Feature/update connector flatchr

src/hrflow_connectors/__init__.py

@@ -1,11 +1,12 @@
+from hrflow_connectors.connectors.flatchr import Flatchr
 from hrflow_connectors.connectors.smartrecruiters import SmartRecruiters
 from hrflow_connectors.connectors.talentsoft import TalentSoft
 from hrflow_connectors.core import backend
 from hrflow_connectors.core.connector import hrflow_connectors_manifest  # noqa
 from hrflow_connectors.core.documentation import generate_docs  # noqa
 
 __version__ = "2.0.0"
-__CONNECTORS__ = [SmartRecruiters, TalentSoft]
+__CONNECTORS__ = [SmartRecruiters, TalentSoft, Flatchr]
 
 # This makes sure that connector are in module namespace
 # and that the automatic workflow code generation should work

src/hrflow_connectors/connectors/flatchr/DOCUMENTATION.md

@@ -0,0 +1,73 @@
+# 📖 Summary
+- [📖 Summary](#-summary)
+- [📝 About flatchr](#-about-flatchr)
+- [📊 Data Flow](#-data-flow)
+- [🔌 Connector Actions](#-connector-actions)
+- [🐍 Quick Start Examples](#-quick-start-examples)
+- [🔗 Useful Links](#-useful-links)
+- [🙏 Special Thanks](#-special-thanks)
+
+
+# 📝 About Flatchr 
+
+Flatchr is a web-based Applicant Tracking System (ATS) and recruitment software. It is designed to help businesses and recruiters manage the recruitment process, from job posting and applicant tracking, to scheduling interviews and managing offers. It has features like candidate management, resume parser, job postings, sourcing, and more. 
+
+
+
+<p align="center">
+<image src=https://user-images.githubusercontent.com/113343504/215117691-36605f2d-ddcf-48be-9d82-b4c660b1cc20.png
+ width=90% height=100% >
+</p>
+
+# 📊 Data Flow 
+In this section, we outline the data flow between different components of the connector. The following schema provides a graphical representation of the data exchange process
+![image](https://user-images.githubusercontent.com/113343504/215127248-6dc5dff3-f64e-4d50-a8ff-093077b45c32.png)
+
+
+# 🔌 Connector Actions
+<p align="center">
+
+
+| Action | Description |
+| ------- |  -------- |
+| [**Push profiles**](docs/push_profiles.md) | Retrieves profiles from a [HrFlow.ai](http://HrFlow.ai) Source and sends them to Flatchr ATS|
+
+</p>
+
+
+# 🐍 Quick Start Examples
+
+To make sure you can successfully run the latest versions of the example scripts, you have to **install the package from PyPi**. To do this, execute the following steps in a new virtual environment:
+```bash
+pip hrflow-connectors
+```
+
+
+To browse the examples of actions corresponding to released versions of 🤗 this connector, you just need to import the module like this :
+
+<p align="center">
+
+```python
+import logging
+from hrflow_connectors import Flatchr
+```
+
+</p>
+
+Once the connector module is imported, you can leverage all the different actions that it offers. 
+
+For more code details checkout connector code 
+
+
+# 🔗 Useful Links
+
+- 📄Visit [Bullhorn](https://www.flatchr.io/) to learn more.
+- ⚙️ API documentation : (https://developers.flatchr.io/docs/getting_started)
+- 💻 [Connector code](https://github.com/Riminder/hrflow-connectors/tree/master/src/hrflow_connectors/connectors/flatchr) on our Github.
+
+
+# 🙏 Special Thanks  
+- 💻 HrFlow.ai: [Arthur STIEVENARD](https://github.com/arhturstiev) - Software Engineer
+- 💻 HrFlow.ai: [Limam VADHEL](https://github.com/limamvadhel) - Software Engineer
+- 💻 HrFlow.ai: [Clement NEGRE](https://github.com/ClemNeg0) - Software Engineer
+- 🤝 Flatchr: [Flatchr for the partnership and accessible documentation](https://flatchr.com/)

