chore: add pyproject

plesna/compute/consume_flux.py

@@ -3,6 +3,6 @@ from plesna.models.flux import Flux, FluxMetaData
 
 def consume_flux(flux: Flux) -> FluxMetaData:
     metadata = flux.transformation.function(
-        sources=flux.sources, targets=flux.targets, **flux.transformation.extra_kwrds
+        sources=flux.sources_dict, targets=flux.targets_dict, **flux.transformation.extra_kwrds
     )
     return FluxMetaData(data=metadata)

plesna/dataplatform.py

@@ -1,5 +1,11 @@
-from plesna.datastore.datacatalogue import DataCatalogue
+from collections.abc import Callable
+from plesna.compute.consume_flux import consume_flux
+from plesna.graph.graph import Graph
 from plesna.graph.graph_set import GraphSet
+from plesna.models.flux import Flux, FluxMetaData
+from plesna.models.graphs import Node
+from plesna.models.libs.flux_graph import flux_to_edgeonset
+from plesna.storage.data_repository.data_repository import DataRepository
 
 
 class DataPlateformError(Exception):
@@ -8,20 +14,80 @@ class DataPlateformError(Exception):
 
 class DataPlateform:
     def __init__(self):
-        self._graphset = GraphSet()
         self._metadata_engine = ""
-        self._transformations = {}
-        self._datacatalogues = {}
+        self._fluxes = {}
+        self._repositories = {}
 
-    def add_datacatalague(self, name: str, datacatalogue: DataCatalogue):
-        if name in self._datacatalogues:
-            raise DataPlateformError("The datacatalogue {name} already exists")
+    def add_repository(self, repository: DataRepository) -> str:
+        if repository.id in self._repositories:
+            raise DataPlateformError("The repository {repository.id} already exists")
 
-        self._datacatalogues[name] = datacatalogue
+        self._repositories[repository.id] = repository
+        return repository.id
 
     @property
-    def datacatalogues(self):
-        return list(self._datacatalogues)
+    def repositories(self) -> list[str]:
+        return list(self._repositories)
 
-    def get_datacatalogue(self, name: str):
-        return self._datacatalogues[name]
+    def repository(self, id: str) -> DataRepository:
+        return self._repositories[id]
+
+    def is_valid_flux(self, flux: Flux) -> bool:
+        return True
+
+    def add_flux(self, flux: Flux) -> str:
+        if flux.id in self._fluxes:
+            raise DataPlateformError("The flux {flux} already exists")
+
+        assert self.is_valid_flux(flux)
+        self._fluxes[flux.id] = flux
+        return flux.id
+
+    @property
+    def fluxes(self) -> list[str]:
+        return list(self._fluxes)
+
+    def flux(self, flux_id: str) -> Flux:
+        return self._fluxes[flux_id]
+
+    def execute_flux(self, flux_id: str) -> FluxMetaData:
+        if flux_id not in self._fluxes:
+            raise DataPlateformError("The flux {flux_id} is not registered")
+        return consume_flux(self._fluxes[flux_id])
+
+    def graphset(
+        self,
+        name_flux: Callable = lambda flux: flux.id,
+        meta_flux: Callable = lambda _: {},
+        name_table: Callable = lambda table: table.id,
+        meta_table: Callable = lambda _: {},
+    ) -> GraphSet:
+        graphset = GraphSet()
+        for flux in self._fluxes.values():
+            edge = flux_to_edgeonset(flux, name_flux, meta_flux, name_table, meta_table)
+            graphset.append(edge)
+
+        return graphset
+
+    def graph(
+        self,
+        name_flux: Callable = lambda flux: flux.id,
+        meta_flux: Callable = lambda _: {},
+        name_table: Callable = lambda table: table.id,
+        meta_table: Callable = lambda _: {},
+    ) -> Graph:
+        """Get the graph of fluxes and tables
+
+        :param name_flux: function on flux to name the edge
+        :param meta_flux: function on flux to attribute metadata to edge
+        :param name_table: function on table to name nodes
+        :param meta_table: function on flux to attribute metadata to nodes
+
+        """
+        graph = self.graphset(name_flux, meta_flux, name_table, meta_table).to_graph()
+        for repo in self._repositories.values():
+            for schema in repo.schemas():
+                for table in repo.tables(schema):
+                    t = repo.table(table)
+                    graph.add_node(Node(name=name_table(t), metadata=meta_table(t)))
+        return graph

plesna/datastore/datastore.py

@@ -1,3 +0,0 @@
-class DataStore:
-    def __init__(self, name):
-        self._name

plesna/datastore/fake_datacatalogue.py

@@ -1,81 +0,0 @@
-from pathlib import Path
-
-from pydantic import BaseModel, computed_field
-
-from plesna.models.storage import Schema, Table
-
-from .datacatalogue import DataCatalogue
-
-
-class FakeSchema(BaseModel):
-    name: str
-
-    @computed_field
-    @property
-    def ref(self) -> Schema:
-        return Schema(
-            id=str(self.name),
-            value=str(self.name),
-        )
-
-
-class FakeTable(BaseModel):
-    name: str
-    data: dict[str, list]
-
-    @computed_field
-    @property
-    def ref(self) -> Table:
-        return Table(
-            id=str(self.name),
-            value=str(self.name),
-        )
-
-
-class FakeDataCatalogue(DataCatalogue):
-    """DataCatalogue based on dictionnaries"""
-
-    def __init__(self, name: str):
-        self.name = name
-
-    def ls(
-        self, dir="", only_files=False, only_directories=False, recursive=False
-    ) -> list[str]:
-        dirpath = self._basepath / dir
-
-        if only_files:
-            return [
-                str(f.relative_to(dirpath))
-                for f in dirpath.iterdir()
-                if not f.is_dir() and not str(f).startswith(".")
-            ]
-
-        if only_directories:
-            if recursive:
-                return [
-                    str(f[0].relative_to(dirpath))
-                    for f in dirpath.walk()
-                    if not str(f).startswith(".")
-                ]
-
-            return [
-                str(f.relative_to(dirpath))
-                for f in dirpath.iterdir()
-                if f.is_dir() and not str(f).startswith(".")
-            ]
-
-        return [
-            str(f.relative_to(dirpath))
-            for f in dirpath.iterdir()
-            if not str(f).startswith(".")
-        ]
-
-    def schemas(self) -> dict[str, FSSchema]:
-        """List schemas (sub directories within basepath)"""
-        subdirectories = self.ls("", only_directories=True, recursive=True)
-        return {str(path): FSSchema(path=path) for path in subdirectories}
-
-    def tables(self, schema_id=".") -> dict[str, FSTable]:
-        """List table in schema (which are files in the directory)"""
-        schema_path = schema_id
-        return {path: FSTable(path=path) for path in self.ls(schema_path, only_files=True)}

plesna/datastore/fs_datacatalogue.py

@@ -1,91 +0,0 @@
-from pathlib import Path
-
-from pydantic import BaseModel, computed_field
-
-from plesna.models.storage import Schema, Table
-
-from .datacatalogue import DataCatalogue
-
-
-class FSTable(BaseModel):
-    path: Path
-
-    @computed_field
-    @property
-    def ref(self) -> Table:
-        return Table(
-            id=str(self.path),
-            value=str(self.path),
-        )
-
-
-class FSSchema(BaseModel):
-    path: Path
-    tables: list[str]
-
-    @computed_field
-    @property
-    def ref(self) -> Schema:
-        return Schema(
-            id=str(self.path),
-            value=str(self.path),
-        )
-
-
-
-class FSDataCatalogue(DataCatalogue):
-    """DataCatalogue based on files tree structure"""
-
-    def __init__(self, name: str, basepath: str = "."):
-        self._basepath = Path(basepath)
-        self.name = name
-
-        assert self._basepath.exists()
-
-    def ls(
-        self, dir="", only_files=False, only_directories=False, recursive=False
-    ) -> list[str]:
-        dirpath = self._basepath / dir
-
-        if only_files:
-            return [
-                str(f.relative_to(dirpath))
-                for f in dirpath.iterdir()
-                if not f.is_dir() and not str(f).startswith(".")
-            ]
-
-        if only_directories:
-            if recursive:
-                return [
-                    str(f[0].relative_to(dirpath))
-                    for f in dirpath.walk()
-                    if not str(f).startswith(".")
-                ]
-
-            return [
-                str(f.relative_to(dirpath))
-                for f in dirpath.iterdir()
-                if f.is_dir() and not str(f).startswith(".")
-            ]
-
-        return [
-            str(f.relative_to(dirpath))
-            for f in dirpath.iterdir()
-            if not str(f).startswith(".")
-        ]
-
-    @property
-    def schemas(self) -> list[str]:
-        """List schemas (sub directories within basepath)"""
-        subdirectories = self.ls("", only_directories=True, recursive=True)
-        return [str(d) for d in subdirectories]
-
-    def schema(self, schema: str) -> FSSchema:
-        """List schemas (sub directories within basepath)"""
-        tables = self.ls(schema, only_files=True)
-        return FSSchema(path=Path(schema), tables=tables)
-
-    def table(self, schema: str, table:str) -> FSTable:
-        """List table in schema (which are files in the directory)"""
-        schema_path = schema_id
-        return {path: FSTable(path=path) for path in self.ls(schema_path, only_files=True)}

