Update readmes

Author: jakubno

README.md

@@ -39,8 +39,8 @@ from e2b_code_interpreter import CodeInterpreter
 with CodeInterpreter() as sandbox:
     sandbox.notebook.exec_cell("x = 1")
 
-    result = sandbox.notebook.exec_cell("x+=1; x")
-    print(result.text)  # outputs 2
+    execution = sandbox.notebook.exec_cell("x+=1; x")
+    print(execution.text)  # outputs 2
 
 ```
 
@@ -52,8 +52,8 @@ import { CodeInterpreter } from '@e2b/code-interpreter'
 const sandbox = await CodeInterpreter.create()
 await sandbox.notebook.execCell('x = 1')
 
-const result = await sandbox.notebook.execCell('x+=1; x')
-console.log(result.text)  // outputs 2
+const execution = await sandbox.notebook.execCell('x+=1; x')
+console.log(execution.text)  // outputs 2
 
 await sandbox.close()
 ```
@@ -86,10 +86,10 @@ with CodeInterpreter() as sandbox:
     sandbox.notebook.exec_cell("!pip install matplotlib")
 
     # plot random graph
-    result = sandbox.notebook.exec_cell(code)
+    execution = sandbox.notebook.exec_cell(code)
 
 # there's your image
-image = result.results[0].png
+image = execution.results[0].png
 
 # example how to show the image / prove it works
 i = base64.b64decode(image)
@@ -121,10 +121,10 @@ plt.show()
 // you can install dependencies in "jupyter notebook style"
 await sandbox.notebook.execCell("!pip install matplotlib")
 
-const result = await sandbox.notebook.execCell(code)
+const execution = await sandbox.notebook.execCell(code)
 
 // this contains the image data, you can e.g. save it to file or send to frontend
-result.data[0].png
+execution.results[0].png
 
 await sandbox.close()
 ```
@@ -138,36 +138,47 @@ from e2b_code_interpreter import CodeInterpreter
 
 code = """
 import time
+import pandas as pd
 
 print("hello")
-time.sleep(5)
+time.sleep(3)
+data = pd.DataFrame(data=[[1, 2], [3, 4]], columns=["A", "B"])
+display(data.head(10))
+time.sleep(3)
 print("world")
 """
+
 with CodeInterpreter() as sandbox:
-    sandbox.notebook.exec_cell(code, on_stdout=print, on_stderr=print)
+    sandbox.notebook.exec_cell(code, on_stdout=print, on_stderr=print, on_display_data=(lambda data: print(data.text)))
+
 ```
 
 #### JavaScript
 
 ```js
 import { CodeInterpreter } from '@e2b/code-interpreter'
 
-code = `
+const code = `
 import time
+import pandas as pd
 
 print("hello")
-time.sleep(5)
+time.sleep(3)
+data = pd.DataFrame(data=[[1, 2], [3, 4]], columns=["A", "B"])
+display(data.head(10))
+time.sleep(3)
 print("world")
 `
 
 const sandbox = await CodeInterpreter.create()
 
 await sandbox.notebook.execCell(code, {
   onStdout: (out) => console.log(out),
-  onStderr: (outErr) => console.error(outErr)
-  onDisplayData: (outData) => console.log(data.text)
+  onStderr: (outErr) => console.error(outErr),
+  onDisplayData: (outData) => console.log(outData.text)
 })
 
+await sandbox.close()
 ```
 
 ### Pre-installed Python packages inside the sandbox

js/README.md

@@ -23,8 +23,8 @@ import { CodeInterpreter } from '@e2b/code-interpreter'
 const sandbox = await CodeInterpreter.create()
 await sandbox.notebook.execCell('x = 1')
 
