bump version to 0.5.12

includes several aspects:

- harden forecast logic with additional error checks
- fix wrong behaviour
- ensure minimum data viability
- extrapolate for multiple data points into the future

fix #19

Co-authored-by: frasu
Reviewed-on: #21
Co-authored-by: foefl <f.foerster@d-opt.com>
Co-committed-by: foefl <f.foerster@d-opt.com>

.gitignore

@@ -3,6 +3,7 @@ prototypes/
 data/
 reports/
 *.code-workspace
+docs/
 
 # credentials
 CREDENTIALS*

pdm.lock

@@ -5,7 +5,7 @@
 groups = ["default", "dev", "lint", "nb", "tests"]
 strategy = ["inherit_metadata"]
 lock_version = "4.5.0"
-content_hash = "sha256:4931e32f8c146a72ad5b0a13c02485ea5ddc727de32fbe7c5e9314bbab05966c"
+content_hash = "sha256:f2a2abd891603796228b21bfeb7a00fd998964fe9303a9e4e5971f63925261e8"
 
 [[metadata.targets]]
 requires_python = ">=3.11"
@@ -579,7 +579,7 @@ files = [
 
 [[package]]
 name = "dopt-basics"
-version = "0.1.2"
+version = "0.1.3"
 requires_python = ">=3.11"
 summary = "basic cross-project tools for Python-based d-opt projects"
 groups = ["default"]
@@ -587,8 +587,19 @@ dependencies = [
     "tzdata>=2025.1",
 ]
 files = [
-    {file = "dopt_basics-0.1.2-py3-none-any.whl", hash = "sha256:dae8b7e31197fb173d98c74ed6f227c3dceaadf980139f0852a7f031d2e78b84"},
-    {file = "dopt_basics-0.1.2.tar.gz", hash = "sha256:dc54942db95b0608fa44f7b612ee3247dad50d2538ad88a1697b3357a8b05634"},
+    {file = "dopt_basics-0.1.3-py3-none-any.whl", hash = "sha256:974c2b442e47f0f05e66ff821ae48a9b12f7b77a8a3bc06fe8ac232e2bc27608"},
+    {file = "dopt_basics-0.1.3.tar.gz", hash = "sha256:22ba30cbd385cb8929cb6a13fe01e253cd7d9617ef637e41609f2468691450e8"},
+]
+
+[[package]]
+name = "et-xmlfile"
+version = "2.0.0"
+requires_python = ">=3.8"
+summary = "An implementation of lxml.xmlfile for the standard library"
+groups = ["dev"]
+files = [
+    {file = "et_xmlfile-2.0.0-py3-none-any.whl", hash = "sha256:7a91720bc756843502c3b7504c77b8fe44217c85c537d85037f0f536151b2caa"},
+    {file = "et_xmlfile-2.0.0.tar.gz", hash = "sha256:dab3f4764309081ce75662649be815c4c9081e88f0837825f90fd28317d4da54"},
 ]
 
 [[package]]
@@ -1450,6 +1461,20 @@ files = [
     {file = "nvidia_nccl_cu12-2.25.1-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:362aed5963fb9ea2ed2f264409baae30143498fd0e5c503aeaa1badd88cdc54a"},
 ]
 
+[[package]]
+name = "openpyxl"
+version = "3.1.5"
+requires_python = ">=3.8"
+summary = "A Python library to read/write Excel 2010 xlsx/xlsm files"
+groups = ["dev"]
+dependencies = [
+    "et-xmlfile",
+]
+files = [
+    {file = "openpyxl-3.1.5-py2.py3-none-any.whl", hash = "sha256:5282c12b107bffeef825f4617dc029afaf41d0ea60823bbb665ef3079dc79de2"},
+    {file = "openpyxl-3.1.5.tar.gz", hash = "sha256:cf0e3cf56142039133628b5acffe8ef0c12bc902d2aadd3e0fe5878dc08d1050"},
+]
+
 [[package]]
 name = "overrides"
 version = "7.7.0"
@@ -1571,6 +1596,31 @@ files = [
     {file = "pexpect-4.9.0.tar.gz", hash = "sha256:ee7d41123f3c9911050ea2c2dac107568dc43b2d3b0c7557a33212c398ead30f"},
 ]
 
+[[package]]
+name = "pip"
+version = "25.1.1"
+requires_python = ">=3.9"
+summary = "The PyPA recommended tool for installing Python packages."
+groups = ["default"]
+files = [
+    {file = "pip-25.1.1-py3-none-any.whl", hash = "sha256:2913a38a2abf4ea6b64ab507bd9e967f3b53dc1ede74b01b0931e1ce548751af"},
+    {file = "pip-25.1.1.tar.gz", hash = "sha256:3de45d411d308d5054c2168185d8da7f9a2cd753dbac8acbfa88a8909ecd9077"},
+]
+
+[[package]]
+name = "pip-system-certs"
+version = "5.2"
+requires_python = ">=3.10"
+summary = "Automatically configures Python to use system certificates via truststore"
+groups = ["default"]
+dependencies = [
+    "pip>=24.2",
+]
+files = [
+    {file = "pip_system_certs-5.2-py3-none-any.whl", hash = "sha256:e6ef3e106d4d02313e33955c2bcc4c2b143b2da07ef91e28a6805a0c1c512126"},
+    {file = "pip_system_certs-5.2.tar.gz", hash = "sha256:80b776b5cf17191bf99d313699b7fce2fdb84eb7bbb225fd134109a82706406f"},
+]
+
 [[package]]
 name = "platformdirs"
 version = "4.3.6"
@@ -1623,7 +1673,7 @@ name = "psutil"
 version = "7.0.0"
 requires_python = ">=3.6"
 summary = "Cross-platform lib for process and system monitoring in Python.  NOTE: the syntax of this script MUST be kept compatible with Python 2.7."
-groups = ["nb"]
+groups = ["default", "nb"]
 files = [
     {file = "psutil-7.0.0-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:101d71dc322e3cffd7cea0650b09b3d08b8e7c4109dd6809fe452dfd00e58b25"},
     {file = "psutil-7.0.0-cp36-abi3-macosx_11_0_arm64.whl", hash = "sha256:39db632f6bb862eeccf56660871433e111b6ea58f2caea825571951d4b6aa3da"},
@@ -2414,6 +2464,17 @@ files = [
     {file = "tinycss2-1.4.0.tar.gz", hash = "sha256:10c0972f6fc0fbee87c3edb76549357415e94548c1ae10ebccdea16fb404a9b7"},
 ]
 
+[[package]]
+name = "tomli-w"
+version = "1.2.0"
+requires_python = ">=3.9"
+summary = "A lil' TOML writer"
+groups = ["dev"]
+files = [
+    {file = "tomli_w-1.2.0-py3-none-any.whl", hash = "sha256:188306098d013b691fcadc011abd66727d3c414c571bb01b1a174ba8c983cf90"},
+    {file = "tomli_w-1.2.0.tar.gz", hash = "sha256:2dd14fac5a47c27be9cd4c976af5a12d87fb1f0b4512f81d69cce3b35ae25021"},
+]
+
 [[package]]
 name = "tomlkit"
 version = "0.13.2"
@@ -2600,8 +2661,8 @@ files = [
 
 [[package]]
 name = "xgboost"
-version = "2.1.4"
-requires_python = ">=3.8"
+version = "3.0.0"
+requires_python = ">=3.10"
 summary = "XGBoost Python Package"
 groups = ["default"]
 dependencies = [
@@ -2610,12 +2671,12 @@ dependencies = [
     "scipy",
 ]
 files = [
-    {file = "xgboost-2.1.4-py3-none-macosx_10_15_x86_64.macosx_11_0_x86_64.macosx_12_0_x86_64.whl", hash = "sha256:78d88da184562deff25c820d943420342014dd55e0f4c017cc4563c2148df5ee"},
-    {file = "xgboost-2.1.4-py3-none-macosx_12_0_arm64.whl", hash = "sha256:523db01d4e74b05c61a985028bde88a4dd380eadc97209310621996d7d5d14a7"},
-    {file = "xgboost-2.1.4-py3-none-manylinux2014_aarch64.whl", hash = "sha256:57c7e98111aceef4b689d7d2ce738564a1f7fe44237136837a47847b8b33bade"},
-    {file = "xgboost-2.1.4-py3-none-manylinux2014_x86_64.whl", hash = "sha256:f1343a512e634822eab30d300bfc00bf777dc869d881cc74854b42173cfcdb14"},
-    {file = "xgboost-2.1.4-py3-none-manylinux_2_28_aarch64.whl", hash = "sha256:d366097d0db047315736f46af852feaa907f6d7371716af741cdce488ae36d20"},
-    {file = "xgboost-2.1.4-py3-none-manylinux_2_28_x86_64.whl", hash = "sha256:8df6da72963969ab2bf49a520c3e147b1e15cbeddd3aa0e3e039b3532c739339"},
-    {file = "xgboost-2.1.4-py3-none-win_amd64.whl", hash = "sha256:8bbfe4fedc151b83a52edbf0de945fd94358b09a81998f2945ad330fd5f20cd6"},
-    {file = "xgboost-2.1.4.tar.gz", hash = "sha256:ab84c4bbedd7fae1a26f61e9dd7897421d5b08454b51c6eb072abc1d346d08d7"},
+    {file = "xgboost-3.0.0-py3-none-macosx_10_15_x86_64.whl", hash = "sha256:ed8cffd7998bd9431c3b0287a70bec8e45c09b43c9474d9dfd261627713bd890"},
+    {file = "xgboost-3.0.0-py3-none-macosx_12_0_arm64.whl", hash = "sha256:314104bd3a1426a40f0c9662eef40e9ab22eb7a8068a42a8d198ce40412db75c"},
+    {file = "xgboost-3.0.0-py3-none-manylinux2014_aarch64.whl", hash = "sha256:72c3405e8dfc37048f9fe339a058fa12b9f0f03bc31d3e56f0887eed2ed2baa1"},
+    {file = "xgboost-3.0.0-py3-none-manylinux2014_x86_64.whl", hash = "sha256:72d39e74649e9b628c4221111aa6a8caa860f2e853b25480424403ee61085126"},
+    {file = "xgboost-3.0.0-py3-none-manylinux_2_28_aarch64.whl", hash = "sha256:7bdee5787f86b83bebd75e2c96caf854760788e5f4203d063da50db5bf0efc5f"},
+    {file = "xgboost-3.0.0-py3-none-manylinux_2_28_x86_64.whl", hash = "sha256:61c7e391e373b8a5312503525c0689f83ef1912a1236377022865ab340f465a4"},
+    {file = "xgboost-3.0.0-py3-none-win_amd64.whl", hash = "sha256:0ea74e97f95b1eddfd27a46b7f22f72ec5a5322e1dc7cb41c9c23fb580763df9"},
+    {file = "xgboost-3.0.0.tar.gz", hash = "sha256:45e95416df6f6f01d9a62e60cf09fc57e5ee34697f3858337c796fac9ce3b9ed"},
 ]

