Compare commits

18 Commits

Author SHA1 Message Date
e794242a03 Feat: test on pandas xlsx and ods file reader 2024-10-07 05:27:46 +02:00
5450de8628 Feat: start testing fs_repository 2024-08-14 10:44:38 +02:00
08c7fbe4c5 Feat: test consume_flux 2024-08-14 07:41:36 +02:00
959b53e6a0 Feat: start flux 2024-08-14 07:22:01 +02:00
91e229eab2 Feat: add __init__ and mod function signature 2024-08-14 07:21:36 +02:00
2de0e5ef5c refact: rename stage to repository 2024-08-07 11:39:33 +02:00
7fb7bc6f5c Feat: put table's callback and layout in factory 2024-07-28 18:49:07 +02:00
612df0a8eb Feat: callback to toggle editing 2024-07-28 17:34:56 +02:00
74882ae572 Feat: add navigation 2024-07-28 12:29:14 +02:00
d8f2fb52e1 feat: organise router path 2024-07-27 19:19:59 +02:00
f9bfb917bd feat: global design 2024-07-27 18:45:20 +02:00
cdad13788a feat: add tailwindcss 2024-07-27 18:22:00 +02:00
29c82ae597 feat: add recursive schema 2024-07-27 17:50:29 +02:00
5b53630688 feat: add schema and table listing 2024-07-27 17:39:09 +02:00
ed6d1c87d1 feat: init dashboard 2024-07-27 15:55:20 +02:00
1ed6ed43ed Feat: add commands in makefile 2024-06-11 17:54:25 +02:00
215e26b84f Feat: adapt to new excel format 2024-04-15 11:59:45 +02:00
b60fa3be17 Feat: add excel export for mart 2024-04-15 11:59:32 +02:00
31 changed files with 864 additions and 35 deletions

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@@ -42,6 +42,18 @@ clean_built:
rm -rf $(DATA_BASE)/staging/**/*.csv
rm -rf $(DATA_BASE)/gold/**/*.csv
rm -rf $(DATA_BASE)/datamart/**/*.csv
rm -rf $(DATA_BASE)/datamart/**/*.xlsx
run_ingest:
python -m scripts ingest
run_feature:
python -m scripts feature
run_datamart:
python -m scripts datamart
build: clean_built run_ingest run_feature run_datamart
clean_all: clean_built clean_raw
@@ -50,3 +62,5 @@ import_nextcloud:
push_nextcloud:
rsync -av ./datas/datamart/ ~/Nextcloud/PLESNA\ Compta\ SYSTEM/DataMart

64
dashboard/app.py Normal file
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@@ -0,0 +1,64 @@
import dash
from dash import Dash, dcc, html
from .datalake import stages
from .pages import config, home, repository, schema, table
external_scripts = [{"src": "https://cdn.tailwindcss.com"}]
# external_script = ["https://tailwindcss.com/", {"src": "https://cdn.tailwindcss.com"}]
app = Dash(
__name__,
use_pages=True,
external_scripts=external_scripts,
suppress_callback_exceptions=True,
)
app.scripts.config.serve_locally = True
dash.register_page(
home.__name__,
path="/",
layout=home.layout,
)
dash.register_page(config.__name__, path="/config", layout=config.layout)
dash.register_page(
repository.__name__,
path_template="/repository/<repository_name>",
layout=repository.layout_factory(stages),
)
dash.register_page(
schema.__name__,
path_template="/stg/<repository_name>/schema/<schema_name>",
layout=schema.layout_factory(stages),
)
dash.register_page(
table.__name__,
path_template="/stg/<repository_name>/schm/<schema_name>/table/<table_name>",
layout=table.layout_factory(stages),
)
table.callback_factory(app)
app.layout = html.Div(
[
html.Div(
[
dcc.Link(
html.H1(
"Plesna",
),
href="/",
className="text-4xl p-4 text-center grow align-baseline",
),
dcc.Link(
"Config",
href="/config",
className="flex-none hover:bg-amber-100 p-4 align-middle",
),
],
className="bg-amber-300 flex flex-row shadow",
),
dash.page_container,
]
)
if __name__ == "__main__":
app.run(debug=True)

