swh.datasets.luigi.file_names module#

Luigi tasks for producing the most common names of every content and datasets based on file names#

class swh.datasets.luigi.file_names.PopularContentNames(*args, **kwargs)[source]#

Bases: Task

Creates a CSV file that contains the most popular name(s) of each content

local_graph_path#

Parameter whose value is a path.

In the task definition, use

class MyTask(luigi.Task):
    existing_file_path = luigi.PathParameter(exists=True)
    new_file_path = luigi.PathParameter()

    def run(self):
        # Get data from existing file
        with self.existing_file_path.open("r", encoding="utf-8") as f:
            data = f.read()

        # Output message in new file
        self.new_file_path.parent.mkdir(parents=True, exist_ok=True)
        with self.new_file_path.open("w", encoding="utf-8") as f:
            f.write("hello from a PathParameter => ")
            f.write(data)

At the command line, use

$ luigi --module my_tasks MyTask --existing-file-path <path> --new-file-path <path>

popular_contents_path#

Parameter whose value is a path.

In the task definition, use

class MyTask(luigi.Task):
    existing_file_path = luigi.PathParameter(exists=True)
    new_file_path = luigi.PathParameter()

    def run(self):
        # Get data from existing file
        with self.existing_file_path.open("r", encoding="utf-8") as f:
            data = f.read()

        # Output message in new file
        self.new_file_path.parent.mkdir(parents=True, exist_ok=True)
        with self.new_file_path.open("w", encoding="utf-8") as f:
            f.write("hello from a PathParameter => ")
            f.write(data)

At the command line, use

$ luigi --module my_tasks MyTask --existing-file-path <path> --new-file-path <path>

graph_name#: Parameter whose value is a str.

max_results_per_content#: Parameter whose value is an int.

popularity_threshold#: Parameter whose value is an int.

property resources#: Return the estimated RAM use of this task.

requires() → List[Task][source]#: Returns an instance of LocalGraph.

output() → LocalTarget[source]#: .csv.zst file that contains the topological order.

run() → None[source]#: Runs popular-content-names from tools/file_names

class swh.datasets.luigi.file_names.PopularContentPaths(*args, **kwargs)[source]#

Bases: Task

Creates a CSV file that contains the most popular path of each content/directory given as input

local_graph_path#

Parameter whose value is a path.

In the task definition, use

class MyTask(luigi.Task):
    existing_file_path = luigi.PathParameter(exists=True)
    new_file_path = luigi.PathParameter()

    def run(self):
        # Get data from existing file
        with self.existing_file_path.open("r", encoding="utf-8") as f:
            data = f.read()

        # Output message in new file
        self.new_file_path.parent.mkdir(parents=True, exist_ok=True)
        with self.new_file_path.open("w", encoding="utf-8") as f:
            f.write("hello from a PathParameter => ")
            f.write(data)

At the command line, use

$ luigi --module my_tasks MyTask --existing-file-path <path> --new-file-path <path>

popular_contents_path#

Parameter whose value is a path.

In the task definition, use

class MyTask(luigi.Task):
    existing_file_path = luigi.PathParameter(exists=True)
    new_file_path = luigi.PathParameter()

    def run(self):
        # Get data from existing file
        with self.existing_file_path.open("r", encoding="utf-8") as f:
            data = f.read()

        # Output message in new file
        self.new_file_path.parent.mkdir(parents=True, exist_ok=True)
        with self.new_file_path.open("w", encoding="utf-8") as f:
            f.write("hello from a PathParameter => ")
            f.write(data)

At the command line, use

$ luigi --module my_tasks MyTask --existing-file-path <path> --new-file-path <path>

graph_name#: Parameter whose value is a str.

input_swhids#

Parameter whose value is a path.