pyproject.toml

@@ -1,11 +1,11 @@
 [project]
 name = "delta-barth"
-version = "0.5.1"
+version = "0.5.12"
 description = "workflows and pipelines for the Python-based Plugin of Delta Barth's ERP system"
 authors = [
     {name = "Florian Förster", email = "f.foerster@d-opt.com"},
 ]
-dependencies = ["scikit-learn>=1.6.1", "pandas>=2.2.3", "xgboost>=2.1.4", "joblib>=1.4.2", "typing-extensions>=4.12.2", "requests>=2.32.3", "pydantic>=2.10.6", "dopt-basics>=0.1.2", "SQLAlchemy>=2.0.39"]
+dependencies = ["scikit-learn>=1.6.1", "pandas>=2.2.3", "xgboost>=2.1.4", "joblib>=1.4.2", "typing-extensions>=4.12.2", "requests>=2.32.3", "pydantic>=2.10.6", "dopt-basics>=0.1.3", "SQLAlchemy>=2.0.39", "psutil>=7.0.0", "pip-system-certs>=5.2"]
 requires-python = ">=3.11"
 readme = "README.md"
 license = {text = "LicenseRef-Proprietary"}
@@ -44,7 +44,8 @@ filterwarnings = [
 ]
 markers = [
     "api_con_required: tests require an API connection (deselect with '-m \"not api_con_required\"')",
-    "new: to test only new tests, usually removed afterwards (deselect with '-m \"not quick\"')",
+    "new: to test only new tests, usually removed afterwards (deselect with '-m \"not new\"')",
+    "forecast: main components of forecast pipeline (deselect with '-m \"not forecast\"')"
 ]
 log_cli = true
 
@@ -73,7 +74,7 @@ directory = "reports/coverage"
 
 
 [tool.bumpversion]
-current_version = "0.5.1"
+current_version = "0.5.12"
 parse = """(?x)
     (?P<major>0|[1-9]\\d*)\\.
     (?P<minor>0|[1-9]\\d*)\\.
@@ -145,6 +146,8 @@ dev = [
     "pdoc3>=0.11.5",
     "bump-my-version>=1.1.1",
     "nox>=2025.2.9",
+    "tomli-w>=1.2.0",
+    "openpyxl>=3.1.5",
 ]
 nb = [
     "jupyterlab>=4.3.5",

scripts/build.ps1

@@ -1 +1,73 @@
-pdm build -d build/
+pdm build --no-sdist -d build/
+
+# Configuration
+$sourceDir = ".\build"
+$destDir = "..\01_releases\runtime"
+$packagePrefix = "delta_barth-"
+$packageSuffix = "-py3-none-any.whl"
+
+# Ensure destination exists
+if (-not (Test-Path $destDir)) {
+    New-Item -ItemType Directory -Path $destDir | Out-Null
+}
+
+# === Build Regex Pattern ===
+$escapedSuffix = [regex]::Escape($packageSuffix)
+
+# Match versions like 1.2.3 or 1.2.3.beta or 1.2.3.beta1
+# Capture the full version as one string, including the optional pre-release after a dot
+$pattern = "^$packagePrefix(?<version>\d+\.\d+\.\d+(?:\.[a-zA-Z0-9\-]+)?)$escapedSuffix$"
+
+Write-Host "Using pattern: $pattern"
+
+# === Get and Filter Files ===
+$allFiles = Get-ChildItem -Path $sourceDir -File
+$matchingFiles = @()
+
+foreach ($file in $allFiles) {
+    if ($file.Name -match $pattern) {
+        $version = $Matches['version']
+        $matchingFiles += [PSCustomObject]@{
+            File = $file
+            Version = $version
+        }
+        Write-Host "Matched: $($file.Name) -> Version: $version"
+    } else {
+        Write-Host "No match: $($file.Name)"
+    }
+}
+
+if ($matchingFiles.Count -eq 0) {
+    Write-Host "No matching package files found."
+    return
+}
+
+# === Convert version strings to sortable format ===
+function Convert-VersionForSort($v) {
+    # Split by dot: e.g., 1.2.3.beta -> [1, 2, 3, "beta"]
+    $parts = $v -split '\.'
+
+    $major = [int]$parts[0]
+    $minor = [int]$parts[1]
+    $patch = [int]$parts[2]
+    $pre   = if ($parts.Count -gt 3) { $parts[3] } else { "~" }  # "~" to ensure stable > prerelease
+
+    return [PSCustomObject]@{
+        Major = $major
+        Minor = $minor
+        Patch = $patch
+        Pre   = $pre
+    }
+}
+
+# === Sort by semantic version + pre-release ===
+$latest = $matchingFiles | Sort-Object {
+    Convert-VersionForSort $_.Version
+} -Descending | Select-Object -First 1
+
+# === Copy and rename to .zip ===
+$baseName = [System.IO.Path]::GetFileNameWithoutExtension($latest.File.Name)
+$newFileName = "$baseName.zip"
+$destPath = Join-Path $destDir $newFileName
+
+Copy-Item -Path $latest.File.FullName -Destination $destPath

scripts/bump_patch.ps1

@@ -0,0 +1,2 @@
+pdm run bump-my-version bump patch
+pdm run bump-my-version show current_version

src/delta_barth/__init__.py

@@ -0,0 +1,3 @@
+import pip_system_certs.wrapt_requests
+
+pip_system_certs.wrapt_requests.inject_truststore()

src/delta_barth/_csharp/json_types.py

@@ -42,7 +42,11 @@ def delta_barth_api_error() -> str:
 
 
 def status_err() -> str:
-    status = Status(code=102, description="internal error occurred", message="caused by test")
+    status = Status(
+        code=102,
+        description="internal error occurred: 'Limit-Überschreitung'",
+        message="caused by test",
+    )
     return status.model_dump_json()
 
 

src/delta_barth/_env.py

@@ -0,0 +1,33 @@
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+from typing import Final
+
+from dopt_basics import io
+
+PY_RUNTIME_FOLDER: Final[str] = "python"
+
+
+def prepare_env(
+    lib_path: Path,
+) -> Path | None:
+    pyrt_folder = io.search_folder_path(
+        starting_path=lib_path,
+        stop_folder_name=PY_RUNTIME_FOLDER,
+        return_inclusive=True,
+    )
+    if pyrt_folder is None:
+        return None
+
+    pth_interpreter = pyrt_folder / "python.exe"
+    if not pth_interpreter.exists():
+        raise FileNotFoundError(
+            f"dopt-delta-barth seems to be deployed in a standalone runtime, "
+            f"but the interpreter was not found under: {pth_interpreter}"
+        )
+
+    setattr(sys, "executable", str(pth_interpreter))
+    setattr(sys, "_base_executable", str(pth_interpreter))
+
+    return pyrt_folder

src/delta_barth/analysis/forecast.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import copy
 import datetime
 import math
 from collections.abc import Mapping, Set
@@ -7,10 +8,12 @@ from dataclasses import asdict
 from datetime import datetime as Datetime
 from typing import TYPE_CHECKING, Final, TypeAlias, cast
 
+import joblib
 import numpy as np
 import pandas as pd
 import scipy.stats
 import sqlalchemy as sql
+from dateutil.relativedelta import relativedelta
 from sklearn.metrics import mean_absolute_error, r2_score
 from sklearn.model_selection import KFold, RandomizedSearchCV
 from xgboost import XGBRegressor
@@ -26,9 +29,10 @@ from delta_barth.api.requests import (
 )
 from delta_barth.constants import (
     COL_MAP_SALES_PROGNOSIS,
+    DEFAULT_DB_ERR_CODE,
     DUMMY_DATA_PATH,
     FEATURES_SALES_PROGNOSIS,
-    SALES_BASE_NUM_DATAPOINTS_MONTHS,
+    MAX_NUM_WORKERS,
     SALES_MIN_NUM_DATAPOINTS,
 )
 from delta_barth.errors import STATUS_HANDLER, wrap_result
@@ -110,7 +114,7 @@ def _parse_df_to_results_wrapped(
     return _parse_df_to_results(data)
 
 
-@wrap_result()
+@wrap_result(code_on_error=DEFAULT_DB_ERR_CODE)
 def _write_sales_forecast_stats_wrapped(
     stats: SalesForecastStatistics,
 ) -> None:
@@ -182,16 +186,17 @@ def _process_sales(
     PipeResult
         _description_
     """
-    # cust_data: CustomerDataSalesForecast = CustomerDataSalesForecast()
-
     # filter data
     data = pipe.data
     assert data is not None, "processing not existing pipe result"
 
     DATE_FEAT: Final[str] = "buchungs_datum"
     SALES_FEAT: Final[str] = "betrag"
-    df_firma = data[(data["betrag"] > 0)]
-    df_cust = df_firma.copy()
+
+    data[DATE_FEAT] = pd.to_datetime(data[DATE_FEAT], errors="coerce")
+    data = data.dropna(subset=["buchungs_datum"])
+    df_filter = data[(data["betrag"] > 0)]
+    df_cust = df_filter.copy()
     df_cust = df_cust.sort_values(by=DATE_FEAT).reset_index()
     len_ds = len(df_cust)
 
@@ -205,7 +210,26 @@ def _process_sales(
     df_cust["jahr"] = df_cust[DATE_FEAT].dt.year
     df_cust["monat"] = df_cust[DATE_FEAT].dt.month
 
