diff --git a/.github/workflows/lint-actions.yaml b/.github/workflows/lint-actions.yaml index 9f7db0d..21cdbb3 100644 --- a/.github/workflows/lint-actions.yaml +++ b/.github/workflows/lint-actions.yaml @@ -53,7 +53,7 @@ jobs: - uses: actions/checkout@v3 - uses: chartboost/ruff-action@v1 with: - version: 0.0.277 + version: 0.0.287 python-requirements: name: Check Python Requirements diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 7af18bb..651f9b4 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -26,7 +26,7 @@ repos: - repo: https://github.com/astral-sh/ruff-pre-commit # Ruff version. - rev: v0.0.284 + rev: v0.0.287 hooks: - id: ruff args: [--fix, --exit-non-zero-on-fix] @@ -53,7 +53,7 @@ repos: - repo: https://github.com/pre-commit/mirrors-mypy - rev: v1.5.0 + rev: v1.5.1 hooks: - id: mypy additional_dependencies: @@ -68,7 +68,7 @@ repos: - id: md-toc - repo: https://github.com/python-poetry/poetry - rev: 1.5.0 + rev: 1.6.0 hooks: - id: poetry-check @@ -78,6 +78,6 @@ repos: - id: validate-html - repo: https://github.com/python-jsonschema/check-jsonschema - rev: 0.24.1 + rev: 0.26.3 hooks: - id: check-github-workflows diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index a131898..ac2c1ed 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -1,70 +1,72 @@ # Contribution guidelines +## Dev Setup + +- [Install Python 3.11](https://www.python.org/downloads/release/python-3111/) +- [Install Poetry](https://python-poetry.org/docs/#installation) +- [Install GiT](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git) +- [Configure GiT](https://support.atlassian.com/bitbucket-cloud/docs/configure-your-dvcs-username-for-commits/) +- [Generate an SSH Key](https://docs.github.com/en/authentication/connecting-to-github-with-ssh/generating-a-new-ssh-key-and-adding-it-to-the-ssh-agent) & [Add SSH Key to GitHub](https://docs.github.com/en/authentication/connecting-to-github-with-ssh/adding-a-new-ssh-key-to-your-github-account) +- [Clone the Project (IDE Specific)](https://docs.github.com/de/repositories/creating-and-managing-repositories/cloning-a-repository) +- [Install the python Project](https://python-poetry.org/docs/basic-usage/#installing-dependencies) +- [Install pre-commit](https://pre-commit.com/#install) + +## Repository structure + +- **src/`aki_prj23_transparenzregister`**: + - This subfolder/`package` contains several subdirectories: + - `ai`: + - Houses AI models and pipelines, including NER and sentiment analysis. + - `config`: + - Contains configuration files such as database connection strings and model files. + - `models`: + - Stores data models. + - `ui`: + - Manages the user interface and dash interface. + - `utils`: + - Contains general tooling functions, including database access and other miscellaneous functions. + +- **tests**: + - Test files organized in a mirrored structure of the 'src' folder. Please at least import every python file you + add. + Please Try to test every function with a test that compares with an example result. If that is not possible it + would be best to find a big consensus that only limited testing is required. ## Code style We defined to use the following formats: + - Whitespace Formatting by [Black](https://github.com/psf/black) -- Docstrings Style see the examples provided by [sphinx napoleon](https://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_google.html) Types in the docstrings are optional but should be consistent per module. +- Docstrings Style see the examples provided + by [sphinx napoleon](https://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_google.html) Types in the + docstrings are optional but should be consistent per module. - Import Order by [isort](https://pycqa.github.io/isort/) -- Strict Typing of function headers see the examples provided by the [mypy](https://mypy.readthedocs.io/en/stable/cheat_sheet_py3.html) documentation. +- Strict Typing of function headers see the examples provided by + the [mypy](https://mypy.readthedocs.io/en/stable/cheat_sheet_py3.html) documentation. +- The generell linting is done by ruff but since ruff is a reimplementation of ruff of many different linters the old + documentations are still valid. +- Ruff can be executed with the `ruff .` command. May errors are auto-fixable with `ruff --fix .` if they are straight + forward changes. ## Language -We decided to use english on everything close to code but will write longer texts that are not close to the code in german. +We decided to use english on everything close to code but will write longer texts that are not close to the code in +german. -## Pre-Commit installation +## Pre-Commit Usage -- clone the project -- install the following python package: - - `pre-commit` - -- execute the command `pre-commit install` to insert the git githook into your local repository. - - for more information read [Python Pre-Commit](https://pre-commit.com/) - - the following code format rules are so enforced: - - Whitespace formatierung: - - Python-[Black](https://github.com/psf/black) - - leading whitespace in all files - - Auto format: yaml, toml, ini +- the following code format rules are so enforced: + - Whitespace formatting: + - Python-[Black](https://github.com/psf/black) + - leading whitespace in all files + - Auto format: yaml, toml, ini - Import norm by: - - [isort](https://pycqa.github.io/isort/) - - absolut module path - - Validierung: - - yaml, toml, json, xml - - Secret detection - - python normen ([pep8](https://peps.python.org/pep-0008/)) with [flake8](https://flake8.pycqa.org/en/latest/) - - type checking with ([mypy](https://github.com/python/mypy)) - -- Install [Python 3.11](https://www.python.org/downloads/release/python-3111/) -- Install Poetry -``` -pip install poetry -``` -- Install dependencies -``` -poetry install -``` - -## Setup - -### Connection strings -Create a `secrets.json` in the root of this repo with the following structure (values to be replaces by desired config): -```json - { - "postgres": { - "username": "postgres", - "password": "postgres", - "host": "localhost", - "database": "postgres", - "port": 5432 - }, - "mongo": { - "username": "username", - "password": "password", - "host": "localhost", - "database": "transparenzregister", - "port": 27017 - } - } -``` -Example usage see [connector.py](./src/aki_prj23_transparenzregister/utils/postgres/connector.py) + - [isort](https://pycqa.github.io/isort/) + - absolut module path + - Validation: + - yaml, toml, json, xml + - Secret detection + - python norms ([pep8](https://peps.python.org/pep-0008/)) + with [ruff](https://github.com/astral-sh/ruff) + - type checking with ([mypy](https://github.com/python/mypy)) +- for more information read [Python Pre-Commit](https://pre-commit.com/) diff --git a/README.md b/README.md index bef0fbe..bc669d1 100644 --- a/README.md +++ b/README.md @@ -1,13 +1,39 @@ # aki_prj23_transparenzregister -[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff) +[![python](https://img.shields.io/badge/Python-3.11-3776AB.svg?style=flat&logo=python&logoColor=white)](https://www.python.org) [![Actions status](https://github.com/astral-sh/ruff/workflows/CI/badge.svg)](https://github.com/astral-sh/ruff/actions) -[![Pytest](https://github.com/fhswf/aki_prj23_transparenzregister/actions/workflows/test-action.yaml/badge.svg?branch=main)](https://github.com/fhswf/aki_prj23_transparenzregister/actions/workflows/test-action.yaml) -[![Python-Lint-Push-Action](https://github.com/fhswf/aki_prj23_transparenzregister/actions/workflows/lint-actions.yaml/badge.svg)](https://github.com/fhswf/aki_prj23_transparenzregister/actions/workflows/lint-actions.yaml) +[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff) +[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit) +[![Checked with mypy](http://www.mypy-lang.org/static/mypy_badge.svg)](http://mypy-lang.org/) +[![Documentation Status](https://readthedocs.org/projects/mypy/badge/?version=stable)](https://mypy.readthedocs.io/en/stable/?badge=stable) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) ## Contributions See the [CONTRIBUTING.md](CONTRIBUTING.md) about how code should be formatted and what kind of rules we set ourselves. -[![bandit](https://github.com/fhswf/aki_prj23_transparenzregister/actions/workflows/bandit-action.yaml/badge.svg)](https://github.com/fhswf/aki_prj23_transparenzregister/actions/workflows/bandit-action.yaml) +## DB Connection settings + +To connect to the SQL db see [sql/connector.py](./src/aki_prj23_transparenzregister/utils/postgres/connector.py) +To connect to the Mongo db see [connect] + +Create a `secrets.json` in the root of this repo with the following structure (values to be replaces by desired config): + +```json + { + "postgres": { + "username": "postgres", + "password": "postgres", + "host": "localhost", + "database": "postgres", + "port": 5432 + }, + "mongo": { + "username": "username", + "password": "password", + "host": "localhost", + "database": "transparenzregister", + "port": 27017 + } +} +``` diff --git a/documentations/index.rst b/documentations/index.rst index 4a4ec1d..20efae3 100644 --- a/documentations/index.rst +++ b/documentations/index.rst @@ -4,6 +4,11 @@ Transparenzregister Dokumentation ================================= This is the documentation for the AKI project group on the german transparenzregister and an Analysis there of. +.. include:: ../README.md + :parser: myst_parser.sphinx_ +.. include:: ../CONTRIBUTING.md + :parser: myst_parser.sphinx_ + .. toctree:: :maxdepth: 3 :caption: Project Management diff --git a/documentations/meeting-notes/Meeting_2023-06-09.md b/documentations/meeting-notes/Meeting_2023-06-09.md index 5570e7f..4626e57 100644 --- a/documentations/meeting-notes/Meeting_2023-06-09.md +++ b/documentations/meeting-notes/Meeting_2023-06-09.md @@ -1,6 +1,7 @@ -# Weekly *5*: 09.06.2023 +# Weekly *6*: 09.06.2023 ## Teilnehmer + - Prof. Arinir - Tristan Nolde - Tim Ronneburg @@ -12,79 +13,86 @@ ## Themen - Stepstone Projekt: - - Gewünscht wird ein initialer Austausch mit Stepstone - - Befürchtung ist, dass es zu einem Hinderniss wird - - Entscheidung liegt daher beim Projekt-Team - - Weitere Informationen sind nicht aktuell nicht vorhanden - - Vorschlag Prof. Arinir: Sollte das Thema nochmal zum Team getragen werden, wird der aktuelle Stand vorgestellt und der Link zum Repo wird geteilt. Darüber hinaus werden keine Ressourcen zugesprochen. - - Vorstellung [vorheriger Absprache](https://github.com/orgs/fhswf/projects/17?pane=issue&itemId=29707639) und Feedback: - - Ändert sich der Scope - Nein - - NDA - Nein - - Veröffentlichung - maximal Impressionen - - Was muss geleistet werden - nicht direkt an Stepstone sondern über FH als Mediator + - Gewünscht wird ein initialer Austausch mit Stepstone + - Befürchtung ist, dass es zu einem Hinderniss wird + - Entscheidung liegt daher beim Projekt-Team + - Weitere Informationen sind nicht aktuell nicht vorhanden + - Vorschlag Prof. Arinir: Sollte das Thema nochmal zum Team getragen werden, wird der aktuelle Stand vorgestellt und + der Link zum Repo wird geteilt. Darüber hinaus werden keine Ressourcen zugesprochen. + - Vorstellung [vorheriger Absprache](https://github.com/orgs/fhswf/projects/17?pane=issue&itemId=29707639) und + Feedback: + - Ändert sich der Scope - Nein + - NDA - Nein + - Veröffentlichung - maximal Impressionen + - Was muss geleistet werden - nicht direkt an Stepstone sondern über FH als Mediator - Sollen Präsentationen vorab zur Verfügung gestellt werden? - - Einige Tage vorher in das Git Repo. hochladen und Prof. Arinir benachrichtigen + - Einige Tage vorher in das Git Repo. hochladen und Prof. Arinir benachrichtigen - Rücksprache Seminarpräsentationen - - Verflechtungsanalyse: - - Graphen Theorie - - Social Network Analyse - - Erweiterung über Graphen Theorie hinaus - - Fokus auf Anwendung und Mehrwert, weniger genauer mathematischer Lösung - - Feedback: - - Präsentation