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@@ -0,0 +1,57 @@
from dash import dcc, html
from ..libs.repository.repository import AbstractRepository
def html_list_schema(stage:AbstractRepository, with_tables=True):
""" Build html list of schema in stage """
ul_classes = "ml-2"
schema_baseurl = f"/stg/{stage.name}/schema/"
if with_tables:
return html.Ul(
[
html.Li(
children = [
dcc.Link(
schema,
href=schema_baseurl + schema,
className="text-lg hover:underline"
),
html_list_table(stage, schema)
],
className=""
) for schema in stage.schemas()
],
className=ul_classes
)
return html.Ul(
[
html.Li(
dcc.Link(
schema,
href=schema_baseurl + schema,
className="text-lg hover:underline"
),
) for schema in stage.schemas()
],
className=ul_classes
)
def html_list_table(stage:AbstractRepository, schema:str):
""" Build html list of table in stage """
table_baseurl = f"/stg/{stage.name}/schm/{schema}/table/"
return html.Ul(
[
html.Li(
dcc.Link(
table,
href=table_baseurl + table,
className="hover:underline"
),
) for table in stage.tables(schema=schema)
],
className="ml-4"
)

14
dashboard/datalake.py Normal file
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@@ -0,0 +1,14 @@
from dotenv import dotenv_values
from .libs.repository.fs_repository import FSRepository
env = {
**dotenv_values(".env"),
}
stages = {
"raw": FSRepository("raw", f"{env['DATA_PATH']}/{env['RAW_SUBPATH']}"),
"staging": FSRepository("staging", f"{env['DATA_PATH']}/{env['STAGING_SUBPATH']}"),
"gold": FSRepository("gold", f"{env['DATA_PATH']}/{env['GOLD_SUBPATH']}"),
"mart": FSRepository("mart", f"{env['DATA_PATH']}/{env['MART_SUBPATH']}"),
}

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@@ -0,0 +1,70 @@
from collections.abc import Callable
from datetime import datetime
import pandas as pd
from pydantic import BaseModel
from ..repository.repository import AbstractRepository
class Schema(BaseModel):
repository: str
schema: str
class Table(BaseModel):
repository: str
schema: str
table: str
class Flux(BaseModel):
sources: list[Table]
destinations: dict[str, Table]
transformation: Callable[[list[pd.DataFrame]], dict[str, pd.DataFrame]]
class State(BaseModel):
statuses: dict[str, dict]
qty_out: int
failed_lines: list[str]
start: datetime
end: datetime
Repositories = dict[str, AbstractRepository]
def open_source(repositories: Repositories, source: Table) -> pd.DataFrame:
return repositories[source.repository].read(source.table, source.schema)
def write_source(
content: pd.DataFrame, repositories: Repositories, destination: Table
) -> str:
return repositories[destination.repository].write(
content, destination.table, destination.schema
)
def consume_flux(flux: Flux, repositories: dict[str, AbstractRepository]) -> State:
start = datetime.now()
src_dfs = [open_source(repositories, source) for source in flux.sources]
built_dfs = flux.transformation(src_dfs)
statuses = {
dest: write_source(df, repositories, flux.destinations[dest])
for dest, df in built_dfs.items()
}
end = datetime.now()
qty_out = 0
failed_lines = []
return State(
statuses=statuses,
qty_out=qty_out,
failed_lines=failed_lines,
start=start,
end=end,
)