plesna/graph/graph.py

@@ -1,28 +1,13 @@
-from functools import reduce
-from typing import Callable
-
+from typing import Set
 from pydantic import BaseModel
-
-
-class Node(BaseModel):
-    name: str
-    infos: dict = {}
-
-    def __hash__(self):
-        return hash(self.name)
-
-
-class Edge(BaseModel):
-    arrow_name: str
-    source: Node
-    target: Node
-    edge_kwrds: dict = {}
+from functools import reduce
+from plesna.models.graphs import Node, Edge
 
 
 class Graph:
     def __init__(self, nodes: list[Node] = [], edges: list[Edge] = []):
-        self._edges = []
-        self._nodes = set()
+        self._edges: list[Edge] = []
+        self._nodes: Set[Node] = set()
         self.add_edges(edges)
         self.add_nodes(nodes)
 

plesna/graph/graph_set.py

@@ -1,21 +1,7 @@
-from typing import Callable
-
-from pydantic import BaseModel
-
-
-class Node(BaseModel):
-    name: str
-    infos: dict = {}
-
-    def __hash__(self):
-        return hash(self.name)
-
-
-class EdgeOnSet(BaseModel):
-    arrow: Callable
-    sources: dict[str, Node]
-    targets: dict[str, Node]
-    edge_kwrds: dict = {}
+from typing import Set
+from plesna.graph.graph import Graph
+from plesna.models.graphs import Edge, EdgeOnSet
+from itertools import product
 
 
 class GraphSet:
@@ -25,12 +11,29 @@ class GraphSet:
 
     def append(self, edge: EdgeOnSet):
         self._edges.append(edge)
-        self._node_sets.add(frozenset(edge.sources.values()))
-        self._node_sets.add(frozenset(edge.targets.values()))
+        self._node_sets.add(frozenset(edge.sources))
+        self._node_sets.add(frozenset(edge.targets))
 
     @property
-    def node_sets(self):
+    def edges(self) -> Set[EdgeOnSet]:
+        return self._edges
+
+    @property
+    def node_sets(self) -> Set[frozenset]:
         return self._node_sets
 
-    def is_valid_dag(self):
-        pass
+    def to_graph(self) -> Graph:
+        graph = Graph()
+        for node_set in self.node_sets:
+            graph.add_nodes(node_set)
+        for edge in self._edges:
+            flatten_edge = [
+                Edge(arrow=edge.arrow, source=s, target=t, metadata=edge.metadata)
+                for (s, t) in product(edge.sources, edge.targets)
+            ]
+            graph.add_edges(flatten_edge)
+
+        return graph
+
+    def is_valid_dag(self) -> bool:
+        return self.to_graph().is_dag()

plesna/libs/string_tools.py

@@ -0,0 +1,18 @@
+import re
+
+
+class StringToolsError(ValueError):
+    pass
+
+
+def extract_values_from_pattern(pattern, string):
+    regex = re.sub(r"{(.+?)}", r"(?P<_\1>.+)", pattern)
+
+    search = re.search(regex, string)
+    if search:
+        values = list(search.groups())
+        keys = re.findall(r"{(.+?)}", pattern)
+        _dict = dict(zip(keys, values))
+        return _dict
+
+    raise StringToolsError(f"Can't parse '{string}' with the pattern '{pattern}'")

plesna/models/flux.py

@@ -1,14 +1,48 @@
-from pydantic import BaseModel
+from collections.abc import Callable
+from pydantic import BaseModel, computed_field
 
 from plesna.models.storage import Table
-from plesna.models.transformation import Transformation
+
+
+class Transformation(BaseModel):
+    """
+    The function have to have at least 2 arguments: sources and targets
+    Other arguments will came throught extra_kwrds
+
+    The function will have to return metadata as dict
+    """
+
+    function: Callable
+    extra_kwrds: dict = {}
 
 
 class Flux(BaseModel):
-    sources: dict[str, Table]
-    targets: dict[str, Table]
+    id: str
+    name: str
+    sources: list[Table]
+    targets: list[Table]
     transformation: Transformation
 
+    @computed_field
+    @property
+    def sources_dict(self) -> dict[str, Table]:
+        return {s.id: s for s in self.sources}
+
+    @computed_field
+    @property
+    def sources_id(self) -> dict[str, Table]:
+        return [s.id for s in self.sources]
+
+    @computed_field
+    @property
+    def targets_id(self) -> dict[str, Table]:
+        return [s.id for s in self.targets]
+
+    @computed_field
+    @property
+    def targets_dict(self) -> dict[str, Table]:
+        return {s.id: s for s in self.targets}
+
 
 class FluxMetaData(BaseModel):
     data: dict

plesna/models/graphs.py

@@ -0,0 +1,23 @@
+from pydantic import BaseModel
+
+
+class Node(BaseModel):
+    name: str
+    metadata: dict = {}
+
+    def __hash__(self):
+        return hash(self.name)
+
+
+class Edge(BaseModel):
+    arrow: str
+    source: Node
+    target: Node
+    metadata: dict = {}
+
+
+class EdgeOnSet(BaseModel):
+    arrow: str
+    sources: list[Node]
+    targets: list[Node]
+    metadata: dict = {}

plesna/models/libs/flux_graph.py

@@ -0,0 +1,29 @@
+from collections.abc import Callable
+from plesna.models.flux import Flux
+from plesna.models.graphs import EdgeOnSet, Node
+
+
+def flux_to_edgeonset(
+    flux: Flux,
+    name_flux: Callable = lambda flux: flux.id,
+    meta_flux: Callable = lambda _: {},
+    name_table: Callable = lambda table: table.id,
+    meta_table: Callable = lambda _: {},
+) -> EdgeOnSet:
+    """Convert a flux to an EdgeOnSet
+
+    :param flux: the flux
+    :name_flux: function on flux which returns the name of the arrow from flux
+    :meta_flux: function on flux which returns a dict to store in metadata field
+    :name_table: function on table which returns the name of node
+    :meta_table: function on table which returns metadata of node
+
+    """
+    sources = [Node(name=name_table(s), metadata=meta_table(s)) for s in flux.sources]
+    targets = [Node(name=name_table(s), metadata=meta_table(s)) for s in flux.targets]
+    return EdgeOnSet(
+        arrow=name_flux(flux),
+        sources=sources,
+        targets=targets,
+        metadata=meta_flux(flux),
+    )

plesna/models/storage.py

@@ -2,24 +2,60 @@ from pydantic import BaseModel
 
 
 class Schema(BaseModel):
-    """Logical agregation for Table
+    """Where multiple tables are stored
 
     id: uniq identifier for the schema
-    value: string which describe where to find the schema in the storage system
-
+    repo_id: id of the repo where the schema belong to
+    name: name of the schema
+    value: string which describe where to find the schema in the repository
     """
 
     id: str
+    repo_id: str
+    name: str
     value: str
+    tables: list[str] = []
 
 
 class Table(BaseModel):
-    """Place where data are stored
+    """Place where same structured data are stored
 
     id: uniq identifier for the table
+    repo_id: id of the repo where the table belong to
+    schema_id: id of the schema where table belong to
+    name: the name of the table
     value: string which describe where to find the table in the storage system
 
