str]) -> Optional[Union[Tuple[int, ...], int]]
"""Parse a string representing a color value.
Color is either a fixed color (when coloring something from the UI, see
the GLYPHS_COLORS constant) or a list of the format [u8, u8, u8, u8],
Glyphs does not support an alpha channel as of 2.5.1 (confirmed by Georg
Seifert), and always writes a 1 to it. This was brought up and is probably
corrected in the next versions.
https://github.com/googlei18n/glyphsLib/pull/363#issuecomment-390418497
"""
if src is None:
return None
# Tuple.
if src[0] == "(":
rgba = tuple(int(v) for v in src[1:-1].split(",") if v)
if not (len(rgba) == 4 and all(0 <= v < 256 for v in rgba)):
raise ValueError(
"Broken color tuple: {}. Must have four values from 0 to 255.".format(
src
)
)
return rgba
# Constant.
return int(src)
|
python
|
{
"resource": ""
}
|
q13575
|
Parser.parse
|
train
|
def parse(self, text):
"""Do the parsing."""
text = tounicode(text, encoding="utf-8")
result, i = self._parse(text, 0)
if text[i:].strip():
self._fail("Unexpected trailing content", text, i)
return result
|
python
|
{
"resource": ""
}
|
q13576
|
Parser.parse_into_object
|
train
|
def parse_into_object(self, res, text):
"""Parse data into an existing GSFont instance."""
text = tounicode(text, encoding="utf-8")
m = self.start_dict_re.match(text, 0)
if m:
i = self._parse_dict_into_object(res, text, 1)
else:
self._fail("not correct file format", text, 0)
if text[i:].strip():
self._fail("Unexpected trailing content", text, i)
return i
|
python
|
{
"resource": ""
}
|
q13577
|
Parser._parse
|
train
|
def _parse(self, text, i):
"""Recursive function to parse a single dictionary, list, or value."""
m = self.start_dict_re.match(text, i)
if m:
parsed = m.group(0)
i += len(parsed)
return self._parse_dict(text, i)
m = self.start_list_re.match(text, i)
if m:
parsed = m.group(0)
i += len(parsed)
return self._parse_list(text, i)
m = self.value_re.match(text, i)
if m:
parsed = m.group(0)
i += len(parsed)
if hasattr(self.current_type, "read"):
reader = self.current_type()
# Give the escaped value to `read` to be symetrical with
# `plistValue` which handles the escaping itself.
value = reader.read(m.group(1))
return value, i
value = self._trim_value(m.group(1))
if self.current_type in (None, dict, OrderedDict):
self.current_type = self._guess_current_type(parsed, value)
if self.current_type == bool:
value = bool(int(value)) # bool(u'0') returns True
return value, i
value = self.current_type(value)
return value, i
m = self.hex_re.match(text, i)
if m:
from glyphsLib.types import BinaryData
parsed, value = m.group(0), m.group(1)
decoded = BinaryData.fromHex(value)
i += len(parsed)
return decoded, i
else:
self._fail("Unexpected content", text, i)
|
python
|
{
"resource": ""
}
|
q13578
|
Parser._parse_dict
|
train
|
def _parse_dict(self, text, i):
"""Parse a dictionary from source text starting at i."""
old_current_type = self.current_type
new_type = self.current_type
if new_type is None:
# customparameter.value needs to be set from the found value
new_type = dict
elif type(new_type) == list:
new_type = new_type[0]
res = new_type()
i = self._parse_dict_into_object(res, text, i)
self.current_type = old_current_type
return res, i
|
python
|
{
"resource": ""
}
|
q13579
|
Parser._parse_list
|
train
|
def _parse_list(self, text, i):
"""Parse a list from source text starting at i."""
res = []
end_match = self.end_list_re.match(text, i)
old_current_type = self.current_type
while not end_match:
list_item, i = self._parse(text, i)
res.append(list_item)
end_match = self.end_list_re.match(text, i)
if not end_match:
m = self.list_delim_re.match(text, i)
if not m:
self._fail("Missing delimiter in list before content", text, i)
parsed = m.group(0)
i += len(parsed)
self.current_type = old_current_type
parsed = end_match.group(0)
i += len(parsed)
return res, i
|
python
|
{
"resource": ""
}
|
q13580
|
Parser._trim_value
|
train
|
def _trim_value(self, value):
"""Trim double quotes off the ends of a value, un-escaping inner
double quotes and literal backslashes. Also convert escapes to unicode.