scheint sehr umfangreich; Wunsch nach Reduzierung der Folienanzahl - - Formeln hinter den Analysen spannend, ggf. doch drauf eingehen, um Kennzahl in Kontext zu setzen - - Visualiserung: - - Prinzipien - - Vorteile - - Bibliotheken für Umsetzung (Network X, PyViz, ...) - - Effekt von Farbwahl - - Erste Umsetzung im Jupyter Notebook - - Feedback: - - Es werden extem viele Datenpunkte angezeigt werden müssen, wie wird dies in den Bibliotheken umgesetzt? Kann dort gefiltert werden? - - Wenn nicht direkt am Graphen (der Darstellung) gefiltert werden kann, dann frühzeitig filtern, bevor der Graph gebaut wird - - Datenspeicherung - - Erste Integration von Visualisierung mit Datenspeicherung - - Vorstellung der "Datencluster" - - Stammdaten - - Stimmungsdaten - - Social Graph - - Zeitseriendaten - - Relationales DB Modell - - Fokus ebenfalls auf Abfrage der Daten für Folge-Projekte wie Visualiserung und Mehrwert fürs Team, weniger Theorie - - Feedback: - - Es müssen Erfahrungen mit der Library und Darstellung gesammelt werden, um den Mehrwert der Lösung hervorzuheben - - Modellierung der Finzanz-Kennzahlen - - Spaltennamen sollen sprechend sein, z.B. "value" statt "sum" - - Präferenz zum Modell mit einzelnem Eintrag mit mehren Kennzahl Spalten stallt generischer Lösung über Enum - - Text Mining - - Fokus auf Sentiment Analyse - - Vergleich verschiedener Lösungen und ML Modelle - - Abschließendes Fazit, welches Tool am besten geeignet ist - - Daten Extraktion - - Fokus auf Web Mining/Scraping im Rahmen des Transparenzregisters - - Datenquellen - - API - - Websites (HTML) - - PDF - - Datenextraktion aus diesen Quellen - - Orchestrierung mit Airflow - - DevOps - - Dependency Management in Python - - Standard requirements.txt - - pip-tools - - poetry - - Vorteile von Lintern - - GitHub - - Actions - - Security - - etc. - - Feedback: - - Git wird als State-of-the-Art angesehen und muss nicht näher erläutert werden + - Verflechtungsanalyse: + - Graphen Theorie + - Social Network Analyse + - Erweiterung über Graphen Theorie hinaus + - Fokus auf Anwendung und Mehrwert, weniger genauer mathematischer Lösung + - Feedback: + - Präsentation scheint sehr umfangreich; Wunsch nach Reduzierung der Folienanzahl + - Formeln hinter den Analysen spannend, ggf. doch drauf eingehen, um Kennzahl in Kontext zu setzen + - Visualiserung: + - Prinzipien + - Vorteile + - Bibliotheken für Umsetzung (Network X, PyViz, ...) + - Effekt von Farbwahl + - Erste Umsetzung im Jupyter Notebook + - Feedback: + - Es werden extem viele Datenpunkte angezeigt werden müssen, wie wird dies in den Bibliotheken umgesetzt? + Kann dort gefiltert werden? + - Wenn nicht direkt am Graphen (der Darstellung) gefiltert werden kann, dann frühzeitig filtern, bevor + der Graph gebaut wird + - Datenspeicherung + - Erste Integration von Visualisierung mit Datenspeicherung + - Vorstellung der "Datencluster" + - Stammdaten + - Stimmungsdaten + - Social Graph + - Zeitseriendaten + - Relationales DB Modell + - Fokus ebenfalls auf Abfrage der Daten für Folge-Projekte wie Visualiserung und Mehrwert fürs Team, weniger + Theorie + - Feedback: + - Es müssen Erfahrungen mit der Library und Darstellung gesammelt werden, um den Mehrwert der Lösung + hervorzuheben + - Modellierung der Finzanz-Kennzahlen + - Spaltennamen sollen sprechend sein, z.B. "value" statt "sum" + - Präferenz zum Modell mit einzelnem Eintrag mit mehren Kennzahl Spalten stallt generischer Lösung über + Enum + - Text Mining + - Fokus auf Sentiment Analyse + - Vergleich verschiedener Lösungen und ML Modelle + - Abschließendes Fazit, welches Tool am besten geeignet ist + - Daten Extraktion + - Fokus auf Web Mining/Scraping im Rahmen des Transparenzregisters + - Datenquellen + - API + - Websites (HTML) + - PDF + - Datenextraktion aus diesen Quellen + - Orchestrierung mit Airflow + - DevOps + - Dependency Management in Python + - Standard requirements.txt + - pip-tools + - poetry + - Vorteile von Lintern + - GitHub + - Actions + - Security + - etc. + - Feedback: + - Git wird als State-of-the-Art angesehen und muss nicht näher erläutert werden ## Abgeleitete Action Items -| Action Item | Verantwortlicher | Deadline | -|-------------|------------------|-----------------| -| Folien hochladen | Projekt Team | vor Präsentationstermin | -| Absprache Abgrenzung von Verflechtungsanalyse und Visualisierung | Tim und Kim | nächster Abgleich | -| Deployment Plan aufstellen | Projekt Team | nach Seminararbeiten | +| Action Item | Verantwortlicher | Deadline | +|------------------------------------------------------------------|------------------|-------------------------| +| Folien hochladen | Projekt Team | vor Präsentationstermin | +| Absprache Abgrenzung von Verflechtungsanalyse und Visualisierung | Tim und Kim | nächster Abgleich | +| Deployment Plan aufstellen | Projekt Team | nach Seminararbeiten | diff --git a/documentations/meeting-notes/Meeting_2023-08-03.md b/documentations/meeting-notes/Meeting_2023-08-03.md index 74cb8ca..2c3199e 100644 --- a/documentations/meeting-notes/Meeting_2023-08-03.md +++ b/documentations/meeting-notes/Meeting_2023-08-03.md @@ -1,6 +1,7 @@ -# Weekly *X*: 03.08.2023 +# Weekly *7*: 03.08.2023 ## Teilnehmer + - Prof. Arinir - Tristan Nolde - Tim Ronneburg (Protokollant) @@ -9,19 +10,19 @@ ## Themen - Präsentieren der Ergebnisse der letzten Wochen: - - Named Entity Recognition - - Vorstellung Datenbank auf dem FH-Cluster: - - Mongo Connector - - Datenspeicherung auf dem Cluster + - Named Entity Recognition + - Vorstellung Datenbank auf dem FH-Cluster: + - Mongo Connector + - Datenspeicherung auf dem Cluster - Weitere Vorgehensweise: - - Idee: Kleine Workshops/Teams - - In 2er Teams die einzelnen Funktionen über Feature Branches erstellen + - Idee: Kleine Workshops/Teams + - In 2er Teams die einzelnen Funktionen über Feature Branches erstellen ## Abgeleitete Action Items -| Action Item | Verantwortlicher | Deadline | -|-------------|------------------|-----------------| -| Mergen