-    monthly_sum = df_cust.groupby(["jahr", "monat"])[SALES_FEAT].sum().reset_index()
+    monthly_sum_data_only = df_cust.groupby(["jahr", "monat"])[SALES_FEAT].sum().reset_index()
+
+    current_year = datetime.datetime.now().year
+    current_month = datetime.datetime.now().month
+    years = range(df_cust["jahr"].min(), current_year + 1)
+
+    all_month_year_combinations = pd.DataFrame(
+        [
+            (year, month)
+            for year in years
+            for month in range(1, 13)
+            if (year < current_year or (year == current_year and month <= current_month))
+        ],
+        columns=["jahr", "monat"],
+    )
+
+    monthly_sum = pd.merge(
+        all_month_year_combinations, monthly_sum_data_only, on=["jahr", "monat"], how="left"
+    )
+    monthly_sum[SALES_FEAT] = monthly_sum[SALES_FEAT].fillna(0)
     monthly_sum[DATE_FEAT] = (
         monthly_sum["monat"].astype(str) + "." + monthly_sum["jahr"].astype(str)
     )
@@ -214,13 +238,17 @@ def _process_sales(
 
     features = ["jahr", "monat"]
     target = SALES_FEAT
-    current_year = datetime.datetime.now().year
-    first_year = cast(int, df_cust["jahr"].min())
+
+    last_date = pd.to_datetime(datetime.datetime.now().strftime("%m.%Y"), format="%m.%Y")
+    future_dates = pd.date_range(
+        start=last_date + pd.DateOffset(months=1), periods=6, freq="MS"
+    )
+    forecast = pd.DataFrame({"datum": future_dates}).set_index("datum")
 
     # Randomized Search
     kfold = KFold(n_splits=5, shuffle=True)
     params: ParamSearchXGBRegressor = {
-        "n_estimators": scipy.stats.poisson(mu=1000),
+        "n_estimators": scipy.stats.poisson(mu=100),
         "learning_rate": [0.03, 0.04, 0.05],
         "max_depth": range(2, 9),
         "min_child_weight": range(1, 5),
@@ -230,40 +258,58 @@ def _process_sales(
         "early_stopping_rounds": [20, 50],
     }
 
+    best_estimator = None
     best_params: BestParametersXGBRegressor | None = None
     best_score_mae: float | None = float("inf")
     best_score_r2: float | None = None
     best_start_year: int | None = None
     too_few_month_points: bool = True
-    forecast: pd.DataFrame | None = None
 
-    for start_year in range(current_year - 4, first_year - 1, -1):
+    dates = cast(pd.DatetimeIndex, monthly_sum.index)
+    # baseline: 3 years - 36 months
+    starting_date = datetime.datetime.now() - relativedelta(months=36)
+
+    target_index, _ = next(
+        ((i, True) for i, date in enumerate(dates) if date >= starting_date),
+        (len(dates) - 1, False),
+    )
+
+    for add_year, date_idx in enumerate(range(target_index, -1, -12)):
+        first_date = dates[date_idx]
+        split_date = dates[-6]
+
         train = cast(
             pd.DataFrame,
-            monthly_sum[monthly_sum.index.year >= start_year].iloc[:-5].copy(),  # type: ignore
+            monthly_sum.loc[first_date:split_date].copy(),  # type: ignore
         )
         test = cast(
             pd.DataFrame,
-            monthly_sum[monthly_sum.index.year >= start_year].iloc[-5:].copy(),  # type: ignore
+            monthly_sum.loc[split_date:].copy(),  # type: ignore
         )
         X_train, X_test = train[features], test[features]
         y_train, y_test = train[target], test[target]
 
-        if len(train) >= (base_num_data_points_months + 10 * (current_year - 4 - start_year)):
+        # test set size fixed at 6 --> first iteration: baseline - 6 entries
+        # for each new year 10 new data points (i.e., sales strictly positive) needed
+        if len(train[train[SALES_FEAT] > 0]) >= (base_num_data_points_months + 10 * add_year):
             too_few_month_points = False
 
-            rand = RandomizedSearchCV(
-                XGBRegressor(),
-                params,
-                scoring="neg_mean_absolute_error",
-                cv=kfold,
-                n_jobs=-1,
-                n_iter=100,
-                verbose=0,
-            )
-            rand.fit(
-                X_train, y_train, eval_set=[(X_train, y_train), (X_test, y_test)], verbose=0
-            )
+            with joblib.parallel_config(backend="loky"):
+                rand = RandomizedSearchCV(
+                    XGBRegressor(),
+                    params,
+                    scoring="neg_mean_absolute_error",
+                    cv=kfold,
+                    n_jobs=MAX_NUM_WORKERS,
+                    n_iter=100,
+                    verbose=0,
+                )
+                rand.fit(
+                    X_train,
+                    y_train,
+                    eval_set=[(X_train, y_train), (X_test, y_test)],
+                    verbose=0,
+                )
             y_pred = rand.best_estimator_.predict(X_test)  # type: ignore
 
             if len(np.unique(y_pred)) != 1:
@@ -272,13 +318,21 @@ def _process_sales(
                     best_params = cast(BestParametersXGBRegressor, rand.best_params_)
                     best_score_mae = error
                     best_score_r2 = cast(float, r2_score(y_test, y_pred))
-                    best_start_year = start_year
-                    print("executed")
-                    forecast = test.copy()
-                    forecast.loc[:, "vorhersage"] = y_pred
+                    # --- new: use first_date for best_start_year
+                    best_start_year = first_date.year
+                    # --- new: store best_estimator
+                    best_estimator = copy.copy(rand.best_estimator_)
+
+    if best_estimator is not None:
+        X_future = pd.DataFrame(
+            {"jahr": future_dates.year, "monat": future_dates.month}, index=future_dates
+        )
+        y_future = best_estimator.predict(X_future)  # type: ignore
+        forecast["vorhersage"] = y_future
+        forecast["jahr"] = forecast.index.year  # type: ignore
+        forecast["monat"] = forecast.index.month  # type: ignore
+        forecast = forecast.reset_index(drop=True)
 
-    if forecast is not None:
-        forecast = forecast.drop(SALES_FEAT, axis=1).reset_index(drop=True)
     best_score_mae = best_score_mae if not math.isinf(best_score_mae) else None
 
     if too_few_month_points:
@@ -294,7 +348,9 @@ def _process_sales(
         pipe.stats(stats)
         return pipe
 
-    assert forecast is not None, "forecast is None, but was attempted to be returned"
+    assert "vorhersage" in forecast.columns, (
+        "forecast does not contain prognosis values, but was attempted to be returned"
+    )
     status = STATUS_HANDLER.SUCCESS
     pipe.success(forecast, status)
     stats = SalesForecastStatistics(
@@ -350,13 +406,13 @@ def _export_on_fail(
 
 def pipeline_sales_forecast(
     session: Session,
-    company_id: int | None = None,
+    company_ids: list[int] | None = None,
     start_date: Datetime | None = None,
 ) -> SalesPrognosisResultsExport:
     logger_pipelines.info("[PIPELINES] Starting main sales forecast pipeline...")
     response, status = get_sales_prognosis_data(
         session,
-        company_id=company_id,
+        company_ids=company_ids,
         start_date=start_date,
     )
     if status != STATUS_HANDLER.SUCCESS:
@@ -383,7 +439,7 @@ def pipeline_sales_forecast(
     pipe = _process_sales(
         pipe,
         min_num_data_points=SALES_MIN_NUM_DATAPOINTS,
-        base_num_data_points_months=SALES_BASE_NUM_DATAPOINTS_MONTHS,
+        base_num_data_points_months=session.cfg.forecast.threshold_month_data_points,
     )
     if pipe.statistics is not None:
         res = _write_sales_forecast_stats_wrapped(pipe.statistics)

src/delta_barth/api/requests.py

@@ -7,17 +7,20 @@ import requests
 from dopt_basics.io import combine_route
 from pydantic import BaseModel, PositiveInt, SkipValidation
 
+from delta_barth.constants import API_CON_TIMEOUT, MAX_LOGIN_RETRIES
 from delta_barth.errors import STATUS_HANDLER
 from delta_barth.types import DelBarApiError, ExportResponse, ResponseType, Status
 
 if TYPE_CHECKING:
+    from requests import Response
+
     from delta_barth.session import Session
 
 
 # ** sales data
 # ** import
 class SalesPrognosisRequestP(BaseModel):
-    FirmaId: SkipValidation[int | None]
+    FirmaIds: SkipValidation[list[int] | None]
     BuchungsDatum: SkipValidation[Datetime | None]
 
