bump min python to 3.8

Author: Christopher Doris

.github/workflows/tests.yml

@@ -56,7 +56,7 @@ jobs:
       fail-fast: true
       matrix:
         os: [ubuntu-latest, windows-latest, macos-latest]
-        pyversion: ["3.x", "3.7"]
+        pyversion: ["3.x", "3.8"]
     steps:
       - uses: actions/checkout@v3
       - name: Set up Python ${{ matrix.pyversion }}

CondaPkg.toml

@@ -3,4 +3,4 @@ version = "<=julia"
 
 [deps.python]
 build = "**cpython**"
-version = ">=3.7,<4"
+version = ">=3.8,<4"

README.md

@@ -14,7 +14,7 @@ Bringing [**Python®**](https://www.python.org/) and [**Julia**](https://juliala
 - Fast non-copying conversion of numeric arrays in either direction: modify Python arrays (e.g. `bytes`, `array.array`, `numpy.ndarray`) from Julia or Julia arrays from Python.
 - Helpful wrappers: interpret Python sequences, dictionaries, arrays, dataframes and IO streams as their Julia counterparts, and vice versa.
 - Beautiful stack-traces.
-- Supports modern systems: tested on Windows, MacOS and Linux, 64-bit, Julia 1.6.1 upwards and Python 3.7 upwards.
+- Supports modern systems: tested on Windows, MacOS and Linux, 64-bit, Julia 1.6.1 upwards and Python 3.8 upwards.
 
 ⭐ If you like this, a GitHub star would be lovely thank you. ⭐
 
@@ -45,4 +45,4 @@ The existing package [PyCall](https://github.com/JuliaPy/PyCall.jl) is another s
 - PythonCall by default never copies mutable objects when converting, but instead directly wraps the mutable object. This means that modifying the converted object modifies the original, and conversion is faster.
 - PythonCall does not usually automatically convert results to Julia values, but leaves them as Python objects. This makes it easier to do Pythonic things with these objects (e.g. accessing methods) and is type-stable.
 - PythonCall installs dependencies into a separate Conda environment for each Julia project. This means each Julia project can have an isolated set of Python dependencies.
-- PythonCall supports Julia 1.6.1+ and Python 3.7+ whereas PyCall supports Julia 0.7+ and Python 2.7+.
+- PythonCall supports Julia 1.6.1+ and Python 3.8+ whereas PyCall supports Julia 0.7+ and Python 2.7+.

docs/src/index.md

@@ -7,4 +7,4 @@ Bringing [**Python®**](https://www.python.org/) and [**Julia**](https://juliala
 - Fast non-copying conversion of numeric arrays in either direction: modify Python arrays (e.g. `bytes`, `array.array`, `numpy.ndarray`) from Julia or Julia arrays from Python.
 - Helpful wrappers: interpret Python sequences, dictionaries, arrays, dataframes and IO streams as their Julia counterparts, and vice versa.
 - Beautiful stack-traces.
-- Works anywhere: tested on Windows, MacOS and Linux, 32- and 64-bit, Julia Julia 1.6.1 upwards and Python 3.7 upwards.
+- Works anywhere: tested on Windows, MacOS and Linux, 32- and 64-bit, Julia Julia 1.6.1 upwards and Python 3.8 upwards.

docs/src/pycall.md

@@ -72,4 +72,4 @@ Note also that JuliaCall will use a separate Julia project for each virtual/cond
 
 ### Compatibility
 
-PyCall supports Julia 0.7+ and Python 2.7+, whereas PythonCall supports Julia 1.6.1+ and Python 3.7+. PyCall requires numpy to be installed, PythonCall doesn't (it provides the same fast array access through the buffer protocol and array interface).
+PyCall supports Julia 0.7+ and Python 2.7+, whereas PythonCall supports Julia 1.6.1+ and Python 3.8+. PyCall requires numpy to be installed, PythonCall doesn't (it provides the same fast array access through the buffer protocol and array interface).

docs/src/releasenotes.md

@@ -3,6 +3,7 @@
 ## 0.9.20 (2024-05-01)
 * The IPython extension is now automatically loaded upon import if IPython is detected.
 * JuliaCall now compatible with Julia 1.10.3.
+* Minimum supported Python version is now 3.8.
 
 ## 0.9.19 (2024-03-19)
 * Bug fixes.

setup.cfg

@@ -15,7 +15,7 @@ zip_safe = False
 package_dir =
     =pysrc
 packages = juliacall
-python_requires = ~=3.7
+python_requires = ~=3.8
 install_requires =
     juliapkg ~=0.1.8