aller Branches zu jedem neuen Termin mit Herrn Arinir | Jeder | jedes Weekly | -| Erstellen der Pipelines | Sebastian, Tristan und Tim | nächstes Weekly | -| Erstellen der Development Datenbank-Instanzen je Entwickler | Sebastian, Tristan und Tim | nächstes Weekly | -| Anlegen der relationalen Postgres DB via Script auf den FH-Cluster | Sebastian, Tristan und Tim | nächstes Weekly | +| Action Item | Verantwortlicher | Deadline | +|--------------------------------------------------------------------|----------------------------|-----------------| +| Mergen aller Branches zu jedem neuen Termin mit Herrn Arinir | Jeder | jedes Weekly | +| Erstellen der Pipelines | Sebastian, Tristan und Tim | nächstes Weekly | +| Erstellen der Development Datenbank-Instanzen je Entwickler | Sebastian, Tristan und Tim | nächstes Weekly | +| Anlegen der relationalen Postgres DB via Script auf den FH-Cluster | Sebastian, Tristan und Tim | nächstes Weekly | diff --git a/documentations/meeting-notes/Meeting_2023-08-17.md b/documentations/meeting-notes/Meeting_2023-08-17.md new file mode 100644 index 0000000..dc2e56b --- /dev/null +++ b/documentations/meeting-notes/Meeting_2023-08-17.md @@ -0,0 +1,44 @@ +# Weekly *8*: 17.08.2023 + +## Teilnehmer + +- Prof. Arinir +- Tristan Nolde +- Tim Ronneburg +- Kim Mesewinkel-Risse +- Phillip Horstenkamp +- Sebastian Zeleny (Protokollant) + +## Themen + +- Welche Services laufen aktuell auf dem Uni-Cluster? + - MongoDB und Postgres mit personalisiertem Zugang über VPN + - **Requirement:** Das Frontend bzw. Visualisierung soll auf dem Cluster laufen, wofür ein Login erwünscht ist, wie + z.B. SSO + - die Services (Text Mining, NER, Sentiment) sollten auch dem Cluster laufen + - Wo sollen CI/CD laufen? + - benötigt werden 2-3 Container für Worker und Services +- ProductionDB: + - DB "transparenzregister" für Produktiveinsatz + - persönliche DB "DB_*Name*" für Development + - Erklärung des Postgres Connectors, welcher die SQL-Alchemy Klassen verwendet, um Tabellen zu erstellen + - Erklärung wie der Connection-String mit dem JsonConfigProvider und der secret.json erzeugt wird +- UI: + - Vorstellung der ersten Visualisierung mit Plotly und Anbindung an ProductionDB + - Dash startet im Hintergrund einen http-Server, welcher über den Port 8050 erreichbar ist + - Dash wird für das Dashboarding verwendet und wird (bei Bedarf) durch weitere Komponenten erweitert +- Abschluß des PoC und Umsetzung der bestehenden Architektur + +## Abgeleitete Action Items + +| Action Item | Verantwortlicher | Deadline | +|------------------------------------------------------------------|------------------|-----------------| +| Anfrage nach Serverressourcen für 2-3 Container bei Prof. Gawron | Prof. Arinir | nächstes Weekly | +| Repo-Struktur dokumentieren | Phillip, Tristan | nächstes Weekly | +| Anlegen von MongoDB-Instanzen für NER und Sentiment | Tristan | nächstes Weekly | +| NER für News | Sebastian | nächstes Weekly | +| Beispiel für MongoConnector | Sebastian | nächstes Weekly | +| Script um News auf Uni-Cluster zu dumpen | Tristan | nächstes Weekly | +| Finanzdaten aus Bundesanzeiger | Tristan | nächstes Weekly | +| Plotly Frontend weiterentwickeln | Kim, Tim | nächstes Weekly | +| Refactoring der SQL-Alchemy Klassen | Phillip | nächstes Weekly | diff --git a/documentations/meeting-notes/Meeting_2023-08-31.md b/documentations/meeting-notes/Meeting_2023-08-31.md new file mode 100644 index 0000000..a77acc8 --- /dev/null +++ b/documentations/meeting-notes/Meeting_2023-08-31.md @@ -0,0 +1,40 @@ +# Weekly *9*: 31.08.2023 + +## Teilnehmer + +- Prof. Arinir +- Tristan Nolde +- Philipp Horstenkamp +- Sebastian Zeleny +- Kim Mesewinkel-Risse (Protokoll) + +## Themen + +- Rückmeldung von Herrn Gawron bzgl. mehr Ressourcen steht noch aus, ggfs. persönliche Absprache nächste Woche möglich + +- Rückfrage von Herrn Arinir bezüglich Aufbau der Software und Architektur + - Gerade werden einzelne Funktionen erstellt, Daten werden ungefiltert in die Mongo DB geschrieben, anschließend + Bereinigung und Übertragung in die Postgres + - Vorstellung aktueller Repo-Struktur durch Tristan, relevanter Code befindet sich im src-Ordner + +- Wie kann sichergestellt werden, dass unsere Ziele erreicht werden? + - Zeitplan/Meilensteinplan gewünscht + - Wann soll was erreicht werden? + - Burndown-Diagramm + -> Umsetzung durch Team beim Präsenzmeeting am 09.09.2023 + +- Kurze Vorstellung der bearbeiteten Themen: NER + Sentiment (Sebastian), Finanzdaten (Tristan), UI (Kim), + Datentransfer (Philipp) + +## Abgeleitete Action Items + +| Action Item | Verantwortlicher | Deadline | +|------------------------------------------------------|------------------|-----------------| +| Festlegung Zeitplan für Präsenztreffen | Alle | 07.09.2023 | +| Zeitplan bzw. Meilensteinplan | Alle | nächstes Weekly | +| Erstellen einer Übersicht aller bestehenden Services | Alle | nächstes Weekly | +| Update bzgl. Cluster und Ressourcen | Herr Arinir | nächstes Weekly | +| Finanzdaten finalisieren | Tristan | nächstes Weekly | +| NER/Sentiment Aggregation | Sebastian | nächstes Weekly | +| Füllen der UI mit Echtdaten | Kim | nächstes Weekly | +| Teststruktur für SQL hinzufügen | Philipp | nächstes Weekly | diff --git a/poetry.lock b/poetry.lock index da63a0b..a2368dd 100644 --- a/poetry.lock +++ b/poetry.lock @@ -28,13 +28,13 @@ test = ["pytest", "pytest-cov"] [[package]] name = "anyio" -version = "3.7.1" +version = "4.0.0" description = "High level compatibility layer for multiple asynchronous event loop implementations" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" files = [ - {file = "anyio-3.7.1-py3-none-any.whl", hash = "sha256:91dee416e570e92c64041bd18b900d1d6fa78dff7048769ce5ac5ddad004fbb5"}, - {file = "anyio-3.7.1.tar.gz", hash = "sha256:44a3c9aba0f5defa43261a8b3efb97891f2bd7d804e0e1f56419befa1adfc780"}, + {file = "anyio-4.0.0-py3-none-any.whl", hash = 