 
@@ -52,34 +55,50 @@ class SalesPrognosisResultsExport(ExportResponse):
 
 def get_sales_prognosis_data(
     session: Session,
-    company_id: int | None = None,
+    company_ids: list[int] | None = None,
     start_date: Datetime | None = None,
 ) -> tuple[SalesPrognosisResponse, Status]:
-    resp, status = session.assert_login()
-    if status != STATUS_HANDLER.SUCCESS:
-        response = SalesPrognosisResponse(daten=tuple())
-        return response, status
-
     ROUTE: Final[str] = "verkauf/umsatzprognosedaten"
     URL: Final = combine_route(session.base_url, ROUTE)
 
     sales_prog_req = SalesPrognosisRequestP(
-        FirmaId=company_id,
+        FirmaIds=company_ids,
         BuchungsDatum=start_date,
     )
-    resp = requests.get(
-        URL,
-        params=sales_prog_req.model_dump(mode="json", exclude_none=True),
-        headers=session.headers,  # type: ignore[argumentType]
-    )
+    empty_response = SalesPrognosisResponse(daten=tuple())
+    if not session.logged_in:
+        _, status = session.login()
+        if status != STATUS_HANDLER.SUCCESS:
+            return empty_response, status
+
+    resp: Response | None = None
+    try:
+        for attempt in range(1, (MAX_LOGIN_RETRIES + 1)):
+            resp = requests.get(
+                URL,
+                params=sales_prog_req.model_dump(mode="json", exclude_none=True),
+                headers=session.headers,  # type: ignore[argumentType]
+                timeout=API_CON_TIMEOUT,
+            )
+            if resp.status_code == 401:
+                _, status = session.relogin()
+                if status != STATUS_HANDLER.SUCCESS and attempt == MAX_LOGIN_RETRIES:
+                    return empty_response, status
+                continue
+            break
+    except requests.exceptions.Timeout:
+        return empty_response, STATUS_HANDLER.pipe_states.CONNECTION_TIMEOUT
+    except requests.exceptions.RequestException:
+        return empty_response, STATUS_HANDLER.pipe_states.CONNECTION_ERROR
 
     response: SalesPrognosisResponse
     status: Status
+    assert resp is not None, "tried to use not defined response"
     if resp.status_code == 200:
         response = SalesPrognosisResponse(**resp.json())
         status = STATUS_HANDLER.SUCCESS
     else:
-        response = SalesPrognosisResponse(daten=tuple())
+        response = empty_response
         err = DelBarApiError(status_code=resp.status_code, **resp.json())
         status = STATUS_HANDLER.api_error(err)
 

src/delta_barth/config.py

@@ -0,0 +1,43 @@
+from __future__ import annotations
+
+from pathlib import Path
+
+import dopt_basics.configs
+from pydantic import BaseModel
+
+
+class Config(BaseModel):
+    forecast: CfgForecast
+
+
+class CfgForecast(BaseModel):
+    threshold_month_data_points: int
+
+
+class LazyCfgLoader:
+    def __init__(
+        self,
+        cfg_path: Path,
+    ) -> None:
+        cfg_path = cfg_path.resolve()
+        assert cfg_path.exists(), f"config path {cfg_path} seems not to exist"
+        assert cfg_path.is_file(), f"config path {cfg_path} seems not to be a file"
+        self._path = cfg_path
+        self._cfg: Config | None = None
+
+    @property
+    def path(self) -> Path:
+        return self._path
+
+    def _load(self) -> Config:
+        cfg = dopt_basics.configs.load_toml(self.path)
+
+        return Config(**cfg)
+
+    def reload(self) -> None:
+        self._cfg = self._load()
+
+    def get(self) -> Config:
+        if self._cfg is None:
+            self._cfg = self._load()
+        return self._cfg

src/delta_barth/constants.py

@@ -1,10 +1,19 @@
+from __future__ import annotations
+
 import enum
 from pathlib import Path
 from typing import Final
 
+import psutil
+
+import delta_barth._env
 from delta_barth.types import DualDict, HttpContentHeaders
 
 # ** config
+CFG_FILENAME: Final[str] = "dopt-cfg.toml"
+CFG_HOT_RELOAD: Final[bool] = True
+cpu_count = psutil.cpu_count(logical=False)
+MAX_NUM_WORKERS: Final[int] = (cpu_count - 1) if cpu_count is not None else 3
 
 # ** lib path
 lib_path = Path(__file__).parent
@@ -13,18 +22,20 @@ LIB_PATH: Final[Path] = lib_path
 dummy_data_pth = LIB_PATH / "_dummy_data"
 assert dummy_data_pth.exists(), f"dummy data path not found: {dummy_data_pth}"
 DUMMY_DATA_PATH: Final[Path] = dummy_data_pth
+# ** runtime and deployment status
+RUNTIME_PATH: Final[Path | None] = delta_barth._env.prepare_env(LIB_PATH)
+deployment_status: bool = False
+if RUNTIME_PATH is not None:
+    deployment_status = True
+DEPLOYMENT_STATUS: Final[bool] = deployment_status
 
-# ** logging
-ENABLE_LOGGING: Final[bool] = False
-LOGGING_TO_FILE: Final[bool] = True
-LOGGING_TO_STDERR: Final[bool] = True
-LOG_FILENAME: Final[str] = "dopt-delbar.log"
 
 # ** databases
-DB_ECHO: Final[bool] = True
+DB_ECHO: Final[bool] = False
 
 # ** error handling
 DEFAULT_INTERNAL_ERR_CODE: Final[int] = 100
+DEFAULT_DB_ERR_CODE: Final[int] = 150
 DEFAULT_API_ERR_CODE: Final[int] = 400
 
 
@@ -38,6 +49,10 @@ class KnownDelBarApiErrorCodes(enum.Enum):
     COMMON = frozenset((400, 401, 409, 500))
 
 
+# ** API
+API_CON_TIMEOUT: Final[float] = 20.0  # secs to response
+MAX_LOGIN_RETRIES: Final[int] = 2
+
 # ** API response parsing
 # ** column mapping [API-Response --> Target-Features]
 COL_MAP_SALES_PROGNOSIS: Final[DualDict[str, str]] = DualDict(
@@ -60,4 +75,6 @@ FEATURES_SALES_PROGNOSIS: Final[frozenset[str]] = frozenset(
 # ** Pipelines
 # ** Forecast
 SALES_MIN_NUM_DATAPOINTS: Final[int] = 36
-SALES_BASE_NUM_DATAPOINTS_MONTHS: Final[int] = 36
+# !! now in config
+# TODO remove later till proven stable
+# SALES_BASE_NUM_DATAPOINTS_MONTHS: Final[int] = 36

src/delta_barth/databases.py

@@ -22,8 +22,8 @@ perf_meas = sql.Table(
     "performance_measurement",
     metadata,
     sql.Column("id", sql.Integer, primary_key=True),
-    sql.Column("execution_duration", sql.Float),
     sql.Column("pipeline_name", sql.String(length=30)),
+    sql.Column("execution_duration", sql.Float),
 )
 # ** ---- forecasts
 sf_stats = sql.Table(

src/delta_barth/dopt-cfg.toml

@@ -0,0 +1,2 @@
+[forecast]
+threshold_month_data_points = 28

src/delta_barth/errors.py

@@ -53,9 +53,19 @@ class UApiError(Exception):
 ## ** internal error handling
 DATA_PIPELINE_STATUS_DESCR: Final[tuple[StatusDescription, ...]] = (
     ("SUCCESS", 0, "Erfolg"),
-    ("TOO_FEW_POINTS", 1, "Datensatz besitzt nicht genügend Datenpunkte"),
-    ("TOO_FEW_MONTH_POINTS", 2, "nach Aggregation pro Monat nicht genügend Datenpunkte"),
-    ("NO_RELIABLE_FORECAST", 3, "Prognosequalität des Modells unzureichend"),
+    (
+        "CONNECTION_TIMEOUT",
+        1,
+        "Der Verbindungsaufbau zum API-Server dauerte zu lange. Ist der Server erreichbar?",
+    ),
+    (
+        "CONNECTION_ERROR",
+        2,
+        "Es ist keine Verbindung zum API-Server möglich. Ist der Server erreichbar?",
+    ),
+    ("TOO_FEW_POINTS", 3, "Datensatz besitzt nicht genügend Datenpunkte"),
+    ("TOO_FEW_MONTH_POINTS", 4, "nach Aggregation pro Monat nicht genügend Datenpunkte"),
+    ("NO_RELIABLE_FORECAST", 5, "Prognosequalität des Modells unzureichend"),
 )
 
 

src/delta_barth/logging.py

@@ -6,14 +6,13 @@ from pathlib import Path
 from time import gmtime
 from typing import Final
 
-from delta_barth.constants import (
-    ENABLE_LOGGING,
-    LOG_FILENAME,
-    LOGGING_TO_FILE,
-    LOGGING_TO_STDERR,
-)
-
 # ** config
+# ** logging
+ENABLE_LOGGING: Final[bool] = True
+LOGGING_TO_FILE: Final[bool] = True
+LOGGING_TO_STDERR: Final[bool] = False
+LOG_FILENAME: Final[str] = "dopt-delbar.log"
+
 logging.Formatter.converter = gmtime
 LOG_FMT: Final[str] = "%(asctime)s | lang_main:%(module)s:%(levelname)s | %(message)s"
 LOG_DATE_FMT: Final[str] = "%Y-%m-%d %H:%M:%S +0000"
@@ -31,6 +30,8 @@ logger_status = logging.getLogger("delta_barth.status")
 logger_status.setLevel(logging.DEBUG)
 logger_session = logging.getLogger("delta_barth.session")
 logger_session.setLevel(logging.DEBUG)
+logger_config = logging.getLogger("delta_barth.config")
+logger_config.setLevel(logging.DEBUG)
 logger_management = logging.getLogger("delta_barth.management")
 logger_management.setLevel(logging.DEBUG)
 logger_wrapped_results = logging.getLogger("delta_barth.wrapped_results")

src/delta_barth/management.py

@@ -14,9 +14,11 @@ SESSION: Final[Session] = Session(HTTP_BASE_CONTENT_HEADERS)
 
 def setup(
     data_path: str,
+    base_url: str,
 ) -> None:  # pragma: no cover
     # at this point: no logging configured
     SESSION.set_data_path(data_path)
+    SESSION.set_base_url(base_url=base_url)
     SESSION.setup()
     logger.info("[EXT-CALL MANAGEMENT] Successfully set up current session")
 
@@ -37,6 +39,7 @@ def set_credentials(
     logger.info("[EXT-CALL MANAGEMENT] Successfully set credentials for current session")
 
 
+# ** not part of external API, only internal
 def get_credentials() -> str:  # pragma: no cover
     logger.info("[EXT-CALL MANAGEMENT] Getting credentials for current session...")
     creds = SESSION.creds
@@ -44,12 +47,15 @@ def get_credentials() -> str:  # pragma: no cover
     return creds.model_dump_json()
 
 
-# ** legacy: not part of external API
 def set_base_url(
     base_url: str,
 ) -> None:  # pragma: no cover
     SESSION.set_base_url(base_url=base_url)
 
 
+def get_data_path() -> str:  # pragma: no cover
+    return str(SESSION.data_path)
+
+
 def get_base_url() -> str:  # pragma: no cover
     return SESSION.base_url

src/delta_barth/pipelines.py

@@ -1,24 +1,83 @@
 """collection of configured data pipelines, intended to be invoked from C#"""
 
+import time
 from datetime import datetime as Datetime
+from typing import Final
 