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@@ -0,0 +1,86 @@
from pathlib import Path
import pandas as pd
from .repository import AbstractRepository
ACCEPTABLE_EXTENTIONS = {
"csv": [".csv"],
"excel": [".xls", ".xlsx"],
}
class FSRepository(AbstractRepository):
def __init__(self, name, basepath, metadata_engine=None):
self.name = name
self.basepath = Path(basepath)
assert self.basepath.exists()
self._metadata_engine = metadata_engine
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, recursive=True) -> list[str]:
return self.ls("", only_directories=True, recursive=True)
def tables(self, schema: str = ".") -> list[str]:
return self.ls(schema, only_files=True)
def build_table_path(self, table: str, schema: str):
table_path = self.basepath
if schema == ".":
return table_path / table
return table_path / schema / table
def infos(self, table: str, schema: str = "."):
table_path = self.build_table_path(table, schema)
pass
def read(self, table: str, schema: str = ".", **read_options):
table_path = self.build_table_path(table, schema)
assert table_path.exists()
extension = table_path.suffix
if extension in ACCEPTABLE_EXTENTIONS["csv"]:
return pd.read_csv(table_path, **read_options)
if extension in ACCEPTABLE_EXTENTIONS["excel"]:
return pd.read_excel(table_path, engine = "openpyxl", **read_options)
raise ValueError("Bad extention. Can't open the table.")
def write(self, content, table: str, schema: str = "."):
table_path = self.build_table_path(table, schema)
pass
def delete_table(self, table: str, schema: str = "."):
table_path = self.build_table_path(table, schema)
pass

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@@ -0,0 +1,5 @@
from abc import ABC
class AbstractMetadataEngine(ABC):
pass

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@@ -0,0 +1,37 @@
import abc
from .metadata import AbstractMetadataEngine
class AbstractRepository(abc.ABC):
metadata_engine = AbstractMetadataEngine
@abc.abstractmethod
def schemas(self) -> list[str]:
"""List schemas"""
raise NotImplementedError
@abc.abstractmethod
def tables(self, schema) -> list[str]:
"""List table in schema"""
raise NotImplementedError
@abc.abstractmethod
def infos(self, table: str, schema: str) -> dict[str, str]:
"""Get infos about the table"""
raise NotImplementedError
@abc.abstractmethod
def read(self, table: str, schema: str):
"""Get content of the table"""
raise NotImplementedError
@abc.abstractmethod
def write(self, content, table: str, schema: str):
"""Write content into the table"""
raise NotImplementedError
@abc.abstractmethod
def delete_table(self, table: str, schema: str):
"""Delete the table"""
raise NotImplementedError

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14
dashboard/pages/config.py Normal file
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@@ -0,0 +1,14 @@
from dash import html
from dotenv import dotenv_values
import os
env = {
**dotenv_values(".env"),
**os.environ,
}
layout = html.Div([
html.H1('This is our Config page'),
html.Ul(children = [html.Li(f"{k} = {v}") for k,v in env.items()]),
])

27
dashboard/pages/home.py Normal file
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@@ -0,0 +1,27 @@
from dash import dcc, html
from ..components.lists import html_list_schema
from ..datalake import stages
layout = html.Div([
html.Div(children=[
html.Ul(
children=[
html.Li(
children=[
dcc.Link(
stagename,
href=f"/stage/{stagename}",
className="text-2xl text-center p-2 bg-amber-100 rounded shadow"
),
html_list_schema(stage)
],
className="flex-1 bg-gray-100 rounded flex flex-col shadow"
) for stagename, stage in stages.items()
],
className="flex flex-row space-x-2"
)
],
className="w-full mt-4 px-2"
),
])

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@@ -0,0 +1,18 @@
from dash import html
from ..components.lists import html_list_schema
from ..libs.repository.repository import AbstractRepository
def layout_factory(repositories: dict[str, AbstractRepository]):
def layout(repository_name: str = ""):
repository = repositories[repository_name]
return html.Div(
[
html.H2(f"{repository.name}", className="text-2xl p-4 py-2"),
html_list_schema(repository),
],
className="flex flex-col",
)
return layout