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"sphinx-rtd-theme (>=1.1.0)"] optional = ["python-socks", "wsaccel"] test = ["websockets"] @@ -5463,7 +5545,10 @@ files = [ [package.dependencies] h11 = ">=0.9.0,<1" +[extras] +ingest = ["selenium"] + [metadata] lock-version = "2.0" python-versions = "^3.11" -content-hash = "462077c1a2385c34d671d89c11525fcf2b4fff35354134f46557c1a43ccfc785" +content-hash = "2022313907bbdb9e2b74f857e3248ee83892e1ae852a381cbe182b1c7537d285" diff --git a/pyproject.toml b/pyproject.toml index 5ce1904..ae2393a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -37,6 +37,7 @@ version = "0.1.0" [tool.poetry.dependencies] SQLAlchemy = {version = "^1.4.46", extras = ["mypy"]} dash = "^2.11.1" +dash-bootstrap-components = "^1.4.2" deutschland = {git = "https://github.com/TrisNol/deutschland.git", branch = "hotfix/python-3.11-support"} loguru = "^0.7.0" matplotlib = "^3.7.1" @@ -89,7 +90,7 @@ pytest-cov = "^4.1.0" pytest-mock = "^3.10.0" pytest-repeat = "^0.9.1" -# TODO Add enrich_company_financials hinzufügen +# TODO Add enrich_company_financials hinzufügen [tool.poetry.scripts] mein_test = "aki_prj23_transparenzregister.utils.postgres.connector:init_db" diff --git a/src/aki_prj23_transparenzregister/ai/__init__.py b/src/aki_prj23_transparenzregister/ai/__init__.py new file mode 100644 index 0000000..3166040 --- /dev/null +++ b/src/aki_prj23_transparenzregister/ai/__init__.py @@ -0,0 +1 @@ +"""This module contains all the ai pipelines.""" diff --git a/src/aki_prj23_transparenzregister/config/__init__.py b/src/aki_prj23_transparenzregister/config/__init__.py index 2730631..f5d43d4 100644 --- a/src/aki_prj23_transparenzregister/config/__init__.py +++ b/src/aki_prj23_transparenzregister/config/__init__.py @@ -1 +1 @@ -"""App configuration.""" +"""App configuration tools.""" diff --git a/src/aki_prj23_transparenzregister/ui/assets/typography.css b/src/aki_prj23_transparenzregister/ui/assets/typography.css new file mode 100644 index 0000000..699a279 --- /dev/null +++ b/src/aki_prj23_transparenzregister/ui/assets/typography.css @@ -0,0 +1,3 @@ +body { + margin: 0; +} diff --git a/src/aki_prj23_transparenzregister/ui/company_finance_dash.py b/src/aki_prj23_transparenzregister/ui/company_finance_dash.py new file mode 100644 index 0000000..8e5c728 --- /dev/null +++ b/src/aki_prj23_transparenzregister/ui/company_finance_dash.py @@ -0,0 +1,392 @@ +"""Dash.""" + +import dash_bootstrap_components as dbc +import pandas as pd +import plotly.graph_objs as go +from dash import Dash, Input, Output, callback, dash_table, dcc, html +from dash.exceptions import PreventUpdate +from sqlalchemy.engine import Engine + +from aki_prj23_transparenzregister.utils.postgres import entities +from aki_prj23_transparenzregister.utils.postgres.connector import ( + get_session, +) + +if __name__ == "__main__": + session = get_session() + query_finance = session.query( + entities.AnnualFinanceStatement, entities.Company.name, entities.Company.id + ).join(entities.Company) + + query_company = session.query(entities.Company, entities.DistrictCourt.name).join( + entities.DistrictCourt + ) + engine = session.bind + if not isinstance(engine, Engine): + raise TypeError + + finance_df: pd.DataFrame = pd.read_sql(str(query_finance), engine) + company_df: pd.DataFrame = pd.read_sql(str(query_company), engine) + + select_company_df = company_df[["company_id", "company_name"]] + select_company_dropdown = select_company_df.to_dict("records") + options = [ + {"label": i["company_name"], "value": i["company_id"]} + for i in select_company_dropdown + ] + + colors = { + "light": "#edefef", + "lavender-blush": "#f3e8ee", + "ash-gray": "#bacdb0", + "cambridge-blue": "#729b79", + "paynes-gray": "#475b63", + "raisin-black": "#2e2c2f", + } + + def financials_figure( + finance_df: pd.DataFrame, company: str, metric: str + ) -> go.Figure: + """Creates plotly line chart for a specific company and a metric.""" + finance_df = finance_df.loc[finance_df["company_name"] == company] + # create figure + fig_line = go.Figure() + # add trace for company 1 + fig_line.add_trace( + go.Scatter( + x=finance_df["annual_finance_statement_date"], + y=finance_df[metric], + name=company, + line_color=colors["raisin-black"], + marker_color=colors["raisin-black"], + ) + ) + # set title and labels + fig_line.update_layout( + title=metric, + xaxis_title="Jahr", + yaxis_title="in Mio.€", + plot_bgcolor=colors["light"], + ) + return fig_line + + tab_style = { + "borderBottom": "1px solid #d6d6d6", + "padding": "6px", + "backgroundColor": "white", + "color": colors["paynes-gray"], + "fontWeight": "bold", + } + + tab_selected_style = { + "borderTop": "1px solid #d6d6d6", + "borderBottom": "1px solid #d6d6d6", + "padding": "6px", + "backgroundColor": colors["paynes-gray"], + "color": "white", + "fontWeight": "bold", + } + + # TBD: get data from database instead of mock data + company = 1 # selected company id + selected_company = company_df.loc[company_df["company_id"] == company] + + turnover = 123456 + stock = "1,23" + company_data = { + "col1": ["Unternehmen", "Straße", "Stadt"], + "col2": [ + selected_company["company_name"][0], + selected_company["company_street"][0], + str( + selected_company["company_zip_code"][0] + + " " + + selected_company["company_city"][0] + ), + ], + "col3": ["Branche", "Amtsgericht", "Gründungsjahr"], + "col4": [ + selected_company["company_sector"][0], + selected_company["district_court_name"][0], + "xxx", + ], + } + df_company_data = pd.DataFrame(data=company_data) + + app = Dash( + __name__, external_stylesheets=[dbc.icons.BOOTSTRAP] + ) # use dbc for icons + + kennzahlen_layout = html.Div( + [ + dcc.Graph( + figure=financials_figure( + finance_df, str(company), "annual_finance_statement_ebit" + ) + ) + ] + ) + + app.layout = html.Div( + [ + # title header of page + html.Div( + style={ + "backgroundColor": colors["raisin-black"], + "border": "1px solid", + }, + children=[ + html.I( + className="bi