+    partitions: list of partitions
+    datas: list of string to access data
+
     """
 
     id: str
+    repo_id: str
+    schema_id: str
+    name: str
+    value: str
+    datas: list[str]
+    partitions: list[str] = []
+    metadata: dict = {}
+
+
+class Partition(BaseModel):
+    """Place where data are stored
+
+    id: uniq identifier for the table
+    repo_id: id of the repo where the table belong to
+    schema_id: id of the schema where table belong to
+    table_id: id of the schema where table belong to
+    name: the name of the partition
+    value: string which describe where to find the partition in the storage system
+
+    """
+
+    id: str
+    repo_id: str
+    schema_id: str
+    table_id: str
+    name: str
     value: str

plesna/models/transformation.py

@@ -1,15 +0,0 @@
-from collections.abc import Callable
-
-from pydantic import BaseModel
-
-
-class Transformation(BaseModel):
-    """
-    The function have to have at least 2 arguments: sources and targets
-    Other arguments will came throught extra_kwrds
-
-    The function will have to return metadata as dict
-    """
-
-    function: Callable
-    extra_kwrds: dict = {}

plesna/storage/data_repository/data_repository.py

@@ -0,0 +1,37 @@
+import abc
+
+from plesna.models.storage import Partition, Schema, Table
+
+
+class DataRepository:
+    def __init__(self, id: str, name: str):
+        self._id = id
+        self._name = name
+
+    @property
+    def id(self) -> str:
+        return self._id
+
+    @property
+    def name(self) -> str:
+        return self._name
+
+    @abc.abstractmethod
+    def schemas(self) -> list[str]:
+        """List schema's ids"""
+        raise NotImplementedError
+
+    @abc.abstractmethod
+    def schema(self, schema_id: str) -> Schema:
+        """Get the schema properties"""
+        raise NotImplementedError
+
+    @abc.abstractmethod
+    def tables(self, schema_id: str) -> list[str]:
+        """List table's name in schema (the id)"""
+        raise NotImplementedError
+
+    @abc.abstractmethod
+    def table(self, table_id: str) -> Table:
+        """Get the table properties (the id)"""
+        raise NotImplementedError

plesna/storage/data_repository/fs_data_repository.py

@@ -0,0 +1,197 @@
+from pathlib import Path
+
+from pydantic import BaseModel, computed_field
+
+from plesna.libs.string_tools import extract_values_from_pattern
+from plesna.models.storage import Schema, Table
+from plesna.storage.data_repository.data_repository import DataRepository
+
+
+class FSTable(BaseModel):
+    name: str
+    repo_id: str
+    schema_id: str
+    id: str
+    path: Path
+    is_partitionned: bool
+    partitions: list[str] = []
+
+    @computed_field
+    @property
+    def ref(self) -> Table:
+        if self.is_partitionned:
+            datas = [str(self.path.absolute() / p) for p in self.partitions]
+        else:
+            datas = [str(self.path.absolute())]
+
+        return Table(
+            id=self.id,
+            repo_id=self.repo_id,
+            schema_id=self.schema_id,
+            name=self.name,
+            value=str(self.path.absolute()),
+            partitions=self.partitions,
+            datas=datas,
+        )
+
+
+class FSSchema(BaseModel):
+    name: str
+    repo_id: str
+    id: str
+    path: Path
+    tables: list[str]
+
+    @computed_field
+    @property
+    def ref(self) -> Schema:
+        return Schema(
+            id=self.id,
+            repo_id=self.repo_id,
+            name=self.name,
+            value=str(self.path.absolute()),
+            tables=self.tables,
+        )
+
+
+class FSRepositoryError(ValueError):
+    pass
+
+
+class FSDataRepository(DataRepository):
+    """Data Repository based on files tree structure
+
+    - first level: schemas
+    - second level: tables
+    - third level: partition (actual datas)
+
+    """
+
+    ID_FMT = {
+        "schema": "{repo_id}-{schema_name}",
+        "table": "{schema_id}-{table_name}",
+    }
+
+    def __init__(self, id: str, name: str, basepath: str):
+        super().__init__(id, name)
+
+        self._basepath = Path(basepath)
+        assert self._basepath.exists()
+
+    def ls(self, dir="", only_files=False, only_directories=False, recursive=False) -> list[str]:
+        """List files in dir
+
+        :param dir: relative path from self._basepath
+        :param only_files: if true return only files
+        :param only_directories: if true return only directories
+        :param recursive: list content recursively (only for)
+        :return: list of string describing path from self._basepath / dir
+        """
+        dirpath = self._basepath / dir
+
+        if recursive:
+            paths = dirpath.rglob("*")
+        else:
+            paths = dirpath.iterdir()
+
+        if only_files:
+            return [
+                str(f.relative_to(dirpath))
+                for f in paths
+                if not f.is_dir() and not str(f).startswith(".")
+            ]
+        if only_directories:
+            return [
+                str(f.relative_to(dirpath))
+                for f in paths
+                if f.is_dir() and not str(f).startswith(".")
+            ]
+
+        return [str(f.relative_to(dirpath)) for f in paths if not str(f).startswith(".")]
+
+    def parse_id(self, string: str, id_type: str) -> dict:
+        if id_type not in self.ID_FMT:
+            raise FSRepositoryError(
+                "Wrong id_type. Gots {id_type} needs to be one of {self.ID_FMT.values}"
+            )
+        parsed = extract_values_from_pattern(self.ID_FMT[id_type], string)
+        if not parsed:
+            raise FSRepositoryError(
+                f"Wrong format for {id_type}. Got {string} need {self.ID_FMT['id_type']}"
+            )
+        return parsed
+
+    def schemas(self) -> list[str]:
+        """List schemas (sub directories within basepath)"""
+        subdirectories = self.ls("", only_directories=True)
+        return [
+            self.ID_FMT["schema"].format(repo_id=self.id, schema_name=d) for d in subdirectories
+        ]
+
+    def _schema(self, schema_id: str) -> FSSchema:
+        """List schemas (sub directories within basepath)"""
+        parsed = self.parse_id(schema_id, "schema")
+
+        repo_id = parsed["repo_id"]
+        schema_name = parsed["schema_name"]
+        schema_path = self._basepath / schema_name
+
+        if repo_id != self.id:
+            raise FSRepositoryError("Trying to get schema that don't belong in this repository")
+
+        tables = self.tables(schema_id)
+        return FSSchema(
+            name=schema_name,
+            id=schema_id,
+            repo_id=self.id,
+            schema_id=schema_id,
+            path=schema_path,
+            tables=tables,
+        )
+
+    def schema(self, schema_id: str) -> Schema:
+        return self._schema(schema_id).ref
+
+    def _tables(self, schema_id: str) -> list[str]:
+        parsed = self.parse_id(schema_id, "schema")
+        tables = self.ls(parsed["schema_name"])
+        return [self.ID_FMT["table"].format(table_name=t, schema_id=schema_id) for t in tables]
+
+    def tables(self, schema_id: str = "") -> list[str]:
+        if schema_id:
+            return self._tables(schema_id)
+
+        tables = []
+        for schema in self.schemas():
+            tables += self._tables(schema)
+        return tables
+
+    def _table(self, table_id: str) -> FSTable:
+        """Get infos on the table"""
+        parsed = self.parse_id(table_id, "table")
+        schema = self._schema(parsed["schema_id"])
+
+        if not schema.path.exists():
+            raise FSRepositoryError(f"The schema {schema.id} does not exists.")
+
+        table_subpath = f"{schema.name}/{parsed['table_name']}"
+        table_path = self._basepath / table_subpath
+
+        is_partitionned = table_path.is_dir()
+        if is_partitionned:
+            partitions = self.ls(table_subpath, only_files=True)
+        else:
+            partitions = []
+
+        return FSTable(
+            name=parsed["table_name"],
+            id=table_id,
+            repo_id=self.id,
+            schema_id=schema.id,
+            path=table_path,
+            is_partitionned=is_partitionned,
+            partitions=partitions,
+        )
+
+    def table(self, table_id: str) -> Table:
+        return self._table(table_id).ref

