feat: Add Omdena class and methods for retrieving datasets, projects,…

… and blogs

This commit adds the `Omdena` class and three methods: `get_datasets()`, `get_projects()`, and `get_blogs()`. These methods allow users to retrieve information about datasets, ongoing projects, and latest blogs from Omdena. The class and methods are implemented in the `omdena.py` file.

dev-documentation.md

@@ -1962,6 +1962,23 @@ The `cars` class includes methods for retrieving job listings:
 | --------------- | ------------------------------------------------------------------- |
 | `.fetch_cars()` | Retrieve car listings from the website for a specified single page. |
 
+---
+
+#### Omdena
+
+```python
+from scrape_up.omdena import Omdena
+
+omdena = Omdena()
+print(omdena.get_projects())
+```
+
+| Methods                     | Details                                                                                              |
+| --------------------------- | ---------------------------------------------------------------------------------------------------- |
+| `.get_datasets()`           | Returns a dictionary of datasets in Omdena.                                                          |
+| `.get_projects()`           | Returns a dictionary of latest ongoing projects in Omdena.                                           |
+| `.get_blogs()`              | Returns a dictionary of latest blogs in Omdena.                                                      |
+---
 
 #### Letterboxd
 

docs/modules/omdena.md

@@ -0,0 +1,13 @@
+Create an instance of `Omdena` class.
+
+```python
+from scrape_up.omdena import Omdena
+
+omdena = Omdena()
+```
+
+| Methods                     | Details                                                                                              |
+| --------------------------- | ---------------------------------------------------------------------------------------------------- |
+| `.get_datasets()`           | Returns a dictionary of datasets in Omdena.                                                          |
+| `.get_projects()`           | Returns a dictionary of latest ongoing projects in Omdena.                                           |
+| `.get_blogs()`              | Returns a dictionary of latest blogs in Omdena.                                                      |

src/scrape_up/omdena/__init__.py

@@ -0,0 +1,3 @@
+from .omdena import Omdena
+
+__all__ = ["Omdena"]