+import sqlalchemy as sql
+
+from delta_barth import databases as db
 from delta_barth.analysis import forecast
+from delta_barth.constants import DEFAULT_DB_ERR_CODE
+from delta_barth.errors import STATUS_HANDLER, wrap_result
 from delta_barth.logging import logger_pipelines as logger
 from delta_barth.management import SESSION
-from delta_barth.types import JsonExportResponse
+from delta_barth.types import JsonExportResponse, PipelineMetrics
+
+
+def _write_performance_metrics(
+    pipeline_name: str,
+    time_start: int,
+    time_end: int,
+) -> PipelineMetrics:
+    if time_end < time_start:
+        raise ValueError("Ending time smaller than starting time")
+    execution_duration = (time_end - time_start) / 1e9
+    metrics = PipelineMetrics(
+        pipeline_name=pipeline_name,
+        execution_duration=execution_duration,
+    )
+
+    with SESSION.db_engine.begin() as con:
+        con.execute(sql.insert(db.perf_meas).values(**metrics))
+
+    return metrics
+
+
+@wrap_result(code_on_error=DEFAULT_DB_ERR_CODE)
+def _write_performance_metrics_wrapped(
+    pipeline_name: str,
+    time_start: int,
+    time_end: int,
+) -> PipelineMetrics:
+    return _write_performance_metrics(pipeline_name, time_start, time_end)
 
 
 def pipeline_sales_forecast(
-    company_id: int | None,
+    company_ids: list[int] | None,
     start_date: Datetime | None,
 ) -> JsonExportResponse:
+    PIPELINE_NAME: Final[str] = "sales_forecast"
     logger.info("[EXT-CALL PIPELINES] Starting main sales forecast pipeline...")
+    t_start = time.perf_counter_ns()
     result = forecast.pipeline_sales_forecast(
-        SESSION, company_id=company_id, start_date=start_date
+        SESSION, company_ids=company_ids, start_date=start_date
     )
     export = JsonExportResponse(result.model_dump_json())
-
+    t_end = time.perf_counter_ns()
     logger.info("[EXT-CALL PIPELINES] Main sales forecast pipeline successful")
+    logger.info("[EXT-CALL PIPELINES] Writing performance metrics...")
+    res = _write_performance_metrics_wrapped(
+        pipeline_name=PIPELINE_NAME,
+        time_start=t_start,
+        time_end=t_end,
+    )
+    if res.status != STATUS_HANDLER.SUCCESS:
+        logger.error(
+            (
+                "[DB-WRITE][METRICS] Pipeline: >%s< - Error on writing "
+                "pipeline metrics to database: %s"
+            ),
+            PIPELINE_NAME,
+            res.status,
+        )
+    else:
+        metrics = res.unwrap()
+        logger.info(
+            "[METRICS] Pipeline: >%s< - Execution time: %.6f",
+            PIPELINE_NAME,
+            metrics["execution_duration"],
+        )
 
     return export
 
@@ -27,14 +86,38 @@ def pipeline_sales_forecast_dummy(
     company_id: int | None,
     start_date: Datetime | None,
 ) -> JsonExportResponse:
+    PIPELINE_NAME: Final[str] = "sales_forecast_dummy"
     logger.info("[EXT-CALL PIPELINES] Starting dummy sales forecast pipeline...")
+    t_start = time.perf_counter_ns()
     result = forecast.pipeline_sales_dummy(
         SESSION,
         company_id=company_id,
         start_date=start_date,
     )
     export = JsonExportResponse(result.model_dump_json())
-
+    t_end = time.perf_counter_ns()
     logger.info("[EXT-CALL PIPELINES] Dummy sales forecast pipeline successful")
+    logger.info("[EXT-CALL PIPELINES] Writing performance metrics...")
+    res = _write_performance_metrics_wrapped(
+        pipeline_name=PIPELINE_NAME,
+        time_start=t_start,
+        time_end=t_end,
+    )
+    if res.status != STATUS_HANDLER.SUCCESS:
+        logger.error(
+            (
+                "[DB-WRITE][METRICS] Pipeline: >%s< - Error on writing "
+                "pipeline metrics to database: %s"
+            ),
+            PIPELINE_NAME,
+            res.status,
+        )
+    else:
+        metrics = res.unwrap()
+        logger.info(
+            "[METRICS] Pipeline: >%s< - Execution time: %.6f",
+            PIPELINE_NAME,
+            metrics["execution_duration"],
+        )
 
     return export

src/delta_barth/session.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import shutil
 from pathlib import Path
 from typing import TYPE_CHECKING, Final
 
@@ -14,12 +15,20 @@ from delta_barth.api.common import (
     LoginResponse,
     validate_credentials,
 )
-from delta_barth.constants import DB_ECHO
+from delta_barth.config import LazyCfgLoader
+from delta_barth.constants import (
+    API_CON_TIMEOUT,
+    CFG_FILENAME,
+    CFG_HOT_RELOAD,
+    DB_ECHO,
+    LIB_PATH,
+)
 from delta_barth.errors import STATUS_HANDLER
 from delta_barth.logging import logger_session as logger
 from delta_barth.types import DelBarApiError, Status
 
 if TYPE_CHECKING:
+    from delta_barth.config import Config
     from delta_barth.types import ApiCredentials, HttpContentHeaders
 
 
@@ -41,6 +50,7 @@ class Session:
         base_headers: HttpContentHeaders,
         db_folder: str = "data",
         logging_folder: str = "logs",
+        cfg_folder: str = "config",
     ) -> None:
         self._setup: bool = False
         self._data_path: Path | None = None
@@ -49,6 +59,10 @@ class Session:
         self._db_engine: sql.Engine | None = None
         self._logging_dir: Path | None = None
         self._logging_folder = logging_folder
+        self._cfg_path: Path | None = None
+        self._cfg_folder = cfg_folder
+        self._cfg_loader: LazyCfgLoader | None = None
+        self._cfg: Config | None = None
         self._creds: ApiCredentials | None = None
         self._base_url: str | None = None
         self._headers = base_headers
@@ -59,6 +73,7 @@ class Session:
         # at this point: no logging configured
         assert not self._setup, "tried to setup session twice"
         self._setup_logging()
+        self._setup_config()
         self._setup_db_management()
         self._setup = True
         logger.info("[SESSION] Setup procedure successful")
@@ -68,6 +83,39 @@ class Session:
         assert self._data_path is not None, "accessed data path not set"
         return self._data_path
 
+    @property
+    def cfg_path(self) -> Path:
+        if self._cfg_path is not None and self._setup:
+            return self._cfg_path
+
+        root = (self.data_path / self._cfg_folder).resolve()
+        cfg_path = root / CFG_FILENAME
+        if not root.exists():
+            root.mkdir(parents=False)
+        self._cfg_path = cfg_path
+        return self._cfg_path
+
+    @property
+    def cfg(self) -> Config:
+        assert self._cfg is not None, "tried to access not set config from session"
+        if CFG_HOT_RELOAD:
+            self.reload_cfg()
+        return self._cfg
+
+    def _setup_config(self) -> None:
+        if not self.cfg_path.exists():
+            src_cfg = LIB_PATH / CFG_FILENAME
+            shutil.copyfile(src_cfg, self.cfg_path)
+
+        self._cfg_loader = LazyCfgLoader(self.cfg_path)
+        self._cfg = self._cfg_loader.get()
+        logger.info("[SESSION] Successfully read and setup config")
+
+    def reload_cfg(self) -> None:
+        assert self._cfg_loader is not None, "tried reloading with no CFG loader intialised"
+        self._cfg_loader.reload()
+        self._cfg = self._cfg_loader.get()
+
     @property
     def db_engine(self) -> sql.Engine:
         assert self._db_engine is not None, "accessed database engine not set"
@@ -78,10 +126,10 @@ class Session:
         if self._db_path is not None and self._setup:
             return self._db_path
 
-        db_root = (self.data_path / self._db_folder).resolve()
-        db_path = db_root / "dopt-data.db"
-        if not db_root.exists():
-            db_root.mkdir(parents=False)
+        root = (self.data_path / self._db_folder).resolve()
+        db_path = root / "dopt-data.db"
+        if not root.exists():
+            root.mkdir(parents=False)
         self._db_path = db_path
         return self._db_path
 
@@ -191,11 +239,18 @@ class Session:
             databaseName=self.creds.database,
             mandantName=self.creds.mandant,
         )
-        resp = requests.put(
-            URL,
-            login_req.model_dump_json(),
-            headers=self.headers,  # type: ignore
-        )
+        empty_response = LoginResponse(token="")
+        try:
+            resp = requests.put(
+                URL,
+                login_req.model_dump_json(),
+                headers=self.headers,  # type: ignore
+                timeout=API_CON_TIMEOUT,
+            )
+        except requests.exceptions.Timeout:  # pragma: no cover
+            return empty_response, STATUS_HANDLER.pipe_states.CONNECTION_TIMEOUT
+        except requests.exceptions.RequestException:  # pragma: no cover
+            return empty_response, STATUS_HANDLER.pipe_states.CONNECTION_ERROR
 
         response: LoginResponse
         status: Status
@@ -204,7 +259,7 @@ class Session:
             status = STATUS_HANDLER.pipe_states.SUCCESS
             self._add_session_token(response.token)
         else:
-            response = LoginResponse(token="")
+            response = empty_response
             err = DelBarApiError(status_code=resp.status_code, **resp.json())
             status = STATUS_HANDLER.api_error(err)
 
@@ -216,12 +271,17 @@ class Session:
         ROUTE: Final[str] = "user/logout"
         URL: Final = combine_route(self.base_url, ROUTE)
 
-        resp = requests.put(
-            URL,
-            headers=self.headers,  # type: ignore
-        )
+        try:
+            resp = requests.put(
+                URL,
+                headers=self.headers,  # type: ignore
+                timeout=API_CON_TIMEOUT,
+            )
+        except requests.exceptions.Timeout:  # pragma: no cover
+            return None, STATUS_HANDLER.pipe_states.CONNECTION_TIMEOUT
+        except requests.exceptions.RequestException:  # pragma: no cover
+            return None, STATUS_HANDLER.pipe_states.CONNECTION_ERROR
 