plesna/storage/datacatalogue.py

@@ -1,6 +1,6 @@
 import abc
 
-from plesna.models.storage import Schema, Table
+from plesna.models.storage import Schema
 
 
 class DataCatalogue:
@@ -22,13 +22,3 @@ class DataCatalogue:
     def tables(self, schema: str) -> list[str]:
         """List table's name in schema"""
         raise NotImplementedError
-
-    @abc.abstractmethod
-    def table(self, schema:str, table:str) -> Table:
-        """Get the table properties"""
-        raise NotImplementedError
-
-    @abc.abstractmethod
-    def infos(self, table: str, schema: str) -> dict[str, str]:
-        """Get infos about the table"""
-        raise NotImplementedError

plesna/storage/metadata_repository/fs_metadata_repository.py

@@ -0,0 +1,132 @@
+from pathlib import Path
+from datetime import datetime
+import csv
+import json
+from typing import Iterable
+
+from plesna.libs.string_tools import StringToolsError, extract_values_from_pattern
+from plesna.storage.metadata_repository.metadata_repository import (
+    ExecutionLog,
+    MetaDataRepository,
+    ModificationLog,
+)
+
+
+class FSMetaDataRepositoryError(ValueError):
+    pass
+
+
+class FSMetaDataRepository(MetaDataRepository):
+    """MetaData Repository based on csv files
+
+    Files organisations: executions and modifications are stored in csv file according to ***_FILEMODEL
+
+    """
+
+    OBJECTS = {
+        "flux": {"filemodel": "{id}_execution.csv", "logmodel": ExecutionLog},
+        "table": {"filemodel": "{id}_execution.csv", "logmodel": ModificationLog},
+    }
+
+    def __init__(self, basepath: str):
+        super().__init__()
+
+        self._basepath = Path(basepath)
+        assert self._basepath.exists()
+
+    def get_things(self, what: str) -> list[str]:
+        """List all ids for 'what'"""
+        whats = []
+        for filepath in self._basepath.iterdir():
+            try:
+                founded = extract_values_from_pattern(
+                    self.OBJECTS[what]["filemodel"], filepath.name
+                )
+            except StringToolsError:
+                pass
+            else:
+                whats.append(founded["id"])
+        return whats
+
+    def fluxes(self) -> list[str]:
+        """List fluxes's ids"""
+        return self.get_things(what="flux")
+
+    def tables(
+        self,
+    ) -> list[str]:
+        """List all table's ids"""
+        return self.get_things(what="table")
+
+    def _add_thing(self, what: str, id: str) -> str:
+        """Add the new things 'what'"""
+        filepath = self._basepath / self.OBJECTS[what]["filemodel"].format(id=id)
+        filepath.touch()
+        with open(filepath, "a") as csvfile:
+            writer = csv.DictWriter(
+                csvfile, fieldnames=self.OBJECTS[what]["logmodel"].model_fields.keys()
+            )
+            writer.writeheader()
+        return id
+
+    def add_flux(self, flux_id: str) -> str:
+        """Get the flux metadata"""
+        return self._add_thing(what="flux", id=flux_id)
+
+    def add_table(self, table_id: str) -> str:
+        """Get the table metadata"""
+        return self._add_thing(what="table", id=table_id)
+
+    def _register_things_event(self, what: str, id: str, dt: datetime, event: dict) -> ExecutionLog:
+        filepath = self._basepath / self.OBJECTS[what]["filemodel"].format(id=id)
+        if not filepath.exists:
+            raise FSMetaDataRepositoryError(f"The {what} {id} hasn't been added yet.")
+
+        metadata_ = self.OBJECTS[what]["logmodel"](datetime=dt, **event)
+
+        with open(filepath, "a") as csvfile:
+            writer = csv.DictWriter(
+                csvfile, fieldnames=self.OBJECTS[what]["logmodel"].model_fields.keys()
+            )
+            writer.writerow(metadata_.to_flat_dict())
+
+        return metadata_
+
+    def register_flux_execution(self, flux_id: str, dt: datetime, output: dict) -> ExecutionLog:
+        """Get the flux metadata"""
+        return self._register_things_event("flux", flux_id, dt, {"output": {"data": output}})
+
+    def register_table_modification(self, table_id: str, dt: datetime, flux_id: str) -> str:
+        """Get the table metadata"""
+        return self._register_things_event("table", table_id, dt, {"flux_id": flux_id})
+
+    def _get_all_log(self, what: str, id: str) -> Iterable[dict]:
+        """Generate log dict from history"""
+        filepath = self._basepath / self.OBJECTS[what]["filemodel"].format(id=id)
+        if not filepath.exists:
+            raise FSMetaDataRepositoryError(f"The {what} {id} hasn't been added yet.")
+        with open(filepath, "r") as csvfile:
+            reader = csv.DictReader(csvfile)
+            for row in reader:
+                yield row
+
+    def flux_logs(self, flux_id: str) -> list[ExecutionLog]:
+        """Get all flux logs"""
+        logs = []
+        for logline in self._get_all_log("flux", flux_id):
+            logline["output"] = json.loads(logline["output"])
+            logs.append(self.OBJECTS["flux"]["logmodel"](**logline))
+
+        return logs
+
+    def flux(self, flux_id: str) -> ExecutionLog:
+        """Get the last flux log"""
+        return max(self.flux_logs(flux_id), key=lambda l: l.datetime)
+
+    def table_logs(self, table_id: str) -> list[ModificationLog]:
+        """Get all table's modification metadatas"""
+        return [ModificationLog(**log) for log in self._get_all_log("table", table_id)]
+
+    def table(self, table_id: str) -> ModificationLog:
+        """Get the last table's modification metadatas"""
+        return max(self.table_logs(table_id), key=lambda l: l.datetime)

plesna/storage/metadata_repository/metadata_repository.py

@@ -0,0 +1,81 @@
+import abc
+from datetime import datetime
+
+from pydantic import BaseModel
+
+from plesna.models.flux import FluxMetaData
+
+
+class ModificationLog(BaseModel):
+    datetime: datetime
+    flux_id: str
+
+    def to_flat_dict(self):
+        return {"datetime": self.datetime.isoformat(), "flux_id": self.flux_id}
+
+
+class ExecutionLog(BaseModel):
+    datetime: datetime
+    output: FluxMetaData
+
+    def to_flat_dict(self):
+        return {"datetime": self.datetime.isoformat(), "output": self.output.model_dump_json()}
+
+
+class MetaDataRepository:
+    """Object that stores metadata about flux, schema, tables"""
+
+    def __init__(self):
+        pass
+
+    @abc.abstractmethod
+    def fluxes(self) -> list[str]:
+        """List fluxes's ids"""
+        raise NotImplementedError
+
+    @abc.abstractmethod
+    def add_flux(self, flux_id: str) -> str:
+        """Get the flux metadata"""
+        raise NotImplementedError
+
+    @abc.abstractmethod
+    def register_flux_execution(self, flux_id: str, dt: datetime, metadata: dict) -> str:
+        """Get the flux metadata"""
+        raise NotImplementedError
+
+    @abc.abstractmethod
+    def flux(self, schema_id: str) -> ExecutionLog:
+        """Get the flux last execution metadata"""
+        raise NotImplementedError
+
+    @abc.abstractmethod
+    def flux_logs(self, schema_id: str) -> list[ExecutionLog]:
+        """Get all the flux execution metadata"""
+        raise NotImplementedError
+
+    @abc.abstractmethod
+    def tables(
+        self,
+    ) -> list[str]:
+        """List all table's ids"""
+        raise NotImplementedError
+
+    @abc.abstractmethod
+    def add_table(self, table_id: str) -> str:
+        """Get the table metadata"""
+        raise NotImplementedError
+
+    @abc.abstractmethod
+    def register_table_modification(self, table_id: str, dt: datetime, metadata: dict) -> str:
+        """Get the table metadata"""
+        raise NotImplementedError
+
+    @abc.abstractmethod
+    def table(self, table_id: str) -> ModificationLog:
+        """Get the last table's modification metadatas"""
+        raise NotImplementedError
+
+    @abc.abstractmethod
+    def table_logs(self, table_id: str) -> list[ModificationLog]:
+        """Get all table's modification metadatas"""
+        raise NotImplementedError