If the string is not quoted, return it unmodified.
"""
if value[0] == '"':
assert value[-1] == '"'
value = value[1:-1].replace('\\"', '"').replace("\\\\", "\\")
return Parser._unescape_re.sub(Parser._unescape_fn, value)
return value
|
python
|
{
"resource": ""
}
|
q13581
|
Parser._fail
|
train
|
def _fail(self, message, text, i):
"""Raise an exception with given message and text at i."""
raise ValueError("{}:\n{}".format(message, text[i : i + 79]))
|
python
|
{
"resource": ""
}
|
q13582
|
build_stylemap_names
|
train
|
def build_stylemap_names(
family_name, style_name, is_bold=False, is_italic=False, linked_style=None
):
"""Build UFO `styleMapFamilyName` and `styleMapStyleName` based on the
family and style names, and the entries in the "Style Linking" section
of the "Instances" tab in the "Font Info".
The value of `styleMapStyleName` can be either "regular", "bold", "italic"
or "bold italic", depending on the values of `is_bold` and `is_italic`.
The `styleMapFamilyName` is a combination of the `family_name` and the
`linked_style`.
If `linked_style` is unset or set to 'Regular', the linked style is equal
to the style_name with the last occurrences of the strings 'Regular',
'Bold' and 'Italic' stripped from it.
"""
styleMapStyleName = (
" ".join(
s for s in ("bold" if is_bold else "", "italic" if is_italic else "") if s
)
or "regular"
)
if not linked_style or linked_style == "Regular":
linked_style = _get_linked_style(style_name, is_bold, is_italic)
if linked_style:
styleMapFamilyName = (family_name or "") + " " + linked_style
else:
styleMapFamilyName = family_name
return styleMapFamilyName, styleMapStyleName
|
python
|
{
"resource": ""
}
|
q13583
|
to_ufo_blue_values
|
train
|
def to_ufo_blue_values(self, ufo, master):
"""Set postscript blue values from Glyphs alignment zones."""
alignment_zones = master.alignmentZones
blue_values = []
other_blues = []
for zone in sorted(alignment_zones):
pos = zone.position
size = zone.size
val_list = blue_values if pos == 0 or size >= 0 else other_blues
val_list.extend(sorted((pos, pos + size)))
ufo.info.postscriptBlueValues = blue_values
ufo.info.postscriptOtherBlues = other_blues
|
python
|
{
"resource": ""
}
|
q13584
|
to_glyphs_blue_values
|
train
|
def to_glyphs_blue_values(self, ufo, master):
"""Sets the GSFontMaster alignmentZones from the postscript blue values."""
zones = []
blue_values = _pairs(ufo.info.postscriptBlueValues)
other_blues = _pairs(ufo.info.postscriptOtherBlues)
for y1, y2 in blue_values:
size = y2 - y1
if y2 == 0:
pos = 0
size = -size
else:
pos = y1
zones.append(self.glyphs_module.GSAlignmentZone(pos, size))
for y1, y2 in other_blues:
size = y1 - y2
pos = y2
zones.append(self.glyphs_module.GSAlignmentZone(pos, size))
master.alignmentZones = sorted(zones, key=lambda zone: -zone.position)
|
python
|
{
"resource": ""
}
|
q13585
|
parse_glyphs_filter
|
train
|
def parse_glyphs_filter(filter_str, is_pre=False):
"""Parses glyphs custom filter string into a dict object that
ufo2ft can consume.