-        response = None
         status: Status
         if resp.status_code == 200:
             status = STATUS_HANDLER.SUCCESS
@@ -230,39 +290,13 @@ class Session:
             err = DelBarApiError(status_code=resp.status_code, **resp.json())
             status = STATUS_HANDLER.api_error(err)
 
-        return response, status
+        return None, status
 
-    def assert_login(
+    def relogin(
         self,
     ) -> tuple[LoginResponse, Status]:
-        # check if login token is still valid
-        # re-login if necessary
         if self.session_token is None:
             return self.login()
 
-        # use known endpoint which requires a valid token in its header
-        # evaluate the response to decide if:
-        # current token is still valid, token is not valid, other errors occurred
-        ROUTE: Final[str] = "verkauf/umsatzprognosedaten"
-        URL: Final = combine_route(self.base_url, ROUTE)
-        params: dict[str, int] = {"FirmaId": 999999}
-        resp = requests.get(
-            URL,
-            params=params,
-            headers=self.headers,  # type: ignore
-        )
-
-        response: LoginResponse
-        status: Status
-        if resp.status_code == 200:
-            response = LoginResponse(token=self.session_token)
-            status = STATUS_HANDLER.SUCCESS
-        elif resp.status_code == 401:
-            self._remove_session_token()
-            response, status = self.login()
-        else:
-            response = LoginResponse(token="")
-            err = DelBarApiError(status_code=resp.status_code, **resp.json())
-            status = STATUS_HANDLER.api_error(err)
-
-        return response, status
+        self._remove_session_token()
+        return self.login()

src/delta_barth/types.py

@@ -47,6 +47,8 @@ class ExportResponse(BaseModel):
 @dataclass(slots=True)
 class DataPipeStates:
     SUCCESS: Status
+    CONNECTION_TIMEOUT: Status
+    CONNECTION_ERROR: Status
     TOO_FEW_POINTS: Status
     TOO_FEW_MONTH_POINTS: Status
     NO_RELIABLE_FORECAST: Status
@@ -139,7 +141,13 @@ class Statistics:
     pass
 
 
-# ** forecasts
+# ** ---- performance
+class PipelineMetrics(t.TypedDict):
+    pipeline_name: str
+    execution_duration: float
+
+
+# ** ---- forecasts
 @dataclass(slots=True)
 class CustomerDataSalesForecast:
     order: list[int] = field(default_factory=list)

tests/_test_data/dopt-cfg.toml

@@ -0,0 +1,2 @@
+[forecast]
+threshold_month_data_points = 28

tests/analysis/test_forecast.py

@@ -1,3 +1,4 @@
+import datetime
 from datetime import datetime as Datetime
 from unittest.mock import patch
 
@@ -255,6 +256,7 @@ def test_preprocess_sales_FailOnTargetFeature(
     assert pipe.results is None
 
 
+@pytest.mark.forecast
 def test_process_sales_Success(sales_data_real_preproc):
     data = sales_data_real_preproc.copy()
     pipe = PipeResult(data, STATUS_HANDLER.SUCCESS)
@@ -277,6 +279,29 @@ def test_process_sales_Success(sales_data_real_preproc):
     assert pipe.statistics.xgb_params is not None
 
 
+@pytest.mark.forecast
+def test_process_sales_InvalidDates(sales_data_real_preproc):
+    false_date = Datetime(2519, 6, 30)
+    data = sales_data_real_preproc.copy()
+    data = data.iloc[:20, :]
+    data["buchungs_datum"] = data["buchungs_datum"].astype(object)
+    data.at[0, "buchungs_datum"] = false_date
+    assert data["buchungs_datum"].dtype.char == "O"
+    assert len(data) == 20
+    pipe = PipeResult(data, STATUS_HANDLER.SUCCESS)
+    pipe = fc._process_sales(
+        pipe,
+        min_num_data_points=36,
+        base_num_data_points_months=36,
+    )
+    assert pipe.status != STATUS_HANDLER.SUCCESS
+    assert pipe.status == STATUS_HANDLER.pipe_states.TOO_FEW_POINTS
+    assert pipe.data is None
+    assert pipe.results is None
+    assert pipe.statistics is not None
+
+
+@pytest.mark.forecast
 def test_process_sales_FailTooFewPoints(sales_data_real_preproc):
     data = sales_data_real_preproc.copy()
     data = data.iloc[:20, :]
@@ -303,6 +328,7 @@ def test_process_sales_FailTooFewPoints(sales_data_real_preproc):
     assert pipe.statistics.xgb_params is None
 
 
+@pytest.mark.forecast
 def test_process_sales_FailTooFewMonthPoints(sales_data_real_preproc):
     data = sales_data_real_preproc.copy()
     pipe = PipeResult(data, STATUS_HANDLER.SUCCESS)
@@ -329,8 +355,19 @@ def test_process_sales_FailTooFewMonthPoints(sales_data_real_preproc):
     assert pipe.statistics.xgb_params is None
 
 
+@pytest.mark.forecast
 def test_process_sales_FailNoReliableForecast(sales_data_real_preproc):
-    data = sales_data_real_preproc.copy()
+    # prepare fake data
+    df = sales_data_real_preproc.copy()
+    f_dates = "buchungs_datum"
+    end = datetime.datetime.now()
+    start = df[f_dates].max()
+    fake_dates = pd.date_range(start, end, freq="MS")
+    fake_data = [(1234, 1014, 1024, 1000, 10, date) for date in fake_dates]
+    fake_df = pd.DataFrame(fake_data, columns=df.columns)
+    enhanced_df = pd.concat((df, fake_df), ignore_index=True)
+
+    data = enhanced_df.copy()
     data["betrag"] = 10000
     print(data["betrag"])
     data = data.iloc[:20000, :]
@@ -340,7 +377,7 @@ def test_process_sales_FailNoReliableForecast(sales_data_real_preproc):
         def __init__(self, *args, **kwargs) -> None:
             class Predictor:
                 def predict(self, *args, **kwargs):
-                    return np.array([1, 1, 1, 1])
+                    return np.array([1, 1, 1, 1], dtype=np.float64)
 
             self.best_estimator_ = Predictor()
 
@@ -354,7 +391,7 @@ def test_process_sales_FailNoReliableForecast(sales_data_real_preproc):
         pipe = fc._process_sales(
             pipe,
             min_num_data_points=1,
-            base_num_data_points_months=-100,
+            base_num_data_points_months=1,
         )
 
     assert pipe.status != STATUS_HANDLER.SUCCESS
@@ -415,27 +452,20 @@ def test_export_on_fail():
     assert res.status.description == status.description
 
 
-@patch("delta_barth.analysis.forecast.SALES_BASE_NUM_DATAPOINTS_MONTHS", 1)
+@patch("delta_barth.session.CFG_HOT_RELOAD", False)
 def test_pipeline_sales_forecast_SuccessDbWrite(exmpl_api_sales_prognosis_resp, session):
-    with patch(
-        "delta_barth.analysis.forecast.get_sales_prognosis_data",
-    ) as mock:
-        mock.return_value = exmpl_api_sales_prognosis_resp, STATUS_HANDLER.SUCCESS
-        with patch("delta_barth.analysis.forecast.SESSION", session):
-            result = fc.pipeline_sales_forecast(None)  # type: ignore
-    print(result)
-    assert result.status == STATUS_HANDLER.SUCCESS
-    assert len(result.response.daten) > 0
-
-
-@patch("delta_barth.analysis.forecast.SALES_BASE_NUM_DATAPOINTS_MONTHS", 1)
-def test_pipeline_sales_forecast_FailDbWrite(exmpl_api_sales_prognosis_resp):
-    with patch(
-        "delta_barth.analysis.forecast.get_sales_prognosis_data",
-    ) as mock:
-        mock.return_value = exmpl_api_sales_prognosis_resp, STATUS_HANDLER.SUCCESS
-        result = fc.pipeline_sales_forecast(None)  # type: ignore
-    print(result)
+    assert session.cfg.forecast.threshold_month_data_points is not None
+    date = Datetime(2023, 8, 15)
+    company_ids = [5661, 1027, 1024]
+    with (
+        patch(
+            "delta_barth.analysis.forecast.get_sales_prognosis_data",
+        ) as get_mock,
+        patch("delta_barth.analysis.forecast.SESSION", session) as sess_mock,
+    ):
+        get_mock.return_value = exmpl_api_sales_prognosis_resp, STATUS_HANDLER.SUCCESS
+        sess_mock.cfg.forecast.threshold_month_data_points = 1
+        result = fc.pipeline_sales_forecast(session, company_ids, date)  # type: ignore
     assert result.status == STATUS_HANDLER.SUCCESS
     assert len(result.response.daten) > 0
 

tests/api/test_requests.py

@@ -1,45 +1,44 @@
 from datetime import datetime as Datetime
 
 import pytest
+import requests
 
 from delta_barth.api import requests as requests_
 
 
 @pytest.mark.api_con_required
 def test_get_sales_prognosis_data_Success(session):
-    resp, status = session.login()
+    # do not login: let routine do it
     # test without company ID
-    assert status.code == 0
-    date = Datetime(2022, 6, 1)
+    date = Datetime(2023, 12, 15)
     resp, status = requests_.get_sales_prognosis_data(session, None, date)
     assert status.code == 0
     assert len(resp.daten) > 0
-    date = Datetime(2030, 1, 1)
+    date = Datetime(2520, 1, 1)
     resp, status = requests_.get_sales_prognosis_data(session, None, date)
     assert status.code == 0
     assert len(resp.daten) == 0
     # test with company ID
     assert status.code == 0
-    date = Datetime(2022, 6, 1)
-    company_id = 1024
-    resp, status = requests_.get_sales_prognosis_data(session, company_id, date)
+    date = Datetime(2023, 8, 15)
+    company_ids = [5661, 1027]
+    resp, status = requests_.get_sales_prognosis_data(session, company_ids, date)
     assert status.code == 0
     assert len(resp.daten) > 0
-    date = Datetime(2030, 1, 1)
-    resp, status = requests_.get_sales_prognosis_data(session, company_id, date)
+    date = Datetime(2520, 1, 1)
+    resp, status = requests_.get_sales_prognosis_data(session, company_ids, date)
     assert status.code == 0
     assert len(resp.daten) == 0
     # test with non-existent company ID
     assert status.code == 0
     date = Datetime(2022, 6, 1)
-    company_id = 1000024
-    resp, status = requests_.get_sales_prognosis_data(session, company_id, date)
-    # TODO check if this behaviour is still considered "successful"
+    company_ids = [1000024]
+    resp, status = requests_.get_sales_prognosis_data(session, company_ids, date)
     assert status.code == 0
     assert len(resp.daten) == 0
     # test without date
-    company_id = 1024
-    resp, status = requests_.get_sales_prognosis_data(session, company_id, None)
+    company_ids = [1024]
+    resp, status = requests_.get_sales_prognosis_data(session, company_ids, None)
     assert status.code == 0
     assert len(resp.daten) > 0
     # test without filters
@@ -52,12 +51,11 @@ def test_get_sales_prognosis_data_Success(session):
 