pyproject.toml

@@ -0,0 +1,16 @@
+[project]
+name = "plesna"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.13"
+dependencies = [
+    "ruff>=0.8.5",
+]
+
+[tool.ruff]
+line-length = 100
+indent-width = 4
+[tool.ruff.lint]
+select = ["E", "F"]
+ignore = ["F401"]

tests/compute/test_consume_flux.py

@@ -1,18 +1,17 @@
 from plesna.compute.consume_flux import consume_flux
-from plesna.models.flux import Flux
+from plesna.models.flux import Flux, Transformation
 from plesna.models.storage import Table
-from plesna.models.transformation import Transformation
 
 
 def test_consume_flux():
-    sources = {
-        "src1": Table(id="src1", value="here"),
-        "src2": Table(id="src2", value="here"),
-    }
-    targets = {
-        "tgt1": Table(id="tgt1", value="this"),
-        "tgt2": Table(id="tgt2", value="that"),
-    }
+    sources = [
+        Table(id="src1", repo_id="test", schema_id="test", name="test", value="here", datas=["d"]),
+        Table(id="src2", repo_id="test", schema_id="test", name="test", value="here", datas=["d"]),
+    ]
+    targets = [
+        Table(id="tgt1", repo_id="test", schema_id="test", name="test", value="this", datas=["d"]),
+        Table(id="tgt2", repo_id="test", schema_id="test", name="test", value="that", datas=["d"]),
+    ]
 
     def func(sources, targets, **kwrds):
         return {
@@ -22,6 +21,8 @@ def test_consume_flux():
         }
 
     flux = Flux(
+        id="flux",
+        name="flux",
         sources=sources,
         targets=targets,
         transformation=Transformation(function=func, extra_kwrds={"extra": "super"}),

tests/dataplatform/test_dataplateform.py

@@ -1,43 +1,280 @@
+import shutil
 from pathlib import Path
 
 import pytest
 
 from plesna.dataplatform import DataPlateform
-from plesna.datastore.fs_datacatalogue import FSDataCatalogue
+from plesna.models.graphs import Edge, EdgeOnSet, Node
+from plesna.models.flux import Flux, Transformation
+from plesna.storage.data_repository.fs_data_repository import FSDataRepository
 
-FIXTURE_DIR = Path(__file__).parent / Path("raw_data")
+FIXTURE_DIR = Path(__file__).parent.parent / Path("raw_datas")
 
 
 @pytest.fixture
-def raw_catalogue(tmp_path):
+def repository(tmp_path) -> FSDataRepository:
+    example_src = FIXTURE_DIR
+    assert example_src.exists()
+
     raw_path = Path(tmp_path) / "raw"
-    raw_path.mkdir()
-    return FSDataCatalogue("raw", raw_path)
+    shutil.copytree(src=example_src.absolute(), dst=raw_path.absolute())
 
-
-@pytest.fixture
-def bronze_catalogue(tmp_path):
     bronze_path = Path(tmp_path) / "bronze"
     bronze_path.mkdir()
-    return FSDataCatalogue("bronze", bronze_path)
+    silver_path = Path(tmp_path) / "silver"
+    silver_path.mkdir()
+
+    return FSDataRepository("test", "test", tmp_path)
+
+
+def test_add_repository(
+    repository: FSDataRepository,
+):
+    dp = DataPlateform()
+    dp.add_repository(repository)
+
+    assert dp.repositories == ["test"]
+
+    assert dp.repository("test") == repository
 
 
 @pytest.fixture
-def silver_catalogue(tmp_path):
-    silver_path = Path(tmp_path) / "silver"
-    silver_path.mkdir()
-    return FSDataCatalogue("silver", silver_path)
+def copy_flux(repository: FSDataRepository) -> Flux:
+    raw_username = [repository.table("test-raw-username")]
+    bronze_username = [repository.table("test-bronze-username")]
+
+    def copy(sources, targets):
+        src_path = Path(sources["test-raw-username"].datas[0])
+        tgt_path = Path(targets["test-bronze-username"].datas[0])
+        shutil.copy(src_path, tgt_path)
+        return {"src_size": src_path.stat().st_size, "tgt_size": tgt_path.stat().st_size}
+
+    extra_kwrds = {}
+
+    raw_brz_copy_username = Flux(
+        id="copy_flux",
+        name="copy",
+        sources=raw_username,
+        targets=bronze_username,
+        transformation=Transformation(function=copy, extra_kwrds=extra_kwrds),
+    )
+    return raw_brz_copy_username
 
 
-def test_add_catalogue(
-    raw_catalogue: FSDataCatalogue,
-    bronze_catalogue: FSDataCatalogue,
-    silver_catalogue: FSDataCatalogue,
-):
+@pytest.fixture
+def foo_flux(repository: FSDataRepository) -> Flux:
+    src = [
+        repository.table("test-raw-username"),
+        repository.table("test-raw-recovery"),
+    ]
+    targets = [repository.table("test-bronze-foo")]
+
+    def foo(sources, targets):
+        return {"who": "foo"}
+
+    extra_kwrds = {}
+
+    flux = Flux(
+        id="foo_flux",
+        name="foo",
+        sources=src,
+        targets=targets,
+        transformation=Transformation(function=foo, extra_kwrds=extra_kwrds),
+    )
+    return flux
+
+
+def test_add_flux(repository: FSDataRepository, copy_flux: Flux, foo_flux: Flux):
+    dataplatform = DataPlateform()
+    dataplatform.add_repository(repository)
+
+    dataplatform.add_flux(flux=copy_flux)
+    assert dataplatform.fluxes == ["copy_flux"]
+    dataplatform.add_flux(flux=foo_flux)
+    assert dataplatform.fluxes == ["copy_flux", "foo_flux"]
+
+    assert dataplatform.flux("copy_flux") == copy_flux
+    assert dataplatform.flux("foo_flux") == foo_flux
+
+
+@pytest.fixture
+def dataplatform(
+    repository: FSDataRepository,
+    foo_flux: Flux,
+    copy_flux: Flux,
+) -> DataPlateform:
     dp = DataPlateform()
-    dp.add_datacatalague("raw", raw_catalogue)
-    dp.add_datacatalague("bronze", bronze_catalogue)
-    dp.add_datacatalague("silver", silver_catalogue)
 