src/scrape_up/omdena/omdena.py

@@ -0,0 +1,144 @@
+import json
+from bs4 import BeautifulSoup as Soup
+from scrape_up.config.request_config import RequestConfig, get
+
+
+class Omdena:
+    """
+    Class - `Omdena`
+
+    | Methods                     | Details                                                                                              |
+    | --------------------------- | ---------------------------------------------------------------------------------------------------- |
+    | `.get_datasets()`           | Returns a dictionary of datasets in Omdena.                                                              |
+    | `.get_projects()`           | Returns a dictionary of latest ongoing projects in Omdena.                                                              |
+    | `.get_blogs()`              | Returns a dictionary of latest blogs in Omdena.                                                              |
+
+    """
+
+    def __init__(self, *, config: RequestConfig = RequestConfig()):
+        self.config = config
+        self.url = f"https://www.omdena.com/"
+
+    def get_datasets(self) -> dict:
+        """
+        Class - `Omdena`
+
+        Example:
+        ```
+        omdena = Omdena()
+        omdena.get_datasets()
+        ```
+
+        Returns the list of available datasets in Omdena.:
+        ```python
+        {'datasets': ['https://datasets.omdena.com//dataset/flood-dataset-(malaysia)', 'https://datasets.omdena.com//dataset/2007-2022-homeless-populations-by-state-(usa)', 'https://datasets.omdena.com//dataset/homelessness-in-the-united-states-(2007-2022)', 'https://datasets.omdena.com//dataset/global-wheat-head-detection-(gwhd)', 'https://datasets.omdena.com//dataset/covid-radiology-images', 'https://datasets.omdena.com//dataset/yearly-economics-and-unemployment-(pakistan)', 'https://datasets.omdena.com//dataset/twitter-data-with-pq-scores']}
+        ```
+        """
+        try:
+            self.url = f"https://datasets.omdena.com"
+            req = get(self.url, self.config)
+            page_soup = Soup(req.content, "html.parser")
+
+            data = page_soup.find_all("div", attrs={"class": f"dataset-grid"})
+            datset_list = []
+
+            for card in data:
+                for i in card.find_all("a"):
+                    datset_list.append(f"{self.url}{i.get('href')}")
+
+            return {"datasets": datset_list}
+
+        except Exception:
+            return None
+
+    def get_blogs(self) -> dict:
+        """
+        Class - `Omdena`
+
+        Example:
+        ```
+        omdena = Omdena()
+        omdena.get_blogs()
+        ```
+
+        Returns the list of latest blogs in Omdena.:
+        ```python
+            {'blogs': [{
+                'title': 'Revolutionizing Short-term Traffic Congestion Prediction with Machine Learning | AI Insights | Omdena Success Story',
+                'description': 'Explore how our project leveraged machine learning and computer vision to predict short-term traffic congestion, revolutionizing urban traffic management.',
+                'url': 'https://cmsnew.omdena.com/blog/predicting-short-term-traffic-congestion-on-urban-roads-using-machine-learning/',
+                'site_name': 'Omdena | Building AI Solutions for Real-World Problems',
+                'image': [{'width': 715,
+                    'height': 520,
+                    'url': 'https://cmsnew.omdena.com/wp-content/uploads/2023/05/Vehicle-and-Vehicle-Direction-Detection.jpeg',
+                    'type': 'image/jpeg'}]}
+            }]
+        ```
+        """
+        try:
+            req = get(f"{self.url}/blog", self.config)
+            page_soup = Soup(req.content, "html.parser")
+
+            data = page_soup.find("script", attrs={"id": f"__NEXT_DATA__"}).text
+            data = json.loads(data)
+
+            keys_ = data["props"]["pageProps"]["articles"][0]["yoast_head_json"].keys()
+            blogs_data = []
+
+            for project in data["props"]["pageProps"]["articles"]:
+                project_data_dict = {}
+                for key in keys_:
+                    if key[:3]=="og_" and key not in ["og_locale", "og_type"]:
+                        project_data_dict[key.replace("og_", "")] = project["yoast_head_json"][key]
+                blogs_data.append(project_data_dict)
+
+            return {"blogs": blogs_data}
+
+        except Exception:
+            return None
+
+    def get_projects(self) -> dict:
+        """
+        Class - `Omdena`
+
+        Example:
+        ```
+        omdena = Omdena()
+        omdena.get_projects()
+        ```
+
+        Returns the list of latest ongoing projects in Omdena.:
+        ```python
+            {'projects': [{
+                'title': 'Building Real-Time Anomaly Detection for Traveling Agency Transactions',
+                'description': 'Join Omdena Top Talent Project to build a real-time anomaly detection system for analyzing transactions on travel agency websites by leveraging data analysis and AI technologies.',
+                'url': 'https://cmsnew.omdena.com/projects/building-real-time-anomaly-detection-for-traveling-agency-transactions/',
+                'site_name': 'Omdena | Building AI Solutions for Real-World Problems',
+                'image': [{'width': 1600,
+                    'height': 1066,
+                    'url': 'https://cmsnew.omdena.com/wp-content/uploads/2024/06/traveling-agency-transactions.jpeg',
+                    'type': 'image/jpeg'}]}
+            }]
+        ```
+        """
+        try:
+            req = get(f"{self.url}/projects", self.config)
+            page_soup = Soup(req.content, "html.parser")
+
+            data = page_soup.find("script", attrs={"id": f"__NEXT_DATA__"}).text
+            data = json.loads(data)
+
+            keys_ = data["props"]["pageProps"]["projects"][0]["yoast_head_json"].keys()
+            projects_data = []
+
+            for project in data["props"]["pageProps"]["projects"]:
+                project_data_dict = {}
+                for key in keys_:
+                    if key[:3]=="og_" and key not in ["og_locale", "og_type"]:
+                        project_data_dict[key.replace("og_", "")] = project["yoast_head_json"][key]
+                projects_data.append(project_data_dict)
+
+            return {"projects": projects_data}
+
+        except Exception:
+            return None