bi-house-door-fill", + style={ + "fontSize": 24, + "paddingLeft": "10px", + "color": "white", + "display": "inline-block", + "verticalAlign": "middle", + }, + ), + html.H1( + children="Transparenzregister für Kapitalgesellschaften", + style={ + "color": "white", + "textAlign": "left", + "margin": "0", + "paddingLeft": "10px", + "paddingBottom": "20px", + "paddingTop": "20px", + "display": "inline-block", + "verticalAlign": "middle", + }, + ), + html.Div( + dcc.Dropdown( + id="select_company", + placeholder="Suche nach Unternehmen oder Person", + ), + style={ + "float": "right", + "width": "30%", + "margin": "0", + "paddingRight": "10px", + "paddingBottom": "20px", + "paddingTop": "20px", + "display": "inline-block", + "verticalAlign": "middle", + }, + ), + ], + ), + # header company name + html.Div( + style={"backgroundColor": colors["paynes-gray"], "border": "1px solid"}, + children=[ + html.H1( + children=selected_company["company_name"][0], + style={ + "color": "white", + "fontSize": 30, + "textAlign": "left", + "margin": "0", + "paddingLeft": "20px", + "paddingBottom": "20px", + "paddingTop": "20px", + }, + ) + ], + ), + html.Div(style={"height": "20px"}), + html.Div(style={"width": "2%", "display": "inline-block"}), + # table basic company information + html.Div( + style={ + "backgroundColor": colors["ash-gray"], + "border": "1px solid", + "border-radius": 10, + "width": "45%", + "height": "150px", + "display": "inline-block", + "vertical-align": "top", + }, + children=[ + html.H5( + children="Stammdaten", + style={ + "color": colors["raisin-black"], + "fontSize": 16, + "textAlign": "center", + "margin": "0", + "paddingBottom": "10px", + "paddingTop": "10px", + }, + ), + dash_table.DataTable( + df_company_data.to_dict("records"), + [{"name": i, "id": i} for i in df_company_data.columns], + style_table={ + "width": "80%", + "overflowX": "auto", + "marginLeft": "auto", + "marginRight": "auto", + "paddingBottom": "20px", + "color": colors["raisin-black"], + }, + # hide header of table + css=[ + { + "selector": "tr:first-child", + "rule": "display: none", + }, + ], + style_cell={"textAlign": "center"}, + style_cell_conditional=[ + {"if": {"column_id": c}, "fontWeight": "bold"} + for c in ["col1", "col3"] + ], + ), + ], + ), + html.Div(style={"width": "2%", "display": "inline-block"}), + html.Div( + style={ + "backgroundColor": colors["ash-gray"], + "border": "1px solid", + "border-radius": 10, + "width": "15%", + "height": "150px", + "display": "inline-block", + "vertical-align": "top", + }, + children=[ + html.H5( + children="Stimmung", + style={ + "color": colors["raisin-black"], + "fontSize": 16, + "textAlign": "center", + "margin": "0", + "paddingBottom": "10px", + "paddingTop": "10px", + }, + ), + ], + ), + html.Div(style={"width": "2%", "display": "inline-block"}), + html.Div( + style={ + "backgroundColor": colors["ash-gray"], + "border": "1px solid", + "border-radius": 10, + "width": "15%", + "height": "150px", + "display": "inline-block", + "vertical-align": "top", + }, + children=[ + html.H5( + children="Aktienkurs", + style={ + "color": colors["raisin-black"], + "fontSize": 16, + "textAlign": "center", + "margin": "0", + "paddingBottom": "10px", + "paddingTop": "10px", + }, + ), + html.H1( + children=stock, + style={ + "color": colors["raisin-black"], + "textAlign": "center", + }, + ), + ], + ), + html.Div(style={"width": "2%", "display": "inline-block"}), + html.Div( + style={ + "backgroundColor": colors["ash-gray"], + "border": "1px solid", + "border-radius": 10, + "width": "15%", + "height": "150px", + "display": "inline-block", + "vertical-align": "top", + }, + children=[ + html.H5( + children="Umsatz", + style={ + "color": colors["raisin-black"], + "fontSize": 16, + "textAlign": "center", + "margin": "0", + "paddingBottom": "10px", + "paddingTop": "10px", + }, + ), + html.H1( + children=turnover, + style={ + "color": colors["raisin-black"], + "textAlign": "center", + }, + ), + ], + ), + html.Div(style={"width": "2%", "display": "inline-block"}), + # ]), + html.Div( + style={ + "marginTop": "20px", + "border": "1px solid", + }, + children=[ + dcc.Tabs( + id="tabs", + value="tab-1", + children=[ + dcc.Tab( + label="Kennzahlen", + value="tab-1", + style=tab_style, + selected_style=tab_selected_style, + children=[kennzahlen_layout], + ), + dcc.Tab( + label="Beteiligte Personen", + value="tab-2", + style=tab_style, + selected_style=tab_selected_style, + ), + dcc.Tab( + label="Stimmung", + value="tab-3", + style=tab_style, + selected_style=tab_selected_style, + ), + dcc.Tab( + label="Verflechtungen", + value="tab-4", + style=tab_style, + selected_style=tab_selected_style, + ), + ], + ), + html.Div(id="tabs-example-content-1"), + ], + ), + ] + ) + + @callback( + Output("select_company", "options"), Input("select_company", "search_value") + ) + def update_options(search_value: str) -> list: + """Update page based on selected company.""" + if not search_value: + raise PreventUpdate + return [o for o in options if search_value in o["label"]] + + app.run_server(debug=True) diff --git a/src/aki_prj23_transparenzregister/ui/company_stats_dash.py b/src/aki_prj23_transparenzregister/ui/company_stats_dash.py index e069c2f..2a46147 100644 --- a/src/aki_prj23_transparenzregister/ui/company_stats_dash.py +++ b/src/aki_prj23_transparenzregister/ui/company_stats_dash.py @@ -1,9 +1,8 @@ """Dash.""" import pandas as pd -from dash import Dash, dash_table +from dash import Dash, Input, Output, callback, dash_table, dcc, html -# from ..utils.postgres.connector import get_engine, init_db from aki_prj23_transparenzregister.utils.postgres import entities from aki_prj23_transparenzregister.utils.postgres.connector import ( get_session, @@ -16,9 +15,29 @@ if __name__ == "__main__": companies_df: pd.DataFrame = pd.read_sql(str(query), session.bind) # type: ignore app = Dash(__name__) - app.layout = dash_table.DataTable( - companies_df.to_dict("records"), - [{"name": i, "id": i} for