-    assert dp.datacatalogues == ["raw", "bronze", "silver"]
-    assert dp.get_datacatalogue("raw") == raw_catalogue
+    dp.add_repository(repository)
+
+    dp.add_flux(foo_flux)
+    dp.add_flux(copy_flux)
+    return dp
+
+
+def test_listing_content(dataplatform: DataPlateform):
+    assert dataplatform.repository("test").schemas() == ["test-raw", "test-bronze", "test-silver"]
+    assert dataplatform.repository("test").schema("test-raw").tables == [
+        "test-raw-username",
+        "test-raw-recovery",
+        "test-raw-salary",
+    ]
+    assert dataplatform.repository("test").table("test-raw-username").partitions == ["username.csv"]
+    assert dataplatform.repository("test").table("test-raw-recovery").partitions == [
+        "2022.csv",
+        "2023.csv",
+        "2024.csv",
+    ]
+
+
+def test_content_from_graphset(dataplatform: DataPlateform):
+    assert dataplatform.graphset().node_sets == {
+        frozenset(
+            {
+                Node(name="test-bronze-username"),
+            }
+        ),
+        frozenset(
+            {
+                Node(name="test-bronze-foo"),
+            }
+        ),
+        frozenset(
+            {
+                Node(name="test-raw-username"),
+            }
+        ),
+        frozenset(
+            {
+                Node(name="test-raw-username"),
+                Node(name="test-raw-recovery"),
+            }
+        ),
+    }
+    assert dataplatform.graphset().edges == [
+        EdgeOnSet(
+            arrow="foo_flux",
+            sources=[Node(name="test-raw-username"), Node(name="test-raw-recovery")],
+            targets=[Node(name="test-bronze-foo")],
+            metadata={},
+        ),
+        EdgeOnSet(
+            arrow="copy_flux",
+            sources=[Node(name="test-raw-username")],
+            targets=[Node(name="test-bronze-username")],
+            metadata={},
+        ),
+    ]
+
+
+def test_content_from_graph(dataplatform: DataPlateform):
+    assert dataplatform.graph().nodes == {
+        Node(name="test-raw-recovery", metadata={}),
+        Node(name="test-raw-salary", metadata={}),
+        Node(name="test-raw-username", metadata={}),
+        Node(name="test-bronze-username", metadata={}),
+        Node(name="test-bronze-foo", metadata={}),
+        Node(name="test-raw-username", metadata={}),
+    }
+    assert dataplatform.graph().edges == [
+        Edge(
+            arrow="foo_flux",
+            source=Node(name="test-raw-username"),
+            target=Node(name="test-bronze-foo"),
+            metadata={},
+        ),
+        Edge(
+            arrow="foo_flux",
+            source=Node(name="test-raw-recovery"),
+            target=Node(name="test-bronze-foo"),
+            metadata={},
+        ),
+        Edge(
+            arrow="copy_flux",
+            source=Node(name="test-raw-username"),
+            target=Node(name="test-bronze-username"),
+            metadata={},
+        ),
+    ]
+
+
+def test_content_from_graph_arguments(dataplatform: DataPlateform):
+    name_flux = lambda flux: f"flux-{flux.id}"
+    meta_flux = lambda flux: {"name": flux.name}
+    meta_table = lambda table: {"id": table.id, "partitions": table.partitions}
+    assert dataplatform.graph(
+        name_flux=name_flux, meta_flux=meta_flux, meta_table=meta_table
+    ).nodes == {
+        Node(name="test-bronze-foo", metadata={"id": "test-bronze-foo", "partitions": []}),
+        Node(
+            name="test-raw-salary", metadata={"id": "test-raw-salary", "partitions": ["salary.pdf"]}
+        ),
+        Node(
+            name="test-raw-recovery",
+            metadata={
+                "id": "test-raw-recovery",
+                "partitions": ["2022.csv", "2023.csv", "2024.csv"],
+            },
+        ),
+        Node(
+            name="test-bronze-username", metadata={"id": "test-bronze-username", "partitions": []}
+        ),
+        Node(
+            name="test-raw-username",
+            metadata={"id": "test-raw-username", "partitions": ["username.csv"]},
+        ),
+    }
+
+    assert dataplatform.graph(
+        name_flux=name_flux, meta_flux=meta_flux, meta_table=meta_table
+    ).edges == [
+        Edge(
+            arrow="flux-foo_flux",
+            source=Node(
+                name="test-raw-username",
+                metadata={"id": "test-raw-username", "partitions": ["username.csv"]},
+            ),
+            target=Node(
+                name="test-bronze-foo", metadata={"id": "test-bronze-foo", "partitions": []}
+            ),
+            metadata={"name": "foo"},
+        ),
+        Edge(
+            arrow="flux-foo_flux",
+            source=Node(
+                name="test-raw-recovery",
+                metadata={
+                    "id": "test-raw-recovery",
+                    "partitions": ["2022.csv", "2023.csv", "2024.csv"],
+                },
+            ),
+            target=Node(
+                name="test-bronze-foo", metadata={"id": "test-bronze-foo", "partitions": []}
+            ),
+            metadata={"name": "foo"},
+        ),
+        Edge(
+            arrow="flux-copy_flux",
+            source=Node(
+                name="test-raw-username",
+                metadata={"id": "test-raw-username", "partitions": ["username.csv"]},
+            ),
+            target=Node(
+                name="test-bronze-username",
+                metadata={"id": "test-bronze-username", "partitions": []},
+            ),
+            metadata={"name": "copy"},
+        ),
+    ]
+
+
+def test_execute_flux(dataplatform: DataPlateform):
+    meta = dataplatform.execute_flux("foo_flux")
+    assert meta.data == {"who": "foo"}
+
+    assert dataplatform.repository("test").schema("test-bronze").tables == []
+
+    meta = dataplatform.execute_flux("copy_flux")
+    assert meta.data == {"src_size": 283, "tgt_size": 283}
+
+    assert dataplatform.repository("test").schema("test-bronze").tables == ["test-bronze-username"]

tests/datastore/test_fs_datacatalogue.py

@@ -1,61 +0,0 @@
-import shutil
-from pathlib import Path
-
-import pytest
-
-from plesna.datastore.fs_datacatalogue import FSDataCatalogue
-from plesna.models.storage import Schema
-
-FIXTURE_DIR = Path(__file__).parent.parent / Path("./raw_datas/")
-
-
-@pytest.fixture
-def location(tmp_path):
-    loc = tmp_path
-    username_loc = loc / "username"
-    username_loc.mkdir()
-    salary_loc = loc / "salary"
-    salary_loc.mkdir()
-    example_src = FIXTURE_DIR
-    assert example_src.exists()
-
-    for f in example_src.glob("*"):
-        if "username" in str(f):
-            shutil.copy(f, username_loc)
-        else:
-            shutil.copy(f, salary_loc)
-
-    return loc
-
-
-def test_init(location):
-    repo = FSDataCatalogue("example", location)
-    assert repo.ls() == [
-        "username",
-        "salary",
-    ]
-
-    assert repo.ls(recursive=True) == [
-        "username",
-        "salary",
-    ]
-
-
-def test_list_schema(location):
-    repo = FSDataCatalogue("example", location)
-
-    assert repo.schemas == [".", "username", "salary"]
-    assert repo.schema(".").ref == Schema(id=".", value=".")
-    assert repo.schema("username").ref == Schema(id="username", value="username")
-
-def test_list_tables_schema(location):
-    repo = FSDataCatalogue("example", location)
-
-    assert repo.schema(".").tables == []
-    assert repo.schema("username").tables == [
-                'username.csv',
-                'username-password-recovery-code.xlsx',
-                'username-password-recovery-code.xls',
-            ]
-    assert repo.schema("salary").tables == ["salary.pdf"]
-

tests/e2e/test_datalake.py

@@ -1,39 +0,0 @@
-from pathlib import Path
-
-import pytest
-
-from plesna.dataplatform import DataPlateform
-from plesna.datastore.fs_datacatalogue import FSDataCatalogue
-
-FIXTURE_DIR = Path(__file__).parent / Path("raw_data")
-
-
-@pytest.fixture
-def raw_catalogue(tmp_path):
-    raw_path = Path(tmp_path) / "raw"
-    return FSDataCatalogue(raw_path)
-
-
-@pytest.fixture
-def bronze_catalogue(tmp_path):
-    bronze_path = Path(tmp_path) / "bronze"
-    return FSDataCatalogue(bronze_path)
-
-
-@pytest.fixture
-def silver_catalogue(tmp_path):
-    silver_path = Path(tmp_path) / "silver"
-    return FSDataCatalogue(silver_path)
-
-
-@pytest.fixture
-def dataplateform(
-    raw_catalogue: FSDataCatalogue,
-    bronze_catalogue: FSDataCatalogue,
-    silver_catalogue: FSDataCatalogue,
-):
-    dp = DataPlateform()
-    dp.add_datacatalague("raw", raw_catalogue)
-    dp.add_datacatalague("bronze", bronze_catalogue)
-    dp.add_datacatalague("silver", silver_catalogue)
-    pass

tests/graphs/test_graph.py

@@ -1,6 +1,7 @@
 import pytest
 
-from plesna.graph.graph import Edge, Graph, Node
+from plesna.graph.graph import Graph
+from plesna.models.graphs import Edge, Node
 
 
 def test_append_nodess():
@@ -19,8 +20,8 @@ def test_append_edges():
     nodeB = Node(name="B")
     nodeC = Node(name="C")
 
-    edge1 = Edge(arrow_name="arrow", source=nodeA, target=nodeC)
-    edge2 = Edge(arrow_name="arrow", source=nodeB, target=nodeC)
+    edge1 = Edge(arrow="arrow", source=nodeA, target=nodeC)
+    edge2 = Edge(arrow="arrow", source=nodeB, target=nodeC)
 
     graph = Graph()
     graph.add_edge(edge1)
@@ -34,7 +35,7 @@ def test_init_edges_nodes():
     nodeB = Node(name="B")
     nodeC = Node(name="C")
 