28
dashboard/pages/schema.py Normal file
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@@ -0,0 +1,28 @@
from dash import dcc, html
from ..libs.repository.repository import AbstractRepository
def layout_factory(repositories: dict[str, AbstractRepository]):
def layout(repository_name: str = "", schema_name: str = ""):
repository = repositories[repository_name]
return html.Div(
[
html.H2(
[
dcc.Link(
f"{repository.name}",
href=f"/repository/{repository.name}",
className="hover:underline",
),
html.Span(" > "),
html.Span(
f"{schema_name}",
),
],
className="text-2xl p-4 py-2",
),
]
)
return layout

130
dashboard/pages/table.py Normal file
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@@ -0,0 +1,130 @@
from dash import Input, Output, State, dash_table, dcc, html
from dash.exceptions import PreventUpdate
from ..libs.repository.repository import AbstractRepository
def layout_factory(repositories: dict[str,AbstractRepository]):
def layout(repository_name:str="", schema_name:str="", table_name:str=""):
repository = repositories[repository_name]
df = repository.read(table=table_name, schema=schema_name)
return html.Div([
dcc.Store(id="table_backup"),
html.Div([
html.H2([
dcc.Link(
f"{repository.name}",
href=f"/repository/{repository.name}",
className="hover:underline"
),
html.Span(" > "),
dcc.Link(
f"{schema_name}",
href=f"/stg/{repository.name}/schema/{schema_name}",
className="hover:underline"
),
html.Span(" > "),
html.Span(table_name),
],
className="text-2xl"
),
html.Div([
html.Button(
"Editer",
id="btn_edit",
className="rounded border px-2 py-1",
style={"display": "block"}
),
html.Button(
"Sauver",
id="btn_save",
className="rounded border px-2 py-1 border-green-500 hover:bg-green-500",
style={"display": "none"}
),
html.Button(
"Annuler",
id="btn_cancel",
className="rounded border px-2 py-1 border-red-500 hover:bg-red-500",
style={"display": "none"}
),
],
className="flex flex-row space-x-2",
id="toolbar"
),
],
className="flex flex-row justify-between p-4"
),
html.Div([
html.Div([
dash_table.DataTable(
id="datatable",
data=df.to_dict('records'),
columns=[{"name": i, "id": i} for i in df.columns],
filter_action="native",
sort_action="native",
sort_mode="multi",
editable=False
)
])
],
className="overflow-y-auto"
),
],
className="p-2"
)
return layout
def callback_factory(app):
@app.callback(
Output("datatable", 'editable', allow_duplicate=True),
Output("table_backup", 'data'),
Input("btn_edit", "n_clicks"),
State("datatable", 'data'),
prevent_initial_call=True
)
def activate_editable(n_clicks, df_src):
if n_clicks is None:
raise PreventUpdate
if n_clicks > 0:
df_backup = df_src.copy()
return True, df_backup
raise PreventUpdate
@app.callback(
Output("datatable", 'editable', allow_duplicate=True),
Output("datatable", 'data', allow_duplicate=True),
Input("btn_cancel", "n_clicks"),
State("table_backup", 'data'),
prevent_initial_call=True
)
def cancel_modifications(n_clicks, data):
if n_clicks is None:
raise PreventUpdate
if n_clicks > 0 and data is not None:
return False, data.copy()
raise PreventUpdate
@app.callback(
Output("datatable", 'editable'),
Output("datatable", 'data'),
Input("btn_save", "n_clicks"),
State("datatable", 'editable'),
)
def save_modifications(n_clicks, editable):
if n_clicks is None:
raise PreventUpdate
if n_clicks > 0:
return not editable
return editable
@app.callback(
Output("btn_edit", "style"),
Output("btn_save", "style"),
Output("btn_cancel", "style"),
Input("datatable", "editable"),
)
def toolbar(editable):
if editable:
return {"display": "none"}, {"display": "block"}, {"display": "block"}
return {"display": "block"}, {"display": "none"}, {"display": "none"}

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@@ -1,5 +1,6 @@
jupyter==1.0.0
pandas==1.5.0
pdf-oralia==0.3.11
pydantic==2.6.1
pandas==2.2.2
pydantic==2.8.2
click==8.1.7
openpyxl==3.1.5
xlrd==2.0.1