Reference:
ufo2ft: https://github.com/googlei18n/ufo2ft
Glyphs 2.3 Handbook July 2016, p184
Args:
filter_str - a string of glyphs app filter
Return:
A dictionary contains the structured filter.
Return None if parse failed.
"""
elements = filter_str.split(";")
if elements[0] == "":
logger.error(
"Failed to parse glyphs filter, expecting a filter name: \
%s",
filter_str,
)
return None
result = {"name": elements[0]}
for idx, elem in enumerate(elements[1:]):
if not elem:
# skip empty arguments
continue
if ":" in elem:
# Key value pair
key, value = elem.split(":", 1)
if key.lower() in ["include", "exclude"]:
if idx != len(elements[1:]) - 1:
logger.error(
"{} can only present as the last argument in the filter. "
"{} is ignored.".format(key, elem)
)
continue
result[key.lower()] = re.split("[ ,]+", value)
else:
if "kwargs" not in result:
result["kwargs"] = {}
result["kwargs"][key] = cast_to_number_or_bool(value)
else:
if "args" not in result:
result["args"] = []
result["args"].append(cast_to_number_or_bool(elem))
if is_pre:
result["pre"] = True
return result
|
python
|
{
"resource": ""
}
|
q13586
|
build_ufo_path
|
train
|
def build_ufo_path(out_dir, family_name, style_name):
"""Build string to use as a UFO path."""
return os.path.join(
out_dir,
"%s-%s.ufo"
% ((family_name or "").replace(" ", ""), (style_name or "").replace(" ", "")),
)
|
python
|
{
"resource": ""
}
|
q13587
|
write_ufo
|
train
|
def write_ufo(ufo, out_dir):
"""Write a UFO."""
out_path = build_ufo_path(out_dir, ufo.info.familyName, ufo.info.styleName)
logger.info("Writing %s" % out_path)
clean_ufo(out_path)
ufo.save(out_path)
|
python
|
{
"resource": ""
}
|
q13588
|
clean_ufo
|
train
|
def clean_ufo(path):
"""Make sure old UFO data is removed, as it may contain deleted glyphs."""
if path.endswith(".ufo") and os.path.exists(path):
shutil.rmtree(path)
|
python
|
{
"resource": ""
}
|
q13589
|
ufo_create_background_layer_for_all_glyphs
|
train
|
def ufo_create_background_layer_for_all_glyphs(ufo_font):
# type: (defcon.Font) -> None
"""Create a background layer for all glyphs in ufo_font if not present to
reduce roundtrip differences."""
if "public.background" in ufo_font.layers:
background = ufo_font.layers["public.background"]
else:
background = ufo_font.newLayer("public.background")
for glyph in ufo_font:
if glyph.name not in background:
background.newGlyph(glyph.name)
|
python
|
{
"resource": ""
}
|
q13590
|
cast_to_number_or_bool
|
train
|
def cast_to_number_or_bool(inputstr):
"""Cast a string to int, float or bool. Return original string if it can't be
converted.
Scientific expression is converted into float.
"""
if inputstr.strip().lower() == "true":
return True
elif inputstr.strip().lower() == "false":
return False
try:
return int(inputstr)
except ValueError:
try:
return float(inputstr)
except ValueError:
return inputstr
|
python
|
{
"resource": ""
}
|
q13591
|
to_ufo_background_image
|
train
|
def to_ufo_background_image(self, ufo_glyph, layer):
"""Copy the backgound image from the GSLayer to the UFO Glyph."""
image = layer.backgroundImage
if image is None:
return
ufo_image = ufo_glyph.image
ufo_image.fileName = image.path
ufo_image.transformation = image.transform
ufo_glyph.lib[CROP_KEY] = list(image.crop)
ufo_glyph.lib[LOCKED_KEY] = image.locked
ufo_glyph.lib[ALPHA_KEY] = image.alpha
|
python
|
{
"resource": ""
}
|
q13592
|
to_glyphs_background_image
|
train
|
def to_glyphs_background_image(self, ufo_glyph, layer):
"""Copy the background image from the UFO Glyph to the GSLayer."""