-const result = await sandbox.notebook.execCell('x += 1; x')
-console.log(result.text)  // outputs 2
+const execution = await sandbox.notebook.execCell('x+=1; x')
+console.log(execution.text)  // outputs 2
 
 await sandbox.close()
 ```
@@ -45,15 +45,15 @@ y = np.sin(x)
 
 plt.plot(x, y)
 plt.show()
-`
+`;
 
 // you can install dependencies in "jupyter notebook style"
 await sandbox.notebook.execCell("!pip install matplotlib")
 
-const result = await sandbox.notebook.execCell(code)
+const execution = await sandbox.notebook.execCell(code)
 
 // this contains the image data, you can e.g. save it to file or send to frontend
-result.data[0].png
+execution.results[0].png
 
 await sandbox.close()
 ```
@@ -63,21 +63,27 @@ await sandbox.close()
 ```js
 import { CodeInterpreter } from '@e2b/code-interpreter'
 
-code = `
+const code = `
 import time
+import pandas as pd
 
 print("hello")
-time.sleep(5)
+time.sleep(3)
+data = pd.DataFrame(data=[[1, 2], [3, 4]], columns=["A", "B"])
+display(data.head(10))
+time.sleep(3)
 print("world")
-`;
+`
 
 const sandbox = await CodeInterpreter.create()
 
-await sandbox.notebook.execCell(
-  code,
-  (out) => console.log(out),
-  (outErr) => console.error(outErr),
-)
+await sandbox.notebook.execCell(code, {
+  onStdout: (out) => console.log(out),
+  onStderr: (outErr) => console.error(outErr),
+  onDisplayData: (outData) => console.log(outData.text)
+})
+
+await sandbox.close()
 ```
 
 ### Pre-installed Python packages inside the sandbox

python/README.md

@@ -21,10 +21,10 @@ pip install e2b-code-interpreter
 from e2b_code_interpreter import CodeInterpreter
 
 with CodeInterpreter() as sandbox:
-    sandbox.exec_cell("x = 1")
+    sandbox.notebook.exec_cell("x = 1")
 
-    result = sandbox.exec_cell("x += 1; x")
-    print(result.text)  # outputs 2
+    execution = sandbox.notebook.exec_cell("x+=1; x")
+    print(execution.text)  # outputs 2
 
 ```
 
@@ -51,21 +51,21 @@ plt.show()
 
 with CodeInterpreter() as sandbox:
     # you can install dependencies in "jupyter notebook style"
-    sandbox.exec_cell("!pip install matplotlib")
+    sandbox.notebook.exec_cell("!pip install matplotlib")
 
     # plot random graph
-    result = sandbox.exec_cell(code)
+    execution = sandbox.notebook.exec_cell(code)
 
-    # there's your image
-    image = result.display_data[0]["image/png"]
+# there's your image
+image = execution.results[0].png
 
-    # example how to show the image / prove it works
-    i = base64.b64decode(image)
-    i = io.BytesIO(i)
-    i = mpimg.imread(i, format='PNG')
+# example how to show the image / prove it works
+i = base64.b64decode(image)
+i = io.BytesIO(i)
+i = mpimg.imread(i, format='PNG')
 
-    plt.imshow(i, interpolation='nearest')
-    plt.show()
+plt.imshow(i, interpolation='nearest')
+plt.show()
 ```
 
 ### Streaming code output
@@ -75,14 +75,18 @@ from e2b_code_interpreter import CodeInterpreter
 
 code = """
 import time
+import pandas as pd
 
 print("hello")
-time.sleep(5)
+time.sleep(3)
+data = pd.DataFrame(data=[[1, 2], [3, 4]], columns=["A", "B"])
+display(data.head(10))
+time.sleep(3)
 print("world")
 """
 
 with CodeInterpreter() as sandbox:
-    sandbox.exec_cell(code, on_stdout=print, on_stderr=print)
+    sandbox.notebook.exec_cell(code, on_stdout=print, on_stderr=print, on_display_data=(lambda data: print(data.text)))
 ```
 
 ### Pre-installed Python packages inside the sandbox