 
 @pytest.mark.api_con_required
-def test_get_sales_prognosis_data_FailLogin(session, mock_get):
-    session.login()
-    code = 500
+def test_get_sales_prognosis_data_NoAuth(session, mock_get):
+    code = 401
     json = {
         "message": "ServerError",
-        "code": "TestExternalServerError",
+        "code": "TestFailAuth",
         "hints": "TestCase",
     }
     mock_get.return_value.status_code = code
@@ -74,6 +72,36 @@ def test_get_sales_prognosis_data_FailLogin(session, mock_get):
     assert status.api_server_error.hints == json["hints"]
 
 
+def test_get_sales_prognosis_data_FailLogin(session, mock_get, mock_put):
+    code = 401
+    json = {
+        "message": "ServerError",
+        "code": "TestFailAuth",
+        "hints": "TestCase",
+    }
+    mock_get.return_value.status_code = code
+    mock_get.return_value.json.return_value = json
+
+    code_put = 500
+    json_put = {
+        "message": "ServerError",
+        "code": "TestUnknownError",
+        "hints": "TestCase",
+    }
+    mock_put.return_value.status_code = code_put
+    mock_put.return_value.json.return_value = json_put
+
+    resp, status = requests_.get_sales_prognosis_data(session, None, None)
+    assert resp is not None
+    assert len(resp.daten) == 0
+    assert status.code == 400
+    assert status.api_server_error is not None
+    assert status.api_server_error.status_code == code_put
+    assert status.api_server_error.message == json_put["message"]
+    assert status.api_server_error.code == json_put["code"]
+    assert status.api_server_error.hints == json_put["hints"]
+
+
 @pytest.mark.api_con_required
 def test_get_sales_prognosis_data_FailApiServer(session, mock_get):
     code = 405
@@ -94,3 +122,21 @@ def test_get_sales_prognosis_data_FailApiServer(session, mock_get):
     assert status.api_server_error.message == json["message"]
     assert status.api_server_error.code == json["code"]
     assert status.api_server_error.hints == json["hints"]
+
+
+def test_get_sales_prognosis_data_FailGetTimeout(session, mock_get):
+    mock_get.side_effect = requests.exceptions.Timeout("Test timeout")
+
+    resp, status = requests_.get_sales_prognosis_data(session, None, None)
+    assert resp is not None
+    assert len(resp.daten) == 0
+    assert status.code == 1
+
+
+def test_get_sales_prognosis_data_FailGetRequestException(session, mock_get):
+    mock_get.side_effect = requests.exceptions.RequestException("Test not timeout")
+
+    resp, status = requests_.get_sales_prognosis_data(session, None, None)
+    assert resp is not None
+    assert len(resp.daten) == 0
+    assert status.code == 2

tests/conftest.py

@@ -8,6 +8,7 @@ from unittest.mock import patch
 
 import pandas as pd
 import pytest
+import tomli_w
 
 import delta_barth.session
 from delta_barth.api.requests import SalesPrognosisResponse
@@ -33,6 +34,28 @@ def api_base_url(credentials) -> str:
     return credentials["base_url"]
 
 
+@pytest.fixture(scope="session")
+def pth_dummy_cfg() -> Path:
+    pwd = Path.cwd()
+    assert "barth" in pwd.parent.name.lower(), "not in project root directory"
+    data_pth = pwd / "./tests/_test_data/dopt-cfg.toml"
+    assert data_pth.exists(), "file to dummy CFG not found"
+    return data_pth
+
+
+@pytest.fixture(scope="function")
+def pth_cfg(pth_dummy_cfg, tmp_path) -> Path:
+    with open(pth_dummy_cfg, "rb") as file:
+        cfg_data = tomllib.load(file)
+
+    target = tmp_path / "dummy_cfg.toml"
+    target.touch()
+    with open(target, "wb") as file:
+        tomli_w.dump(cfg_data, file)
+
+    return target
+
+
 @pytest.fixture(scope="session")
 def sales_data_real() -> pd.DataFrame:
     pwd = Path.cwd()
@@ -95,7 +118,7 @@ def mock_put():
         yield mock
 
 
-@pytest.fixture
+@pytest.fixture(scope="function")
 def mock_get():
     with patch("requests.get") as mock:
         yield mock

tests/test_config.py

@@ -0,0 +1,40 @@
+import tomllib
+
+import tomli_w
+
+from delta_barth import config
+
+
+def test_CfgLoader_Init(pth_cfg):
+    loader = config.LazyCfgLoader(pth_cfg)
+
+    assert loader.path == pth_cfg
+    assert loader._cfg is None
+
+
+def test_CfgLoader_Get(pth_cfg):
+    loader = config.LazyCfgLoader(pth_cfg)
+
+    parsed_cfg = loader.get()
+    assert isinstance(parsed_cfg, config.Config)
+    assert parsed_cfg.forecast.threshold_month_data_points == 28
+
+
+def test_CfgLoader_Reload(pth_cfg):
+    loader = config.LazyCfgLoader(pth_cfg)
+
+    parsed_cfg = loader.get()
+    assert isinstance(parsed_cfg, config.Config)
+    assert parsed_cfg.forecast.threshold_month_data_points == 28
+    # modify config and reload
+    with open(pth_cfg, "rb") as file:
+        cfg_data = tomllib.load(file)
+    cfg_data["forecast"]["threshold_month_data_points"] = 30
+    with open(pth_cfg, "wb") as file:
+        tomli_w.dump(cfg_data, file)
+
+    assert parsed_cfg.forecast.threshold_month_data_points == 28
+    loader.reload()
+    parsed_cfg = loader.get()
+    assert isinstance(parsed_cfg, config.Config)
+    assert parsed_cfg.forecast.threshold_month_data_points == 30

tests/test_env.py

@@ -0,0 +1,49 @@
+import importlib
+import sys
+from unittest.mock import patch
+
+import pytest
+
+import delta_barth.constants
+from delta_barth import _env
+
+
+@patch("delta_barth._env.PY_RUNTIME_FOLDER", "test123456")
+def test_prepare_env_NoRuntimeFolder(tmp_path):
+    ret = _env.prepare_env(tmp_path)
+    assert ret is None
+
+
+@patch("delta_barth._env.PY_RUNTIME_FOLDER", "base")
+def test_prepare_env_FailNoInterpreter(tmp_path_factory):
+    mocked_lib_pth = tmp_path_factory.mktemp("path") / "to/base/folder/lib/"
+    mocked_lib_pth.mkdir(parents=True, exist_ok=True)
+    with pytest.raises(FileNotFoundError):
+        _ = _env.prepare_env(mocked_lib_pth)
+
+
+@patch("delta_barth._env.PY_RUNTIME_FOLDER", "base")
+def test_prepare_env_Success(tmp_path_factory):
+    mocked_lib_pth = tmp_path_factory.mktemp("path") / "to/base/folder/lib/"
+    mocked_lib_pth.mkdir(parents=True, exist_ok=True)
+    rt_path = mocked_lib_pth.parents[1]
+    mocked_interpreter = rt_path / "python.exe"
+    mocked_interpreter.touch()
+    assert mocked_interpreter.exists()
+    ret = _env.prepare_env(mocked_lib_pth)
+    assert ret == rt_path
+    # sys attributes
+    executable = getattr(sys, "executable")
+    assert executable == str(mocked_interpreter)
+    base_executable = getattr(sys, "_base_executable")
+    assert base_executable == str(mocked_interpreter)
+
+    class MockPath:
+        def __init__(self, *args, **kwargs):
+            self.parent = mocked_lib_pth
+
+    with patch("pathlib.Path", MockPath):
+        (mocked_lib_pth / "_dummy_data").mkdir(exist_ok=True)
+        importlib.reload(delta_barth.constants)
+        assert delta_barth.constants.DEPLOYMENT_STATUS
+        assert delta_barth.constants.RUNTIME_PATH == rt_path

tests/test_pipelines.py

@@ -1,22 +1,65 @@
-import importlib
 import json
+from datetime import datetime as Datetime
 from unittest.mock import patch
 
 import pytest
+import sqlalchemy as sql
 
-import delta_barth.pipelines
+from delta_barth import databases as db
 from delta_barth import pipelines as pl
 from delta_barth.errors import STATUS_HANDLER
 