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@@ -79,7 +79,11 @@ def feature():
def datamart():
from .gold_mart import FLUXES_LOT
consume_fluxes(fluxes=FLUXES_LOT, origin_path=GOLD_PATH, dest_path=MART_PATH)
consume_fluxes(
fluxes=FLUXES_LOT,
origin_path=GOLD_PATH,
dest_path=MART_PATH,
)
if __name__ == "__main__":

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@@ -4,7 +4,7 @@ from collections.abc import Callable
from pathlib import Path
import pandas as pd
from pydantic import BaseModel
from pydantic import BaseModel, Field
class Source(BaseModel):
@@ -38,21 +38,51 @@ class Transformation(BaseModel):
extra_kwrds: dict = {}
def to_csv(df, dest_basename: Path) -> Path:
dest = dest_basename.parent / (dest_basename.stem + ".csv")
if dest.exists():
df.to_csv(dest, mode="a", header=False, index=False)
else:
df.to_csv(dest, index=False)
return dest
def to_excel(df, dest_basename: Path) -> Path:
dest = dest_basename.parent / (dest_basename.stem + ".xlsx")
if dest.exists():
raise ValueError(f"The destination exits {dest}")
else:
df.to_excel(dest)
return dest
class Destination(BaseModel):
name: str
writer: Callable = Field(to_csv)
def _write(
self,
df: pd.DataFrame,
dest_basename: Path,
writing_func: Callable | None = None,
) -> Path:
if writing_func is None:
writing_func = self.writer
return writing_func(df, dest_basename)
def write(
self, df: pd.DataFrame, dest_path: Path, writing_func: Callable
self, df: pd.DataFrame, dest_path: Path, writing_func: Callable | None = None
) -> list[Path]:
dest_basename = dest_path / self.name
return [writing_func(df, dest_basename)]
return [self._write(df, dest_basename, writing_func)]
class SplitDestination(Destination):
split_column: str
def write(
self, df: pd.DataFrame, dest_path: Path, writing_func: Callable
self, df: pd.DataFrame, dest_path: Path, writing_func: Callable | None = None
) -> list[Path]:
wrote_files = []
@@ -60,7 +90,7 @@ class SplitDestination(Destination):
filtered_df = df[df[self.split_column] == col_value]
dest_basename = dest_path / f"{self.name}-{col_value}"
dest = writing_func(filtered_df, dest_basename)
dest = self._write(filtered_df, dest_basename, writing_func)
wrote_files.append(dest)
return wrote_files
@@ -72,15 +102,6 @@ class Flux(BaseModel):
destination: Destination
def to_csv(df, dest_basename: Path) -> Path:
dest = dest_basename.parent / (dest_basename.stem + ".csv")
if dest.exists():
df.to_csv(dest, mode="a", header=False, index=False)
else:
df.to_csv(dest, index=False)
return dest
def write_split_by(
df: pd.DataFrame, column: str, dest_path: Path, name: str, writing_func
) -> list[Path]:
@@ -119,26 +140,38 @@ def split_duplicates(
return no_duplicates, duplicated
def consume_flux(
name: str,
flux: Flux,
origin_path: Path,
dest_path: Path,
duplicated={},
):
logging.info(f"Consume {name}")
src_df = []
for filename, df in extract_sources(flux.sources, origin_path):
logging.info(f"Extracting {filename}")
df, duplicated = split_duplicates(df, str(filename), duplicated)
src_df.append(df)
logging.info(f"Execute {flux.transformation.function.__name__}")
df = flux.transformation.function(src_df, **flux.transformation.extra_kwrds)
files = flux.destination.write(df, dest_path)
logging.info(f"{files} written")
return files
def consume_fluxes(
fluxes: dict[str, Flux],
origin_path: Path,
dest_path: Path,
writing_func=to_csv,
):
duplicated = {}
wrote_files = []
for name, flux in fluxes.items():
logging.info(f"Consume {name}")
src_df = []
for filename, df in extract_sources(flux.sources, origin_path):
logging.info(f"Extracting {filename}")
df, duplicated = split_duplicates(df, str(filename), duplicated)
src_df.append(df)
logging.info(f"Execute {flux.transformation.function.__name__}")
df = flux.transformation.function(src_df, **flux.transformation.extra_kwrds)
files = flux.destination.write(df, dest_path, writing_func)
logging.info(f"{files} written")
files = consume_flux(name, flux, origin_path, dest_path, duplicated)
wrote_files += files
return wrote_files