i in companies_df.columns], + app.layout = html.Div( + [ + html.H1(children="Company Data", style={"textAlign": "center"}), + html.Div( + [ + dcc.Dropdown( + companies_df.company_name.unique(), + "Firma 1", + id="dropdown-selection", + ), + ] + ), + html.Div(id="data_table"), + ] ) + @callback(Output("data_table", "children"), Input("dropdown-selection", "value")) + def display_table(value: str) -> dash_table: + """Output table with company stats based on dropdown value.""" + dff = companies_df[companies_df.company_name == value] + return dash_table.DataTable( + data=dff.to_dict("records"), + columns=[{"id": c, "name": c} for c in companies_df.columns], + ) + app.run(debug=True) diff --git a/src/aki_prj23_transparenzregister/utils/enumy_types.py b/src/aki_prj23_transparenzregister/utils/enumy_types.py index e8edbf0..30901de 100644 --- a/src/aki_prj23_transparenzregister/utils/enumy_types.py +++ b/src/aki_prj23_transparenzregister/utils/enumy_types.py @@ -2,15 +2,20 @@ import enum -class RelationTypeEnum(enum.Enum): +class RelationTypeEnum(enum.IntEnum): """RelationTypeEnum.""" - executive = "Executive" - auditor = "Auditor" - supervisory_board = "Supervisory_Board" - managing_director = "Managing_Directory" - authorized_representative = "Authorized_Representative" - final_auditor = "Final_Auditor" + EXECUTIVE = enum.auto() + AUDITOR = enum.auto() + SUPERVISORY_BOARD = enum.auto() + MANAGING_DIRECTOR = enum.auto() + AUTHORIZED_REPRESENTATIVE = enum.auto() + FINAL_AUDITOR = enum.auto() + + PARTICIPATES_WITH = enum.auto() + HAS_SHARES_OF = enum.auto() + IS_SUPPLIED_BY = enum.auto() + WORKS_WITH = enum.auto() class SentimentTypeEnum(enum.Enum): @@ -20,12 +25,3 @@ class SentimentTypeEnum(enum.Enum): sustainability = "sustainability" environmental_aspects = "environmental_aspects" perception = "perception" - - -class RelationTypeCompanyEnum(enum.Enum): - """RelationTypeCompanyEnum.""" - - participates_with = "participates_with" - has_shares_of = "has_shares_of" - is_supplied_by = "is_supplied_by" - works_with = "works_with" diff --git a/src/aki_prj23_transparenzregister/utils/postgres/connector.py b/src/aki_prj23_transparenzregister/utils/postgres/connector.py index 5fab529..5b41fac 100644 --- a/src/aki_prj23_transparenzregister/utils/postgres/connector.py +++ b/src/aki_prj23_transparenzregister/utils/postgres/connector.py @@ -1,11 +1,10 @@ """Module containing connection utils for PostgreSQL DB.""" from sqlalchemy import create_engine from sqlalchemy.engine import URL, Engine -from sqlalchemy.orm import Session, sessionmaker +from sqlalchemy.orm import Session, declarative_base, sessionmaker from aki_prj23_transparenzregister.config.config_providers import JsonFileConfigProvider from aki_prj23_transparenzregister.config.config_template import PostgreConnectionString -from aki_prj23_transparenzregister.utils.postgres.entities import Base def get_engine(conn_args: PostgreConnectionString) -> Engine: @@ -34,6 +33,9 @@ def get_session() -> Session: # pragma: no cover return session() +Base = declarative_base() + + def init_db() -> None: """Initialize DB with all defined entities.""" config_provider = JsonFileConfigProvider("./secrets.json") diff --git a/src/aki_prj23_transparenzregister/utils/postgres/entities.py b/src/aki_prj23_transparenzregister/utils/postgres/entities.py index 53b2a36..bda9b67 100644 --- a/src/aki_prj23_transparenzregister/utils/postgres/entities.py +++ b/src/aki_prj23_transparenzregister/utils/postgres/entities.py @@ -1,20 +1,15 @@ """ORM entities for Prod. DB.""" -import uuid from datetime import datetime import sqlalchemy as sa -from sqlalchemy.orm import ( - declarative_base, -) from aki_prj23_transparenzregister.utils.enumy_types import ( - RelationTypeCompanyEnum, RelationTypeEnum, SentimentTypeEnum, ) +from aki_prj23_transparenzregister.utils.postgres.connector import Base # # create an object *district_court* which inherits attributes from Base-class -Base = declarative_base() class DistrictCourt(Base): @@ -22,9 +17,9 @@ class DistrictCourt(Base): __tablename__ = "district_court" - id = sa.Column(sa.Integer, primary_key=True) + id = sa.Column(sa.Integer, primary_key=True, autoincrement=True) city = sa.Column(sa.String(100), nullable=False) - name = sa.Column(sa.String(100), nullable=False) + name = sa.Column(sa.String(100), nullable=False, unique=True) class Company(Base): @@ -33,32 +28,48 @@ class Company(Base): __tablename__ = "company" __table_args__ = ( - sa.PrimaryKeyConstraint("id"), sa.UniqueConstraint("hr", "court_id"), + sa.UniqueConstraint("name", "city"), + sa.UniqueConstraint("name", "zip_code"), + sa.UniqueConstraint("name"), ) - id = sa.Column(sa.String, primary_key=True, default=uuid.uuid4, unique=True) - hr = sa.Column(sa.Integer, nullable=False) + id = sa.Column(sa.Integer, primary_key=True, autoincrement=True) + hr = sa.Column(sa.String, nullable=False) court_id = sa.Column( sa.Integer, sa.ForeignKey("district_court.id"), nullable=False, ) - name = sa.Column(sa.String(100), nullable=False) - street = sa.Column(sa.String(100), nullable=False) - zip_code = sa.Column(sa.String(5), nullable=False) - city = sa.Column(sa.String(100), nullable=False) - sector = sa.Column(sa.String(100), nullable=False) + name = sa.Column(sa.String(150), nullable=False) + street = sa.Column(sa.String(100), nullable=True) + zip_code = sa.Column(sa.String(5), nullable=True) + city = sa.Column(sa.String(100), nullable=True) + last_update = sa.Column(sa.Date, nullable=False) + sector = sa.Column(sa.String(100), nullable=True) -class Finance(Base): - """Finance.""" +class Person(Base): + """Person.""" - __tablename__ = "finance" + __tablename__ = "person" + __table_args__ = (sa.UniqueConstraint("name", "surname", "date_of_birth"),) id = sa.Column(sa.Integer, primary_key=True) - company_id = sa.Column(sa.String, sa.ForeignKey("company.id")) - date = sa.Column(sa.DateTime(timezone=True), default=datetime.now) + name = sa.Column(sa.String(100), nullable=False) + surname = sa.Column(sa.String(100), nullable=False) + date_of_birth = sa.Column(sa.Date, nullable=False) + works_for = sa.Column(sa.String(100), nullable=True) + + +class AnnualFinanceStatement(Base): + """Finance.""" + + __tablename__ = "annual_finance_statement" + + id = sa.Column(sa.Integer, primary_key=True) + company_id = sa.Column(sa.Integer, sa.ForeignKey("company.id")) + date = sa.Column(sa.DateTime(timezone=True), nullable=False) total_volume = sa.Column(sa.Float) ebit = sa.Column(sa.Float) ebitda = sa.Column(sa.Float) @@ -68,7 +79,6 @@ class Finance(Base): debt = sa.Column(sa.Float) return_on_equity = sa.Column(sa.Float) capital_turnover_rate = sa.Column(sa.Float) - # company: Mapped[Company] = relationship(Company) @@ -79,7 +89,7 @@ class Sentiment(Base): __tablename__ = "sentiment" id = sa.Column(sa.Integer, primary_key=True) - company_id = sa.Column(sa.String, sa.ForeignKey("company.id")) + company_id = sa.Column(sa.Integer, sa.ForeignKey("company.id")) date = sa.Column(sa.DateTime(timezone=True), default=datetime.now) sentiment_type = sa.Column( sa.Enum(SentimentTypeEnum), @@ -87,53 +97,48 @@ class Sentiment(Base): ) value = sa.Column(sa.Float(), nullable=False) source = sa.Column(sa.String(100)) - # sentiment = relationship(Company) # create person object -class Person(Base): - """Person.""" - __tablename__ = "person" +class Relation(Base): + """A super table containing all relations.""" + + __tablename__ = "relation" id = sa.Column(sa.Integer, primary_key=True) - name = sa.Column(sa.String(100), nullable=False) - surname = sa.Column(sa.String(100), nullable=False) - works_for = sa.Column(sa.String(100)) + company_id = sa.Column(sa.Integer, sa.ForeignKey("company.id")) + + date_from = sa.Column(sa.DateTime(timezone=True), nullable=True) + date_to = sa.Column(sa.DateTime(timezone=True), nullable=True) + + relation = sa.Column(sa.Enum(RelationTypeEnum), nullable=False) # create own relation type and person_relation object -class PersonRelation(Base): +class PersonRelation(Relation): """PersonRelation.""" __tablename__ = "person_relation" - id = sa.Column(sa.Integer, primary_key=True) - company_id = sa.Column(sa.String, sa.ForeignKey("company.id")) - person_id = sa.Column(sa.Integer, sa.ForeignKey(Person.id)) - date_from = sa.Column(sa.DateTime(timezone=True), default=datetime.now) - date_to = sa.Column(sa.DateTime(timezone=True), default=datetime.now) - relation = sa.Column(sa.Enum(RelationTypeEnum), nullable=False) + id = sa.Column(sa.Integer, sa.ForeignKey("relation.id"), primary_key=True) + person_id = sa.Column(sa.Integer, sa.ForeignKey("person.id")) # company = relationship("Company") # person = relationship("Person", foreign_keys=[person_id]) # company = relationship('Company', foreign_keys=[company_hr,company_court]) + __table_args__ = {"extend_existing": True} # create own relation type and company_relation object -class CompanyRelation(Base): +class CompanyRelation(Relation): """CompanyRelation.""" __tablename__ = "company_relation" - id = sa.Column(sa.Integer, primary_key=True) - company1_id = sa.Column(sa.String, sa.ForeignKey("company.id"), nullable=False) - company2_id = sa.Column(sa.String, sa.ForeignKey("company.id"), nullable=False) - date_from = sa.Column(sa.DateTime(timezone=True), default=datetime.now) - date_to = sa.Column(sa.DateTime(timezone=True), default=datetime.now) - relation = sa.Column(sa.Enum(RelationTypeCompanyEnum), nullable=False) + id = sa.Column(sa.Integer, sa.ForeignKey("relation.id"), primary_key=True) + company2_id = sa.Column(sa.Integer, sa.ForeignKey("company.id"), nullable=False) # company = relationship("Company") - __table_args__ = {"extend_existing": True} diff --git a/tests/config/__init__.py b/tests/config/__init__.py deleted file mode 100644 index 6275ce4..0000000 --- a/tests/config/__init__.py +++ /dev/null @@ -1 +0,0 @@ -"""Tests for config module.""" diff --git a/tests/ui/company_finance_dash_test.py b/tests/ui/company_finance_dash_test.py new file mode 100644 index 0000000..e5d29ce --- /dev/null +++ b/tests/ui/company_finance_dash_test.py @@ -0,0 +1,7 @@ +"""Test for the company stats dashboard.""" +from aki_prj23_transparenzregister.ui import company_finance_dash + + +def test_import() -> None: + """Checks if an import co company_stats_dash can be made.""" + assert company_finance_dash is not None diff --git a/tests/utils/mongo/__init__.py b/tests/utils/mongo/__init__.py deleted file mode 100644 index cf97370..0000000 --- a/tests/utils/mongo/__init__.py +++ /dev/null @@ -1 +0,0 @@ -"""Mongo utils module.""" diff --git a/tests/utils/postgres/__init__.py b/tests/utils/postgres/__init__.py deleted file mode 100644 index a4ce3a4..0000000 --- a/tests/utils/postgres/__init__.py +++ /dev/null @@ -1 +0,0 @@ -"""Tests for utils.postgres module.""" diff --git a/tests/utils/postgres/connector_test.py b/tests/utils/postgres/connector_test.py index ec9aaf2..35e0c94 100644 --- a/tests/utils/postgres/connector_test.py +++ b/tests/utils/postgres/connector_test.py @@ -18,7 +18,7 @@ def test_init_db() -> None: with patch( "aki_prj23_transparenzregister.utils.postgres.connector.get_engine" ) as mock_get_engine, patch( - "aki_prj23_transparenzregister.utils.postgres.entities.declarative_base" + "aki_prj23_transparenzregister.utils.postgres.connector.declarative_base" ) as mock_declarative_base, patch( "aki_prj23_transparenzregister.utils.postgres.connector.JsonFileConfigProvider" ) as mock_provider: @@ -33,4 +33,3 @@ def test_init_db() -> None: mock_value.get_postgre_connection_string.return_value = "" init_db() - assert True diff --git a/tests/utils/postgres/entities_test.py b/tests/utils/postgres/entities_test.py index bb67ffe..69d376c 100644 --- a/tests/utils/postgres/entities_test.py +++ b/tests/utils/postgres/entities_test.py @@ -1,4 +1,4 @@ def test_import() -> None: from aki_prj23_transparenzregister.utils.postgres import entities - assert entities is not None + assert entities