-    edge1 = Edge(arrow_name="arrow", source=nodeB, target=nodeC)
+    edge1 = Edge(arrow="arrow", source=nodeB, target=nodeC)
 
     graph = Graph()
     graph.add_node(nodeA)
@@ -56,19 +57,19 @@ def nodes():
 @pytest.fixture
 def dag_edges(nodes):
     return {
-        "1": Edge(arrow_name="arrow", source=nodes["A"], target=nodes["C"]),
-        "2": Edge(arrow_name="arrow", source=nodes["B"], target=nodes["C"]),
-        "3": Edge(arrow_name="arrow", source=nodes["C"], target=nodes["D"]),
+        "1": Edge(arrow="arrow", source=nodes["A"], target=nodes["C"]),
+        "2": Edge(arrow="arrow", source=nodes["B"], target=nodes["C"]),
+        "3": Edge(arrow="arrow", source=nodes["C"], target=nodes["D"]),
     }
 
 
 @pytest.fixture
 def notdag_edges(nodes):
     return {
-        "1": Edge(arrow_name="arrow", source=nodes["A"], target=nodes["C"]),
-        "2": Edge(arrow_name="arrow", source=nodes["B"], target=nodes["C"]),
-        "3": Edge(arrow_name="arrow", source=nodes["C"], target=nodes["D"]),
-        "4": Edge(arrow_name="arrow", source=nodes["D"], target=nodes["B"]),
+        "1": Edge(arrow="arrow", source=nodes["A"], target=nodes["C"]),
+        "2": Edge(arrow="arrow", source=nodes["B"], target=nodes["C"]),
+        "3": Edge(arrow="arrow", source=nodes["C"], target=nodes["D"]),
+        "4": Edge(arrow="arrow", source=nodes["D"], target=nodes["B"]),
     }
 
 
@@ -94,9 +95,7 @@ def test_get_sources_from(nodes, dag_edges):
     assert graph.get_direct_sources_from(nodes["C"]) == set([nodes["A"], nodes["B"]])
     assert graph.get_direct_sources_from(nodes["D"]) == set([nodes["C"]])
 
-    assert graph.get_sources_from(nodes["D"]) == set(
-        [nodes["A"], nodes["B"], nodes["C"]]
-    )
+    assert graph.get_sources_from(nodes["D"]) == set([nodes["A"], nodes["B"], nodes["C"]])
 
 
 def test_valid_dage(dag_edges, notdag_edges):

tests/graphs/test_graph_set.py

@@ -1,18 +1,43 @@
-from plesna.graph.graph_set import EdgeOnSet, GraphSet, Node
+from plesna.graph.graph import Graph
+from plesna.graph.graph_set import GraphSet
+from plesna.models.graphs import Edge, EdgeOnSet, Node
 
 
 def test_init():
+    graph_set = GraphSet()
+
     nodeA = Node(name="A")
     nodeB = Node(name="B")
     nodeC = Node(name="C")
+    edge1 = EdgeOnSet(arrow="arrow", sources=[nodeA, nodeB], targets=[nodeC])
 
-    def arrow(sources, targets):
-        targets["C"].infos["res"] = sources["A"].name + sources["B"].name
-
-    edge1 = EdgeOnSet(
-        arrow=arrow, sources={"A": nodeA, "B": nodeB}, targets={"C": nodeC}
-    )
-    graph_set = GraphSet()
     graph_set.append(edge1)
 
     assert graph_set.node_sets == {frozenset([nodeA, nodeB]), frozenset([nodeC])}
+
+
+def test_to_graph():
+    graph_set = GraphSet()
+
+    nodeA = Node(name="A")
+    nodeB = Node(name="B")
+    nodeC = Node(name="C")
+    nodeD = Node(name="D")
+    edge1 = EdgeOnSet(arrow="arrow-AB-C", sources=[nodeA, nodeB], targets=[nodeC])
+    edge2 = EdgeOnSet(arrow="arrow-C-D", sources=[nodeC], targets=[nodeD])
+
+    graph_set.append(edge1)
+    graph_set.append(edge2)
+
+    graph = graph_set.to_graph()
+    assert graph.nodes == {
+        nodeA,
+        nodeB,
+        nodeC,
+        nodeD,
+    }
+    assert graph.edges == [
+        Edge(arrow="arrow-AB-C", source=nodeA, target=nodeC),
+        Edge(arrow="arrow-AB-C", source=nodeB, target=nodeC),
+        Edge(arrow="arrow-C-D", source=nodeC, target=nodeD),
+    ]

tests/libs/test_string_tools.py

@@ -0,0 +1,18 @@
+import pytest
+
+from plesna.libs.string_tools import StringToolsError, extract_values_from_pattern
+
+
+def test_extract_values_from_pattern():
+    source = "id:truc-bidule-machin"
+    pattern = "id:{champ1}-{champ2}-machin"
+
+    assert extract_values_from_pattern(pattern, source) == {"champ1": "truc", "champ2": "bidule"}
+
+
+def test_extract_values_from_pattern_no_match():
+    source = "id:truc-bidule"
+    pattern = "id:{champ1}-{champ2}-machin"
+
+    with pytest.raises(StringToolsError):
+        extract_values_from_pattern(pattern, source)

tests/raw_datas/recovery/2022.csv

@@ -0,0 +1,3 @@
+Identifier,One-time password
+9012,12se74
+2070,04ap67

tests/raw_datas/recovery/2023.csv

@@ -0,0 +1,4 @@
+Identifier,One-time password
+9012,32ui83
+9346,14ju73
+5079,09ja61

tests/raw_datas/recovery/2024.csv

@@ -0,0 +1,4 @@
+Identifier,One-time password
+9012,74iu23
+2070,12io89
+5079,85nc83

tests/raw_datas/username.csv

@@ -1,7 +0,0 @@
-Username;Identifier;First name;Last name
-booker12;9012;Rachel;Booker
-grey07;2070;Laura;Grey
-johnson81;4081;Craig;Johnson
-jenkins46;9346;Mary;Jenkins
-smith79;5079;Jamie;Smith
-

tests/raw_datas/username/username.csv

@@ -0,0 +1,6 @@
+Username,Identifier,First name,Last name,Department,Location
+booker12,9012,Rachel,Booker,Sales,Manchester
+grey07,2070,Laura,Grey,Depot,London
+johnson81,4081,Craig,Johnson,Depot,London
+jenkins46,9346,Mary,Jenkins,Engineering,Manchester
+smith79,5079,Jamie,Smith,Engineering,Manchester