In the task definition, use

class MyTask(luigi.Task):
    existing_file_path = luigi.PathParameter(exists=True)
    new_file_path = luigi.PathParameter()

    def run(self):
        # Get data from existing file
        with self.existing_file_path.open("r", encoding="utf-8") as f:
            data = f.read()

        # Output message in new file
        self.new_file_path.parent.mkdir(parents=True, exist_ok=True)
        with self.new_file_path.open("w", encoding="utf-8") as f:
            f.write("hello from a PathParameter => ")
            f.write(data)

At the command line, use

$ luigi --module my_tasks MyTask --existing-file-path <path> --new-file-path <path>

max_depth#: Parameter whose value is an int.

property resources#: Return the estimated RAM use of this task.

requires() → List[Task][source]#: Returns an instance of LocalGraph.

output() → LocalTarget[source]#: .csv.zst file that contains the topological order.

run() → None[source]#: Runs org.softwareheritage.graph.utils.PopularContentPaths and compresses

class swh.datasets.luigi.file_names.PopularContentNamesOrcToS3(*args, **kwargs)[source]#

Bases: _ParquetToS3ToAthenaTask

Reads the CSV from PopularContents, converts it to ORC, upload the ORC to S3, and create an Athena table for it.

popular_contents_path#

Parameter whose value is a path.

In the task definition, use

class MyTask(luigi.Task):
    existing_file_path = luigi.PathParameter(exists=True)
    new_file_path = luigi.PathParameter()

    def run(self):
        # Get data from existing file
        with self.existing_file_path.open("r", encoding="utf-8") as f:
            data = f.read()

        # Output message in new file
        self.new_file_path.parent.mkdir(parents=True, exist_ok=True)
        with self.new_file_path.open("w", encoding="utf-8") as f:
            f.write("hello from a PathParameter => ")
            f.write(data)

At the command line, use

$ luigi --module my_tasks MyTask --existing-file-path <path> --new-file-path <path>

dataset_name#: Parameter whose value is a str.

s3_athena_output_location#: A parameter that strip trailing slashes

requires() → PopularContentNames[source]#: Returns corresponding PopularContentNames instance

class swh.datasets.luigi.file_names.ListFilesByName(*args, **kwargs)[source]#

Bases: Task

From every refs/heads/master, refs/heads/main, or HEAD branch in any snapshot, browse the whole directory tree looking for files named <filename>, and lists them to stdout.

local_graph_path#

Parameter whose value is a path.

In the task definition, use

class MyTask(luigi.Task):
    existing_file_path = luigi.PathParameter(exists=True)
    new_file_path = luigi.PathParameter()

    def run(self):
        # Get data from existing file
        with self.existing_file_path.open("r", encoding="utf-8") as f:
            data = f.read()

        # Output message in new file
        self.new_file_path.parent.mkdir(parents=True, exist_ok=True)
        with self.new_file_path.open("w", encoding="utf-8") as f:
            f.write("hello from a PathParameter => ")
            f.write(data)

At the command line, use

$ luigi --module my_tasks MyTask --existing-file-path <path> --new-file-path <path>

graph_name#: Parameter whose value is a str.

output_path#

Parameter whose value is a path.

In the task definition, use

class MyTask(luigi.Task):
    existing_file_path = luigi.PathParameter(exists=True)
    new_file_path = luigi.PathParameter()

    def run(self):
        # Get data from existing file
        with self.existing_file_path.open("r", encoding="utf-8") as f:
            data = f.read()

        # Output message in new file
        self.new_file_path.parent.mkdir(parents=True, exist_ok=True)
        with self.new_file_path.open("w", encoding="utf-8") as f:
            f.write("hello from a PathParameter => ")
            f.write(data)

At the command line, use

$ luigi --module my_tasks MyTask --existing-file-path <path> --new-file-path <path>

file_name#: Parameter whose value is a str.

property resources#: Return the estimated RAM use of this task.

requires() → List[Task][source]#: Returns an instance of LocalGraph.

output() → LocalTarget[source]#: Directory of .csv.zst files containing the list of file occurrences with that name.

run() → None[source]#: Runs org.softwareheritage.graph.utils.PopularContentNames and compresses