ufo_image = ufo_glyph.image
if ufo_image.fileName is None:
return
image = self.glyphs_module.GSBackgroundImage()
image.path = ufo_image.fileName
image.transform = Transform(*ufo_image.transformation)
if CROP_KEY in ufo_glyph.lib:
x, y, w, h = ufo_glyph.lib[CROP_KEY]
image.crop = Rect(Point(x, y), Size(w, h))
if LOCKED_KEY in ufo_glyph.lib:
image.locked = ufo_glyph.lib[LOCKED_KEY]
if ALPHA_KEY in ufo_glyph.lib:
image.alpha = ufo_glyph.lib[ALPHA_KEY]
layer.backgroundImage = image
|
python
|
{
"resource": ""
}
|
q13593
|
Api.add_resource
|
train
|
def add_resource(
self,
base_rule,
base_view,
alternate_view=None,
alternate_rule=None,
id_rule=None,
app=None,
):
"""Add route or routes for a resource.
:param str base_rule: The URL rule for the resource. This will be
prefixed by the API prefix.
:param base_view: Class-based view for the resource.
:param alternate_view: If specified, an alternate class-based view for
the resource. Usually, this will be a detail view, when the base
view is a list view.
:param alternate_rule: If specified, the URL rule for the alternate
view. This will be prefixed by the API prefix. This is mutually
exclusive with id_rule, and must not be specified if alternate_view
is not specified.
:type alternate_rule: str or None
:param id_rule: If specified, a suffix to append to base_rule to get
the alternate view URL rule. If alternate_view is specified, and
alternate_rule is not, then this defaults to '<id>'. This is
mutually exclusive with alternate_rule, and must not be specified
if alternate_view is not specified.
:type id_rule: str or None
:param app: If specified, the application to which to add the route(s).
Otherwise, this will be the bound application, if present.
"""
if alternate_view:
if not alternate_rule:
id_rule = id_rule or DEFAULT_ID_RULE
alternate_rule = posixpath.join(base_rule, id_rule)
else:
assert id_rule is None
else:
assert alternate_rule is None
assert id_rule is None
app = self._get_app(app)
endpoint = self._get_endpoint(base_view, alternate_view)
# Store the view rules for reference. Doesn't support multiple routes
# mapped to same view.
views = app.extensions['resty'].views
base_rule_full = '{}{}'.format(self.prefix, base_rule)
base_view_func = base_view.as_view(endpoint)
if not alternate_view:
app.add_url_rule(base_rule_full, view_func=base_view_func)
views[base_view] = Resource(base_view, base_rule_full)
return
alternate_rule_full = '{}{}'.format(self.prefix, alternate_rule)
alternate_view_func = alternate_view.as_view(endpoint)
@functools.wraps(base_view_func)
def view_func(*args, **kwargs):
if flask.request.url_rule.rule == base_rule_full:
return base_view_func(*args, **kwargs)
else:
return alternate_view_func(*args, **kwargs)
app.add_url_rule(
base_rule_full, view_func=view_func, endpoint=endpoint,
methods=base_view.methods,
)
app.add_url_rule(
alternate_rule_full, view_func=view_func, endpoint=endpoint,
methods=alternate_view.methods,
)
views[base_view] = Resource(base_view, base_rule_full)
views[alternate_view] = Resource(alternate_view, alternate_rule_full)
|
python
|
{
"resource": ""
}
|
q13594
|
Api.add_ping
|
train
|
def add_ping(self, rule, status_code=200, app=None):
"""Add a ping route.
:param str rule: The URL rule. This will not use the API prefix, as the
ping endpoint is not really part of the API.
:param int status_code: The ping response status code. The default is
200 rather than the more correct 204 because many health checks
look for 200s.
:param app: If specified, the application to which to add the route.
Otherwise, this will be the bound application, if present.