 
-@patch("delta_barth.analysis.forecast.SALES_BASE_NUM_DATAPOINTS_MONTHS", 1)
-def test_sales_prognosis_pipeline(exmpl_api_sales_prognosis_resp):
-    with patch(
-        "delta_barth.analysis.forecast.get_sales_prognosis_data",
-    ) as mock:
-        mock.return_value = (exmpl_api_sales_prognosis_resp, STATUS_HANDLER.SUCCESS)
-        importlib.reload(delta_barth.pipelines)
-        json_export = pl.pipeline_sales_forecast(None, None)
+def test_write_performance_metrics_Success(session):
+    pipe_name = "test_pipe"
+    t_start = 20_000_000_000
+    t_end = 30_000_000_000
+
+    with patch("delta_barth.pipelines.SESSION", session):
+        metrics = pl._write_performance_metrics(
+            pipeline_name=pipe_name,
+            time_start=t_start,
+            time_end=t_end,
+        )
+    assert metrics["pipeline_name"] == pipe_name
+    assert metrics["execution_duration"] == 10
+
+    with session.db_engine.begin() as con:
+        ret = con.execute(sql.select(db.perf_meas))
+
+    metrics = ret.all()[-1]
+    assert metrics.pipeline_name == pipe_name
+    assert metrics.execution_duration == 10
+
+
+def test_write_performance_metrics_FailStartingTime(session):
+    pipe_name = "test_pipe"
+    t_start = 30_000_000_000
+    t_end = 20_000_000_000
+
+    with patch("delta_barth.pipelines.SESSION", session):
+        with pytest.raises(ValueError):
+            _ = pl._write_performance_metrics(
+                pipeline_name=pipe_name,
+                time_start=t_start,
+                time_end=t_end,
+            )
+
+
+@patch("delta_barth.session.CFG_HOT_RELOAD", False)
+def test_sales_prognosis_pipeline(exmpl_api_sales_prognosis_resp, session, monkeypatch):
+    date = Datetime(2023, 8, 15)
+    company_ids = [5661, 1027, 1024]
+    with (
+        patch(
+            "delta_barth.analysis.forecast.get_sales_prognosis_data",
+        ) as get_mock,
+        patch("delta_barth.pipelines.SESSION", session),
+        patch("delta_barth.analysis.forecast.SESSION", session) as sess_mock,
+    ):
+        get_mock.return_value = (exmpl_api_sales_prognosis_resp, STATUS_HANDLER.SUCCESS)
+        sess_mock.cfg.forecast.threshold_month_data_points = 1
+        json_export = pl.pipeline_sales_forecast(company_ids, date)
 
     assert isinstance(json_export, str)
     parsed_resp = json.loads(json_export)
@@ -27,9 +70,17 @@ def test_sales_prognosis_pipeline(exmpl_api_sales_prognosis_resp):
     assert "code" in parsed_resp["status"]
     assert parsed_resp["status"]["code"] == 0
 
+    with session.db_engine.begin() as con:
+        ret = con.execute(sql.select(db.perf_meas))
 
-def test_sales_prognosis_pipeline_dummy():
-    json_export = pl.pipeline_sales_forecast_dummy(None, None)
+    metrics = ret.all()[-1]
+    assert metrics.pipeline_name == "sales_forecast"
+    assert metrics.execution_duration > 0
+
+
+def test_sales_prognosis_pipeline_dummy(session):
+    with patch("delta_barth.pipelines.SESSION", session):
+        json_export = pl.pipeline_sales_forecast_dummy(None, None)
 
     assert isinstance(json_export, str)
     parsed_resp = json.loads(json_export)
@@ -43,3 +94,10 @@ def test_sales_prognosis_pipeline_dummy():
     assert entry["vorhersage"] == pytest.approx(47261.058594)
     assert "code" in parsed_resp["status"]
     assert parsed_resp["status"]["code"] == 0
+
+    with session.db_engine.begin() as con:
+        ret = con.execute(sql.select(db.perf_meas))
+
+    metrics = ret.all()[-1]
+    assert metrics.pipeline_name == "sales_forecast_dummy"
+    assert metrics.execution_duration > 0

tests/test_session.py

@@ -1,15 +1,18 @@
+import tomllib
 from pathlib import Path
 from unittest.mock import patch
 
 import pytest
+import tomli_w
 
+import delta_barth.config
 import delta_barth.session
 from delta_barth import logging
 from delta_barth.constants import (
     DEFAULT_API_ERR_CODE,
     HTTP_BASE_CONTENT_HEADERS,
-    LOG_FILENAME,
 )
+from delta_barth.logging import LOG_FILENAME
 
 
 def test_validate_path_Success():
@@ -62,8 +65,82 @@ def test_session_setup_db_management(tmp_path):
     assert db_path.exists()
 
 
+def test_session_setup_config(tmp_path):
+    str_path = str(tmp_path)
+    foldername: str = "cfg_test"
+    target_cfg_dir = tmp_path / foldername
+    session = delta_barth.session.Session(HTTP_BASE_CONTENT_HEADERS, cfg_folder=foldername)
+    session.set_data_path(str_path)
+    cfg_path = session.cfg_path
+    assert cfg_path.parent.exists()
+    assert cfg_path.parent == target_cfg_dir
+    assert not cfg_path.exists()
+    session.setup()
+    cfg_path2 = session.cfg_path
+    assert cfg_path2 == cfg_path
+    assert session._cfg is not None
+    assert cfg_path.exists()
+    assert session.cfg.forecast.threshold_month_data_points == 28
+
+
+@patch("delta_barth.session.CFG_HOT_RELOAD", False)
+def test_session_reload_config_NoHotReload(tmp_path):
+    str_path = str(tmp_path)
+    foldername: str = "cfg_test"
+    target_cfg_dir = tmp_path / foldername
+    session = delta_barth.session.Session(HTTP_BASE_CONTENT_HEADERS, cfg_folder=foldername)
+    session.set_data_path(str_path)
+    cfg_path = session.cfg_path
+    assert cfg_path.parent.exists()
+    assert cfg_path.parent == target_cfg_dir
+    assert not cfg_path.exists()
+    session.setup()
+    assert cfg_path.exists()
+    parsed_cfg = session.cfg
+    assert isinstance(parsed_cfg, delta_barth.config.Config)
+    # modify config and reload
+    with open(cfg_path, "rb") as file:
+        cfg_data = tomllib.load(file)
+    cfg_data["forecast"]["threshold_month_data_points"] = 30
+    with open(cfg_path, "wb") as file:
+        tomli_w.dump(cfg_data, file)
+
+    assert session.cfg.forecast.threshold_month_data_points == 28
+
+    session.reload_cfg()
+    reload_cfg = session.cfg
+    assert isinstance(reload_cfg, delta_barth.config.Config)
+    assert reload_cfg.forecast.threshold_month_data_points == 30
+
+
+@patch("delta_barth.session.CFG_HOT_RELOAD", True)
+def test_session_reload_config_HotReload(tmp_path):
+    str_path = str(tmp_path)
+    foldername: str = "cfg_test"
+    target_cfg_dir = tmp_path / foldername
+    session = delta_barth.session.Session(HTTP_BASE_CONTENT_HEADERS, cfg_folder=foldername)
+    session.set_data_path(str_path)
+    cfg_path = session.cfg_path
+    assert cfg_path.parent.exists()
+    assert cfg_path.parent == target_cfg_dir
+    assert not cfg_path.exists()
+    session.setup()
+    assert cfg_path.exists()
+    parsed_cfg = session.cfg
+    assert isinstance(parsed_cfg, delta_barth.config.Config)
+    # modify config and reload
+    with open(cfg_path, "rb") as file:
+        cfg_data = tomllib.load(file)
+    cfg_data["forecast"]["threshold_month_data_points"] = 30
+    with open(cfg_path, "wb") as file:
+        tomli_w.dump(cfg_data, file)
+
+    assert session.cfg.forecast.threshold_month_data_points == 30
+
+
 @patch("delta_barth.logging.ENABLE_LOGGING", True)
 @patch("delta_barth.logging.LOGGING_TO_FILE", True)
+@patch("delta_barth.logging.LOGGING_TO_STDERR", True)
 def test_session_setup_logging(tmp_path):
     str_path = str(tmp_path)
     foldername: str = "logging_test"
@@ -237,11 +314,11 @@ def test_login_logout_FailApiServer(session, mock_put):
 
 
 @pytest.mark.api_con_required
-def test_assert_login_SuccessLoggedOut(session):
+def test_relogin_SuccessLoggedOut(session):
     assert session.session_token is None
     assert session._creds is not None
     # test logged out state
-    resp, status = session.assert_login()
+    resp, status = session.relogin()
     assert resp is not None
     assert status.code == 0
     assert session.session_token is not None
@@ -250,74 +327,17 @@ def test_assert_login_SuccessLoggedOut(session):
 
 
 @pytest.mark.api_con_required
-def test_assert_login_SuccessStillLoggedIn(session):
+def test_relogin_SuccessStillLoggedIn(session):
     assert session.session_token is None
     assert session._creds is not None
     resp, status = session.login()
-    resp, status = session.assert_login()
+    old_token = session.session_token
+    assert old_token is not None
+    resp, status = session.relogin()
     assert resp is not None
     assert status.code == 0
     assert session.session_token is not None
+    assert session.session_token != old_token
+
     resp, status = session.logout()
     assert status.code == 0
-
-
-@pytest.mark.api_con_required
-def test_assert_login_ReloginNoValidAuth(session, mock_get):
-    code = 401
-    json = {
-        "message": "AuthentificationError",
-        "code": "TestAssertLoginAfter",
-        "hints": "TestCase",
-    }
-    mock_get.return_value.status_code = code
-    mock_get.return_value.json.return_value = json
-
-    resp, status = session.login()
-
-    resp, status = session.assert_login()
-    assert resp is not None
-    assert status.code == 0
-    assert session.session_token is not None
-    resp, status = session.logout()
-    assert status.code == 0
-
-
-@pytest.mark.api_con_required
-def test_assert_login_ReloginWrongToken(session):
-    # triggers code 401
-    assert session.session_token is None
-    assert session._creds is not None
-    _, status = session.login()
-    assert status.code == 0
-    session._session_token = "WRONGTOKEN"
-    resp, status = session.assert_login()
-    assert resp is not None
-    assert status.code == 0
-    assert session.session_token is not None
-    resp, status = session.logout()
-    assert status.code == 0
-
-
-@pytest.mark.api_con_required
-def test_assert_login_FailApiServer(session, mock_get):
-    code = 500
-    json = {
-        "message": "ServerError",
-        "code": "TestExternalServerError",
-        "hints": "TestCase",
-    }
-    mock_get.return_value.status_code = code
-    mock_get.return_value.json.return_value = json
-
-    resp, status = session.login()
-
-    resp, status = session.assert_login()
-    assert resp is not None
-    assert not resp.token
-    assert status.code == 400
-    assert status.api_server_error is not None
-    assert status.api_server_error.status_code == code
-    assert status.api_server_error.message == json["message"]
-    assert status.api_server_error.code == json["code"]
-    assert status.api_server_error.hints == json["hints"]