src/hrflow_connectors/connectors/flatchr/README.md

@@ -0,0 +1,73 @@
+# 📖 Summary
+- [📖 Summary](#-summary)
+- [📝 About flatchr](#-about-flatchr)
+- [📊 Data Flow](#-data-flow)
+- [🔌 Connector Actions](#-connector-actions)
+- [🐍 Quick Start Examples](#-quick-start-examples)
+- [🔗 Useful Links](#-useful-links)
+- [🙏 Special Thanks](#-special-thanks)
+
+
+# 📝 About Flatchr 
+
+Flatchr is a web-based Applicant Tracking System (ATS) and recruitment software. It is designed to help businesses and recruiters manage the recruitment process, from job posting and applicant tracking, to scheduling interviews and managing offers. It has features like candidate management, resume parser, job postings, sourcing, and more. 
+
+
+
+<p align="center">
+<image src=https://user-images.githubusercontent.com/113343504/215117691-36605f2d-ddcf-48be-9d82-b4c660b1cc20.png
+ width=90% height=100% >
+</p>
+
+# 📊 Data Flow 
+In this section, we outline the data flow between different components of the connector. The following schema provides a graphical representation of the data exchange process
+![image](https://user-images.githubusercontent.com/113343504/215127248-6dc5dff3-f64e-4d50-a8ff-093077b45c32.png)
+
+
+# 🔌 Connector Actions
+<p align="center">
+
+
+| Action | Description |
+| ------- |  -------- |
+| [**Push profiles**](docs/push_profiles.md) | Retrieves profiles from a [HrFlow.ai](http://HrFlow.ai) Source and sends them to Flatchr ATS|
+
+</p>
+
+
+# 🐍 Quick Start Examples
+
+To make sure you can successfully run the latest versions of the example scripts, you have to **install the package from PyPi**. To do this, execute the following steps in a new virtual environment:
+```bash
+pip hrflow-connectors
+```
+
+
+To browse the examples of actions corresponding to released versions of 🤗 this connector, you just need to import the module like this :
+
+<p align="center">
+
+```python
+import logging
+from hrflow_connectors import Flatchr
+```
+
+</p>
+
+Once the connector module is imported, you can leverage all the different actions that it offers. 
+
+For more code details checkout connector code 
+
+
+# 🔗 Useful Links
+
+- 📄Visit [Bullhorn](https://www.flatchr.io/) to learn more.
+- ⚙️ API documentation : (https://developers.flatchr.io/docs/getting_started)
+- 💻 [Connector code](https://github.com/Riminder/hrflow-connectors/tree/master/src/hrflow_connectors/connectors/flatchr) on our Github.
+
+
+# 🙏 Special Thanks  
+- 💻 HrFlow.ai: [Arthur STIEVENARD](https://github.com/arhturstiev) - Software Engineer
+- 💻 HrFlow.ai: [Limam VADHEL](https://github.com/limamvadhel) - Software Engineer
+- 💻 HrFlow.ai: [Clement NEGRE](https://github.com/ClemNeg0) - Software Engineer
+- 🤝 Flatchr: [Flatchr for the partnership and accessible documentation](https://flatchr.com/)

src/hrflow_connectors/connectors/flatchr/__init__.py

@@ -0,0 +1 @@
+from hrflow_connectors.connectors.flatchr.connector import Flatchr  # noqa