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@@ -11,6 +11,7 @@ from scripts.flux import (
SplitDestination,
Transformation,
consume_fluxes,
to_excel,
)
logger = logging.getLogger(__name__)
@@ -26,7 +27,9 @@ FLUXES_LOT = {
"Lots": Flux(
sources=[CSVSource(filename="CRG/crg-*.csv")],
transformation=Transformation(function=build_lots),
destination=SplitDestination(name="Lot/lot", split_column="Lot"),
destination=SplitDestination(
name="Lot/lot", split_column="Lot", writer=to_excel
),
),
}
@@ -75,6 +78,8 @@ if __name__ == "__main__":
pnl_fluxes = {}
files = consume_fluxes(
fluxes=pnl_fluxes, origin_path=gold_path, dest_path=mart_path
fluxes=pnl_fluxes,
origin_path=gold_path,
dest_path=mart_path,
)
print(files)

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@@ -12,9 +12,9 @@ logger.setLevel(logging.DEBUG)
def extract_cat(cat: pd.DataFrame):
cat_drop = list(cat[cat["Nouvelles"] == "NE PAS IMPORTER"]["Anciennes"])
cat_drop = list(cat[cat["Nouvelles"] == "NE PAS IMPORTER"])
# cat_drop = list(cat[cat["Nouvelles"] == "NE PAS IMPORTER"]["Anciennes"])
cat_trans = cat[cat["Nouvelles"] != "NE PAS IMPORTER"]
trans = {}
for _, (old, new) in cat_trans.iterrows():
trans[old] = new
@@ -140,7 +140,7 @@ FLUXES_CRG = {
),
"2022 - charge.xlsx": Flux(
sources=[
ExcelSource(filename="2022 - charge.xlsx", sheet_name="Sheet1"),
ExcelSource(filename="2022 - charge.xlsx", sheet_name="DB CRG"),
],
transformation=Transformation(
function=trans_2022_charge,

0
tests/__init__.py Normal file
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@@ -0,0 +1,7 @@
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
1 Username Identifier First name Last name
2 booker12 9012 Rachel Booker
3 grey07 2070 Laura Grey
4 johnson81 4081 Craig Johnson
5 jenkins46 9346 Mary Jenkins
6 smith79 5079 Jamie Smith

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@@ -0,0 +1,84 @@
import shutil
from pathlib import Path
import pytest
from pandas import pandas
from dashboard.libs.repository.fs_repository import FSRepository
EXAMPLE_DIR = "./tests/repository/fs_examples/"
@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 = Path(EXAMPLE_DIR)
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 = FSRepository("example", location)
assert repo.ls() == [
"username",
"salary",
]
assert repo.schemas() == [
".",
"username",
"salary",
]
assert repo.tables() == []
assert repo.tables("username") == [
"username.csv",
"username-password-recovery-code.xlsx",
"username-password-recovery-code.xls",
]
assert repo.tables("salary") == ["salary.pdf"]
def test_read_csv(location):
repo = FSRepository("example", location)
username = repo.read("username.csv", "username", delimiter=";")
assert list(username.columns) == [
"Username",
"Identifier",
"First name",
"Last name",
]
assert len(username.index) == 5
def test_fake_read_xlsx(location):
repo = FSRepository("example", location)
df = pandas.read_excel(
location / "username" / "username-password-recovery-code.xls"
)
print(df)
def test_read_xlsx(location):
repo = FSRepository("example", location)
username = repo.read("username-password-recovery-code.xls", "username")
assert list(username.columns) == [
"Username",
"Identifier",
"One-time password",
"Recovery code",
"First name",
"Last name",
"Department",
"Location",
]
assert len(username.index) == 5