tests/storage/test_fs_data_repository.py

@@ -0,0 +1,115 @@
+import shutil
+from pathlib import Path
+
+import pytest
+
+from plesna.storage.data_repository.fs_data_repository import FSDataRepository
+
+FIXTURE_DIR = Path(__file__).parent.parent / Path("./raw_datas/")
+
+
+@pytest.fixture
+def location(tmp_path):
+    schema = tmp_path / "schema"
+    example_src = FIXTURE_DIR
+    assert example_src.exists()
+
+    shutil.copytree(src=example_src.absolute(), dst=schema.absolute())
+
+    return tmp_path
+
+
+def test_init(location):
+    repo = FSDataRepository("example", "example", location)
+    assert repo.ls() == [
+        "schema",
+    ]
+    assert repo.ls(dir="schema") == [
+        "username",
+        "recovery",
+        "salary",
+    ]
+
+    assert repo.ls(recursive=True) == [
+        "schema",
+        "schema/username",
+        "schema/recovery",
+        "schema/salary",
+        "schema/username/username.csv",
+        "schema/recovery/2022.csv",
+        "schema/recovery/2023.csv",
+        "schema/recovery/2024.csv",
+        "schema/salary/salary.pdf",
+    ]
+
+
+@pytest.fixture
+def repository(location) -> FSDataRepository:
+    return FSDataRepository("repo_id", "example", location)
+
+
+def test_list_schemas(repository):
+    assert repository.schemas() == ["repo_id-schema"]
+
+
+def test_describe_schema(location, repository):
+    schema = repository.schema("repo_id-schema")
+    assert schema.name == "schema"
+    assert schema.id == "repo_id-schema"
+    assert schema.repo_id == "repo_id"
+    assert schema.value == str(location / "schema")
+    assert schema.tables == [
+        "repo_id-schema-username",
+        "repo_id-schema-recovery",
+        "repo_id-schema-salary",
+    ]
+
+
+def test_list_tables_schema(repository):
+    assert repository.schema("repo_id-schema").tables == [
+        "repo_id-schema-username",
+        "repo_id-schema-recovery",
+        "repo_id-schema-salary",
+    ]
+    assert repository.tables("repo_id-schema") == [
+        "repo_id-schema-username",
+        "repo_id-schema-recovery",
+        "repo_id-schema-salary",
+    ]
+    assert repository.tables() == [
+        "repo_id-schema-username",
+        "repo_id-schema-recovery",
+        "repo_id-schema-salary",
+    ]
+
+
+def test_describe_table(location, repository):
+    table = repository.table("repo_id-schema-username")
+
+    assert table.id == "repo_id-schema-username"
+    assert table.repo_id == "repo_id"
+    assert table.schema_id == "repo_id-schema"
+    assert table.name == "username"
+    assert table.value == str(location / "schema" / "username")
+    assert table.partitions == ["username.csv"]
+    assert table.datas == [table.value + "/username.csv"]
+
+
+def test_describe_table_with_partitions(location, repository):
+    table = repository.table("repo_id-schema-recovery")
+
+    assert table.id == "repo_id-schema-recovery"
+    assert table.repo_id == "repo_id"
+    assert table.schema_id == "repo_id-schema"
+    assert table.name == "recovery"
+    assert table.value == str(location / "schema" / "recovery")
+    assert table.partitions == [
+        "2022.csv",
+        "2023.csv",
+        "2024.csv",
+    ]
+    assert table.datas == [
+        table.value + "/2022.csv",
+        table.value + "/2023.csv",
+        table.value + "/2024.csv",
+    ]

tests/storage/test_fs_metadata_repository.py

@@ -0,0 +1,182 @@
+from datetime import datetime
+import shutil
+from pathlib import Path
+
+import pytest
+
+from plesna.models.flux import FluxMetaData
+from plesna.storage.metadata_repository.fs_metadata_repository import FSMetaDataRepository
+from plesna.storage.metadata_repository.metadata_repository import ExecutionLog, ModificationLog
+
+
+@pytest.fixture
+def location(tmp_path):
+    catalogpath = tmp_path / "catalog"
+    catalogpath.mkdir()
+
+    return catalogpath
+
+
+def test_init(location):
+    repo = FSMetaDataRepository(location)
+
+
+@pytest.fixture
+def metadata_repository(location) -> FSMetaDataRepository:
+    return FSMetaDataRepository(location)
+
+
+def test_add_flux(location, metadata_repository):
+    flux_id = "my_flux"
+    metadata_repository.add_flux(flux_id)
+
+    metadata_filepath = location / metadata_repository.OBJECTS["flux"]["filemodel"].format(
+        id=flux_id
+    )
+    assert metadata_filepath.exists()
+
+    with open(metadata_filepath, "r") as csvfile:
+        content = csvfile.read()
+        assert content == "datetime,output\n"
+
+
+def test_add_and_list_fluxes(metadata_repository):
+    flux_ids = ["my_flux", "flux2", "blahblah"]
+    for f in flux_ids:
+        metadata_repository.add_flux(f)
+    assert metadata_repository.fluxes() == flux_ids
+
+
+def test_register_flux_execution(location, metadata_repository):
+    flux_id = "my_flux"
+    metadata_repository.add_flux(flux_id)
+
+    metadata_repository.register_flux_execution(
+        flux_id,
+        datetime(2023, 3, 15, 14, 30),
+        output={
+            "truc": "machin",
+        },
+    )
+
+    metadata_filepath = location / metadata_repository.OBJECTS["flux"]["filemodel"].format(
+        id=flux_id
+    )
+    with open(metadata_filepath, "r") as csvfile:
+        content = csvfile.read()
+        assert (
+            content == 'datetime,output\n2023-03-15T14:30:00,"{""data"":{""truc"":""machin""}}"\n'
+        )
+
+
+def test_register_and_get_exec_logs(metadata_repository):
+    flux_id = "my_flux"
+    metadata_repository.add_flux(flux_id)
+
+    metadata_repository.register_flux_execution(
+        flux_id,
+        datetime(2023, 3, 15, 14, 30),
+        output={"truc": "machin"},
+    )
+    metadata_repository.register_flux_execution(
+        flux_id,
+        datetime(2024, 3, 15, 14, 30),
+        output={
+            "truc": "chose",
+        },
+    )
+
+    logs = metadata_repository.flux_logs(flux_id)
+    assert logs == [
+        ExecutionLog(
+            datetime=datetime(2023, 3, 15, 14, 30),
+            output=FluxMetaData(data={"truc": "machin"}),
+        ),
+        ExecutionLog(
+            datetime=datetime(2024, 3, 15, 14, 30),
+            output=FluxMetaData(data={"truc": "chose"}),
+        ),
+    ]
+
+
+def test_register_and_get_last_exec_log(metadata_repository):
+    flux_id = "my_flux"
+    metadata_repository.add_flux(flux_id)
+
+    metadata_repository.register_flux_execution(
+        flux_id,
+        datetime(2023, 3, 15, 14, 30),
+        output={"truc": "machin"},
+    )
+    metadata_repository.register_flux_execution(
+        flux_id,
+        datetime(2024, 3, 15, 14, 30),
+        output={
+            "truc": "chose",
+        },
+    )
+
+    logs = metadata_repository.flux(flux_id)
+    assert logs == ExecutionLog(
+        datetime=datetime(2024, 3, 15, 14, 30),
+        output=FluxMetaData(data={"truc": "chose"}),
+    )
+
+
+def test_add_and_list_tables(metadata_repository):
+    table_ids = ["my_table", "table2", "blahblah"]
+    for f in table_ids:
+        metadata_repository.add_table(f)
+    assert metadata_repository.tables() == table_ids
+
+
+def test_register_table_modification(location, metadata_repository):
+    table_id = "my_table"
+    flux_id = "my_flux"
+    metadata_repository.add_table(table_id)
+
+    metadata_repository.register_table_modification(
+        table_id, datetime(2023, 3, 15, 14, 30), flux_id
+    )
+
+    metadata_filepath = location / metadata_repository.OBJECTS["table"]["filemodel"].format(
+        id=table_id
+    )
+    with open(metadata_filepath, "r") as csvfile:
+        content = csvfile.read()
+        assert content == "datetime,flux_id\n2023-03-15T14:30:00,my_flux\n"
+
+
+def test_register_and_get_mod_logs(metadata_repository):
+    table_id = "my_table"
+    flux_id = "my_flux"
+    metadata_repository.add_table(table_id)
+
+    metadata_repository.register_table_modification(
+        table_id, datetime(2023, 3, 15, 14, 30), flux_id
+    )
+    metadata_repository.register_table_modification(
+        table_id, datetime(2024, 3, 15, 14, 30), flux_id
+    )
+
+    logs = metadata_repository.table_logs(table_id)
+    assert logs == [
+        ModificationLog(datetime=datetime(2023, 3, 15, 14, 30), flux_id=flux_id),
+        ModificationLog(datetime=datetime(2024, 3, 15, 14, 30), flux_id=flux_id),
+    ]
+
+
+def test_register_and_get_last_log(metadata_repository):
+    table_id = "my_table"
+    flux_id = "my_flux"
+    metadata_repository.add_table(table_id)
+
+    metadata_repository.register_table_modification(
+        table_id, datetime(2023, 3, 15, 14, 30), flux_id
+    )
+    metadata_repository.register_table_modification(
+        table_id, datetime(2024, 3, 15, 14, 30), flux_id
+    )
+
+    logs = metadata_repository.table(table_id)
+    assert logs == ModificationLog(datetime=datetime(2024, 3, 15, 14, 30), flux_id=flux_id)