Merge branch 'master' into feat/add-profile-json-to-parsing-warehouse

CHANGELOG.md

@@ -2,6 +2,18 @@
 
 
 
+## v4.10.0 (2024-02-29)
+
+### Feature
+
+* feat: make docs maintains notebooks folder for each connector
+BREAKING CHANGE: for users that rely on generate_docs helper ([`77b8da9`](https://github.com/Riminder/hrflow-connectors/commit/77b8da9db409c396fe7e5abe94894fe8665ac614))
+
+### Fix
+
+* fix: exclude .gitkeep in notebooks from calculation of connector update_at in main readme ([`4f465c8`](https://github.com/Riminder/hrflow-connectors/commit/4f465c8d0918958267166f8bbacbe31504f1dbd4))
+
+
 ## v4.9.0 (2024-02-19)
 
 ### Feature

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "hrflow-connectors"
-version = "4.9.0"
+version = "4.10.0"
 description = "hrflow-connectors is an open source project created by HrFlow.ai to allow developers to connect easily HR ecosystem component."
 license = "Apache-2.0"
 authors = ["HrFlow.ai <support+hrflow_connectors@hrflow.ai>"]

src/hrflow_connectors/connectors/digitalrecruiters/README.md

@@ -52,7 +52,7 @@ To make sure you can successfully run the latest versions of the example scripts
 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">
-<image src=https://github.com/Riminder/hrflow-connectors/assets/135601200/c09d00f8-8332-4315-aeab-dd1beed301cc width=90% height=100% >
+<image src=https://github.com/Riminder/hrflow-connectors/assets/135601200/089bc6d4-f7bb-4095-8b26-dda7b0de2538 width=90% height=100% >
 </p>
 
 Once the connector module is imported, you can leverage all the different actions that it offers.

src/hrflow_connectors/connectors/jobology/README.md

@@ -63,7 +63,7 @@ For more code details checkout connector code.
 
 # 🔗 Useful Links
 
-- 📄Visit [Jobology](https://www.jobology.com/) to learn more.
+- 📄Visit [Jobology](https://www.jobology.fr/) to learn more.
 - 💻 [Connector code](https://github.com/Riminder/hrflow-connectors/tree/master/src/hrflow_connectors/connectors/jobology) on our Github.
 
 

src/hrflow_connectors/connectors/lever/README.md

@@ -4,7 +4,6 @@
   - [😍 Why is it a big deal for Lever customers & partners?](#-why-is-it-a-big-deal-for-lever-customers--partners)
 - [🔧 How does it work?](#-how-does-it-work)
   - [📊 Data integration capabilities:](#-data-integration-capabilities)
-  - [🧠 Artificial Intelligence capabilities:](#-artificial-intelligence-capabilities)
 - [🔌 Connector Actions](#-connector-actions)
 - [💍 Quick Start Examples](#-quick-start-examples)
 - [🔗 Useful Links](#-useful-links)
@@ -15,6 +14,9 @@
 
 > Lever is a modern recruitment platform that helps companies streamline their hiring process.
 
+<p align="center">
+<image src=https://github.com/Riminder/hrflow-connectors/assets/135601200/138a7d3b-d14d-4095-a50a-3a5395cb69e7 width=90% height=100% >
+</p>
 
 ## 😍 Why is it a big deal for Lever customers & partners?
 
@@ -27,13 +29,8 @@ This new connector will enable:
 - ⬅️ Send Profiles data from Lever to a Destination of your choice.
 - ➡️ Send Profiles data from a Source of your choice to Lever.
 - ⬅️ Send Jobs data from Lever to a Destination of your choice.
-- ➡️ Send Jobs data from a Source of your choice to Lever.
 
 
-## 🧠 Artificial Intelligence capabilities:
-- Extract, Structure, and Categorize Talent & Workforce data
-- Search, Score, and Match Profiles & Jobs with our APIs and AI Widgets (**Matching Custom Tab in Lever**)
-
 
 # 🔌 Connector Actions
 <p align="center">
@@ -47,6 +44,10 @@ This new connector will enable:
 
 </p>
 
+<p align="center">
+<image src=https://github.com/Riminder/hrflow-connectors/assets/135601200/313c58d9-e5b4-48f6-98d0-1e5c37021daf width=90% height=100% >
+</p>
+
 
 # 💍 Quick Start Examples
 
@@ -55,6 +56,9 @@ To make sure you can successfully run the latest versions of the example scripts
 
 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">
+<image src=https://github.com/Riminder/hrflow-connectors/assets/135601200/534807aa-34a4-422f-8fbc-26b5e00c5c34 width=90% height=100% >
+</p>
 
 Once the connector module is imported, you can leverage all the different actions that it offers.
 