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tests/test_flux.py Normal file
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import pandas as pd
import pytest
from dashboard.libs.flux.flux import Flux, consume_flux
from dashboard.libs.repository.repository import AbstractRepository
FakeTable = pd.DataFrame
FakeSchema = dict[str, pd.DataFrame]
FakeSchemas = dict[str, FakeSchema]
class FakeRepository(AbstractRepository):
def __init__(self, schemas: FakeSchemas):
self._schemas = {}
for schema_name, tables in schemas.items():
schema = {}
for table, df in tables.items():
schema[table] = {
"df": df,
"metadata": {
"status": "new",
"qty_read": 0,
"qty_write": 0,
},
}
self._schemas[schema_name] = schema
def schemas(self):
"""List schemas"""
return list(self._schemas.keys())
def tables(self, schema):
"""List table's name in schema"""
return list(self._schemas[schema].keys())
def infos(self, table: str, schema: str) -> dict[str, str]:
"""Get infos about the table"""
return self._schemas[schema][table]["metadata"]
def read(self, table, schema) -> pd.DataFrame:
"""Get content of the table"""
self._schemas[schema][table]["metadata"]["qty_read"] += 1
return self._schemas[schema][table]["df"]
def write(self, content, table, schema) -> dict[str, str]:
"""Write content into the table"""
try:
self._schemas[schema][table]["df"] = content
except KeyError:
self._schemas[schema][table] = {
"df": content,
"metadata": {
"status": "new",
"qty_read": 0,
"qty_write": 0,
},
}
self._schemas[schema][table]["metadata"]["status"] = "modified"
self._schemas[schema][table]["metadata"]["qty_write"] += 1
return self.infos(table, schema)
def delete_table(self, table, schema):
"""Delete the table"""
raise NotImplementedError
def test_fakerepository():
fakerepository = FakeRepository(
{
"foo": {
"table1": pd.DataFrame({"A": []}),
"table2": pd.DataFrame({"B": []}),
},
"bar": {
"table1": pd.DataFrame({"C": []}),
"table2": pd.DataFrame({"D": []}),
},
}
)
assert fakerepository.schemas() == ["foo", "bar"]
assert fakerepository.tables("foo") == ["table1", "table2"]
assert fakerepository.infos("table1", "foo") == {
"status": "new",
"qty_read": 0,
"qty_write": 0,
}
assert fakerepository.read("table1", "foo").equals(pd.DataFrame({"A": []}))
assert fakerepository.infos("table1", "foo") == {
"status": "new",
"qty_read": 1,
"qty_write": 0,
}
df = pd.DataFrame({"A": [1, 2]})
assert fakerepository.write(df, "table1", "foo") == {
"status": "modified",
"qty_read": 1,
"qty_write": 1,
}
def test_consume_flux():
source_repository = FakeRepository(
{
"source": {
"table1": pd.DataFrame({"A": [1, 2, 3]}),
},
}
)
dest_repository = FakeRepository(
{
"destination": {},
}
)
repositories = {
"source": source_repository,
"dest": dest_repository,
}
transformation = lambda dfs: {"dest": dfs[0] * 2}
flux = Flux(
sources=[{"repository": "source", "schema": "source", "table": "table1"}],
destinations={
"dest": {"repository": "dest", "schema": "destination", "table": "table1"}
},
transformation=transformation,
)
state = consume_flux(flux, repositories)
assert state.statuses["dest"] == {'status': 'modified', 'qty_read': 0, 'qty_write': 1}
assert dest_repository.read("table1", "destination").equals(pd.DataFrame({"A": [2, 4, 6]}))