"""
app = self._get_app(app)
@app.route(rule)
def ping():
return '', status_code
|
python
|
{
"resource": ""
}
|
q13595
|
UFOBuilder.masters
|
train
|
def masters(self):
"""Get an iterator over master UFOs that match the given family_name.
"""
if self._sources:
for source in self._sources.values():
yield source.font
return
# Store set of actually existing master (layer) ids. This helps with
# catching dangling layer data that Glyphs may ignore, e.g. when
# copying glyphs from other fonts with, naturally, different master
# ids. Note: Masters have unique ids according to the Glyphs
# documentation and can therefore be stored in a set.
master_layer_ids = {m.id for m in self.font.masters}
# stores background data from "associated layers"
supplementary_layer_data = []
# TODO(jamesgk) maybe create one font at a time to reduce memory usage
# TODO: (jany) in the future, return a lazy iterator that builds UFOs
# on demand.
self.to_ufo_font_attributes(self.family_name)
# Generate the main (master) layers first.
for glyph in self.font.glyphs:
for layer in glyph.layers.values():
if layer.associatedMasterId != layer.layerId:
# The layer is not the main layer of a master
# Store all layers, even the invalid ones, and just skip
# them and print a warning below.
supplementary_layer_data.append((glyph, layer))
continue
ufo_layer = self.to_ufo_layer(glyph, layer)
ufo_glyph = ufo_layer.newGlyph(glyph.name)
self.to_ufo_glyph(ufo_glyph, layer, glyph)
# And sublayers (brace, bracket, ...) second.
for glyph, layer in supplementary_layer_data:
if (
layer.layerId not in master_layer_ids
and layer.associatedMasterId not in master_layer_ids
):
if self.minimize_glyphs_diffs:
self.logger.warning(
'{}, glyph "{}": Layer "{}" is dangling and will be '
"skipped. Did you copy a glyph from a different font?"
" If so, you should clean up any phantom layers not "
"associated with an actual master.".format(
self.font.familyName, glyph.name, layer.layerId
)
)
continue
if not layer.name:
# Empty layer names are invalid according to the UFO spec.
if self.minimize_glyphs_diffs:
self.logger.warning(
'{}, glyph "{}": Contains layer without a name which '
"will be skipped.".format(self.font.familyName, glyph.name)
)
continue
# Save processing bracket layers for when designspace() is called, as we
# have to extract them to free-standing glyphs.
if (
"[" in layer.name
and "]" in layer.name
and ".background" not in layer.name
):
self.bracket_layers.append(layer)
else:
ufo_layer = self.to_ufo_layer(glyph, layer)
ufo_glyph = ufo_layer.newGlyph(glyph.name)
self.to_ufo_glyph(ufo_glyph, layer, layer.parent)
for source in self._sources.values():
ufo = source.font
if self.propagate_anchors:
self.to_ufo_propagate_font_anchors(ufo)
for layer in ufo.layers:
self.to_ufo_layer_lib(layer)
# Sanitize skip list and write it to both Designspace- and UFO-level lib keys.
# The latter is unnecessary when using e.g. the `ufo2ft.compile*FromDS`
# functions, but the data may take a different path. Writing it everywhere can
# save on surprises/logic in other software.
skip_export_glyphs = self._designspace.lib.get("public.skipExportGlyphs")
if skip_export_glyphs is not None:
skip_export_glyphs = sorted(set(skip_export_glyphs))
self._designspace.lib["public.skipExportGlyphs"] = skip_export_glyphs
for source in self._sources.values():
source.font.lib["public.skipExportGlyphs"] = skip_export_glyphs
self.to_ufo_features() # This depends on the glyphOrder key
self.to_ufo_groups()
self.to_ufo_kerning()
for source in self._sources.values():
yield source.font
|
python
|
{
"resource": ""
}
|
q13596
|
UFOBuilder.designspace
|
train
|
def designspace(self):
"""Get a designspace Document instance that links the masters together
and holds instance data.