src/hrflow_connectors/connectors/flatchr/connector.py

@@ -0,0 +1,233 @@
+import base64
+import typing as t
+
+import requests
+
+from hrflow_connectors.connectors.flatchr.warehouse import FlatchrProfileWarehouse
+from hrflow_connectors.connectors.hrflow.warehouse import HrFlowProfileWarehouse
+from hrflow_connectors.core import (
+    BaseActionParameters,
+    Connector,
+    ConnectorAction,
+    WorkflowType,
+)
+
+
+def get_candidate_attachments(hrflow_profile: t.Dict) -> t.Dict:
+    attachments_list = hrflow_profile.get("attachments")
+    # We try to find 'resume' (which is 'original' after traitments).
+    # If we don't find it, we search 'original'.
+    fall_backs = ["resume", "original"]
+
+    for file_name in fall_backs:
+        for attachment in attachments_list:
+            if attachment["file_name"] == file_name:
+                # Get the base64's resume from its AWS url.
+                url = attachment["public_url"]
+                response = requests.get(url)
+                b64 = base64.b64encode(response.content)
+                return b64.decode()
+    return None
+
+
+def get_education_list(hrflow_profile: t.Dict) -> t.Dict:
+    hrflow_education_list = hrflow_profile["educations"]
+    flatchr_education_list = []
+
+    for education in hrflow_education_list:
+        location = education.get("location")
+        flatchr_education = {
+            "institution": {
+                "communication": {
+                    "address": [
+                        {"formattedAddress": location.get("text") if location else None}
+                    ]
+                },
+                "name": education.get("school"),
+            },
+            "educationLevelCodes": [{"name": education.get("title")}],
+            "educationDegrees": [
+                {
+                    "name": education.get("title"),
+                    "date": education.get("date_start"),
+                    "specializations": [],
+                }
+            ],
+            "end": education.get("date_end"),
+            "descriptions": [education.get("description")],
+        }
+        flatchr_education_list.append(flatchr_education)
+    return flatchr_education_list
+
+
+def get_experiences_list(hrflow_profile: t.Dict) -> t.Dict:
+    hrflow_experiences_list = hrflow_profile["experiences"]
+    flatchr_experiences_list = []
+
+    for experience in hrflow_experiences_list:
+        location = experience.get("location")
+        flatchr_education = {
+            "title": experience.get("title"),
+            "positionHistories": [
+                {
+                    "organization": {
+                        "communication": {
+                            "address": [
+                                {
+                                    "countryCode": None,
+                                    "city": None,
+                                    "postalCode": None,
+                                    "geoLocation": {
+                                        "latitude": location.get("lat"),
+                                        "longitude": location.get("lng"),
+                                    },
+                                    "formattedAddress": location.get("text")
+                                    if location
+                                    else None,
+                                }
+                            ]
+                        },
+                        "name": experience.get("company"),
+                    },
+                    "jobCategories": [],
+                    "jobLevels": [],
+                    "start": experience.get("date_start"),
+                    "current": None,
+                }
+            ],
+            "start": experience.get("date_start"),
+            "current": None,
+            "descriptions": [experience.get("description")],
+        }
+        flatchr_experiences_list.append(flatchr_education)
+    return flatchr_experiences_list
+
+
+def get_name() -> t.Dict:
+    name = {
+        "formattedName": "Undefined",
+        "given": "Undefined",
+        "family": "Undefined",
+    }
+    return name
+
+
+def get_phone(hrflow_profile: t.Dict) -> t.Dict:
+    info = hrflow_profile.get("info")
+    phone = [{"dialNumber": info.get("phone") if info else "XXXXX", "useCode": None}]
+    return phone
+
+
+def get_email(hrflow_profile: t.Dict) -> t.Dict:
+    info = hrflow_profile.get("info")
+
+    email = [{"address": info.get("email") if info else None}]
+    return email
+
+
+def get_position(hrflow_profile: t.Dict) -> t.Dict:
+    hrflow_experiences_list = hrflow_profile["experiences"]
+    position = []
+
+    for experience in hrflow_experiences_list:
+        if experience.get("title") is not None and experience.get("title") != "":
+            position.append(experience.get("title"))
+
+    return position
+
+
+def get_employment_positions(hrflow_profile: t.Dict) -> t.Dict:
+    hrflow_experiences_list = hrflow_profile["experiences"]
+    employment_positions = []
+
+    for experience in hrflow_experiences_list:
+        if experience.get("company") is not None and experience.get("company") != "":
+            employment_positions.append(experience.get("company"))
+
+    return employment_positions
+
+
+def format_profile(hrflow_profile: t.Dict) -> t.Dict:
+
+    # CREATE PROFILE
+    data = hrflow_profile
+
+    info = data.get("info")
+    email = info.get("email") if info else None
+    if email is None:
+        reference = data.get("reference")
+        raise Exception(f"No email for hrflow_profile {reference} but one is mandatory")
+
+    create_profile_body = {
+        "vacancy": None,
+        "firstname": info.get("first_name")
+        if info.get("first_name") is not None
+        else "N/A",
+        "lastname": info.get("last_name")
+        if info.get("last_name") is not None
+        else "N/A",
+        "type": "document",
+        "email": email,
+        "resume": {
+            "fileName": "resume.pdf",
+            "contentType": "application/octet-stream",
+            "data": get_candidate_attachments(data),
+        },
+    }
+
+    # ENRICH PROFILE
+
+    value = {
+        "address": {
+            "administrative_area_level_1": data["info"]["location"].get("text"),
+            "location_lat": data["info"]["location"].get("lat"),
+            "location_lng": data["info"]["location"].get("lng"),
+        },
+        "education": get_education_list(data),
+        "employment": get_experiences_list(data),
+        "name": get_name(),
+        "phone": get_phone(data),
+        "email": get_email(data),
+        "position": get_position(data),
+        "employment_positions": get_employment_positions(data),
+        "experience": int(data.get("experiences_duration")),
+    }
+
+    enrich_profile_body = {
+        "app_name": "HRMatch",
+        "reference": data["info"].get("email"),
+        "name": "parsing",
+        "type": "applicants",
+        "value": value,
+    }
+    # When the action needs to send several requests to push a profile
+    # We group the formats of the different requests in a `profile_body_dict`.
+    profile_body_dict = dict(
+        create_profile_body=create_profile_body,
+        enrich_profile_body=enrich_profile_body,
+    )
+    return profile_body_dict
+
+
+DESCRIPTION = (
+    "Avec le digital, recruter est devenu beaucoup plus compliqué qu'avant."
+    " Flatchr centralise et simplifie vos processus de recrutement pour le rendre aussi"
+    " simple que télécharger un film sur Netflix."
+)
+Flatchr = Connector(
+    name="Flatchr",
+    description=DESCRIPTION,
+    url="https://www.flatchr.io/",
+    actions=[
+        ConnectorAction(
+            name="push_profile",
+            trigger_type=WorkflowType.catch,
+            description="Writes profile from Hrflow.ai Source to Flatchr",
+            parameters=BaseActionParameters.with_defaults(
+                "WriteProfileActionParameters", format=format_profile
+            ),
+            origin=HrFlowProfileWarehouse,
+            target=FlatchrProfileWarehouse,
+        ),
+    ],
+)