src/hrflow_connectors/connectors/salesforce/README.md

@@ -87,6 +87,9 @@ Once logged to your Salesforce environment go to Setup then click Create > Custo
 <image width="1919" alt="HrFlow Experiences" src="https://github.com/Riminder/hrflow-connectors/assets/65894619/3006d23f-2944-4e8e-89b1-c6b58a49de21">
 <image width="1919" alt="HrFlow Attachments" src="https://github.com/Riminder/hrflow-connectors/assets/65894619/dfcdba59-658b-4a75-870b-99c991f53935">
 
+## Hrflow.ai Recruiter Copilot Widget installed in Salesforce
+<image width="1919" alt="Scoring" src="https://github.com/Riminder/hrflow-connectors/assets/135601200/2434d21a-1994-4e16-a6b0-65d7e2a6fa49">
+
 # 📊 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
 

src/hrflow_connectors/core/documentation.py

@@ -5,7 +5,7 @@
 import subprocess
 import typing as t
 from contextvars import ContextVar
-from datetime import datetime
+from datetime import datetime, timezone
 from pathlib import Path
 
 from pydantic import BaseModel
@@ -34,7 +34,7 @@ def CONNECTOR_LISTING_REGEXP_F(name: str) -> str:
     return (
         r"\|\s*\[?\*{0,2}(?i:(?P<name>"
         + r" ?".join([c for c in name if c.strip()])
-        + r"))\*{0,2}(\]\([^)]+\))?\s*\|[^|]+\|[^|]+\|\s*(\*|_)(?P<release_date>[\d\/]+)(\*|_)\s*\|.+"
+        + r"))\*{0,2}(\]\([^)]+\))?\s*\|[^|]+\|[^|]+\|\s*(\*|_)(?P<release_date>[\d\/]+)(\*|_)\s*\|\s*(\*|_)(?P<update_date>[\d\/]+)(\*|_)\s*\|.+"
     )
 
 
@@ -43,10 +43,13 @@ def CONNECTOR_LISTING_REGEXP_F(name: str) -> str:
 )
 
 
+GIT_UPDATE_EXCLUDE_PATTERN = (
+    r"(notebooks/\.gitkeep|README\.md|test\-config\.yaml|logo\.png|docs/)"
+)
 GIT_UPDATE_TIMEOUT = 5
 GIT_UPDATE_DATE = """
 git ls-tree -r --name-only HEAD {base_connector_path}/{connector} | while read filename; do
-  echo "$(git log -1 --format="%aI" -- $filename)"
+  echo "$(git log -1 --format="%aI" -- $filename) $filename"
 done
 """
 
@@ -185,9 +188,16 @@ def update_root_readme(connectors: t.List[Connector], root: Path) -> t.Dict:
                 "Subprocess run for Git update dates failed for connector {} with"
                 " errors {}".format(model.name.lower(), result.stderr)
             )
+        filtered = [
+            line.split(" ")[0]
+            for line in filter(
+                lambda line: not re.search(GIT_UPDATE_EXCLUDE_PATTERN, line),
+                result.stdout.strip().splitlines(),
+            )
+        ]
         updated_at = datetime.fromisoformat(
             max(
-                result.stdout.strip().splitlines(),
+                filtered,
                 key=lambda d: datetime.fromisoformat(d),
             )
         )
@@ -209,6 +219,13 @@ def update_root_readme(connectors: t.List[Connector], root: Path) -> t.Dict:
                     model.name, pattern
                 )
             )
+        current_updated_at = datetime.strptime(
+            match.group("update_date"), "%d/%m/%Y"
+        ).replace(tzinfo=timezone.utc)
+        updated_at = (
+            current_updated_at if current_updated_at >= updated_at else updated_at
+        )
+
         updated_listing = (
             "| [**{name}**]({readme_link}) | {type} | :white_check_mark: |"
             " *{release_date}* | *{updated_at}* | {pull_profile_list_status} |"
@@ -235,6 +252,9 @@ def update_root_readme(connectors: t.List[Connector], root: Path) -> t.Dict:
     readme.write_bytes(readme_content.encode())
 
 
+KEEP_EMPTY_NOTEBOOKS = ".gitkeep"
+
+
 def generate_docs(
     connectors: t.List[Connector], connectors_directory: Path = CONNECTORS_DIRECTORY
 ) -> None:
@@ -281,6 +301,26 @@ def generate_docs(
             )
             updated_readme_content = py_37_38_compat_patch(updated_readme_content)
             readme.write_bytes(updated_readme_content.encode())
+
+        notebooks_directory = connector_directory / "notebooks"
+        empty_dir_file = notebooks_directory / KEEP_EMPTY_NOTEBOOKS
+        create_empty_file = True
+
+        if notebooks_directory.is_dir():
+            for child in notebooks_directory.iterdir():
+                if not child.name == empty_dir_file.name:
+                    create_empty_file = False
+                    try:
+                        empty_dir_file.unlink()
+                    except FileNotFoundError:
+                        pass
+                    break
+        else:
+            notebooks_directory.mkdir()
+
+        if create_empty_file:
+            empty_dir_file.touch()
+
         if len(model.actions) > 0:
             action_docs_directory = connector_directory / "docs"
             if not action_docs_directory.is_dir():