"""
if self._designspace_is_complete:
return self._designspace
self._designspace_is_complete = True
list(self.masters) # Make sure that the UFOs are built
self.to_designspace_axes()
self.to_designspace_sources()
self.to_designspace_instances()
self.to_designspace_family_user_data()
if self.bracket_layers:
self._apply_bracket_layers()
# append base style shared by all masters to designspace file name
base_family = self.family_name or "Unnamed"
base_style = find_base_style(self.font.masters)
if base_style:
base_style = "-" + base_style
name = (base_family + base_style).replace(" ", "") + ".designspace"
self.designspace.filename = name
return self._designspace
|
python
|
{
"resource": ""
}
|
q13597
|
GlyphsBuilder.font
|
train
|
def font(self):
"""Get the GSFont built from the UFOs + designspace."""
if self._font is not None:
return self._font
# Sort UFOS in the original order from the Glyphs file
sorted_sources = self.to_glyphs_ordered_masters()
# Convert all full source UFOs to Glyphs masters. Sources with layer names
# are assumed to be sparse or "brace" layers and are ignored because Glyphs
# considers them to be special layers and will handle them itself.
self._font = self.glyphs_module.GSFont()
self._sources = OrderedDict() # Same as in UFOBuilder
for index, source in enumerate(s for s in sorted_sources if not s.layerName):
master = self.glyphs_module.GSFontMaster()
# Filter bracket glyphs out of public.glyphOrder.
if GLYPH_ORDER_KEY in source.font.lib:
source.font.lib[GLYPH_ORDER_KEY] = [
glyph_name
for glyph_name in source.font.lib[GLYPH_ORDER_KEY]
if ".BRACKET." not in glyph_name
]
self.to_glyphs_font_attributes(source, master, is_initial=(index == 0))
self.to_glyphs_master_attributes(source, master)
self._font.masters.insert(len(self._font.masters), master)
self._sources[master.id] = source
# First, move free-standing bracket glyphs back to layers to avoid dealing
# with GSLayer transplantation.
for bracket_glyph in [g for g in source.font if ".BRACKET." in g.name]:
base_glyph, threshold = bracket_glyph.name.split(".BRACKET.")
try:
int(threshold)
except ValueError:
raise ValueError(
"Glyph '{}' has malformed bracket layer name. Must be '<glyph "
"name>.BRACKET.<crossover value>'.".format(bracket_glyph)
)
layer_name = bracket_glyph.lib.get(
GLYPHLIB_PREFIX + "_originalLayerName", "[{}]".format(threshold)
)
if layer_name not in source.font.layers:
ufo_layer = source.font.newLayer(layer_name)
else:
ufo_layer = source.font.layers[layer_name]
bracket_glyph_new = ufo_layer.newGlyph(base_glyph)
bracket_glyph_new.copyDataFromGlyph(bracket_glyph)
# Remove all freestanding bracket layer glyphs from all layers.
for layer in source.font.layers:
if bracket_glyph.name in layer:
del layer[bracket_glyph.name]
for layer in _sorted_backgrounds_last(source.font.layers):
self.to_glyphs_layer_lib(layer)
for glyph in layer:
self.to_glyphs_glyph(glyph, layer, master)
self.to_glyphs_features()
self.to_glyphs_groups()
self.to_glyphs_kerning()
# Now that all GSGlyph are built, restore the glyph order
if self.designspace.sources:
first_ufo = self.designspace.sources[0].font
if GLYPH_ORDER_KEY in first_ufo.lib:
glyph_order = first_ufo.lib[GLYPH_ORDER_KEY]
lookup = {name: i for i, name in enumerate(glyph_order)}
self.font.glyphs = sorted(
self.font.glyphs, key=lambda glyph: lookup.get(glyph.name, 1 << 63)
)
# FIXME: (jany) We only do that on the first one. Maybe we should
# merge the various `public.glyphorder` values?
# Restore the layer ordering in each glyph
for glyph in self._font.glyphs:
self.to_glyphs_layer_order(glyph)
self.to_glyphs_family_user_data_from_designspace()
self.to_glyphs_axes()
self.to_glyphs_sources()
self.to_glyphs_instances()
return self._font
|
python
|
{
"resource": ""
}
|
q13598
|
GlyphsBuilder._valid_designspace
|
train
|
def _valid_designspace(self, designspace):
"""Make sure that the user-provided designspace has loaded fonts and
that names are the same as those from the UFOs.
"""
# TODO: (jany) really make a copy to avoid modifying the original object
copy = designspace
# Load only full UFO masters, sparse or "brace" layer sources are assumed
# to point to existing layers within one of the full masters.
for source in (s for s in copy.sources if not s.layerName):
if not hasattr(source, "font") or source.font is None:
if source.path:
# FIXME: (jany) consider not changing the caller's objects
source.font = defcon.Font(source.path)
else:
dirname = os.path.dirname(designspace.path)
ufo_path = os.path.join(dirname, source.filename)
source.font = defcon.Font(ufo_path)
if source.location is None:
source.location = {}
for name in ("familyName", "styleName"):
if getattr(source, name) != getattr(source.font.info, name):
self.logger.warning(
dedent(
"""\
The {name} is different between the UFO and the designspace source:
source filename: {filename}
source {name}: {source_name}
ufo {name}: {ufo_name}
The UFO name will be used.
"""
).format(
name=name,
filename=source.filename,
source_name=getattr(source, name),
ufo_name=getattr(source.font.info, name),
)
)
setattr(source, name, getattr(source.font.info, name))
return copy
|
python
|
{
"resource": ""
}
|
q13599
|
GlyphsBuilder._fake_designspace
|
train
|
def _fake_designspace(self, ufos):
"""Build a fake designspace with the given UFOs as sources, so that all
builder functions can rely on the presence of a designspace.
"""
designspace = designspaceLib.DesignSpaceDocument()
ufo_to_location = defaultdict(dict)
# Make weight and width axis if relevant
for info_key, axis_def in zip(
("openTypeOS2WeightClass", "openTypeOS2WidthClass"),
(WEIGHT_AXIS_DEF, WIDTH_AXIS_DEF),
):
axis = designspace.newAxisDescriptor()
axis.tag = axis_def.tag
axis.name = axis_def.name
mapping = []
for ufo in ufos:
user_loc = getattr(ufo.info, info_key)
if user_loc is not None:
design_loc = class_to_value(axis_def.tag, user_loc)
mapping.append((user_loc, design_loc))
ufo_to_location[ufo][axis_def.name] = design_loc
mapping = sorted(set(mapping))
if len(mapping) > 1:
axis.map = mapping
axis.minimum = min([user_loc for user_loc, _ in mapping])
axis.maximum = max([user_loc for user_loc, _ in mapping])
axis.default = min(
axis.maximum, max(axis.minimum, axis_def.default_user_loc)
)
designspace.addAxis(axis)
for ufo in ufos:
source = designspace.newSourceDescriptor()
source.font = ufo
source.familyName = ufo.info.familyName
source.styleName = ufo.info.styleName
# source.name = '%s %s' % (source.familyName, source.styleName)
source.path = ufo.path
source.location = ufo_to_location[ufo]
designspace.addSource(source)
# UFO-level skip list lib keys are usually ignored, except when we don't have a
# Designspace file to start from. If they exist in the UFOs, promote them to a
# Designspace-level lib key. However, to avoid accidents, expect the list to
# exist in none or be the same in all UFOs.
if any("public.skipExportGlyphs" in ufo.lib for ufo in ufos):
skip_export_glyphs = {
frozenset(ufo.lib.get("public.skipExportGlyphs", [])) for ufo in ufos
}
if len(skip_export_glyphs) == 1:
designspace.lib["public.skipExportGlyphs"] = sorted(
next(iter(skip_export_glyphs))
)
else:
raise ValueError(
"The `public.skipExportGlyphs` list of all UFOs must either not "
"exist or be the same in every UFO."
)
return designspace
|
python
|
{
"resource": ""
}
|
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